TBPN Live - Slop vs. Steel Showdown w/ Delian & Everett, GPT-5 Backlash, Trump Eyes Intel Stake | Bill Bishop, Jimmy Goodrich, Lennart Heim, David Stout, Cameron Schiller, Cyriac Roeding, NFM Live

Starting point is 00:00:00 You're watching the TVPN! Today is Friday, August 15th, 2025. We are live from the TBPN Ultradome, the Temple of Technology, the Fortress of Finance, the Capital of Capital. We have the debate of the century, the debate of the year, a showdown between former Founder Fund, Founders Fund, colleagues. Friends turned foes. Friends turned rivals. Everett Randall, he's been on the show before. Delian Asperuhov. He's also been on the show. They haven't been mincing words, John. They haven't. have been throwing shots back and forth every TBPN appearance. Yes. They're calling the other one out. Yes. And so they will be debating and right now we're going to settle this strategies. We're going to settle it today on the stream. The Slop versus Steel debate,

Starting point is 00:00:44 which is better high margin software or capex intensive re-industrialization efforts. That's right. We will bring in Delian and Everett into the studio. Welcome to the stream. How you guys doing? I like that background. Very good. energized here we go we're going to be breaking it down live here yeah we're going to be breaking it down live all all every time one of you gets a point i'll put a put a little point reality style if if things get out of hand we'll be banging the gong and bringing order like it's a gavel uh but i'm sure i'm sure this will be uh i'm sure everyone will be civil oh i'm sure keep the name calling to a minimum uh good to have you both thanks so much for being here

Starting point is 00:01:24 let's let's let's kick it off let's start off what's your least favorite thing about the other I'm kidding. You could kick it off with the original story. Like how did this all start basically? Yeah, yeah, yeah. Give us a backstory. Yeah. You want to give it?

Starting point is 00:01:38 Yep, I'm happy to. So we were back at Founders Fund. We were starting to beef up our CRM and data science efforts. And so we were integrating some external data into our CRM, figuring out how we could filter opportunities better to each of the, each of the investment team professionals. And we were looking, and we were looking at the different data, I was like, oh, it'd be really nice if we could filter this by gross margins so that all of the negative gross margin companies that come into our CRM, we could give them all the Delian, because it seems like those are the types of companies that he loves to invest in. The rivalry between, you know, the low gross margin side of the house and the high gross margin side of the house was born then. Okay. And Delian, justify why do you like these businesses?

Starting point is 00:02:30 What true are you in? Is that even a fair characterization? Fair characterization, I think, you know, my sort of one line would be, I'm not sure that, you know, sort of gross margin is actually like the right thing to focus on in a business, especially either sort of early on. What you want to be thinking about is obviously EBITDA margin, in particular terminal, you know, EBITO margin. And so when I think about the like, at least founders filled ethos to, you know,

Starting point is 00:02:52 sort of investing, we think that that term. terminal EBITDA margin, mostly is determined by ultimately how much of a monopoly your company can be in the long term. And so if you look at, you know, sort of mag 7 today, obviously there's a decent chunk of them that, you know, have some phenomenal, you know, sort of gross margins. And those tend to be the ones that are a little more software oriented. If you look at the one that is at the biggest scale and has the best EBITO margins, it's the one that is the most, you know, basically hardware oriented. For sure, some of it propped up by like Kuda and they're like, you know, sort of software side of the house. But like, Nvidia is the one that is performing

Starting point is 00:03:20 the best of all of those. And then even if you study within those, you know, which of those, you you know, companies on the hardware side have monopolies versus, you know, sort of not. You see it's the one that with the monopoly, you know, clearly outperform the ones that don't, right? So Tesla, obviously, in that, you know, sort of mag seven, but a part of why they, you know, sort of suffer much worse margins than like an Apple or in a video is because, like, they actually do have, you know, you know, competition. And so my general characterization of, you know, sort of SaaS is people always, you know, sort of study their original, you sort of gross margin, but weren't burdening in the, you know,

Starting point is 00:03:47 sort of cost of sales, marketing, et cetera. And because you just have much less of monopoly typically in SaaS, that ends up totally, you know, hurting your ebidot, you know, margin profile. So take, like, the, like, the favorite, you know, terminal scale thought of as a monopoly, you know, sort of SaaS company that, you know, I'm sure loves, Salesforce, their market share and all things, CRM is 25%. And so that's why you end up seeing, like, yeah, gross margin profiles only burdened by, like, you know, cloud, you know, sort of cost.

Starting point is 00:04:12 But their ebidot margin profile that is like, you know, sort of 40%. And so, you know, the reason that I like these negative gross margin businesses is, yes, they're like tougher to start. They may be more equity intensive at the beginning, but end up with way better, you know, or terminal margin profiles versus, you know, Ev loves to, you know, invest in the, you know, AI slopcos that might have early gross margins in revenues. But so, Ev, what's the bull case for software?

Starting point is 00:04:35 What's the bull case for SaaS? What's the bull case for AI slopcos? Look, so to quote the godfather Neil Mehta himself, the laws of great businesses are the laws of great businesses. The job of a business in the capital society is to maximize, and find the efficiency frontier for three things. Roik, aka return on invested capital, the amount of capital you can actually deploy

Starting point is 00:05:01 and how long you can deploy that amount of capital at and above market Roik. There's a lot of different framings for the paths to do this and how companies can actually do this. The one that people like in tech circles is Hamilton-Henler, Seven Powers. A company accumulates power in the form of scale economies, network effects, whatever power you want to take,

Starting point is 00:05:21 and then uses that power to produce above-marking. market ROICs for as long as possible and with as much capital invested in the business as possible. There are great Adams-based businesses that do this. There are terrible atom-based businesses that don't do this. There are great digital businesses that do this. There's terrible digital businesses that don't do this. I mean, you want to hear about a great Adams-based business that does this, listen to the acquired pod on Costco. Like, it's certainly not like a Adams versus SaaS thing necessarily. The advantage that digital businesses have is that in this process of producing above market Roik for a long time is that their product form factor and the way

Starting point is 00:05:57 that the distribute their product lends itself more to the process of creating power, I'd argue, than most Adams-based businesses. So if you think about like network effects, the best place to create network effects is in a digital marketplace like an Uber and Airbnb or a DoorDash. And so there's a lot of these forms of power that naturally lend themselves to digital products and the scalability of digital products tends to be a lot a lot greater than than physical products and so you can see these these rapid growth trajectories like we're seeing from open a ianthropic and many others when did you guys find common ground was it uh in the e-scooter era

Starting point is 00:06:33 the the sort of 15-minute delivery era were you ever able to kind of come together and say like yeah this is you know we can both agree that this is uh this is not good or good i mean uh to be Fair. Kleiner Perkins, Founders Fund have both invested in Figma, Stripe, Airbnb. There is some portfolio overlap. Rippling too, right? Rippling as well. There's a couple of modern health, I believe, as well. There's a few others. But yeah, to Jurety's point, where else is the common ground and where else is the divide? Or the consensus in the disagreement. Yeah, is you to say, you know, we're texting before this of like, you know, what are sort of two companies that I think, you know, both of us were enthusiastic about in, you know,

Starting point is 00:07:13 sort of 2021, actually both have, you know, sort of trended well, but our, you know, sort of counterpoints our two arguments. And the ones that we kind of came up with were, you know, 2021, I was really, you know, high conviction on Hadrian in 2021. I was super, you know, sort of high conviction on Rippling. Both those investments have, you know, sort of performed quite well over the last couple of years, but look, you know, sort of wildly different in terms of profile. You know, rippling, like many other, you know, sort of SaaS companies does end up having, you know, an initial, you know, very high gross margin, but does still have to spend a lot on sales and marketing to bring in, you know, sort of net new customers. Hadrian on the flip

Starting point is 00:07:46 side, deeply, you know, sort of negative gross margin to start. But now as they've gotten to scale, they actually have like super limited, you know, sort of sales and marketing spend because there's only like, you know, 10, 15 customers that matter. And the moment that you're delivering for them, they just proactively start, you know, sort of throwing revenue, you know, at you. And so, you know, I think there are times where, you know, both of our, you know, sort of stories, obviously, you know, can play out. The thing that I'd be curious to hear from, you know, sort of average is to actually, like, compare, contrast, you know, you were bringing up, you know, some of these digital businesses, you know, that end up having

Starting point is 00:08:13 these, you know, network effects. I would kind of argue that, like, you know, the like 2010s, negative gross margin businesses, like, you know, the like Uber, DoorDash, you know, you know, types. I think of as more as like, you know, Adams businesses, but there was a whole set of investors in, like, the mid-2010s that were generally unwilling to approach both Adams-based businesses that started with negative gross margin, but even some of these local marketplaces that started with negative gross margin that, like, swore off of the Ubers, the door dashes, et cetera. You know, it's very clear that Uber, DoorDash, through, you know, lots of investment, through building out these local, you know, certain networks of, you know, both supply and demand, we're able to, and, you know, drivers were able to eventually get to a point where now they actually, you know, have very attractive, you know, sort of financial profiles. Today, the equivalent of that is, like, there's all these investors that, you know, back in the 2010s would have refused to invest into any company that had negative gross margin and are all now pouring cash into both the, like, AI application layer companies and then, like, you know, foundation models that all have, like, ridiculously.

Starting point is 00:09:08 I mean, I forget, I think it's, girly is nonstop, you know, not my favorite person in the world, but Gurley is nonstop talking about, like, you know, what is going on here? They're selling a buck for 90 cents. So, so I think, I think it's an important example because you had that, you know, plenty of examples of these chained losses during that, that era where a restaurant was selling something below cost to a platform that was selling something below cost to a logistics provider, an individual contractor that, like, maybe wasn't actually making money if you factored in depreciation and fuel costs of their vehicle.

Starting point is 00:09:39 And that ultimately worked out, right? DoorDash is a massive, fantastic business based on the power of the American consumer. But when you compare that to today where a lot of the conversation on the timeline this week has been the margin profile of this new generation of software companies that has to pay a lot for sales and marketing, but also inference. And so I think like the debate should really be, you know, continue to be around just how quickly will the cost per token fall. And I think a lot of people have a lot of confidence around that. But I think that that is the key thing that Everett's sort of like broad investment thesis right now is dependent on. Yeah, like FD, think there's going to be that same path of like Uber for a while had a bunch of negative gross margin people going into it. Like do you actually think there's that a cool way?

Starting point is 00:10:32 I want to pull this post up. Everett actually posted this January 31 of 2024. So over 18 months ago, he said, I'm making a real effort to not take for granted the $3 Uber across town era of AI. And I hope you are too. And so I guess the question is, and it's funny because then a bunch of people, I thought it was a good point. I thought it was a hot take then. And I think then a bunch of people kind of parroted that take all over the timeline. Stole your whole flow, as you'd like to say. But I guess the question is like, are we in some sort of different regime right now where the traditional gravity and like fundamentals of software investing have changed because we are out of the zero marginal cost era and does that impose risks to the strategy that, you know, have you sort of employed or like we're kind of putting you in this whole in this box? But if the fundamental structure of zero marginal cost era is going away, that that presuppose. presumably forces like a rewrite of your logic around investing, I would imagine. Yeah, I think that the biggest variable that's changed from the 2010s, SAS era to today, is that in the 2010s, and you basically made this point without making it, Delian, though, is that the thing that that was missing from your talk track is that the competitive intensity of SaaS during the 2010s was much, much, much lower than it is today.

Starting point is 00:11:57 Like during the 2010s, there was an entire crop of companies in the 2000s. but then especially in the 2010s, you could basically pick either a vertical segment, you know, like HVAC or car dealerships, or you could do a horizontal function like the CRM or, you know, some very niche workflow for like the finance team. You could build a software product around that workflow or around that vertical. And you really only had to deal with typically like two to three competitors. Like there really wasn't that much competition relative to what there is today. And there was less just like general pricing pressure, competitive pressure.

Starting point is 00:12:32 just the general pressure that you actually had a lot with some of the digital marketplaces early on. And so like I think there was a whole crop of investors then and like the SaaS investors then were like, well, we don't need to, we don't need a bunch of cash burn. And it's actually, it's a really unhealthy indicator if these SaaS companies are producing a bunch of burn because they're not competing with anybody. So if they can't like sell their product for good union economics on day one when the competitive intensity isn't very high, then they're probably not a very good business. I think the thing that's changed now is one, you have the change from zero marginal cost to actual meaningful marginal costs in the form of inference. And it's also

Starting point is 00:13:10 just a hell of a lot more competitive than it used to be. And so you are and by the way, there's an immense, it was probably 10x more capital than there was 15 years ago to go into these companies. And so like every single category now has become like mini ride share or like mini Uber market where it's like, hey, there's probably a really big pot of gold at the end of the tunnel. And we need to be the ones that get first to scale. And in a lot of these categories, the ones that have gotten first to scale have gotten a lot of brand equity out of it and have gotten a pretty resounding lead. I think the only other piece I would say, I lost my sharing thought. So yeah, yeah, but it's going to be basically it's going to be like a capital fight now

Starting point is 00:13:48 on the on the SaaS side. I wonder if if the contrarian trade around hard tech is is entering a similar era where it's become consensus and so we're going to see more capital fights and when a founder goes out and says yeah i'm going to do something crazy but i need to spend a billion dollars of capex people are just like yeah i this could be the next base yeah it made sense to have a capital war in ride share but now we have a capital war in like this niche agentic workflow in some industry that that most people have never heard of and then also a capital here's 200 million dollars for funding military boats and uAS and ua p like all these different sub segments are going to want to up, if capital war start popping up there, that could potentially be a headwind to Delian's

Starting point is 00:14:32 model? Is that roughly correct? How would you, how would you fight back against that? Look, I think it's always, you know, sort of important to talk about, you know, sort of specifics here, right? Yeah. You know, one of Eves, you know, sort of major investments in the last year is this, you know, company called captions that basically does AI captioning of, you know, various sort of videos on social media. When I think about, you know, handing, you know, sort of two Stanford grads and $100 million to go try and, you know, sort of replicate that, Yeah, it feels like, you know, they could, you know, go do something like that. There's like, you know, clear, you know, voice recognition models.

Starting point is 00:15:02 They can go, you know, sort of pay on ads on TikTok, et cetera. And you could probably go and replicate that. And so, you know, you know, our one line, our founders fund is competition is for losers. And so, you know, I think I was a loser for investing in food. Now, shots fire. And you just delivered Deli, so thank you. Now, you know, if you take, you know, sort of two Stanford grads in $200 million and tell them, hey, I need you to go replicate this manufacturing facility. and go start building a bunch of, you know, sort of satellites, reentry vehicles, you know,

Starting point is 00:15:31 bioreactors that can actually survive the environment of space. Most, you know, sort of stand for grads, you know, can't go, you know, as chat, GPT, how to go do that. And yet, yet, yet, hasn't really faced significant competition, irrespective of the fact that, you know, all things space factories are thought to be, you know, sort of the hot new thing. To be clear, we use captions here on clips. We enjoy the captions app. We thank for making it possible and subsidizing our. And there is a YC, there is a WADA-esque YC company.

Starting point is 00:16:00 So you're coming for you. You know, Indian Varda, I think, will be a little bit less competitive than, you know, Indian captions. Also, if you're the caption CEO and, you know, Founders Fund is trying to invest in your next round, please don't let us do that. They're a helpful counterpoint for me. Delian, you were, you were correct that it was getting, it was getting too friendly of a debate. Yeah.

Starting point is 00:16:18 I did want to make sure I could pin this one on you. If you can recite the equation for a return on invested capital, I will, victory to you and I will donate $5,000 to a charity of your choice. Hopefully he's got Cluley running. My equivalent for ever, it will be if you can explain, you know, basically why you can't create microgravity down here on Earth, I will also donate $5,000 to a charity of your choice. But I don't think of it, you know, I may not have the basic understanding of business physics,

Starting point is 00:16:47 but you don't have the basic understanding of physics and one's more important about understanding the universe around you. Okay. I mean, I'm pretty fixated on the 2035. five midas list. Yeah. That's really kind of the final that's this that's this debate last year or I forget whether or not you've made it up there. Oh, taking shot. Tough. Not even on the brink yet. You know, we rejoins, you know, KP after you and she beats you laughing me. It's okay. It's okay. Eventually we're going to, we're going to bring back the

Starting point is 00:17:14 extra names in Kleiner Perkins. It used to be Kleiner Perkins, Coffield, buyers. It's going to be Kleiner Perkins, Randall, Brasswell, eventually once we're working on it. We're working on it. We're pitching it where where should we go next geordie i guess uh everett how are you how quickly like how much should people be fixated on the cost per token with these frontier models over the next six months like how how long can can uh venture capital sort of like backstop these uh chain losses yeah i think that the the way to delineate um the whole so so obviously like I think there was this kind of consensus narrative that like every, you know, 12, 18 months token costs were going down an order of magnitude.

Starting point is 00:18:00 I think that did hold for a while. I think what you've seen now is like actually for frontier models that started to peter out of it. And like pricing has actually started, it's still going down. It's not going down nearly as much as it, as it used to when, like, when we were kind of in the, like, the meat of the curve of capability improvements on frontier LLMs in terms of pricing curve. So I think that the way that you want to delineate it is like, there's a certain, like, what I always tell everyone is that like there hasn't been a chat GPT query since GPT4 that like my mom hasn't been able to ask and have it answered by the model.

Starting point is 00:18:34 So there's like the mom test of models where like there's a growing subset of tasks like economic or knowledge tasks that the models are tasked to do that no longer need frontier intelligence. And when you're not on the frontier, either through open source or just like the cheapening and distilling of. of older models, like the price still falls off a cliff. Sure. There's going to be a very, very large set of tasks that models do that are not on the frontier, and those are going to continue to get dirt cheap. I actually think that at the frontier, you're probably going to see continued price decreases on a per token basis, but nowhere near what you saw before,

Starting point is 00:19:09 which was like this order of magnitude decrease on a very regular cadence. And so I think, I think for like depending on the company, it's going to depend on one, if you've actually built a company that has enough power where you have pricing power, where you can price above the kind of marginal token price from the actual model providers. And then two, like how much of your inference actually needs to be at the frontier? Like how much of your inference can be an older model that's much, much cheaper versus how much do you need to do on the actual frontier? I think that's what you're seeing.

