TBPN - Weekly Recap: Grok 4 Launch, Texas Floods, Web Browser War, Top Signals, Meta Smart Glasses

Episode Date: July 12, 2025

(00:00) - Intro (00:03) - Texas Floods Controversy (03:39) - Augustus Doricko (Rainmaker) (31:04) - Top Signals (01:05:09) - Grok Goes Out of Control (01:14:49) - Grok 4 Launch Breakdown (01:48:06) - Ben Thomson (Stratechery) (02:27:59) - Meta Doubles Down on Smart Glasses (02:35:21) - OpenAI to release Web Browser TBPN.com is made possible by: Ramp - https://ramp.comFigma - https://figma.comVanta - https://vanta.comLinear - https://linear.appEight Sleep - https://eightsleep.com/tbpnWander - https://wander.com/tbpnPublic - https://public.comAdQuick - https://adquick.comBezel - https://getbezel.com Numeral - https://www.numeralhq.comPolymarket - https://polymarket.comAttio - https://attio.com/tbpnFin - https://fin.ai/tbpnGraphite - https://graphite.devFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

You're watching TBPN. Rainmaker stands accused of having a role in the Texas floods. This is a very, very sad story. It's on the cover of the Wall Street Journal, not the Rainmaker part. That has been contained on X, but I'll give you a little update on what's going on in Texas. So Texas rescue grows urgent as toll mounts. At least 70 were killed in weekend floods as more bad weather complicates the search. The search for swept away, for those swept away by punishing

flash floods in central Texas over the holiday took on new urgency Sunday as the death toll climbed to 70 and nearly a dozen girls from a private summer camp remained missing. Rescuers combing the swollen banks of the Guadalupe River were holding out hope that survivors might still be found. The potential for more bad weather Sunday also loomed over ground and air operations. The National Weather Service warned of more rainfall and slow-moving thunderstorms that could create flash floods and in the already saturated. In the already saturated areas in the Texas hill country. So this blew up on X and people were asking Augustus did Rainmaker, was Rainmaker operating in the area around that time? Cloud Seeding Startup Rainmaker

is under fire after deadly July 4th floods in Texas. CEO Augusta Jericho, who's been on the show multiple times, will join us today at noon to break it down. He's already explained his side of the story on X several times, but we will ask him a lot more questions. He says the natural disaster in the Texas, Texan Hill Country is a tragedy. My prayers are with Texas. Rainmaker did not operate in the affected areas on the third or fourth or contributed to the floods that occurred over the region. Rainmaker will always be fully transparent and he gives a timeline of the events. He says overnight from the third and fourth moisture surged into hill country from the Pacific as remnants of the tropical storm bury moved across the region at 1 a.m. on July 4th,

National Weather Service, which we work closely with to maintain awareness of severe weather systems, issued a flash flood warning for San Angelo, Texas. Note summer convective cloud seeding operations in Texas do not occur during overnight hours. At 4 a.m. on July 4th, NWS issued a life-threatening emergency warning and flooding insured. He says, did Rainmaker conduct any operations that could have impacted the floods? He says, no. The last seating mission prior to the July 4th event was during the early afternoon of July 2nd when a brief cloud seating mission was flown over the eastern portions of south central Texas and two clouds receded. These clouds persisted for about two hours after seating before dissipating between 3 p.m. and 4 p.m. CDT. Natural clouds typically have lifespans

of 30 minutes to a few hours at most, even with the most persistent storm systems rarely maintaining the same cloud structure for more than 12 to 18 hours. The clouds that were seated on July 2nd dissipated over 24 hours. I have that I'm sure. he'll have answers to is why do cloud seeding operations in the immediately before a massive storm is coming through? Yeah. That's the question that a lot of people have. But we will get into that when he joins the show. Yeah.

I mean, there's a big question about how effective is cloud seeding. Could you start a flash flood if you tried? Does this work? Someone was paying for this because it's not a nonprofit. like obviously I believe it was state level state level so the state might buy cloud seeding operations in one way there could be you know mistake he says that he's not involved at all so we will dig into that with him our next guest is here Augustus de Rico the CEO founder of Rainmaker welcome to stream

Augustus how are you doing uh John Geordy thanks for having me I am doing well I'm obviously talking to a lot of people about the flooding that's gone on in Texas and and appreciate the opportunity to clarify that Rainmaker and Cloud Seating had nothing to do with the flooding that unfolded. And even in spite of that, I think that it's a tragedy that it did happen and certainly don't want anybody to use this opportunity, use this controversy to blame cloud seeding for the sake of popular political support. And you may have seen that Marjorie Taylor Green is proposing running a bill to ban all forms of weather modification based on those that we saw in the Florida State House legislature earlier this year. I think it would

be both disrespectful to the families involved and baseless and without any technical or scientific credibility if that legislation were to go through. So I'm happy to talk about the course of events, what Cloudisina is, what it's not here with you today. Yeah, let's kick it off with the high level on what actually happened in Texas, where things stand now, the status of the rescue operations, and kind of the timeline that's more broad. Yeah, absolutely. So this phenomenon of this flooding was global in scope. It was referred to as a low probability high impact event.

I encourage people to go to Matthew Capucci on X. He gave a great outline. He's a meteorologist that has a lot of expertise on severe weather forecasting. But Tropical Storm Barry, the remnants of which blew into Texas, was going to cause inordinate flooding regardless. And that area of Texas is also known as flash flood alley because these events do happen. Now, four trillion gallons of precipitation occurring over the course of just a couple days is pretty out of distribution. But we are seeing an increase in these sorts of severe climatic events over time and especially down and around

the Gulf. So just to go over the timeline after having clarified that it was the remnants of tropical storm Barry and the conversions of large mesoscale. phenomena that induced that flooding. It was at about 1 a.m. on the fourth that the National Weather Service issued a flash flood warning. And then it was at about 4 a.m. on the 4th where they said that there was a life-threatening emergency underway. It was over two days prior that Rainmaker had suspended all of its cloud seeding operations

in Texas because, one, our forecasters and our meteorologists saw that there was going to be the severe weather event, and we need and operate to produce more water when there was already the event coming. But two, we suspended operations in accordance with the Texas Department of Licensing and Regulations suspension criteria, where if there is a severe weather warning from the National Weather Service or there is too much saturation of the soil, we have to ground operations. So we do so both voluntarily and in accordance with existing statutes. Okay. So the cloud seeding operation that happened prior. to the storm, who was the client?

Like, I mean, I assume someone was paying you. Sometimes it's the government. Sometimes it's an individual or farmer or business. Walk me through where they were, who they are, what their goal is by procuring your services. Sure. So it's obvious that at this moment in time, that region of Texas does not need more water. However, throughout the Western United States, farms, conservationists, governments concerned with their aquifer supply of water and also reservoirs for both industrial and residential drinking water,

contract with Rainmaker to produce more water via cloud seeding. And in the case of Texas, the South Texas Weather Modification Association, the West Texas Weather Modification Association, and multiple other entities exist as conglomerations of both