Starting point is 00:19:38 Like, you know, everyone loves to talk about Cursor and Chris Pake over at Pace Capital had this really great kind of like mini essay, I think only like last night or a couple of nights ago. And he talked about like, no one knows if Cursor has power yet because, you know, coders and developers, they're very, very, like they're taste makers. They're very good at understanding the quality of the models and how much inference they're getting. And there's a lot of price sensitivity for them because they have a really good understanding of how much inference they're getting. And so no one really knows, I think no one can definitively say whether a lot

Starting point is 00:20:07 of those types of companies have actual power with their users or if they're just drawn to an interface for frontier models or not. And so I think that's what everyone needs to be looking out for is those two things. Like, do you actually have power? Like, will people give you margin above the marginal cost of tokens. And then two, like, do we even need the frontier inference for the vast majority of your product? Or is that, or is there a lot that you can offload to cheaper models? Yeah, I mean, I guess your counter, you know, said there, Everett is that, you know, a majority of what the foundation models are providing in terms of the, you know, sort of value there in users is starting to be, you know, sort of obviated

Starting point is 00:20:39 by the, like, you know, historical generation, even some of the ones that are, you know, sort of open source. So it seemed to imply that where value is accruing and where you'd expect the highest revenue growth wouldn't necessarily be at the foundation layer, but you'd see it more at the application layer since those folks can squat models out. But like in reality, that's like literally just not what actually is happening. Like if you look at which companies are, you know, sort of fastest on user growth, user growth, et cetera, it is the foundation model companies. It seems like a part of it is that they also have, you know, sort of the most pricing power where, yes, you know, your mom, you know, uses GPT4, but like she's not the one that's

Starting point is 00:21:12 necessarily paying like, you know, $100,000, $10,000 per month versus the true frontier capabilities on like, you know, AI coding, the pro users, the one that actually do care about, you know, maybe your mom is fine with 115 IQ model and that's like fine for the rest of her life because she's just like not asking it that difficult of questions versus the people that actually are willing to, you know, should pay are the ones that actually do care about the 140, 160, 180 IQ. Again, maybe at some point that gets, you know, should commoditize as well. But my sort of counter to you would be, you've made this argument that it seems to imply, hey, you know, things will accrue to the AI application layer, which if I understand your

Starting point is 00:21:45 you guys' portfolios largely where you guys invested. But in reality, that's not what's played out. The places that have captured the most revenue growth, the most market share have been the ones that are actually pushing the true frontier, you know, of the, you know, so technology forward. And so far, at least in last 18 months, your thesis is not playing out at all. Well, to be clear, isn't it somewhat widely understood that Anthropic has negative gross margins as well? So it's not like they're doing. Like, I have a point was that you want to invest these companies that have the, you know, sort of seven powers and, like, you know, in the, you know, days of like Uber, you know, DoorDash, et cetera, that did end up, you sort of translating.

Starting point is 00:22:21 It seems like Nvidia has the most power, then the foundation model labs, maybe then the application layer. We'll see how much power develops in the application layer. But we'll let you, we'll let you respond. Oh, yeah. I was going to say that, that basically what Delian said was just wrong, because even though it is, even though, like, if you, if you think about, okay, like, let's take, like, whatever OpenEI and Anthropics recently reported revenue run rate is, the majority of all that or at least the plurality of all of that is chat GPT and chat GPT even though it is served by a foundation model company is an application it is a consumer subscription that has an immense amount of power it has an immense amount of branding like you know it is the only is like

Starting point is 00:22:58 the first billion plus user consumer application that's been developed by a new company in a really long time and so I think that like you could put whatever models you wanted through chat GPT at this point and it would not knock it off of its perch I think that is power. Like you could you could run Claude three sonnet through chat GPT and I guarantee people like the average user wouldn't actually know the difference. And that to me is power. And just because the foundation model companies are producing apps themselves doesn't mean that it's not the application layer that it's, uh, that that is accruing the value. Okay. Then my question is, you know, you've got, you know, opening eye with the best possible consumer application layer,

Starting point is 00:23:33 you've got Anthropic that like shifted over to positive gross margins and those margins they're expanding and yet clienters not investing into either of those foundation model either companies why uh i cannot comment on our current investment activities okay uh can you comment wait can you come on down don't i mean look i just do you like making money or do you like you know yeah going to all the competition can you comment on on donald boat have either of you bought anything for donald boat the notorious e-begger on x.com the everything app Like my little brother, you know, you know, played the unal reverse card and I tried to get Donald's book to buy him something. Oh, smart.

Starting point is 00:24:11 You know, contrary. Let's talk about revenue quality because I think that you guys run into this in your respective domains every single day. Just like in AI, you can have low quality revenue. Like that might be the explosion of like consumer prompt to app activity, you know, might not be the highest quality revenue. meanwhile on the hard tech side if somebody gets like a random like cibber or like experimental gets like experimental budget from some branch of the military and it's like a fine you know fixed length contract it's not necessarily the right strategy to slap like a 50x revenue multiple on it so like what's your view on on both of those and then i want to talk about if we should get into

Starting point is 00:24:58 if accounting rules even matter at this point yeah yeah for sure Yeah, I mean, in hardware land, we think about this all the time of like, there's clear differences in quality of revenue, everything from like, you know, defense, you know, program of record. You have to value that very differently than even like a $50 million, you know, SBIR. And so it has been interesting to see a bunch of investors coming into this field where I think there's a lot of preexisting 10 years of rules around software of like what, you know, healthy revenue looks like rule 40. There's all these things that like, you know, even if you're somewhat unsophisticated, infinite blog posts. When you look at that in the world of like hardware and defense, you know, sort of investing or aerospace, there aren't like infinite blog. post for people to study. And so I admit that I'm sometimes amazed when I watch people come in, even for, I should never, you know, sort of trash my own portfolio. But sometimes

Starting point is 00:25:41 even my own portfolio companies, I watch people invest in them. And I'm like, wow, like, you just have a deep underappreciation for just like how long this company has until gross margin flips to like positive. How long it's going to be until they're actually, you know, sort of a ready to, you know, go scale revenue. Even if it on the back end, it might be attractive. It may be years and years for them to, you know, sort of get there. And so, yeah, I see huge variation on that. And then mostly what I end up, you know, sort of seeing is people just come in and like slap a 10 to I even saw 100x rev rate multiple on this like hardware company recently and I was like holy shit wow people like not have an IRR for a long

Starting point is 00:26:16 time yeah I think um so Delian's hero and close mentor Bill Gurley had an essay a long time ago called the 10x revenue club and I think it's like a good abstraction for kind of like tech revenue quality and like what makes up revenue quality and it's things like you know how durable is the revenue. Like if you sign a customer, are they going to stay for a year or 20 years? You know, how much contribution profit is going to come off of that revenue stream over time? All the basics. And I think you can like take those same building box and apply to AI. I think there's several things that are worse for AI than at least than relative to SaaS for now. So generally gross like gross margins are lower, which means contribution profit coming off is lower.

Starting point is 00:26:56 I actually think that like depending on the category, you could have customers that are more sticky or less sticky. Like I know the meme is that everything's experimental run rate. and none of these customers are actually sticky. I think we see something very, very different among our group of portfolio companies. I think the biggest lever that didn't exist in SaaS, that exists in AI, that could be a huge call option boon for the revenue quality of AI,

Starting point is 00:27:17 is the actual contract sizes as people start to eat into potential labor budgets. I know this is still kind of like inning one and inning two, and it's also like a little bit of a meme where everyone's like, oh, it's going to replace labor and labor's 10 times SaaS, and it hasn't really happened yet. But I think if you look at some of these coding tools and you look at something like Claude, that is the first place where you can really actually say,

Starting point is 00:27:37 like, no, this is replacing the labor that a developer would do, and it is paid for on like a metered consumption basis. And the monetization numbers we're hearing around developers using CloudCode are pretty crazy in terms of like, wow, that's like you're paying like one-tenth of like a developer's full in cost to a company on an annualized basis for this product. And so I think that the like the thing to watch is like durability of revenue plus the amount of actual revenue that a customer can give you. And I think that you're going to end up the amount of gross profit that a customer can contribute over time. And I do think as some customers crack these agentic products that look and monetize more like labor, AI revenue could actually exceed the quality of SaaS revenue just because you're getting so much more gross profit per customer or like customer relationship than you would on the SaaS side, even though there are clearly things that are worse about AI revenue at this current point in time than there are about SaaS revenue. Dillon, how do you think about the moral imperative of a venture capitalist to invest in positive sum versus zero-sum markets, this idea that you're re-industrializing America, you're saving the West versus moving chips around, you personally, versus moving chips around the poker table, taking from some legacy, you know, web 1.0 company and putting it into an AI company. what's your what's your thinking and argument there is is is a a a market beating

Starting point is 00:29:01 ROIC all that you need yeah I you know I think Peter always reminds us like you know our number one job is deliver returns for is RLP's and so I actually tend to not try to either sort of overly moralize when like analyzing the things that I want to you sort of invest into for sure when it comes into like policy and I'm in DC and I like need to you know sort of report to you know the Security Council that you know Bill Gurley is at either sort of Chinese spy and their investments that he's making should probably be banned from the United States. Yeah, for sure there, I have, you know, sort of moral imperatives and things that influence that may end up, you know, shifting R.O.C., right? So, you know, but when it comes

Starting point is 00:29:35 to, you know, like, which literal investments are we making, I think of it is just like, yeah, you just have to, you know, sort of make the, you know, sort of best possible investments irrespective of, you know, sort of moral imperatives. But in some ways, I tend to think, it turns out, actually, if you, you know, go to immoral, then that ends up, you know, sort affecting RICs. So, you know, and the last thing that I would at least, you know, sort of, you know, close on, you know, for my, you know, sort of question, you know, for Everett is, you know, one of the upsides of Founders Fund is, you know, we're very, you know, sort of, you know, let's say, non-centralized, distributed, you know, not many, you know, sort of rules, which,

Starting point is 00:30:10 you know, ever, for some reason, you sort of chose to leave. And so I know nowadays, everything that he says publicly, you know, probably, you know, five comms people and five compliance people that either, you know, sort of approve it. I have my only request to you is, you know, to blink twice if somebody's, you know, got a gun behind the camera. I'm trying to shoot you and never say anything that, you know, goes through an office script. It's all you got to tell us, brother. Yeah, let us know. Hey, our wonderful marketing partner, Allie, is behind the camera with a green and red paddle.

Starting point is 00:30:36 And she has to be able to raise the red paddle yet. So that's great. That's great. Well, thank you both for joining. Last question. Are you worried about Uncle Sam potentially having sharp elbows now that we're hearing about the federal government taking a stake in Intel, any concerns about him going down the stack into the early stage game competing for those seed in Series A allocations? Look, if Trump Capital wants to, you know, sort of

Starting point is 00:31:01 mark up some of the, you know, reindustrialization companies, I'm all for it, baby, cheap cost of capital. You're all for it. Yeah, I'll say two things. I'd say one, I think the EV of like the enterprise value of founders fund probably three X the night that Trump got elected. So I don't, I don't think Delian would complain about that. And then as a parting gift, Delian, You know, I think this conversation's been great, and it's made me realize why you want to build factories in space, because your math on Earth doesn't make any sense. Well, thank you both for joining. You're both good sports. We'll have to do this again.

Starting point is 00:31:35 I think it might be a draw. We'll have to have you both back soon. Thanks so much for hopping on. Great stuff. We'll see you guys later. Cheers. Let me tell you about ramp.com. Time is money.

Starting point is 00:31:43 Say both. Easy use corporate cards, bill payment, accounting, and a whole lot more. A whole lot more. Do accounting rules matter? Yes. They do. Yes, they do. And you can enforce accounting rules on ramp.com all in one place. Go to ramp. That was, that was beautiful. Two, two former colleagues barely holding back from saying things that they would ultimately regret. But they did. They did a good job.

Starting point is 00:32:06 They did great. Yeah. I like the debate format. We should definitely do more of those. I think that was a lot of fun. I think the chat enjoyed it. My, my favorite rude comment in here, oh, we got Andrew Reed in the chat, Everett versus Delian. who can grow the most average beards? Oh my God. Thank you for watching Andrew. Let us know when you've selected an opponent and we'll have you on the show to debate someone. Yeah, I think we need to get the Holy Trinity.

Starting point is 00:32:34 Yes, yes. If you're new to TBPN, the Holy Trinity is of course the three venture capital firms that have done a seed deal in a now hyperscaler or now Mag 7 company, so that is Sequoia Capital, Founders Fund with Meta, originally Facebook, and, Kleiner Perkins, of course. And so the Holy Trinity are the three most storied venture capital firms in the Valley,

Starting point is 00:32:57 much like the three famous watch brands, the Holy Trinity, Vachron Constan, Patech Philippe, and Ademar Pige. Of course. Over in Switzerland. If you enjoy this stream and you want to make your own stream, get on re-stream, one live stream, 30 plus destinations, multi-stream and reach your audience wherever they are. If you're the backbone of TPP, you're doing the launch, streaming is the way to do it. You don't have

Starting point is 00:33:23 to try to poach Ben or anyone else on our team. You can just go to restream. It's fantastic. Check it out. Anyway, going back to the Death Star, the Vague Post. We're one week out from GPT-5. How has your GPT-5 experience been? Also, Tyler, the chat wanted you to answer. Explain the formula for ROIC.

Starting point is 00:33:47 The formula. So, yeah, I think it's, I believe it's operating income divided by book value of invested capital, right? Oh, you got it. Clearly's running, clearly. That's off the dome. That's off the dome. I did not just look it up. And then what did, what was Delian's rebuttal? He wanted why you can't achieve microgravity on Earth? Why can't you achieve microgravity on Earth? Do you know that? You're a physicist. You studied physics. You should get this. I'll have to get back to you. Let me think about that. Let me think about that.

Starting point is 00:34:20 I think it's just the, wait, I actually, I can't really explain it. That's kind of hard. I mean, I know that it's like Earth has a gravitational field and we don't have the technology to reverse gravity, but I can't really tell you why we don't have the technology to create an anti-gravity chamber on Earth. Like, I can't walk through the physics for that. I just know that you can't do it on Earth, but mostly because...

Starting point is 00:34:39 We've been trying to get a gong and microgravity here on Earth. I think it's that challenging. You can do it for like a very short amount of time right it's like when you see you ever see the planes yeah that's not that's not actually microgravity that's just falling right that's just falling in a pressurized capsule like you're still under the you because you are you are literally falling down to earth during that you just your surrounding environment is pressurized and so it feels like you're floating but in fact

Starting point is 00:35:05 you're you're you're really just falling closer to earth like when the plane goes down you are you are descent descending there's no there's no machine on earth that will effectively like levitate something and reduce the force of gravity to zero on earth or even or even reduce it significantly yeah but like that's the whole thing it's like from the observer it's the same yeah but uh for for space manufacturing for like growing a crystal the reason that you can't do it on earth is because it's too like it's not long enough no no no no i i think that i think that even if you even if you tried to do something in that in that plane scenario uh like you're still subject to the force of gravity, even though you're, because you're effectively falling, even though you're not feeling like the relative, like the wind speed, you still are under the force of gravity. I don't know. We'll have to figure it out. We'll have to have Del back and explain it to us. Anyway, what's your one week, one week review of GPT-5? What's your takeaway? Jordy? I've been, I've been, it's been fine. It hasn't been that drastic. I

Starting point is 00:36:12 I still find myself navigating between different models using the switcher. Have you turned on the legacy models? I haven't gone into the hidden. No. So, Tyler, you have, though. Explain this. Yeah, so if you just go into settings, you can turn on legacy models. Well, so all I have in legacy models is 4.0.

Starting point is 00:36:31 So 4.0 came back as a drop down, but you can go into the settings and turn on legacy models. And then you can access 4.5, right? Yeah. So 4.5 still there. 4103 oh so you can access them all but it's tucked behind even more menu I think that the Ben Thompson take was that they are that they are not being bold enough as a consumer company and telling people you know the Henry Ford thing if I asked people what they wanted they would have set a faster horse you know I gave them one color of car black I didn't

Starting point is 00:37:03 ask them for input on that Steve Jobs did the same thing famously with with Apple made a bunch of bold product decisions and then just said consumers I don't I'm not taking input you want you want a headphone jack too bad I'm taking it away you want an extra port on your Macbook you want a what was the thing that they took away they took away all the ports for a while they had no ports for a while it was just USBC ports on the edge and so when Facebook's been similar with the with the removal of the original feed and then the and then they moved away from a chronological feed to an algorithmic feed and there was a

Starting point is 00:37:38 lot of pushback for that but Mark Zuckerberg channeled a mentor of his Steve Jobs and said, you know, I know that this is better for the long term. I know that this is better for everyone in the long term and that people will ultimately love this. I mean, the main thing is it's very interesting that they, this was reported by Alex Heath and the Verge last night. Apparently he got dinner with Sam Altman, I think and Greg as well or some other executives. And they said last night about an hour before the dinner started, Open AI pushed an update to bring back the quote-unquote warmth of 4-0, which is what the Reddit, the Redditors of the world, the AI as my boyfriend, enthusiasts were clamoring for.

Starting point is 00:38:24 So it's interesting to see how quickly they folded there. I think, yeah, clearly they made users distraught. I also think of, I imagine a lot of those users were paying the top-tier subscription. and I you know again it's hard to read too much into Reddit or really anything you see online but a lot of people were canceling or threatening to cancel if they didn't bring that functionality back so anyways Sam I mean I would expect going forward like constant changes and iterations just like the YouTube algorithm is constantly changing the X algorithm is constantly changing yeah these updates get pushed very incrementally there's constantly tweaks that are happening so Sam is

Starting point is 00:39:06 quoted saying, I think we totally screwed up some things on the rollout. On the other hand, our API traffic doubled in 48 hours and is growing. We're out of GPUs. Chad GPT has been hitting a new high of users every day. A lot of users really do love the model switcher. I think we've learned a lesson about what it means to upgrade a product for hundreds of millions of people in one day. Yeah, it's always tough. He pegged the percentage of Chad GPT users who have unhealthy relationships with the product at way under 1%. I agree with that. That sounds right. but acknowledge that OpenAI employees are having a lot of meetings about the topic. Quote, there are people who actually felt like they had a relationship with ChatGBT.

Starting point is 00:39:40 And again, in this article, this post that we read yesterday on the show that he posted eight years ago called The Merge, talking about the inevitable point that humans and machines merge. He said, the merge can take a lot of forms. We could plug electrodes into our brains or we could all just become really close friends with a chatbot. So he was aware, you know, credit to Sam for calling this one pretty much perfectly because clearly, you know, it's millions and millions and millions. You know, even if it's way under 1% of this is, you know, tens of millions, right? Yeah. Yeah.

Starting point is 00:40:22 Yeah. I mean, hundreds of millions of daily users. Yeah, probably like under a million. So hundreds of thousands of people, that's a lot that could have an unhealthy relationship. Yeah. Okay. Way under 1%. So millions of people.

Starting point is 00:40:33 Maybe. I would get. They're not quite at a billion active users. So, and then a lot of those user international in terms of like the, I mean, not that really matters. You want to be keeping everyone healthy. But, yeah, we're talking about like hundreds of thousands of people that are potentially negatively affected.

Starting point is 00:40:49 So they got to drive that to, you know, 0.1% and then 0.01% and then, you know, get as close to zero as possible. There's always going to be some people that, you know, use, they read the newspaper and they go crazy. But, you know, the more that you can do, the better. Sam says you will definitely see some companies go make Japanese anime bots because they think they've identified something here that works. You will not see us do that.

Starting point is 00:41:12 We will continue to work hard at making a useful app and we will try to let users use it the way they want, but not so much that people who have really fragile mental states get exploited accidentally. Well, as they continue to iterate on the product, they have to use figma.com. Think bigger, build faster. Figma helps designing development teams build great products together. Go make something I'm figure to make today. From the chat for Ben, Ben Kohler, a producer, was recently followed by Reed Hoffman.

Starting point is 00:41:39 And the question is, did Ben get any Hoffman chat? Did he slide in the DMs or did he just follow you for updates? I think just for updates. Just for updates. If you're not following Ben, you've got to follow him. He posts constantly. He posts constantly throughout the show when big things happen, when crazy stuff's happening on the stream. He's kind of like the premium feed.

Starting point is 00:41:59 Like, you know, we put a lot of stuff on the main account. Ben's the behind the scenes guy. go follow him. Boys back here too. Yeah, the whole crew. So my final takeaway from the Death Star Vague post is that there was this viral image when in the lead up to the GPT4 launch is this data visualization and we can pull it up as the first slide in the deck.

Starting point is 00:42:22 It was visualizing the number of parameters in the model and this went very viral multiple times. So it was GPT3 had 175 billion parameters and GPT4 had 100 trillion parameters. And so you see the small dot and then the huge circle. And a lot of people were afraid by this and it was kind of this indication of exponential takeoff. And we really did see a qualitative improvement in just scaling up the pre-training run from GPT3 to GPT4. But GPT 4.5 taught us that pre-training scale is in fact not all you need. And the way to make a great AI product in the modern era is a mixture of techniques, experts, and researchers. You need a whole host of things, particularly with GPT-5. It feels like they RLed on a lot of different problems. And so to me, the Death Star Post

Starting point is 00:43:15 represents an even bigger circle from that GPT4 circle. So the Death Star is the biggest possible circle. And it's an expansion of that GPT3, GPT4, GPT4, GPT. But couldn't you read this that GPT-5 is the Earth? No, no. GPT-5 is the Death Star, or the perception of GPT-5 as just being a bigger model is the Death Star. Open AI blew that up. They blew up the metaphorical big circle with a model that isn't just bigger. Semi-analysis said the release is the router.

Starting point is 00:43:49 The router is the release. And what that means is that the gain in the value delivered by this product, is not just a bigger circle. It's a more complex coordination. It's all the different X-Wings working together in tandem. And then the Millennium Falcon comes in and saves the day. That's the, that's when, you know, the model router acts like triggers a reasoning step. And it thinks for a long time.

Starting point is 00:44:22 The Death Star is the end of the pre-training scaling law. Well, let's get in. into some more coverage here from Alex Heath. Sam says, you should expect Open AI to spend trillions of dollars on data center construction in the not very distant future. He confidently told the room. We have to make these horrible trade-offs right now. We have better models and we just can't offer them

Starting point is 00:44:44 because we don't have the capacity. We have other kinds of new products and services we'd love to offer. So obviously agent making that more widely available, I think is what he's alluding to. He also thinks we're in an AI bubble. When bubbles happen, smart people get over-excited about a kernel of truth. If you look at most of the bubbles in history, like the tech bubble, there was a real thing.

Starting point is 00:45:08 Tech was really important, but the internet was a really big deal. People got over-excited. Are we in the phase where investors as a whole are over-excited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes. Yes. So he obviously contributed to this excitement.

Starting point is 00:45:27 in a... Sort of, yeah. I would say that he... He didn't invest in very many competitors. And if there's a power law here, it could play out like the social media bubble where there was an immense amount of excitement around Facebook cracked it.

Starting point is 00:45:42 It's on the way to be a trillion-dollar company. And there was a belief for a while that it would be oligopolistic and Twitter and Foursquare and Pinterest and Snapchat would also be trillion-dollar companies. But that didn't happen. And if you invest it,

Starting point is 00:45:57 I'm just saying in those companies at unicorn valuations, you have not seen fantastic return on invested capital as opposed to. I just think it's fair to say that Sam helped get people overexcited and that in many ways he was saying, you know, with GPT6, we might be, you know, discovering novel physics and curing what? Who's the we there? Is the we open AI? Or is the we every company that's raising in the valley right now?

Starting point is 00:46:27 It's an important distinction. Speaking for open AI, but I think people are going to naturally take that as AI as an industry broadly in terms of its potential. So people might start thinking, yeah, maybe the 20th best LLM has a good shot at curing cancer. But the 20th best social network was not worth 1 20th of Facebook. It was worth 1,000th of Facebook or 1 20,000. of Facebook. And that's the nature of these power laws. But my take is that, so the model, the release being the router and this shift towards

Starting point is 00:47:10 open AI potentially shifting into dominating agentic commerce, having a monetizable free tier, this is actually a bull case for super intelligence. A lot of people on the timeline were like, oh, GPT5 was supposed to be like, you know, an order of magnitude gain, something really qualitative, like you use it and just feels different. It's just 100% on all the benchmarks, whatever. It wasn't that. It felt very incremental. And a lot of people were kind of, you know, we're plateauing all of that. But I think that, I think that shifting to a, shifting to a freemium model of a monetized free tier is actually a bullcase for building the trillion dollar cluster. And my thinking goes like this. So you can, you can build the first GPT,

Starting point is 00:47:55 to GPT3 cluster with nonprofit donations. Like $100 million gets it done. And that advanced them to that stage. But to do the GPT4 training run, they could not marshal the capital in the nonprofit space. They had to become the for-profit. They had to get venture dollars in. And yeah, and so basically like the Shogoth

Starting point is 00:48:16 demanded capitalism. This is the Nicolland take that artificial intelligence was sent back from the future to invent capitalism. Have you heard this take? great. And so the idea is, you know, like you could not get to GPT4, GPD5 without a for-profit company with the promise of return on investment. And so you pulled in all the venture dollars. The question is to build a trillion dollar cluster, I think Mossa is going to be tapped out soon. I think Mossa is a card you can play once. I think that there is a limit to how much capital

Starting point is 00:48:51 you can marshal in the private markets, even in the public markets. I just, just think it's impossible to raise a trillion dollars necessarily and that cluster must be funded must be funded by free cash flow it must be funded it must be underwritten by a company that can justify a return on investment from their direct product and so we're seeing this right now with Google and Facebook and yeah looking at a investing with their free cash flow yeah they're investing their free cash flow yeah they're doing some some some some debt but I think I think to get to the really really big numbers the trillion dollar cluster it's going to have to be built on just continual free cash low investment from a company. Tyler, what do you got, Tyler?

Starting point is 00:49:27 What do you think about like situational awareness like nationalizing labs? You think governments can fund the way? We're about to nationalize Intel. So maybe that's a path down the road. I don't, I don't know. I don't I don't think it's on the horizon anytime soon. Mostly because we're just not seeing capabilities that would threaten. It comes actually insane. So so a week ago. when that reporting from the journal on leopold's situational awareness everyone is just dragging him dragging him dragging him dragging him being like his fund is his fund is probably blown up already it's up 21% in the last five days oh my god oh it's a gong for leopold ochenbrenner and situational awareness uh yeah anyways there's some more there's some more interesting stuff in here i i i i i i i

Starting point is 00:50:23 I don't see it happening until the labs pose a threat to the US government in some way and are so dominant. I don't think we're at that phase. We're getting into the danger zone. We're in like new Google territory. It's a dominant consumer app. So there's some more interesting reporting here

Starting point is 00:50:42 from Alex. He says, Sam confirmed recent reports that Open AI is planning to fund a brain computer interface startup to rival NeurLink. I think that neural interfaces are cool ideas to explore. So Sam, I would like to be able to think something and have ChatGPT respond to it. And of course, I think it was the Financial Times who was reporting that Sam Altman would be a co-founder of this company, Merge. Does Fiji Simo joining OpenAI to run applications imply there will be other standalone apps besides ChatGPT?

Starting point is 00:51:14 Sam Altman says, yes, you should expect that from us. He hinted at his social media ambitions, quote, I am interested in whether or not it is possible to build a much cooler kind of social experience with AI. He also said, if Chrome is really going to sell, we should take a look at it. Alex says, well, Altman has a lot of interest. It's not clear. It's not actually clear that running Open AI over the long run is one of them. Sam says, I'm not a naturally well-suited person to be a public company CEO, he said at one point.

Starting point is 00:51:44 Can you imagine me on an earnings call? I then, Alex then asked if he would be CEO in a few years. Sam says I mean maybe maybe an AI is in three years that's a long time I love it I love it that's great some other else I love Vanta automate compliance managed risk improved trust continuously Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program so a few more points in here Altman had notes on making GPD5 we had this big GPU crunch we could go make another

Starting point is 00:52:19 giant model we could make that and a lot of people would want to use it and we would disappoint them. And so we said, let's make a really smart, really useful model, but also let's try to optimize for inference costs. And I think we did a great job with that. Obviously, we're clearly wanting to be more competitive with Claude in Anthropics API business. On the AI device with Johnny Ive, Sam said it's going to take us a while, but I think

Starting point is 00:52:47 you'll think it is very worth the weight. I think it is incredible. you don't get a new computing paradigm very often. There have been like only two in the last 50 years, so just let yourself be happy and surprised. Only two what? New computing paradigms. Oh, yeah, yeah.

Starting point is 00:53:03 He says, so just let yourself be happy and surprised. In the last 50 years, he says? In the last 50 years. PC era, mobile, cloud. I guess mobile and cloud are tied together. He's been Thompson-Pilled. On the future of web and publisher, Sam says, I do think people will go to fewer websites.

Starting point is 00:53:18 I think people will care more about human, crafted content than ever. My directional bet would be that human created, human endorsed, human curated content all goes up in value dramatically. Let's go. Let's hear it for our live stream. Human curated.

Starting point is 00:53:31 Human handmade. Seriously, I mean, what AGI means, Sam says, maybe the milestone that's most relevant to us is when most of our research cluster is allocated to the AI researcher instead of the human researchers. But I don't think that's going to be so binary because I think it'll feel like people get a little more help and a little more help and a little more help.

Starting point is 00:53:51 He also said, if we didn't pay for training, we'd be a very profitable company. That's a good question. So, Tyler, have you thought more about what happened to GPT 4.5? People, it's like, people always say, like, oh, it was so bad. And same thing with GPD5. It's like, okay, do you remember when we had Jack on, and he talked about his blog?

Starting point is 00:54:12 It said, GPD, or 4.5 is like as good as we should expect. Yep. Five is the same thing. I think it's a good model. Yep. If you, wait, okay, if you would please consult the graphs. Okay, pull up the meter. So my question with GPT 4.5 is, I understand that it's as good as we should expect.

Starting point is 00:54:32 The question is just, is it in the money? Because GPT2 was also on that curve and deeply unprofitable, right? They had to pay not a ton of money to train it, and it made basically no money because they didn't even sell it as an API. Remember, we talked to Greg Rockman. And he was like, we had to pay people to use our models. Then all of a sudden, the 3.5, the 3.5 DaVinci came out. Some people were using that. They might have spent, I don't know, $10 million training GPT3, 3.5.

Starting point is 00:55:00 And some people paid for it. They probably made their money back. Who knows? Then GPT4, they do the big training run, the 100 trillion parameters, the big circle. And that has to be one of the most profitable training runs ever. Because they maybe spent $100 million, but they are making a billion dollars a month, inferencing it and like the inference cost is probably gross margin positive more or less but 4.5 they probably sounds like they paid a billion

Starting point is 00:55:25 dollars to train it something like that a lot of money to train this big model and it's expensive and yes it's better but it's not better to the point where people are willing to bear the cost of inference for it so it's kind of mothballed and you can see that in the app it's like yeah but it's like okay it's worth one AI researcher I mean I think that the value of that like R&D like the knowledge that they now have training the next model is probably worth a billion dollars. Totally. If you're considered AI researchers worth billion dollars easily.

Starting point is 00:55:53 100% worth doing 100% not a big deal for their financials, not a big, it's just interesting that we went from a paradigm of like like the big, like the big training run was unprofitable, then it was massively profitable, then it went back to being unprofitable. And the profitable research that they were doing shifted to some RL that they did on, you know, hallucination to reduce the hallucination rate, like that RL run, probably not a billion dollars in training cost, I don't know, but it's clearly making the product better. People are going to use ChatsyPTC more.

Starting point is 00:56:27 They're going to be more likely to upgrade. And if the hallucination rate is lower, people are going to trust it to go shop for me. And they're going to make a ton of money off of that, right? Just an interesting dynamic. Yeah, I mean, I think a lot of people were like singling out this quote. if we didn't pay for training, we'd be a very profitable company. And just, you know, obviously it's easy to poke a little bit of funny that. He's saying he's gross margin positive.

Starting point is 00:56:49 No, no, I know. I know. But still, anytime you have a CEO being like, if we didn't have this cost, we'd be profitable, it's always. Yeah, I mean, the follow up on the earnings call would be Sam, any place to stop training then? Well, well, yeah, exactly. So we said, net profits. You know, this is whatever it said, and this is what we said, you know, in response to the GPT5 launch is that the product is. now the most important thing. And whatever Everett said just now was that, you know, you could,

Starting point is 00:57:18 you could swap in much cheaper models, even open source models, and people would still be using the product in the way that they are. Last quote from Sam from Alex's coverage, he says, I don't use Google anymore. I legitimately cannot tell you the last time I did a Google search. Mogged. Yeah, and this is, so this is the interesting thing, right? When you think about the browser wars, which we went from the browser wars a month ago being like everybody's making their own browser to now everybody's just trying to buy Chrome. And it's still very much up in the air whether they'll be forced to sell it. Google's not going to sell it, you know, by choice. And but it just does feel that chat GPT with with GPT or chat GPT agent is effectively a web

Starting point is 00:58:04 browser already. Yeah, you're just browsing the web. Yeah, that's great. And so I, uh, I I think that the real browser war is the fact that chatGBT functions as Chrome plus Google search in a single product already. Yep, yep. No, this is a great take. I completely agree. Wildcard, truth social buys Chrome. Truth Browser. This would be the most aligned.

Starting point is 00:58:29 Yes, this would be the most aligned with the current administration. Tyler, what's you got for me? Okay, so yesterday it's not here anymore, but if you went to opening ad.com slash new tab page, they like leaked this page. like not on purpose someone just found it but it's basically like very close to like a browser style where you would type in and then it would like auto fill some possible questions then you could like save uh like links and stuff so like it very much looked like the the chrome like home page yeah i i wonder in the context of mobile i mean using using generative AI to generate code and html has just completely pilled me on the the generative ui elements and i feel like

Starting point is 00:59:08 Like, I would probably be less interested, especially since I, I mean, I use chat GPT mostly on my phone. I use Chrome mostly on my computer, on my Mac. And so, and so I wind up, like, it's a very different style of working, and I can imagine that the evolution here is not the chat GPT app likes opening eye frames and and Safari web views and surfacing something that actually renders the native HTML. It's more like it scrapes all the HTML from a website into the reasoning chain. It gets all those tokens and then it kind of just like reinstantiate the UI in like native elements and kind of cleans it up for me. And so I'm getting like a hybrid of like chat GPD used to just be pure text response. Then it became text response and it also has links in there now.

Starting point is 01:00:07 and it also has... Commerce. Yeah, it also has tables, and it can put in images now. And if you search for a product, it can share, like, little preview images with a link. And so they're hydrating, like, the tokens. And think about how bad 99% of websites are.

Starting point is 01:00:28 I completely agree. They're so bad, right? It's hard to navigate them. There's pop-ups and things like that. There are people that deliberately browse the web with JavaScript turned off because it forces websites into a more usable plain text experience. And most websites have a fallback

Starting point is 01:00:47 in case JavaScript's not working or blocked. And so you can wind up going to the United Airlines checkout and it'll be just like normal buttons instead of like the page is jumping around, refreshing pop-ups, all that stuff. All that stuff gets turned off and some people like it. I haven't done cookies, yeah. Anyway, if you're trying to improve your website, you're managing your GitHub installation.

Starting point is 01:01:08 You've got to get on graphite code review for the age of AI. Graphite helps teams, helps teams on GitHub ship higher quality software faster. Well, pull this up in the timeline. Boys, we have a post here from the New York Stock Exchange, otherwise known as the New York style exchange. And here we are. Let's go. Nicey president, Lynn Martin stuns in the TBPN spring summer 2025 collection.

Starting point is 01:01:35 Thank you for. acting as our model for this this season's TBPN collection where we really designed it for tech and finance leaders that that are you know dedicating their lives to improving capital markets yeah and maintaining American dominance yeah globally that was the North Star with the with the with the Collegonia is like oh this was designed for your next hike yeah this was designed for Everest well this was designed for the trading floor on an IPO day this was designed for the hike up to that bell. Exactly. And for the Mount Everest of capital

Starting point is 01:02:10 markets, the New York Stock Exchange. For the gong hit that retires the next TBPN gong. Yes, exactly, exactly. We have, I think we can skip over this coverage from the Wall Street Journal. They said opening eyes rocky GPT5 rollout shows struggle to remain. Yeah, so this article, which was released a couple days ago, the title is opening eyes rocky GPT5 rollout shows struggling. to remain undisputed AI leader and it's basically just coverage from a bunch of people complaining and it doesn't capture any of the actual underlying doesn't feel like they're struggling to remain the undisputed consumer AI leader I think you could argue that yeah there's certainly a much closer race in code gen yeah so I yeah I put that in just as a

Starting point is 01:03:00 reminder to talk about GPT-5 the the real news is the financial Times has a story on Deepseek that isn't super deep in terms of the coverage, but there are some interesting tidbits in here. So the article is Deepseek's next AI model stalled by Beijing push to take up Chinese chips. We talked about this a little bit with the Nvidia age 20 now available in China and what that means for deep seek. So deep seek, obviously everyone should know is the disruptive Chinese open source frontier reasoning model maker from high flyer they were in the high they were in the high they were in the high frequency trading business then they decided to go into foundation model training and they developed and they

Starting point is 01:03:45 developed a very very solid open source language model very quickly and it surprised everyone we started talking about Jevin's paradox and the idea that cheaper AI will just wind up driving more and more adoption we've certainly seen that and the sell-off that happened in the AI trade in the public markets came rip roaring back and invidia rocketed to over a four trillion dollar valuation after they'd sold off slightly after the deep seek news so apparently they've been trying to get this R2 release out the next version of their of their reasoning model and they're having a hard time because allegedly they're using chips from

Starting point is 01:04:24 Huawei so China the CCP and Beijing has pushed deep seek to switch from Nvidia to Huawei. Everyone suspected. And it was in it and it's it's not technically illegal to use Nvidia chips, but it is politically incorrect according to one person familiar with the conversations. Currently, yes. And and and and there were export controls. There were never any import controls. So if you're high flyer or deep seek and someone comes to you from Malaysia and says, hey, I got I got a hundred thousand H-100s right here. You want to buy them? I fell off a truck. You're, you're, welcome to buy those, at least you were, now it's politically incorrect to do so. And so Walway hasn't really gotten the job done.

Starting point is 01:05:11 Lots of recent model releases have failed to live up to expectations. This is what happened with GPD 4.5, Lama 4 Bohemith. Like the models are getting more, they're getting bigger, there's more and more integration points in the training cluster as you're actually building these out. There's power management issues, there's memory issues, there's all these different things. And that's why the AI researchers are making so much. such high salaries and the trade deals are happening because if that there's one researcher who can tell you that line of code is going to result in 20 million or more or 200 million that's really valuable and so this case shines a light on the on the exact nature of the gap between nvdia and wawaway so when the wawaway ascend cloud matrix 384 came out everyone was kind of saying okay wow like wawa is basically caught up it's not as efficient on a on a on a

Starting point is 01:06:01 dollar per flop basis like it's more energy intensive but if you're willing to spend a little bit more energy you basically get the same capabilities that might not be the truth like like there might be actually some qualitative value to CUDA and the reliability of the drivers and the software on top of in video and actually the underlying chips as well such that even if you have the three gorge is dam you have cheap energy you have nuclear power China's developing more and more energy, it's getting cheaper and cheaper. Even if you have cheap energy, if you go to set up the massive data center to do the huge training run on Huawei Cloud Matrix, 384, you might still

Starting point is 01:06:39 be in trouble and you might not be able to get the model out the door. It could be something else, though. We don't really know. This is all kind of just like little tidbits. I mean, it's notable that all of these have led to, they originally wanted to launch R2 in May and it's still delayed. Yep, yep. And so it'll be interesting to see how deep seek reacts. They could potentially say, you know what, like we're like Huawei's just not getting the job done. We'll deal with the, we'll deal with the pushback from Beijing. We're putting in a huge order for H20s from Nvidia. We want the best, or at least the best that's available to us, even though the age 20 of course is four years old at this point. Yeah. And severely nerfed. So we'll see when

Starting point is 01:07:23 will they get R2 out? How powerful it will it be? And most important, importantly, what will the cost per million tokens be? Because if we get an 03 level model from DeepSeek and it's a hundred times cheaper, even if that doesn't displace Open AI meaningfully because Open AI is operating at the application layer, it will be incredibly bullish for every wrapper company because all of their gross margins will flip positive very, very quickly because they'll need to do some fine tuning. We'll need to see what perplexity did, where they made. instead of deep seek they made it like 1776 Seek or something like that they did a fine

Starting point is 01:08:04 tune on it to kind of make it more American but the most important thing was that the deep seek researchers figured out a bunch of interesting hacks to make make just inference way way way way cheaper anyway speaking of rapper companies application layer companies that we love Julius what analysis do you want to run chat with your data and get expert level insights in seconds. Ask Julius to analyze your data. Like two million users have already done folks from Princeton, BCG. Love, Julius. I wish, my only, my, the only thing I would change with Julius is I wish it was Rahul. Yeah. Or sunwalker.a.ai.com. But it's always time for just like the Ford Motor Company, you know. The Sunwalker artificial intelligence company.

Starting point is 01:08:55 Maybe. Maybe it could happen. So T.R. Taxis has a take on the, on the, the, the, the deep seek story because they think it's a confused narrative with no sources of Deep Seek confirming it. So T.R. Taxis says, this story is so insane. Dream narrative for burgers and their pure hearted vassals. Yeah, I guess. That I might well, that I might well cook up my own. Also based on half-bake rumors, experience. in an authoritarian society and just a little bit of sleuthing. As expected, the plot thickens. Xi Jinping's heavy-handed central government approach, a stalling development is the take that TOR taxes might be debunking here. Deep Seek was a breakout hit, but patronage networks

Starting point is 01:09:40 don't reform overnight. The actual Chinese national champion in AI is, as we know, Huawei, they get unconditional subsidies and the nation's hopes are pinned on them. On a software side, it's also Singwa, the university and their brainchild ZAI. with GLMs, but Huawei does everything. In February, the party asked Ren Zhengfei to partner with major AI labs, including DeepSeek, and beat America at AI.

Starting point is 01:10:06 They approached DeepSeek, sending personnel to adopt ascend clusters for V3 inference. We've seen papers following from that, and we know these clusters now work at Silicon Flow and elsewhere. They also suggested training the next generation models on Huawei, but were privately told, by, probably after some experiments, that the Ascend ecosystem is not yet mature or reliable enough and will go with H-800s. Thank you very much. With the knowledge gained, they had set out to train Pangu Ultra MOE mixture of experts as a reproduction of V3R1 and may or may not have failed at that due to interconnect issues and broad lack of competence resorting to repackaging R1 with the intent to report to the party that DeepSeek had proven uncooperative. But there's nothing special there.

Starting point is 01:10:55 do equally well and will soon surpass Saur. Now, as DeepSeek is not releasing any rumored R2, the timeline never once made sense, and that's a big issue. You need to have your timeline straight. There's renewed discussion about importing Nvidia. They are trying to spin this to their benefit, leaking to journalists that it was Deepseek that had failed at R2, while Huawei's Noah's Ark small model lab is moving smoothly.

Starting point is 01:11:22 They may know that V4 is planned to come out late enough that they still have some hope of producing a more persuasive internal result. For now they are probably optimizing Cloud Matrix hardware and CINN testing 910D and 920 and hiring people with LLM expertise. The above is an educated guess. The serious argument is that if you want to talk about the failure of Huawei's hardware, it's important to focus squarely on Huawei and not a fanciful and unprecedented narrative where a historically independent startup is forced into changing their training stack by heavy-handed

Starting point is 01:11:53 politicians and so the takeaway here is that Huawei might actually be significantly behind Nvidia and it's less about the CCP saying you know we want I mean of course the of course the reason the CCP is saying by Huawei is because they want to improve Huawei and give them as many advance as many advantages as possible to get to the frontier and and provide you know the best AI training hardware possible but the the the flip side is is that Deepseek is down to use anything and train on a bunch of different stuff. And really, they are, they probably, at least according to this,

Starting point is 01:12:31 they really are just having trouble training on large Huawei clusters. And so they're like, let's get back in the Kuta ecosystem. Anyway, let me tell you about profound. Get your brand mentioned by ChatGPT, reach millions of consumers who are using AI to discover new products and brands. Get a demo. Go to Profound. be like the mag five what did uh what did james say he said something well you were saying like

Starting point is 01:12:57 i can't say who's using it but oh yeah the fortune five the fortune five he's got a fortune five client yeah so it's like one of five companies will leave it to you guys to uh 20% chance you just to guess it correctly um anyway uh lots of people making money on the intel story so the story today is that uh the uh the trump administration uh just last week called for the resignation of Lip Bhutan, said that his ties to China were too much for an American champion like Intel. But Donald Trump has reversed course and called TAN a success. And the idea of the U.S. government buying a stake in Intel is now floating around. I don't love the idea of the people that brought us the TSA, running the most advanced

Starting point is 01:13:41 manufacturing process humanity has ever produced. Or the folks behind the DMV. The folks behind the DMV getting in the fab, getting into the clean room, might be a little bit of a stretch for me. But Intel does need better shareholders. There was a few years ago before the Chips Act. Long-term patient shareholders. Exactly.

Starting point is 01:14:00 People were talking about, oh, we need an American semiconductor champion. This was during like the reindustrialization meme kicking off. Everyone was saying this, like, we need American chips. And yet no one was like, I'm going to actually go build a position in Intel. And so everyone was like, yeah, we need this. It was a, what is it, a cocktail? position. It was a cocktail position, meaning something people like to talk about at cocktail

Starting point is 01:14:24 parties, but they don't actually put their money where their mouth is. So you sound smart saying we need to, yeah, we need to make Intel an American champion, we need to make chips in America, but I'm not willing to put any money on the line to actually do it. And so Intel's share price has been kind of in the dumps. Well, until recently. Until recently. So Dan Gallagher in the journal says federal support could get the trouble chip maker over some hurdles, but risks great harm to the U.S. tech sector. We can get into it. So Intel definitely needs help, but the government support always comes with strings attached, and those strings in this case could ultimately trip up the Silicon Valley pioneer in the broader U.S. chip industry. The Trump administration is discussing

Starting point is 01:15:01 options with Intel that would involve the federal government taking a financial stake in the troubled chipmaker. The idea came up during President Trump's meeting with Intel CEO Lip Bhutan on Monday, and the discussions are still in an early stage. This is so funny after talking to Fabricated knowledge over at semi-analysis about like his main thing was like the problem with the Intel board is that there's too many government type people on the board politicians there's too many politicians too many like famous people writers thinkers there's not enough like just people that understand scientists we need like physicists on the board and like technologists we need like an Elon type or like you know someone who understands the actual tech yeah I mean to

Starting point is 01:15:43 steel man it's like Trump has you know a multi-billion dollar digital assets business. He has a multi-billion-dollar social media company. He is the founder of a tech unicorn, so it's on his first rodeo in the tech industry. That's right. So you got to give him some credit if he was able to get in there. So Dan says that marks a fast turnaround, given Trump was calling for Tan to be fired just days ago. The news was encouraging for Intel's beleaguered investors who have watched the chip industry's once undisputed leader lose more than half its market cap in less than two years. The stock jumped 7% Thursday on the initial reports of the talks and gain more ground early Friday morning. But investors should still be wary. Intel's problems are such

Starting point is 01:16:21 that even a big check from Uncle Sam won't fully solve them. The company has burned a total of nearly $40 billion in cash over the past three years trying to regain its manufacturing lead from TSMC. Intel has also been granted up to $8 billion so far in direct funding through the Chips Act, but that hasn't been enough. Intel's most state-of-the-art production process called 18A was supposed to close the gap with TSM, but the company admitted on its own second quarter earnings call last month that 18A will be used mostly for its own products, meaning few outside chip designers have found the technology compelling enough to sign on as customers of Intel's contract manufacturing service. Wall Street expects another $7 billion in negative

Starting point is 01:17:04 free cash flow this year, according to estimates from visible Alpha. Sorry, take me a second. double-d-d there on the soundboard. Tan told investors in the same call that he won't commit major capital spending to Intel's next process called 14A without commitments from external customers, smart. They couldn't get a customer for that. That was widely seen as Tan drawing a line in the sand, a line by which he would determine whether to keep Intel in the business of manufacturing chips. But Intel pulling out of that business would be detrimental to the government's efforts

Starting point is 01:17:34 to shore up domestic chip making for national security and supply chain stability reasons. Doug over its semi-analysis was talking about. about how the chip design business seemed like it could be a target for, like, PE in the sense that if you came in and kind of overhaul-Haw-TAN is going to come in. Yeah. If you, you know, dramatically cut cost and really focused on serving customers and, of course, raising prices, there's probably a good business there, but that the Foundry business was critical and we don't want to risk losing that.

Starting point is 01:18:09 Yeah, Hawk Tans, the CEO, Broadcom. I just wanted to say, have a great flight, John Exley. He says he's taking off. He's landing in one hour. And if you're trying to set up a semiconductor line, if you're trying to build or plan products, get on linear. Linear.com. Great idea.

Starting point is 01:18:26 It's a purpose-built tool for planning and building products. Meet the system for modern software development, streamline issues, projects, and product roadmaps. So I... This chart chipped away. Chipped away. Intel and TSM revenue. Ripping.

Starting point is 01:18:42 So I'm still sort of slid on this. We have some guests on the show today to talk about the dynamic between the U.S. and China in the semiconductor race. I'm sort of open to the idea that we sort of solve the U.S.-based manufacturing of semiconductors through partnerships with TSM and Samsung, even though those are not American companies.

Starting point is 01:19:04 If they set up fabs here in some sort of negative conflict scenario, it's like, well, we still have the, the factories here. Even if it's run by a company in South Korea or Japan or Taiwan, like the factory should continue to produce for the most part because most of the team that would be building. And I think the pushback there is we don't have the talent, which is key to staying on the leading edge. Yes, that's true. But I mean, yields at TSM Arizona have been good so far and it feels like we could continue to scale up. and it feels like a lot of the talent will be coming over. And so there's a little bit of like, you know, you start to ramp up that supply.

Starting point is 01:19:44 But it does feel like Intel is particularly good at the trailing edge, but maybe that goes international, but to South America, unclear where it goes. Unclear how, at least to me, how important Intel is as like a strategic company versus just like it's one of the greatest technology companies America's ever produced. It's a crown jewel. It should just be protected because it. it's it's like good for the America brand versus like if Intel disappear tomorrow like how how bad would things be in America like would we be able to get by with with other

Starting point is 01:20:18 suppliers yeah so we do have AMD we do have we do have in video of Nvidia and then TSM and and and Samsung are not in China that's not where we buy our chips from so well Dan in the journal says the government might for instance pressure chip designers like Nvidia, AMD, or Qualcomm to manufacture with Intel perhaps as a condition for getting export licenses for China, and that could easily go wrong. If companies are forced to use Intel's factories before they can make chips with production yields that match TSMCs, it could result in inferior products and wastage by Intel because so much silicon has to be thrown out to make a working chip. More broadly, if chip designers are using Intel fabs, even though they aren't the most advanced

Starting point is 01:20:59 or efficient, the entire U.S. chip industry could lose competitiveness. That would undermine the ultimate goal of government intervention in the industry, which is to maintain American technological supremacy. Yeah. The Rubicon of state intervention in chips has already crossed the administration, already signed significant leverage over Intel, has already has significant leverage over Intel, thanks to government factory expansion grants that place limits on how it can restructure its chip design and manufacturing arms without government consent. But the federal government must take care not to go too far lest it undermined the market model that made American technology.

Starting point is 01:21:37 Slippery slope. It is. But at the same time, there is a case to be made. And I guess, you know, like if you put the U.S. sovereign wealth fund under the direction of Leopold Oshenbrenner, there is a case just for make money for the taxpayer. And this is actually the opposite of a bailout. This is what Tim Geithner got in trouble for during the, not in trouble. He was ultimately vindicated during the financial crisis in 2008.

Starting point is 01:22:03 He went and made a bunch of loans to banks on the order of like billions and billions of dollars. And everyone was like, this is a bailout for Wall Street. This is a bailout for the banks. But he actually only invested in the banks that made it through the crisis. And so those loans, those backstop debt instruments, were paid back with interest. And so the U.S. taxpayer actually made money on those deals. It feels a little weird. But the same thing could happen here.

Starting point is 01:22:31 Like, Intel's a $11, $110 billion company. If the U.S. invests and is able to do things to turn it into a $300 billion company, well, like, that's an extra 3x for the U.S. taxpayer. And it doesn't actually result in any, like, lost money. It's not a bail. And if Trump can just get three Xs and string like a hundred of those together in a row, we'll solve the whole, you know, federal debt. That's a high watermark. I think he should be targeting, you know, a nice 5x fund for the first run, then raise 10x more and then scale up and then, you know, start deploying the big money, big money.

Starting point is 01:23:14 You should buy 100% of Intel. What you got, Tyler? This is like we should give, put Jane Street, you know, high frequency lawmaking. Yes, just optimize for GDP. Direct right access to the legal code. Yeah. So anything they can do to just maybe one of the. the foundation labs actually instead of nationalizing the labs we need to need to you know corporatize the government and let and do a re reinforcement learning environment with a verifiable reward the verifiable reward being the stock market price but the business but the business is the

Starting point is 01:23:47 government exactly so what what what can you what can you change in the legal code to make the stock market go up and so you're just feeding off of that constantly rewriting the the legal code well Zoomer at ZumiZoom has been going viral again. He says why AI is a house of cards. He has an entire thread breaking down these sort of chained losses that we've been talking about. And he's getting community noted quite a bit. Someone added 1H100 can serve thousands of users at once depending on batch size and model. For inference, you don't dedicate a GPU to a single user.

Starting point is 01:24:28 You load the model, then stream requests for many users in parallel. numbers in this post are also widely widely exaggerated yeah this might have come from a group chat originally that was maybe not fully fact-checked but you know told told a compelling story so yeah and Nick Carter says compelling threat if you ignore that inference gets 10 to a thousand X cheaper every year if you're willing to pay two hundred dollars a month for AI and VC funding sub and VC funding subsidizes half of that simply wait six months I would say you know Mr. Randall earlier on the show said it's actually not all of a sudden getting 10 or

Starting point is 01:25:06 a thousand X cheaper, at least for frontier models. But the point he made is that a lot of prompts could be served with older, cheaper models and that's going to be a big focus. I mean, clearly that was a focus for Open AI with the recent launch. Yeah, I dug into this to see, you know, how would we really hit a thousand X cheaper this year on on the models? And would the, would the gross margin profiles these AI companies flip extremely quickly or is it more like a five-year change to really optimize this stuff I'm kind of split on it I you know the the charts that Nick Carter shared here are pretty compelling I just hope that the trend continues because the the dynamic of reasoning models and test time inference is slightly

Starting point is 01:25:51 different like you are just it's it's less algorithmic driven it's more just throwing raw compute at it and generating a ton of tokens so I don't know Tyler Do you think you're closer to 10x cheaper inference every year? Thousandex cheaper inference every year? What type of gain in cost per token do you expect over the next few years? Don't make mistakes. Do you mean in what models are you talking about? Like frontier level models?

Starting point is 01:26:21 All the models. I think Frontier will probably stay similar price. And then you'll just see over time, like now we have open source models that are easily as good as like two years ago. Yeah. Right? You have like 4-0, which is super cheap. But open source doesn't mean free.

Starting point is 01:26:34 Like it means free, no license, but you still have to inference it on an Nvidia GPU that costs money. And you have to spend electricity that costs money. Just open sourcing a model does not reduce the cost to zero. But when you open source something, you can like distill it even further. You can like, you get some, you know, optimizations there. That's cheaper. So, so O3 Pro, let's call that like an expensive frontier model.

Starting point is 01:26:59 How cheap do you think that is next year? Do you think it's 10 times cheaper, two times cheaper, a thousand times cheaper? Like an equivalent model of a... Yeah, O3 Pro, heavy reasoning, thanks for 10 minutes, generates tons of tokens. In a single year? I'm probably closest to 2X. 2X. Yeah, I wouldn't say massive games.

Starting point is 01:27:24 Well, guys, I hate to interrupt, but there's some breaking news. William, Jong, is proud to announce. that he's the reigning Open A.I McNugget champion. He ate 55 nuggets in 10 minutes. Absolutely incredible. There's some other great news. Numeral HQ, sales tax and autopilot. Spend less than five minutes per month on sales tax compliance.

Starting point is 01:27:44 Go to Numeral HQ to get started. And we have our third guest of the stream since we already did the debate. We have Bill Bishop and Cynicism. How are you doing? Signed you. How are you? Thanks for having me. Thanks for hopping on.

Starting point is 01:27:57 We really appreciate you taking the time. Give us, I mean, I'm super familiar with your work. I think everyone should be, but give us the high level of the pushback that you saw yesterday. We enjoyed having you in the comments. And I want to know how you would frame the counter argument to what Aaron Ginn was making yesterday. Okay. Well, thanks for having me. And I'm impressed that you guys respond to jerk comments.

Starting point is 01:28:19 That's good. I don't see it as a jerk comment. Well, yeah, we don't see it. I think it's extremely fair pushback. 100%. Okay. When I have Aaron Ginnon, I see it as having Jensen Wong on the show. show okay well that is that is how i see it too so that's exactly and and i can't have er i can't

Starting point is 01:28:36 have jensen come and whiteboard out pros and cons with me and i can't throw random jokes at jensen all day long but i can to erin and so i enjoy uh having him sit there and i can throw stuff at him and of course he has he has his uh his opinions and his arguments um but it's great to have somebody that can speak the language of invidia so yeah no and i again i i think um Thanks for having me. I'm psyched to see you guys on Substack, too, which is great. And I see your running show today. You've got two great guests, Jimmy Goodrich, and Leonard, who are going to be way better on sort of this discussion. So I think that what I would say is what's been interesting to watch. And I think talking about the reversal on the H20 trip, we got our H20 chip from the video. We got to remember, right, there was a proposal teed up for the Biden folks to ban the H20.

Starting point is 01:29:28 and they never did it for whatever reason Trump comes in actually bans it so it looks like he's paying more hawkish and then a couple months later because of really effective lobbying from Nvidia and specifically from Jensen Huang at the principal level at the you know to the president to David yeah I mean it's not even it's not even traditional lobbying because they're only they're spending like seven low seven figures on lobby probably 10 times that on Jensen Wong's like flight schedule right no it's it's brilliant they say sort of you know disrupt the lobbying business go right to the decider. Go direct.

Starting point is 01:30:01 And how the narrative is shifted. And so Trump, on the one hand, looked like he was tough for China. Then he backs off. And then, of course, he gets a bunch of flack for, oh, my God, he's caving to China. He's caving to Jensen, right? Yeah.

Starting point is 01:30:11 When, in fact, he sort of did what Biden didn't do. And then because of this personal interaction and the personal effort from Jensen Huang, he reversed course. And I think it has to be seen in the context of the broader where I think there was a correct decision, the rescission of the AI diffusion rule, right? which was really, you know, David Sachs was, I think, a big advocate of getting rid of that rule with a Biden administration rule that was going to limit countries that could buy Nvidia GPUs, right?

Starting point is 01:30:37 The idea that the U.S. needs to lead, the U.S. needs to be out there competing with China, not just limiting. And the way to do that is to get people hooked on the U.S. AI stack, specifically in VDIA globally, ex-China. That makes a lot of sense. The China decision on H20, I think, is flawed. But the idea that, oh, we're going to keep China hooked on Nvidia by selling them H20. And then I think, you know, the Jensen Huang is lobbying to sell sort of the next somewhat nerved chip, right? A little better, but still not near the top of the Nvidia product suite. The idea that just invidia is better, Kuta is better than the Chinese, the Chinese hyperscalers, you know, the Alibaba, Tencent, Bite Dance, Deep Seek.

Starting point is 01:31:23 they're going to want to stay with NVIDIA, make sense in a world that is sort of a normal political economy, a normal competitive world, doesn't make sense in the context of a world or market that's run by the Chinese, you know, the Communist Party of China. And Xi Jinping made very clear in April at this polypure study session that was about AI, specifically said he wants China to build its own indigenous AI stack. And so they understand very well this idea that, you know, NVIDIA wants to hook their companies on NVIDIA hardware, the party wants self-reliance. And so this idea that we need to compete, America needs to compete by selling into China

Starting point is 01:32:03 and therefore they're addicted, they won't break it, that I think is fundamentally naive and misunderstands how the party operates. I think what it does is it helps China fill the gap between where they are now in terms of lagging capabilities and lagging output or quantities in terms of the Huawei chips it gets them to where they need to be over time, but they're going to be only intensifying their efforts

Starting point is 01:32:26 to strip out Nvidia, to break any reliance on the USAAI tech stock. And so by selling H-20 chips now, we're just helping China keep in the race when, in fact, if they weren't able to get the H-20s, it probably, I think, would help the U.S. at least maintain a lead if not start accelerating and accelerating some amount of separation. What's your reaction to the commentary showing that the CCP is actually like actively pushing back against deep seek, which is, you know, the clear open source or maybe not totally clear, but an open source, an open source leader. But yeah, your reaction to the news that Beijing asked Chinese Foundation labs to not buy NVIDIA, which is effectively, even if it means,

Starting point is 01:33:17 delaying like deep sea cards too so there was a financial times report yesterday where it said they were encouraged we would love to know what what the encouragement really was but yes they were encouraged to use the Huawei I think it was the latest the send chips which were all based on dyes that were illegally fabbed at TSMC where Huawei used a cutout company that was related to Bitmain called soft go to get I think it was two million dyes from TSMC that they can't make on their own in China And even then, they're still not where they need to be.

Starting point is 01:33:49 And so I think that this goes, you have that news. You have the news since the announcement by the Trump administration that they were going to allow, again, allow licenses or give licenses to sell H20 to China. You've had significant pushback from some of the regulars in China. You've had talk about the chips are unsafe. Maybe they have backdoors. They're environmentally unfriendly. They're security risks. And so I think what you're seeing, you know, there's different hypotheses about what's going on on the pushback.

Starting point is 01:34:16 on the H20, it's maybe they're trying to negotiate for the better chip. I personally think it's actually more of a manifestation of parts of the system really just are like, we need to stop this reliance on American ships. We need to make sure we're focused on building our own pathway to self-reliance. And that, I think, is related to that news that DeepSeek is being encouraged to use these lesser chip, even if it delays them, because ultimately, when they figure how to use them. And the report said Huawei has engineers on site

Starting point is 01:34:51 trying to work through it. Ultimately, that will help China because that will help them solve over time the various bottlenecks they're facing. But I think... You can read into it. And one way you can read into it is that the CCP doesn't believe

Starting point is 01:35:04 in this sort of fast takeoff scenario, you know, like runaway AI in the next, you know, two years, right? Which I think broadly, I don't know, a lot of people that still believe in that, but it's notable. No, I think that's right. I think this is more of a, we're going to, we are going to set the foundation for doing it in a self-reliant way, even if it takes us longer.

Starting point is 01:35:25 And so that's where I think what's been interesting to watch in NVIDIA is how the narratives have shifted in D.C., where the NVIDIA line of we have to compete, we have to compete, we have to sell in the China, we have to addict them, is basically everywhere now. There's just like, there's barely any pushback. And certainly in the government, from what I'm understanding, there's no longer any process, right? back to the whole sort of how did jensen lobby to get decision made there's no process there no there no like all the many of the people who worked on these issues were fired um and and now it's basically like he gets to the principal gets to the lutnik or sacks or the president and that's the decision there's no like national security discussions there's no process anymore yeah it feels like interestingly people often project uh like a monolithic culture upon china but then

Starting point is 01:36:14 severe division within America and it feels like there might be some division on both sides in the sense that in America there are arguments for let's export all the GPUs keep them dependent on us versus let's let's hold it back and hurt their ability to scale and then in China they might be saying the same thing hey we need to just buy buy buy and stay near the frontier this will actually help us accelerate and then there'll be a different argument for for maybe maybe we need to just there's also there's also the you know in many ways way's deep seek the original deep seek release was was in some ways economic warfare on on nvidia right you saw this massive sell off immediately well and there and there was clearly a somewhat

Starting point is 01:36:58 of a coordinated hype yeah i mean the app store the app store chart you know deep seek getting all these downloads was completely fake twitter bots to the trolls and so and so i think there's you could also read into this and think uh uh Beijing doesn't think that the next deep seek release regardless of how much progress they make around efficiency will have the same effect on you know making Nvidia sell off you know yeah massively do you have any do you have any context on previous technological revolutions and and the history of the US China relations like going back to like the cloud or mobile like was there ever any similar considerations of don't sell iPhones it felt like in the previous

Starting point is 01:37:40 era every big tech CEO was like I'm going to massively tam expand by getting into China and then they got blocked and this is kind of the opposite where Jensen's been playing that and then now he's having to pull back and the government's like the U.S. government's the one that's saying don't sell the China whereas in the past with Uber and Google and Facebook it's been the Chinese government saying don't come here with your technology. I think this is fairly unique as far as I in my memory certainly with this sort of important technology there have been certain types of things that the U.S. government hasn't allowed to be sold into China, but not at the scale or the sort of the economic importance or the, frankly,

Starting point is 01:38:17 the market cap importance. Zooming out, how do you feel like U.S. China relations are just going generally? I feel like two years ago, there was a ton of saber rattling about we need to get sharp on Taiwan. Everyone needs to learn what TSM is. We need to talk about defense technology and Taiwan invasion in, you know, six months, 12 months. It's happening. It's going to happen. And then it feels like we've been in a bit of a lull, a little bit more economic warfare, but it feels like we might be coming out of a period of high tensions. Just give me like the general pulse check from your side. It's a great question and it's one that it's still quite unclear. I think that

Starting point is 01:39:01 you see the beginning of the Trump administration, the economic tensions rose pretty high. Those have come back down to, you know, where there's now a sort of a tariffs are high, but there's a, it's calmer, although the Chinese, in part, it's calmer, I think, because the Chinese pulled out their export control trump card, so to speak, around rare earths and rare earth magnets and really, I think, showed the U.S. that they had actually a lot of leverage that the U.S. didn't necessarily appreciate. And so I think you're in a bit of a law on the U.S. side because there are things, like, for example, on the technology stuff, you know, they were, a bunch of new actions around export controls, around chip related stuff, they're all tabled, right? In part, I think, because of how the Chinese were able to push back on the, initially, the beginning of the sort of the trade war using their rare earth's card.

Starting point is 01:39:56 Generally, though, when you look at the broader, you know, you look at Taiwan, you look at sort of things like the South China Sea, you know, the, the, the, you look at the other economic issues around, you know, what the U.S. states overcapacity, the structural issues are not going away. We are, I think, as you said, we're in a bit of a lull, and the Trump administration seems to be more focused on the transactional bit, parts of the relationship for now. But, you know, there are some people who want to talk about it.

Starting point is 01:40:29 Maybe it'll be this grand bargain, you know, Trump and she may meet this fall, and they'll have some great grand bargain. You know, it's hard to see how that would happen and how it be sustainable just because of the real structural issues and relationship. But there's no question that the narratives have been shifting. The Chinese have been working really hard on people-to-people sort of stuff that has, I think, pulled us back from the sort of peak of China Hawks. I said, you know, my Sharp China podcast last fall or the end of the year, we were joking. I said, you know, I think we've hit peak China Hawk. Right. No, seriously, right? It's going to, it's going to sort of moderate at least for the time being. I think that's what we're seeing.

Starting point is 01:41:10 Is the rare earth element stuff an ace in the deck of cards or is it more like a Jack or a queen? I think about, you know, we haven't even gotten to the, obviously, Taiwan invasion feels like more of the ace in terms of just like how much pressure that would put on the relationship. But also Apple, it feels like if China were to put pressure on Apple, that would potentially be more. more disruptive to the American economy just because it's such a huge company. It's so critical to American technology than rare earths. Or is there some other dynamic at play there? I think the Chinese, you know, Apple is one of those companies that every time their tensions, it comes up, well, China can do something to Apple.

Starting point is 01:41:53 And they have, you know, Tim Cook has been brilliant at managing President Trump and brilliant at managing Xi Jinping. And, you know, Apple, there was a great book that was written about Apple. Patrick McGee. I mean, Apple has, does a lot for the Chinese economy. They employ a lot of people directly and indirectly. The Chinese so far have not really bothered them in any direct way. The rare earth is one where they have the ability to effectively disrupt significant parts of U.S. industry and European industry. And they did that. And that, I think, is why you see, you saw the U.S. sort of pull back pretty quickly in the trade discussions. And, you know, the way

Starting point is 01:42:32 the U.S. did it is after the first meeting in, where was it, it was in London, Geneva, at the first meeting, all of a sudden the U.S. added these new export controls on jet engines and other things because the Chinese weren't giving the rare earth magnets that the U.S. thought they were. Yeah. That is the one where the Chinese can cause pain immediately. Yeah, yeah, yeah. So with Apple, if China does anything to Apple, that's like a million people unemployed in China, very disrupted to the Chinese economy. Whereas with rare earths like you could stockpile them you could you it's not as critical of like a labor market in china no it doesn't if they can't sell to us it it it's basically it hurts the couple

Starting point is 01:43:13 like one or two state owned companies effectively got it got it so so it truly is more leverage for them but it's but it's the card that you can only play for a certain period of time and if the u.s government and allies get serious about solving that bottleneck it can get solved the problem is it may be the trump administration now is serious this is not an this was not an unknown issue The Chinese threatened this in the first Trump administration. The Trump administration, then we had COVID, nothing really happened. Biden administration admired the problem, wrote some papers, had some meetings, didn't fix it. Now maybe there's the urgency to actually address it.

Starting point is 01:43:43 Yep, that makes sense. Last question from my side. What is general sentiment from on the ground in China? What's your read on sentiment among business leaders today? Not being there. That's a harder question to answer. When you look at some of the data and the surveys, you know, you look at some of the multinationals. I think there is a, the surveys from various foreign chambers of commerce tend to be generally pretty pessimistic, more pessimistic they've been in years.

Starting point is 01:44:12 When you look at some of the surveys around Chinese business confidence, it is maybe bottomed, not particularly positive. Certainly there are pockets that are positive. We talk about the deep seek moment. that has had a real catalytic effect on certain tech sectors. And you certainly see the Chinese stock market. Chinese stock market's up pretty big this year. You know, things like AI stocks are up, AI concept stocks are up big, some of the chip stocks are up big. You know, the H20 news and the fact that the Chinese maybe not want the H20s was good for some of the domestic chip companies.

Starting point is 01:44:46 So in those sectors, you know, you look at robotics, I think they're feeling quite confident because both the markets there and then they've got massive government support. So it's a mixed bag. Well, thank you so much for helping on. We are going to jump on with Jimmy Goodrich, but we'd love to have you back. I mean, this is going on here and any time. Also, if you're ever in the chat and you have a comment, you want to, you want to extrapolate on. We'll just drop you. You just join the same link that you have.

Starting point is 01:45:09 Really, you can join us. We got to live. So anytime. Now you're going to do it. Appreciate it. You'd love to see you. Cheers, Bill. Have a good one.

Starting point is 01:45:14 Thanks. Cheers. Have a good weekend. Cheers. Let me tell you about fin. A.I, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bankoffs, number one in ranking on G2, Finn. absolute legends. And we have Jimmy Goodrich in the re-stream waiting room. Let's bring him in

Starting point is 01:45:30 right now and continue our conversation on chips and China. How are you doing? Welcome to the show. Welcome to the show. Hey, good to see you guys. Good to see you too. I'm not sure if you were, if you've been tuning in or Bill Bishop gave you a highlight, a summary of the debate. We've been debating the pros and cons of exporting H-20s to China. And the back and forth America has had threatening to ban it, actually banning them. then pulling back on the band would love for me to tell uh would love for you to tell us how you've processed that story where you've sat on the issue over time and where you're sitting today yeah no i caught the tail on event i think it was a great discussion with bill you always got

Starting point is 01:46:10 really uh good insights to add i mean clearly it's been a roller coaster i mean u s export controls on china have typically been this sort of the government thinks about doing things it leaks out in reuters or the wall street journal that there might be doing an export control. China learns about it about nine, 12 months in advance. They stoppile everything they need. Then they watch the Americans sort of debate openly, you know, in our democracy, which is messy. I think they look back all this is kind of silly. And then they kind of have imposed a restriction. Then they undo it. I think it's just all kind of comical for Beijing. So how big do you think the age 20 issue really is?

Starting point is 01:46:49 Some people are talking it up is like the most important chip. It's going to completely unlock deep seek R3, it's going to be this amazing moment for them. On the other side, folks are saying it's a four-year-old, it's a four-year-old chip, it's heavily nerfed. Like, yes, deep seek figured out a way to optimize around some of the limitations, but in general, this is not a real threat. How are you feeling about the actual value of the capability provided by the Kuta ecosystem on top of the H20? I mean, I think it's still a very valuable chip for China and for China's AI model developers for two reasons. One, in the AI world, obviously, you've sort of gone to this in depth on your show.

Starting point is 01:47:26 It's about training and inference, and particularly for inference is where you need memory bandwidth, and that's where the H20 excels. In fact, on a cost per token basis, it's probably the most competitive inference generating chip in the world because it's the same memory bandwidth of a hopper, but at a reduced price. So it's a great value chip for inference.

Starting point is 01:47:46 And another key factor here is quantity, is that Nvidia can provide them in millions of units. That is something that Huawei and no indigenous producer today can do because of the export controls, because of the complexity of advanced no chip manufacturing, China's indigenous chip manufacturing ecosystem might in the future, but does not right now have the ability to produce enough to satisfy their own domestic demand. So at least temporarily in this sort of one to two year window, the H20, and then possibly a downgrade of Blackwell, still going to be very useful China to China.

Starting point is 01:48:20 And on top of that, of course, there's the Kuda. advantage and if you talk to any AI model developer in China they want to develop their model on the invidia stack they've been doing it since college days everybody knows how to code on kuda it's a big pain to move to another supplier i mean just moving to amd for example is difficult so you know let alone a much smaller much more nascent developed chinese competitor so i i think it's actually going to be a big game changer for the deployment of a i for the scaling up of chinese AI models. And if you think about, you know, reasoning and inference, if you want to develop more capable AI agents, they're going to be doing more task-free autonomously. That's where

Starting point is 01:49:01 H-20, high-memory bandwidth, good inference chips are going to come into play. Do you think it's smart for Beijing to take maybe a more long-term view here and say we're going to throttle development in a short term to really develop the industry locally? Well, I think they've got two sort of interest groups they're trying to take care of. On the one hand, they have their AI upper stack companies, the model developers, Deepseek, Moonshot, Emmy, Baidu, Tencent. They want just to be able to put out competitive models. And frankly, having spoken to many of them, they'd much rather use a better, more capable chip, irregardless of where it's from. And Nvidia certainly wins out in that right now.

Starting point is 01:49:47 On the other hand, you know, China has a self-sufficiency national target that Xi Jinping set as part of the 20th Party Congress, called it Putsidiji Zichang or national technology self-sufficiency. And he's talked specifically about using its secure and controllable indigenous chips. And there are set aside Huawei about a dozen indigenous GPU suppliers in China who want to take advantage of Nvidia not being in the market and expand their market share. And so, on the one hand, Beijing is welcoming NVIDIA back in. They're rolling out the red carpet when Jensen comes. They also, it doesn't matter why, they want an executive who's actively lobbying against tech restrictions in Washington. They want to reward that behavior.

Starting point is 01:50:31 But on the other hand, they want to create a space for these indigenous GPU players. It's going to be in things like state-owned contracts, China mobile, telecom procurement contracts are going to go mostly to those kind of hallway and other firms. But I expect sort of the Baidu Ali Baba, Tencent, hyper-scaler contracts are still going to be majority in Vidiya, particularly if they can get the licenses. So Beijing sort of balancing both of these constituents. In fact, within China, there are many who actually don't like Huawei. There was a Chinese Academy of Science, very senior computer scientist, who's a vice minister in the Chinese government and party, and a talk of his leaked earlier this year where he was criticizing Huawei and saying, Beijing should not let Huawei dominate the AI stack in China.

Starting point is 01:51:15 It's not healthy. They can't have a single large monopoly that the government should support and that they should be supporting competition with inside the Chinese system. So, you know, China is not a, let's give everything to Huawei. There's a lot of people who think they're too aggressive. They're kind of like the apple of China. Nobody wants to really do business with them because they're cheap on price and very aggressive. It's like the long or the wolf culture.

Starting point is 01:51:38 So, you know, Huawei has its own enemies with inside China, Interesting. Yeah, so let me walk through the current thinking, and you can kind of push back on my reasoning chain here. So we are now maybe in an era of plateauing. We're not on the cusp of superintelligence by merely scaling up, you know, a bigger large language model. And so what really matters is that inference is the actual deployment of AI getting AI all throughout the every crack in the economy is souping up the various SaaS systems and putting agentic workflows all over the place, increasing GDP not to 20% overnight, but maybe just bumping it from 2% to 3%, 1 point or something like that. And so giving the H20 to China allows them to do that, allows them to scale inference, distributed

Starting point is 01:52:34 inference nationally into all sorts of businesses from DJI will benefit from this marginally with slightly more AI all over their organization to, you know, some small machine shop that might be using it to run their HR software more efficiently. And so although it is somewhat of a more level playing field, we are still in the domain of just economic competition. And so it's not a major national, it's not perceived as a major national security risk, it's mainly an opportunity for an American company to just play by the traditional rules of free market capitalism and export their goods all over the world. Is that like roughly the modern thinking,

Starting point is 01:53:20 you think? I'd say I agree with you on that first point. If we want to help enable China to be competitive in AI, want to help their AI model companies get access to the best infrared chips, want to help them scale up their deployment, win in the market at home, and possibly also export their models globally, then absolutely we should be selling, you know, more H-20s to China. I just don't think that's in our national interest. You know, of course, it's in, it's in Vividia's interest. They want, you know, they are agnostic to who wins in the AI race. Because at the end of the day, whoever wins is still going to be buying a boatload

Starting point is 01:53:55 of MVIDIA chips in Silicon. And so whether they're Chinese, whether they're from the UAE or from the United States, you know, it's, you know, multinational company that's selling Silicon is really not going to care where their chips are going to and what they're enabling, from a sort of flagged country perspective. I do think, though, if you look at disinformation and cyber warfare, and you look at the capability that autonomous agents are going to be able to, even at current GPT5 or future R2 level coding capability,

Starting point is 01:54:28 if you think about scaling that up with 1,000, 2,000 autonomous agentic AI coding capabilities, they're going to be doing vulnerability scanning, cyber offensive warfare, you really start to get an exponential capability increase. And so I do worry that, you know, the Chinese state with, you know, two dozen H20 capable inference data centers could use that to do more autonomous cyber activity. That's nefarious. And on the same side, disinformation. If you can have models that can reason for longer and on an agentic basis,

Starting point is 01:55:01 interact with people online, shift populations, opinion in places like Taiwan, That's incredibly dangerous, and we've already seen the New York Times reported about 10 days ago that state-owned companies connected to the Chinese state are using DeepSeek, which is going to be inferenced on, you guess what, the best silicon possible, to do exactly that, which is disinformation campaigns against Taiwan and the United States. So actually, I do think there is a national security concern here. One, there's an economic security leadership concern, and then there is an enablement capability down the road that is actually. going to be you know i i think happening relatively soon last question another uh concern people have had is just like giving giving the party in Beijing broadly access to more compute and the potential applications of that in a military context specifically drone warfare is that's something that you you worry about very much or yeah i mean there's you know there's like traditional applications of high performance competing super competing which is useful for weapons modeling simulation you

Starting point is 01:56:05 don't need multiple large systems to do that you might have a couple of two a couple of boutique standalone government HBC systems where where more of that model data is going to be useful is if you're using large distributed systems of federated drones collecting data acting autonomously for example think about a world where you have your PLA signals intelligence communications battalion that's in real time collecting all the battlefield communications in a Taiwan operation. Then they're transcribing that in real time into a written product that's being

Starting point is 01:56:39 analyzed by autonomous agents in real time, and then getting field reports into their commanders in real time, telling them, hey, you know, there's a, you have a squad that's hit counterfire on this beach north of Taiwan. They haven't even reported it up to their

Starting point is 01:56:55 superiors, but the autonomous agent AI system might actually be able to get that, deploy a drone. If you think about just those capabilities in the future, that's where inference really matters. And that's where it's going to scale up and create tons of economic opportunities for Chinese companies and e-commerce and all sorts of other areas, finance and SaaS. But also on the military side, it's really endless if you could think about the applications as well. Great, great answer. Last question for me, what's going on with TikTok? It was the talk

Starting point is 01:57:27 of the timeline earlier this year. Everybody seems to have forgotten about it. Any updates? there. You know, I don't have a whole lot. I think it's one of these things where it's pretty obvious what happened to it. You know, the president likes the tool, thought it was useful for his election. You know, they've continuously renewed the clock on that 90-day extension. Unfortunately, you know, there's no longer really an operating national security council inside the White House like you would have traditionally to kind of figure out and coordinate the interagency on a solution. So I think at the moment- That feels like something. that you mentioned earlier Beijing kind of laughing about how our you know we have our democratic

Starting point is 01:58:09 system just publicly debates all these issues creating this ability for them to you know make make changes in advance but this feels like one of those things I mean they have to be just laughing laughing about how we've dealt with this entire issue to date I mean like with many of our things I think they they look back and just don't think we're a very serious country I mean, maybe with the exception of parts of our military, they think the U.S. is sort of a, you know, badass that should not be messed around with. But, I mean, look at us on rare earth. We can't get our act together, export controls. We're moving back and forth.

Starting point is 01:58:46 Whether or not we think we should actually, you know, get our act together in onshore ship manufacturing. We're, you know, interested in tell here a little bit and then TSM there a little bit. You know, the Chinese government, I think, from their perspective, like, look, we've got a 10-year plan, a 15-year plan, a 50. there's actually a hundred year plan and they're just sticking to it and they see us just kind of all over the place and i just don't think they take us very seriously unfortunately well in a hundred years we know the plan in america celebrate the 350th anniversary you know there's going to be a party and maybe a maybe a ufc fight that's what we can on the white house line anyway thank you so much thank you for joining jimmy very insightful we'd love to have you back and talk more as the stories

Starting point is 01:59:26 develop this is great yeah happy to chat more you guys are always welcome uh we'll talk to me Cheers. In other news, a Rune post has hit the timeline. Roon says, agree with Delian. Roon. T.S. Rune has spoken. Agree with Delian on the Maoist perspective that data centers should be turned into steel plants.

Starting point is 01:59:49 I love it. And you know what else? I love Adio. Customer relationship magic. Adio is the AI Native CRM that builds scales and grows your company to the next level. If you have a free calendar this weekend. fill it up with onboarding to adio and spend spend 48 hours just playing around in there doing some deals in other news we have a we we are our next guest is in the

Starting point is 02:00:12 restream rating where we will bring in Leonard Heim the second time on the show I want to talk about mr. beast he says he plans to take a hundred software engineers and lock them in a room with no cursor subscription with the first person to ship something that compiles taking home one million dollars wow this is from Vass absolutely fantastic. I originally read this not as a joke. Oh, he's actually doing the PMF or die thing because that kind of would work. And I thought it was with a cursor subscription. And then I was thinking about like, wow, he could wind up, if he covers the bills, he could wind up spending $2 million on this challenge. But Mr. B should get into software-based challenges. I would like to

Starting point is 02:00:55 see him have a different Mr. Beast of Software. He should have a horse in the code gen race. Yeah. It was clear that PMF or die was on to something, but it required someone to make it their life's work. Exactly. And if someone was really, I'm going to be the Mr. Beast of tech, I'm going to be doing crazy challenges all the time, live streaming, experimenting with all the different formats. There's clearly something there. I think Cluelly should run it back. Cluelly is a good candidate. Well, Cluelly Hackathon. Anyway, we have Leonard back in the studio. Welcome to the TVPN Ultradrome Leonard. How you doing? Hey, happy Friday. Happy Friday. love to talk about Mr. Beast instead of age 20s again, you know, why we're already on it.

Starting point is 02:01:32 Yeah. I mean, on that note, the Mr. Beast, if he was going to lock a bunch of, a bunch of programmers in a room with cursor, how bad do you think the gross margins would be? Do you have a take on gross margins of application layer companies? We've been talking about that all week. Do you have any insight in there? Anything that is muttering through your whisper network? unfortunately i'm not in san francisco so i don't know how code does nowadays work and i'm out of the old breed you know when i when i did software engineering it didn't have AI um but i always notice

Starting point is 02:02:07 when i use my clot plan and i run out of like queries and was like oh damn i i need to write on my own and think of my own who do i query and then i spin up my second chat givety subscription so i think it would already apply to me um being stuck without AI is is quite a problem nowadays well uh give me the give me the current read your current take the latest and greatest on the 20 debate where do you stand pro exports pro banning the exports how how has anything shifted your thinking around it over the past do you want to nationalize invidia do you want to invest in intel you're trying to buy low what do you think well the last time i was listening to the president speaking about invidia he was more

Starting point is 02:02:48 talking about initially wanted to break them up i know national right because they were so big break them up but then roll them up later we've seen this we've seen this we've seen this we've seen this playbook like 20 times with Trump and we get shocked every single time he comes out and says something this is the worst thing ever and then a week later it's the best thing ever and we're partnering and we're doing a deal ever so roller coaster well what he said during the what was it it was the action plan launch right yeah I was sitting in a room he was talking about Jensen pointing to Jensen and he was just saying I wanted to break them up but it's so complex and I think just basically somebody convinced him it's really hard and therefore you you're not supposed to break him very up

Starting point is 02:03:24 Yeah. Right. So fair enough. NVIDIA doesn't have as clean of a line to break up as Intel where, you know, you could gaming. We're taking you over here. Yeah. Yeah.

Starting point is 02:03:35 We need to see your focus on. The GIFARDS are going somewhere else. Yeah. What would you do? You'd open source Kuda or spin that into a separate company. Like if you were even to break up in video, like what would you actually do? Do you have any idea? Yeah.

Starting point is 02:03:47 I think the soft vehicle system might probably be the strongest one here. But again, it just goes hand in hand with the design, right? So again, yeah, I think it's a thing. fairly hard one. But for what it's worth, I think the market share is only going to go down. Like, there's more and more competitors. I mean, the total, totally valuation will go up. Don't get wrong. I'm like, I'm bullish on AI and Nvidia. But like all the other companies, all the other chip designers, they're just getting better. Is that, is that driven by AMD catching up or new? What does Aaron call them? They're like the new types of chips like Cerebrus, Grock,

Starting point is 02:04:17 and etched. I forget what they're called. There's a new name for these crop of ASICs that are designed specifically for AI and and they they could potentially pose a challenge but they're certainly not taking market share yet it feels like it's it's mostly Nvidia then AMD then maybe some Huawei the hypers they're right there the TPUs AWS with the trainium Google has the TPU since forever I'm mostly thinking about them right I think it's pretty clearly the case they have all the incentives in the world to build on AI chips and reduce NVIDE's margin sure on the startups let's see how they're doing right I think

Starting point is 02:04:53 hardware is hard, hardware startups generally fail. But if they find the right niche, you know, it's pretty hard. And video builds this more general thing. And if you're like a hardware startup, you want to find like a more narrow niche to be like more application specific. And if you hit the right point, right, whatever next big thing is in AI, they might succeed. And we just see more and more of them getting there, right? And like we see Anthropic and other companies using Google GPUs using Traneum.

Starting point is 02:05:17 And again, the debate of the showy of Huawei is also getting better. They will also just, the market share can only increase. Okay, help me reconcile this. Google DeepMind's been seemingly fine with TPU and not having Kuda in their back pocket. They're on the parade of frontier. The Gemini models are great. V-O-3 is great. The new Genie model is great.

Starting point is 02:05:40 It seems like they are not suffering or falling behind despite not having Kuda access. But then simultaneously we're hearing that Deep Seek, High Flyer, Ali Baba. They want to train on Nvidia. They're not satisfied with Huawei. Why is Huawei behind Google's TPU business? I think that's the example always bring up. And people say it's going to be so hard to switch Huawei. Google eventually succeeded, but also Google struggled.

Starting point is 02:06:09 The TPUs are pretty, pretty odd. This was way before an AI hype. And they actually also struggled. I'm not sure if you guys remember TensorFlow. This was originally what they did, right? And then later they switched to Jax and right, and they have the pie torch and everything around that. that. So I think over time they were struggling with software, but I generally see this as a

Starting point is 02:06:27 one-time investment and Google is a big enough of a company that can just pay this one-time investment and then you develop on top of it and eventually you will be there and you break even. You could probably do a survey if people are doing fine, like probably people still prefer CUDA because it's a bigger ecosystem, but it's just saying Google is doing fine and again Huawei will struggle, it will take some time, but eventually they will get there. In particular if they can use cursor along the right, while doing it. AI helps you to build your AI ecosystem. And I guess to some degree the flip side is like, TPUs have full access to TSM, ASML, and Huawei is restricted all throughout the supply chain. And so, yeah, and so, like, the latest Huawei chips, we were just talking to Bill Bishop.

Starting point is 02:07:07 He was saying that, like, that was from, like, two million, was it, dyes that they got from TSM through a shell company. And so they have this, like, one-time batch of supply chain, like, ease. And then from then on, they were supply chain constrained again. So then they had to go back to doing everything themselves. And that was a lot harder. Whereas Google just calls up at TSM and says, hey, do everything that you do for Nvidia. Just do it with our design, which is like probably slightly different.

Starting point is 02:07:34 Right, right. Anything else you want to dig into? No, I think we've covered. Yeah, I think we've hit this pretty hard. Well, actually, have you guys covered the semiconductor supply chain and how good Huawei is? Because there's this quantity thing is at the, like in the middle of the debate, in my opinion, which I think is being missed here. Please.

Starting point is 02:07:51 So everybody compares the NVDA H20 to the Huawei A's and 910C, and that's the best chip that's been putting out there. And if we look at the Huawei Asa 910C, it's like 80% there when H100 is. So like two or three years later than Nvidia, they're finally slowly getting there and approaching on the hardware specs alone. And again, we can look at the specification sheet, compare them one by one, but it's never tells the real story, right? If you would do this with AMD and Nvidia, AMD is on paper on the chips as good as

Starting point is 02:08:19 in video though one of them is 95% market share they have one less than five right so looking at the spec sheets is never enough that's where the software ecosystem come in where we just talked about Huawei is definitely struggling there I think they will eventually get there they just need to have more developers and I think that's exactly one argument favor of letting the H20 go there right the more people use the H20 less people use to Huawei so less developers are developing the ecosystem yeah but where then comes in is how many chips can they produce We got one number undersecretary class testified, so he's supposed to tell the truth,

Starting point is 02:08:54 200,000 ASE and chips this year. Versus, we're trying to sell, I think it's 700,000 to a million H-20s this year to China. So this is where then the debate struggles, right? So if we wouldn't sell them the H-20s, it's not like they have more ASE-910 C standard, then maybe they have more developers then, but they share a limited number of GPU resources.

Starting point is 02:09:14 And that's the thing, which I think needs to be debated here. And you can fall on both sides of the debate here. but like we need to understand that china is struggling and they cheated these it's not even two million dice it's 2.9 million dyes right because they're struggling so much with their own production interesting yeah so yeah i mean maybe 200 000's enough for people to actually bootstrap that software ecosystem certainly something to keep tracking uh i think people consistently overestimate china on a bunch in a bunch of different areas yeah yeah i mean they can do software i think they will eventually

Starting point is 02:09:48 get there and I think the idea they're just like Huawei's ecosystem will always be terrible is just look don't go wrong I would hope it's true right but they got good coders they got good designers they will just get better on all of these kinds of things and maybe Kuda will always be better but like Huawei is probably at the bottom right now regarding how good the ecosystem is and when the deep seek engineers you know they're getting to it and they're struggling well we'll get better right I think that's that's for granted independent of the 2000 ships or million chips yeah I think I still fall on the camp of probably H20 exports do put enough pressure on Huawei to justify it, but it's it's tricky. This is a this is a thorny one. It's not it's not extremely clear cut for me. Have you landed? We should do a case study on Amphropic because they're the most beautiful example because they got so many different ships they're using.

Starting point is 02:10:37 Yeah. Right. And how's it going for them right? Like how long did it take to train on trainium? Are they training on trainium? Are they deploying on trainium? And I think this would give us an insight. How many engineers are they spinning there and how bad bad as it still is.

Starting point is 02:10:49 I think one question, one question is, you know, is Beijing playing 4D chess by leaking out, you know, don't use the H20, don't use the H20, so then they, is that we just pile them into the country, right? I think so. Is it for D chess? It's just like, you create an artificial demand. You say like, look guys, you better buy some 910 Cs, you really don't want to. So we tell them, oh, if it's for sensitive government use, you'd rather use 910 C's.

Starting point is 02:11:16 So we only see strong encouragements, not full-on bans yet. And we've seen the same game with CPUs. Ask Intel how it's going. I mean, Intel in general, but also Intel CPU market in China. The government also started encouraging there, basically, can you please use homegrown CPUs? Yeah. Right?

Starting point is 02:11:34 So we've seen it all over. Yeah, I mean, it would be super easy for the Chinese government to import some crazy tariff, level the playing field more that way, like even ban the H20 importation. Like there's so many different levers that they could pull. And the fact that they've stopped, they've only gone as far as like strong encouragement. We've kind of inflated that to be like, it's political incorrectness. Yeah, if people inflate to be like it would be insane, it's suicide to not to go against a recommendation from the, from the CCP. But it does feel like they could have gone a lot further very easily if they wanted to.

Starting point is 02:12:08 So we'll have to see. I mean, it'll show up in Nvidia's earnings, right? We'll see. Or we'll probably get data. So we'll have to have you back on that. but thank you so much for stopping by great to see you hope you have a great weekend we'll talk to you same to you talk soon take care and if you're looking to get some sleep this weekend get an eight sleep a pod five they got a five year warranty and 30-night risk free trial free returns free shipping

Starting point is 02:12:29 gordon i was going to say john exley has landed he's landed yes let's hear it for john xly welcome back to the stream thank you joining we have we got to pull this up uh trump and putin are meeting right now and I have a video in the chat team if we want to pull this up very cool look at this John so Trump and Putin are walking and what do you see whoa oh that'll flyover that's a show of force where are they that is wild yeah what what a display of force I wonder I wonder where they're meeting is they're in Alaska Alaska okay that's sort of neutral ground I guess it's technically America but yeah flying the bottom we got our bears there yeah that's another they should they should have a bunch of you know codiac bears stamp peace to meet

Starting point is 02:13:23 uh Alaska anyway it'll be interesting to see what comes out of that hopefully it's a resolution of the ukraine war i mean like trump has been you know talking a big game about uh being anti war wanting to know more foreign wars no don't send all the money overseas and and save that for the taxpayer Say that for real estate deals, baby. We could be building, you know, golden skyscrapers in America with all those drones we're sending, but we'll see where it goes. But hopefully a peaceful, a peaceful resolution. We will see.

Starting point is 02:13:54 Well, next up we have David from... Addquick, adquick.com, out-of-home advertising made easy and measurable saying about the headaches of out-of-home advertising. Only AdQquick combines technology, out-of-home expertise, and data to enable efficient, seamless, ad buying across the globe. And we do have our next guest here. Welcome to the stream. Welcome to the show.

Starting point is 02:14:11 Thank you so much. What you got for us. Jordy's warming up. He's got the mallet ready. He wants to hit the gong. It's the first one of the stream. You got some good news for us? Yeah.

Starting point is 02:14:24 Yeah. Web AI. We're working on some pretty interesting things. Just recently we announced our new knowledge graph mechanism, which is out benchmarked all of the best models year to date. by how much uh 7% 7% let's go there we go

Starting point is 02:14:49 we like to hit the gong for big numbers we like to hit the gong for big fundraisers we also like to hit the gong for for improvements benchmark maxing yeah no no fundraising announcement today soon soon i can't i can't leak it today well we'll be refreshing uh our for rocks account but you have in fact raise money yeah talk about yeah And that's gong word.

Starting point is 02:15:09 Talk more about the genesis of the business, why you started it and, yeah, what got you guys here. Yeah, yeah, absolutely. So WebAIs really focused on building models that can live on devices, like the ones on your desk, right? So the genesis, the company really started working. Like on a watch or? Yeah, absolutely. Yeah, absolutely. All of it.

Starting point is 02:15:35 Yes. So company started by working in computer vision. And we were working on how could we take like the YOLO models, if you guys are familiar with those, it was in the early, like, 2016 era. These were like the biggest models because language models weren't really mature yet. And did early work there, ended up creating our own runtime engine, so our own AI library and our own network protocol. And what this enabled is us to run state-of-the-art AI models across devices distributed. So when you think about the future of intelligence, we really believe that. that civilization model is the most likely outcome

Starting point is 02:16:11 for super intelligence. And what we're building is the rails for that. So we serve and distribute models across hardware. So we're running some of the world's largest models today on things like a laptop. So when we say we out benchmark like Opus 4 or GP5 in knowledge retrieval, that's happening on a laptop. So it's a pretty significant breakthrough in modeling.

Starting point is 02:16:33 And we're doing this in lots of different industries. But what we believe is going to be, a big step change in, you know, unit economics for AI as well. It's just not there in the cloud model. Seems very important because all week we've been talking about gross margins or the lack thereof in a bunch, you know, a bunch of these different applications. In France is basically free when it happens on device, right? That's the goal. Yeah. And you can do some things that cloud players can't do, right? So part of the way we're getting this accuracy, like there's always like this no free lunch, Right. So why wouldn't, you know, Anthropic do what we're doing to get this huge accuracy retrieval bump? Well, it's RAM intensive. So if we're distributing across devices, we can arbitrage, right? So we can say, okay, we'll pull more RAM because we're inferring on a device. But if you're hosting this for a million users on NVIDIA, you can't do that. You can't load, you know, additional RAM resource for every user. It's just not efficient. But there's there's, there's, there's, there's, there's, there's,

Starting point is 02:17:36 real things that happen on the edge that unlock, I think, technological paradigms in AI that are more meaningful, like more accuracy, more context, all of that. And we're seeing that in real time. What about privacy, too? Absolutely, right? So in our stack, everything's downstream only. So when we partner with the group, like we work with the ORA ring, if you know that company, we're doing the AI for them. And think about health data. Like, you want that to be private. So the dream there is how can we facilitate personalized models for millions of users that never leave their device react to this post from take kim author of the invidia way says here's what i would do if i was the ceo of apple quadruple the ram and iPhones to 32 gigs have the max model at 64 gigs

Starting point is 02:18:22 memory is oxygen for local on device AI more equals smarter and more powerful take the margin hit memory isn't even that expensive what do you think i think i think i think memory I think he's right. I think memory is fundamental in these models. I also think we need to tread lightly on this idea that we're retooling infrastructure and we're making all these big bets on hardware with, frankly, a pretty immature algorithm. Transformers are not necessarily the winning algorithm. So I think we need to be cautiously optimistic, but we need to continue to work on what's next. Like, I just, you retool based on all of these factors and an algorithm changes.

Starting point is 02:19:06 And we don't know what the long tail of hardware is going to look like. And InVidio was really relevant because pre-training and all this, but now pre-training isn't really happening at the same level it used to. And I think generally more RAM is a safe decision. But also, I don't know if I would jump in and like totally rewrite how we're building chips until we know that this is architecture we want to stick with would you recommend someone buying a new mac max it out and get the most memory yeah absolutely absolutely just yeah why not why not um what about diffusion models do you think that there's a chance that they have a comeback we saw that demo from google where they

Starting point is 02:19:45 were doing uh text uh like token generation through a diffusion model felt kind of like a wild card scenario i don't know yeah it's actually performing on benchmarks but seemed like uh a path a path in the tech tree that was kind of, you know, more or less forgotten, relegated to image generation, but then kind of making a comeback maybe? I think there's lots of things that have been unexplored, relatively speaking. We spent so much time on Transformers, but we haven't spent equivalent amount of energy and dollars on other architectures that we know work. And we know they work at specific things, but there's typically a broader application.

Starting point is 02:20:20 I think it's really interesting. I mean, we're working on new architectures today with both like the public sector, as well as the private sector. And we're seeing a lot of breakthroughs that I think make the transformer look a little old. Oh, interesting. How do you think about the business model here? Because you're not going to be selling hardware

Starting point is 02:20:42 to an OEM in the supply chain, but you're also not an API, so you're not pricing on consumption basis. It feels like there's a world where companies are comping you to an open source thing that they have to implement. Like, how, how, like, what does a great relationship with a big device manufacturer, like, edge computing provider look like for you? Yeah, I think, I think WebAI, one, we have a license, right?

Starting point is 02:21:09 Because we have a proprietary tech stack. We're not a rapper. We appreciate rapper companies. We think they're doing cool things. But we own our stack pretty vertically. So we own our runtime, our AI library, and our tooling around that. And so when we work with a partner, we typically structure. a base license minimum. And when we have that, when we have that license, we can, you know,

Starting point is 02:21:32 inject forward deployed engineers to work with these companies that honestly just don't have the AI talent quite yet. And they need help. And I think that's something that people aren't talking about is, you know, like these products don't necessarily solve a problem out of the box. A lot of these enterprises like Fortune 100 need help. And so we do that. And additionally, there's a way to take part in the success and the deployment. So the usage fees we can get, even though we're on device. So because our network is managing that. So you can imagine Web AI you have two and a half million custom devices or maybe it's an iPhone and we're shipping across that. Our network manages all of that. So we collect fees on that.

Starting point is 02:22:11 So it sounds like it's somewhat case by case but you could imagine charging like a per device license but also like a per token license in the future. Her answer is typically how we structure it. So it could be a book. It could be a one word answer. as long as it's an output that's solving a problem. We mostly work in mission critical use cases, like things like reassembling engines with multimodal AI, health diagnostics, public sector work. Yeah. How quickly are you going to kill Jordi's battery if you're doing test time inference on device?

Starting point is 02:22:47 He's been already complaining about the iPhone not having enough battery life, but it feels like there was a glimmer of hope when we were just like, let's just distill the models. and it'll just be like a pretty short inference chain. But if you're, even if you distill the model, if you're inferencing for 10 minutes, that feels like a lot of heat in my pocket. Well, I don't know what Jordy is using. I would assume it's a pretty nice phone.

Starting point is 02:23:13 It's like an iPhone pro. Yeah, it's the latest. Yeah. Yeah. So, I mean, you mentioned quantizing. So I'm going to talk a little bit about that and what we're doing there. So we released an open source paper around a tech

Starting point is 02:23:26 that we were building early. that we've now expanded and it's a little, it's more sophisticated now, but the principle's still there. It's called EWQ. And instead of just quantizing, and tell me if I'm going way too tactical here, quantizing traditionally, you have like a fixed value.

Starting point is 02:23:41 So we have, let's say, you have a full precision model. And when you quantize something, you say, okay, I'm going to quantize it to four bit, or I'm going to go to 16 bit. And so you're just drastically chopping the model down, right? So from the float values that it can pass through. With EWQ, what we, do is we have something called device profiling. So when a WebAI model hits your phone, it's running

Starting point is 02:24:04 our webframe library, and it profiles your hardware. And then what we do is on inference, we run EWQ. And what EWQ does is it does real-time quantization. So based on your question and the inference, and what it leads to is close to 30 to 40% model reduction size in RAMP while retaining accuracy. So what that means is we get bigger models inferring. And instead, of like this one size fits all quantitation, we dynamically do that on inference. And what that leads to is less energy consumption, higher accuracy, less usage on the device. Yeah, so somewhat similar to the model routing that we're seeing in chat GPT now. What were your overall reactions to GPT5? It's just an MOE router. I was kind of hoping it was a new foundational model.

Starting point is 02:24:52 And when you interact with it, it's really clear that it's just a way to dynamically control price based on a question. So, like, you ask a question, they route you to a different model. If it's coding, it will route you to a different model. I can see where that's valuable. I have a lot of people that are non-technical that are in my life, and I've watched them now switch off of GPT after the five release to things like ROC, which is kind of shocking to me. But I think people were used to a certain standard of response and now the lack of transparency and picking the model you're engaging with, I think created some whiplash. But I'm sure there's areas where it's amazing. I haven't really gotten to tap into everything there.

Starting point is 02:25:37 Been enjoying a lot of the anthropic releases and typically probably tend to lean that way. Cool. Well, thank you so much. Congrats on all the progress. And I hope you have a great weekend. Come back again soon. yeah absolutely yeah we're excited yeah yeah absolutely great to me david thanks for yeah thank you for joining let me tell you about public dot com investing for those who take it seriously

Starting point is 02:25:59 they got multi-asset investing industry giving yields they're trusted by millions folks uh should we go to um what did samma mean by this if we didn't pay for training we'd be very profitable we talked about this uh christen culver says most successful coups in history Napoleon Bonaparte's coup of 18 Brumeir, October Revolution in Russia, 1917, the Nazi seizure of power in 1933, Egyptian coup d'atatat, 1952, the Chilean coup in 1973, and the Open Door Retail Army at Open in 2025. First of worked at Open Door, correct? I believe. Must have.

Starting point is 02:26:42 And so she's having fun. It'll be interesting to see in other news. Yeah, so the CEO stepped down. This morning. Yeah, this morning. So Kerry Wheeler posted on X. Today I'm stepping down as CEO of Open Door. When the board of directors asked me to take on this role at the end of 2022, the company was in crisis, the real estate market was punishing, the business needed a reset, and the path forward was uncertain.

Starting point is 02:27:05 My mandate was clear, stabilize the company and do what was necessary to survive. Of course, I said yes, because I believed in Open Door. It wasn't easy, and it wasn't about glamorous headlines, but we stopped bleeding. We restructured the business, rebuilt an exceptional leadership team, got an NPS of 80. And she says, I'm pleased the leadership team will continue to execute on the vision strategy. I'm closing this chapter with pride, clarity, and gratitude. So good luck. It is wild.

Starting point is 02:27:30 Open doors up 200% in the last 30 days. And the retail army said, no, we want more. They want more. New leadership. Retail traders are crushing it. Well, I'm excited to see where Kerry will. Wheeler goes next. We should watch the new Jason Carmen film.

Starting point is 02:27:50 We have Cameron Schiller coming on the stream in just a few minutes. Let's pull up the latest work from Jason Carmen. I'll be right back. Dear son. Some time ago, one, one, we have the left on. The machines. roared.

Starting point is 02:28:17 The steel bent to our hands. We built for the stars, for our land, and for your future. We went fast. We went far. It made us strong. It united us. It united us. Then, the sound faded.

Starting point is 02:29:06 The hunger to build. To build. Drifted away. Those who knew grew tired. But now, the fire returns. The steel

Starting point is 02:29:55 is ready. The country needs you. New boundaries beckoned. Who will you be? Where will you take us? The stars are calling. Our future is waiting. So will you answer? It's a sick fit, we need one of those. When we're discussing hard tech, we should have gotten a seat today.

Starting point is 02:30:54 Huge missed. Anyway, new video from Rangeview, we have the CEO, Cameron Schiller in the studio and the TVP and Ultrajum. Welcome to the stream, Cameron. How you doing? What's happening? Hey guys. Good to see you. I have so many questions. Are you, did you act in that? Are you in that? I am not in that. That was a big question. You're not in the suit. What? You got it. How I thought you financed this whole thing. I thought you made this happen and you didn't get a cameo. You got to put yourself in. The machine's got cameos. And I believe that last scene takes place at Rangeview HQ. Is that correct? Did I clock it correct? That is correct. That takes place in our technology demonstrator factor. We're running to. We got a production facility. the street which we'll see in some some new videos coming out cool but that was at this facility which we've been at a hour just busting at the seam so we've got a we've got to move and you'll see a bunch of content from that new one that place

Starting point is 02:31:45 is sick they used to build space shuttle engines there that's awesome wow yeah the space shuttle shot was fantastic I mean Jason Carmen he puts on a clinic every time he drops a video what what inspired it what was the message you want to send is this just is this a recruiting film I noticed like the the follow-up post was like come work for us this is not like a an ad that you'll be running to get customers necessarily, or is it just kind of like vision film? What was the thinking? Yeah, I mean, it's really a message to America. I think it's a wake-up call. It's a question of who we really want to be as a country. What do we want to do?

Starting point is 02:32:17 Right? I think, I mean, that was a big part of my life growing up going back and forth to China. And, you know, I saw the American dream in China when I was there. I saw people from the center of the country moved to the coast to work extremely hard and make a life for themselves. And when I came back to America growing up, I just didn't see that here. And I think we have to bring it back. I think for national security reasons, I think, across the globe. So the real question is, you know, can America bring it back? Because we need to make a lot of parts very soon. And this is less so about range view. I mean, America needs a thousand range views. This is about people that are considering making a big pivot in their life to work on something that matters to the world. And when you say

Starting point is 02:32:59 make a lot of parts very soon. Is that specifically like defense tech and warfare? Are you seeing, are you worried about great power competition or is it more like we won't get the next generation of 9-11 or like the next great physical product won't be made without this happen? The one that I care about the most is the second one. But the first one is definitely very real. If you think about it, you know, America did some amazing stuff. The F-117, we invented stealth technology, the SR-71. All that stuff happened in America, and that happened because I think of factory towns. I mean, I'm calling him from El Sigundo. This is a town that literally runs on jet fuel. Like, there is a refinery that's right next door, that's pumping jet fuel out, you know, under

Starting point is 02:33:47 this city to feed to LAX, which is on the other side of the city. And you feel it in the air. Like there's something that happens when a community wants to be a part of something great in the world. And when we look around, everything around us has been made in China now. And with it, you know, with it slipping, I think a great calling to be a part of something amazing has slipped as well. So we really need to bring that back. We're going to do that with parts. We're going to do that with new technologies that enable factory towns all across the country. Yeah, I mean, I think it's super...

Starting point is 02:34:23 What's going on behind you? There's like some scrolling image. What is that? Might be, I mean, we've got a lot of screens in that. Oh, is this a screen? It's like a TV or something? Yeah. I mean, there's a lot of lights and there's a lot of this camera reacts with...

Starting point is 02:34:37 Yeah, yeah. Right, right, right. Yeah, I think what you're... One way to kind of summarize what you're kind of getting at in, from my view, is it's important for American dynamism to not be like a venture hype cycle that's sort of it's it's not something that can be accomplished in two years since you know moving to el caganda became popular and a meme and it needs to endure and who helps with that was it me you jason camera yeah we might have played a role a little bit to do with it but i mean

Starting point is 02:35:14 i i guess the question is like you you say this is like a you know a wake-up call for america like are we not awake? I feel like, I feel like a lot of these, a lot of this message is broken through like like what, what's left to say? What, what, what do we need to? I say it's broken through in the bubble. Yeah, yeah, maybe it's the bubble. Maybe it's the bubble. Yeah, what, I mean, what is your take on like the reindustrialist summit's huge? Like the, you know, the American dynamism summit is huge. Like, like, like people seem to be beating the drum. People are at the White House. They're in D.C. They're a fraction of the size of Salesforce dream force. John.

Starting point is 02:35:49 That's exactly it. Yeah. Are you going to be there? Dreamforce? Let's get you there. This man loves Enterprise SaaS. He won't admit it on camera. He plays this character that he likes re-industrialization.

Starting point is 02:36:00 But really, he just wants to, he just wants to code. Yeah, it's all I want to do. That's all I want to do, John D. No, we need to have more people. It's A, it's inside the bubble, and B, we need to encourage the people that are working on the problems to focus on the things that matter. And that's actually making parts. We need more factories. We need more metal moving.

Starting point is 02:36:18 Moving. metal is the problem right now. There's a lot of people building tools for factories. There aren't that many factories. Yeah, yeah, yeah. So if you want to join, build a factory, make parts move, you know, do real stuff in the supply chain. I'm not talking like screwdriver factories bolting on imported components. That's the vast majority of, you know, assembly in America is like what's left. So we don't need that. We need people working on hard problems. We also need you to 1000x. We need you to 1000x range view. You said earlier we need a thousand range views, but why don't, why don't you just be copy and paste your shell?

Starting point is 02:36:50 I'm working as hard as I can. What is, well, what can you tell us about? Work harder. Well, what can you tell us about the state of the art in, in manufacturing? I know you, there's, there's additive manufacturing, subtractive manufacturing, there's CNC. We've talked to people that are 3D printing metal now. There's casting.

Starting point is 02:37:06 What, what are you excited about? What are you focused on? And where do you think there's still pockets of opportunity? Yeah, great question. So we are working on casting. And we are trying to give casting at CNC moment. Yeah, and explain casting for those who don't. There's a casting. It's liquefying molten metal, pouring it into a mold.

Starting point is 02:37:24 It's solidifying. And you're getting the part that has that shape. And almost everything is cast. It's, you know, even CNC shops buy castings. Today, castings have eroded so much that machine shops are just buying cast blocks. And then they waste a whole bunch of time cutting apart into, you know, into its final part. you know, a lot of chiseling. But if you get really good at casting, you actually just cast 99% of the way

Starting point is 02:37:48 and then touch the final bits up with the drill bit. So there's no one size fits all solution in manufacturing. It's one of the first things you learn. It takes like a hundred humans from, you know, mining the ore out of the ground to installing the bracket on the end of the thing to actually make something happen. And there's a ton of folks.

Starting point is 02:38:04 I think for people looking at technology, they're used to looking at manufacturing is just another sector. You know, there's fintech, health tech, manufacturing tech. The truth is, manufacturing represents more of America's GDP than all of tech combined. And so it's huge. And so inside the manufacturing of all these sectors, and so many have just not been looked at yet or not been touched.

Starting point is 02:38:28 And so we're seeing resurgence. The other thing is, you know, you maybe shouldn't have financed these things exclusively with all venture capital because the risk profile just isn't the same in the factory, right? Like if my factory burns down, I'm going to still have, you know, 1,000 pounds of super alloy. You know, maybe the crate that it wasn't caught on fire, but like, they're not going to move, right? So you should have, it's not risky. It's not a risky bet. So you shouldn't buy that stuff for that.

Starting point is 02:38:51 So I think there's a whole new level of financing that's going to come in. And you see this happening with a few of these big factory companies where you're getting really smart finance deals, where you buy the technology improvements with venture capital for those returns. But the rest of the factory is finance in a different way. Yeah, that makes sense. If I were to pull a hot take out of you based on what you just said, it sounds like potentially the American manufacturing. industry has over-rotated towards subtractive manufacturing and needs to rebuild additive manufacturing or casting capability. Is that like roughly a reasonable take that you... Additive and casting are not the same. Additive is like this SPAC machine that's blown

Starting point is 02:39:27 up actively as we see. There are a few amazing people doing additive. For the most part, like it's missing on qualification and it's missing on real unit economics at scale, which is as a whole that's what America's missing, like really being able to build stuff at scale. If we had to triple the manufacturing output of the country, we'd be cooked. Totally cooked. Like, it would take us five years to get the factories up to do that. And all the factories that would start would be sending the money overseas because none of this equipment is made in America anymore. We lost the factory industry, but we also lost the factory and machine tool industry. So all this stuff just goes overseas. So I wouldn't say that additive is, is it, I think casting is really important. A lot of

Starting point is 02:40:02 these traditional forms of manufacturing are really coming back and making a big play. But we should just be encouraging everyone to make a lot of parts like we we need so many parts and we need to get started immediately parts maxing talk about your dad talk about the influence there jason tased it a little bit but i haven't heard the story yeah yeah he's a big big part of uh big part of my life um he's always encouraged me to be very very honest and and real about uh about this this world which i think is really important adventure um and he he was a maker himself um you know his family was Pittsburgh and he There's a, you know, Midwestern family values, and they, you know, they, he came here to work on the B1 Bone. The Super Sonic Bomber was pretty sick.

Starting point is 02:40:47 And then I ended up growing up next to where Skunk Works was founded. So, you know, Bob Hope Airport, actually, yeah, for one said, all that stuff happened there. And then it went out to Palmdale. And then it became a service-based industry. Lots of B2B SaaS and entertainment happened in the area. And it really changed. But he always, you know, kept me, kept me centered. And he's a huge influence on my life.

Starting point is 02:41:08 And actually, same with Jason's dad. So we bonded over that a lot. And they're becoming increasingly large parts of both of our lives. Can you raise like a billion and then run this ad as a Super Bowl ad? You guys want to help me? Yeah, we got to get him back on the venture training.

Starting point is 02:41:25 Cameron's always very like, oh, anti-venture, but we need to run this film as a Super Bowl ad. Spack Rangeview, come on. We can bring your own. Just to get the capital for a Super Bowl ad And then you can figure out to take private. 10 years of Super Bowl ads, run it every year. This is not going to happen overnight.

Starting point is 02:41:43 Yeah, I'm in. Let's talk about it. Let's make a game plan. Fantastic. Well, thank you so much for hopping on. Congratulations. We'll talk to you soon. And where can people go to apply for jobs?

Starting point is 02:41:53 I know that that's important right now. Rangeview.com, scroll down careers. Rangeview.com. You heard of here. Thank you so much for having on. Have a great weekend. We'll talk to you soon. And I will talk to you about Bezell.

Starting point is 02:42:05 You want to manufacture something? manufacturer or yourself a watch on getbezzle.com. You bezel concierge is available now to source you any watch on the planet. Seriously, any watch? Any watch. They got them all. Well, I'm very excited for this next. Well, okay, so there's, I was going to, I thought we had our friends over at NFM live.

Starting point is 02:42:26 They will be coming on in just a few minutes. But we will be joined by Surak or Surac. Syriac. Siriac. Good to meet you. Thank you for joining the stream. Why don't you take us off with the introduction? on yourself and the company.

Starting point is 02:42:39 All right, well, I am Syriag from Early. Early is an early cancer treatment company. And essentially what we do is we create genetic constructs that are injected into your body. And they disperse everywhere in your body. They enter healthy cells randomly. And if you happen to have cancer cells, they will also enter those.

Starting point is 02:43:04 But only if it's cancer, These genetic constructs will switch on like a light switch, and then they turn the cancer cells into little factories that are forced to make any protein of choice. In other words, you can make something that makes the cancer visible, or you can make something that activates your immune system to attack and kill the cancer. So the whole thing is relevant because in the last 50 years, we've always tried to find some markers on cancer cells that make them detectable or drugable, right? Billions of dollars have gone into that. And yet we still have 600,000. Yeah, we still have 600,000 people dying from cancer in the US every year and 10 million globally. So something needs to change.

Starting point is 02:44:02 What's the background of the company? Is the tech transfer that's come out of an academic lab? What is your background? Yeah, I'm actually not a biologist. Out of 35 people, I'm like one of two or three people who don't have that background. I'm an engineer. I'm a serial entrepreneur. And the idea came out of Stanford University.

Starting point is 02:44:20 And it was one of the world's top people in early cancer detection, who then himself sadly passed away from cancer. Wow. Including his own son. died at 16 from cancer and his wife died two years after him the whole family is wiped out so i met him was that out of curiosity was that environmental exposure or no no no it's mostly genetic and the the mother had a genetic a genetic mutation that then got transferred to the son and what sam gambier died from the inventor of the whole thing is unclear to this point it was

Starting point is 02:44:58 It was a cancer of unknown origin. You didn't even know where the primary tumor came from. So a very tragic story, but he was committed to flipping the tables against cancer. So I don't know if you guys have Jordy or John, whether you have anybody in your family or in your friend's circle that has been affected by cancer. Yeah, of course. You know, it's just kind of crazy that we are always behind. a step behind or two steps behind we're always trying to find the next marker that we could hook

Starting point is 02:45:34 onto so what if we could stop looking for any marker altogether what if instead we could force the cancer to reveal itself and make its own therapy to kill itself so what's the pathway to commercialization imagine you have to go through FDA approvals at some point yeah we have to go through a phase one, two, three trial, and then to commercialization. And we have spent the last seven years cracking this really hard problem. You know what the biggest problem is in cancer? What's a cancer cell and what's not a cancer cell? Yeah, of course. Because, you know, different from a virus, this is your own cell that has changed just a little bit. And so differentiating that from a normal cell or from something that looks like cancer but is totally benign, is really hard.

Starting point is 02:46:31 And that's what we've spent so much time and energy on with AI. We're essentially producing AI results, liquefy them, put them into the body into a cancer drug that then forces the cancer to produce its own therapy against itself. And what's the latest news with the company? Well, we just raised $44 million. Congratulations. We have not cheap work you're doing. Sounds expensive. Yeah, biotech is not cheap.

Starting point is 02:47:07 So, you know, I don't know how much you know about the biotech world. It is in the biggest funding crash in the last 20 years. On both the public side, the private side, I know that the government funding is certainly at an all-time low. but that's right across everything actually you net you named them it the private funding is extremely low because of two reasons high interest rates which immediately affect a long running product like bio takes 10 to 12 years right and then AI is like a vacuum cleaner for money it sucks up all the money that goes to tech firms because for VC companies many of them believe they can make a faster return by putting it into AI

Starting point is 02:47:51 classic tech, but bio and AI is a great interface that is now coming to fruition. And then the pharma companies, they are concerned about tariffs. They are concerned about China catching up to the U.S. and they start buying ideas and drugs there. And then the government is not stepping in to flatten out the curve. And here I would actually say, we really got to make a national commitment to biotech to flatten out this funding curve because, you know, at the end of the day, would you like to be dependent on China providing the most developed life-saving drugs

Starting point is 02:48:30 for cancer, for autoimmune diseases? Do we really want to depend on that? I mean, it's good if they supply them, but what if they don't one day? So we should actually have a national commitment to biotech to make it, to retain the world leadership that the U.S. has had for, last 50 years yeah good point uh well thank you so much for stopping by have a great west rest super important work and uh have a great weekend and congratulations we'll talk to you soon thank you talk soon bye bye cheers we have some major guests in the restream waiting room let me tell you about

Starting point is 02:49:05 wander first wander find your happy place find your happy place book of wander with inspiring views hotel great amenities dreamy beds top-tier cleaning and 24-7 concierge service it's a vacation you know but better well joined by this is the moment all been waiting for they're calling it the brothers welcome to the show you guys look fantastic we got headphones on let's go how you doing yeah yeah give us some energy come on come on what time is it in time is it at us yeah it's five oh five 50 in the morning in the okay so we're just waking up here here i'm gonna help you guys i'm gonna help you guys wake up There we go.

Starting point is 02:49:52 There we go. Thank you. Thank you. So, talk to us. How has it been going? How has it been running the show? What inspired you? Obviously, you know, TBPN inspired a little bit,

Starting point is 02:50:06 but have you been working in media? What's the background story here? Yeah, give us life stories. Yeah, so both of us coming from venture capital backgrounds. We've been based in Seoul for over like four or five years. So yeah, we love this industry, you know, private market, VC tech, startup, this whole industrial complex. And we thought that it's something, you know, we could do above just, you know, pure investment. And, you know, media could be the, like, perfect complementary medium.

Starting point is 02:50:37 So, I mean, you know, anyway, we were doing our own thing, you know, like running our own, like, running our own, like, blog and, you know, writing assays, like, since a few years ago. ago and this guy here, Songzhung, he actually, you know, with his friends, is running one of the biggest, you know, VC newsletters in Korea. And, you know, I'm running my own blog too. So, you know, earlier this year, we thought that, oh, you know, podcasts could be the most optimal medium to reach your, you know, the wider audience and also to reach the global markets. And we found you guys randomly on the feed.

Starting point is 02:51:09 Yeah. Oh, yeah, this is the shit. This is the, this is the, this is the, we got a, we got a, yeah. Yeah, so, you know, of course, you know, we, if there's anything, we want to benchmark from the U.S., it's not all in, you know, it's not the boomer institution, you know, like, medium, so, you can you do. So, so what's your, what's your guys' schedule? Are you, have you quit the other stuff yet? Are you going all in? Are you just putting, how much time are you putting up? Is it three hours a day? Do you have multiple guests? Like, like, what, what have you taken from the show? What, what's working? What isn't, what needs to be different to secure? succeed in Korea? So I would say, so okay, first of all, so we're like running like three times a week.

Starting point is 02:51:55 So we will ramp it up. You got to get those numbers up. You got to get those numbers up. What are people going to do on the other days a week? Yeah. They respect to just twiddle their thumbs. Does the Korean tech economy not function five days a week? 24-7?

Starting point is 02:52:10 Okay, but we're going to ramp it up. I'm letting you check us out in like six months. We might be running like seven days a week. Who knows? Let's see it. I love it. Yeah, yeah. So anyway, yeah, you know, the Korean tech market is as vibrant as, you know, as the U.S., I would say.

Starting point is 02:52:25 But, you know, like, but, you know, we are just kind of like, you know, being the frontier in this, like, you know, hold a new media and like this, like, you know. Well, in many ways, we're old media. Yeah, we are old media. This is just television. You say that? It's just TV. Is it? Talk to me about the.

Starting point is 02:52:45 guests do you have dream guests who's the palmer lucky of of korea who's the elon musk of korea who do you want to get on who have you had on what what uh we have a lot of venture capitalists but then we have analysts politicians we've kind of gone all over the place uh where have you had success uh doing guest interviews or are you even doing guest interviews yet you believe you are right so we're in the very initial phase you know so um we've only embody a lot um so you know only a limited number of guests but so far we have some you know like uh DMs, engineers, also venture capitalists, also authors who just published books. But, you know, we want to have, actually, we want to bring in everyone, you know,

Starting point is 02:53:25 everyone VIP, you know, even the president, you know, like, like, you know, like, even Trump, who knows. So we want to bring you guys in our show. Yeah, we'd be happy to. Let's do it. Let's do it. Well, you make us wake up at 5 a.m., I guess. We do. We're ready.

Starting point is 02:53:41 I mean, I mean, that wouldn't work time zone-wise, but it'd be more like, instead of going to bed, we'll pop on your guys' show. Yeah. Are you guys live at 11 a.m. local? It's like 6 p.m. on L.A. 6 p.m. in L.A.? Oh, yeah. Yeah, we can do that.

Starting point is 02:53:58 Dinner time. Our wives will be very happy we're bailing on dinner to go on the N.F. What's the Open AI of Korea? Yeah, what's the hottest company? What's the one that everyone's focused on? S.K. Hynix is obviously like later stage, but what, who is ascendant?

Starting point is 02:54:15 Okay, Open Air of Korea. Okay, we got a best treasure here. It's tough. I would definitely pick, you know, in terms of like, you know, semi-conductor business, SKHionics, Samsung, semiconductor, of course. And also we got some, you know, like Hasha Korean developers at Open AI. So, you know, like, how do you say, how do you say cracked engineer in Korean? Like, like, you know, like, you know, like, a, you know, like, a, you know, like, a, you know, like a, I can hear that.

Starting point is 02:54:45 yeah yeah the team loves it the teams loves it uh that's great anything else do already no this is great uh we're we we we love what you guys are doing um and uh happy to come on the show and uh have fun have fun out there and you guys look sharp too thank you for for um for make you know copy and pasting the suits as well yeah this this is one in this book from you guys but you know like uh as as we want to you know like make our own path and only you know from here on so um yeah we're gonna build our own brand this is nfm live and fm live love it well we support you guys enjoy thanks for coming on we'll talk to you soon thank you good stuff good stuff lads they they're also pretty well positioned to cover defense tech

Starting point is 02:55:37 korean uh south korea obviously has mandatory military service I think most people kind of interrupts college. They kind of take a break from school, go serve, then go back. So anyways, glad that we have contact with the Korean market. Yes, yes, definitely. Last post, close it out from Andrew Reed. I knew you were going to pull this one out. These shoes have gotten an obscenely high market share while accumulating zero aura.

Starting point is 02:56:05 What are these? These are, I think, veilas. I never heard of this. wouldn't, wouldn't, uh, definitely came, you know, kind of a, he's just taking shots left and right. Uh, I think they're vehah, vehahs, uh, vehaz, uh, they had a pair of these at one point. You did? Yeah, they were very much just like, shoes to me. Number one question on, on Google, why is vea so popular? I mean, I wonder if the business is doing well. I wonder if they figured out some sort of distribution, some arbitrage, maybe some, uh, I don't know, are they

Starting point is 02:56:38 more D to C it does seem like a newer brand and I certainly do founded in 2004 okay so headquartered in France France interesting and yeah I don't know I mean I think they just kind of tapped into the common projects sneaker era well that that was just like the definitive white like a sneaker right but common common that was the gap in the market no one to create a white sneaker i mean a white leather sneaker that was that was not from a no no no but not sportswear that's a key thing not like basketball themed streetwear right something that was versatile but uh but yeah i wouldn't uh wouldn't be those wouldn't be cut dead in them those would be or farming you if you put them off yes yes you got to be careful not to get aura farmed by your own

Starting point is 02:57:32 clothing it happens sometimes it happens the best of them but i'm happy for veha's success i'm happy for their success overnight success 21 years keep it going anyway that's our show thank you so much for listening and watching and enjoying the debate we will see you on monday leave us five stars on apple podcast and spotify can't wait and thank you i cannot wait i cannot wait for monday i was i was i can't believe we get to do this again and i figured it was friday no you really did think we still had you thought today was thursday i thought we were a day behind and i thought we still had more time but well have a fantastic weekends folks we love you see you bye Thank you.

TBPN Live - Slop vs. Steel Showdown w/ Delian & Everett, GPT-5 Backlash, Trump Eyes Intel Stake | Bill Bishop, Jimmy Goodrich, Lennart Heim, David Stout, Cameron Schiller, Cyriac Roeding, NFM Live

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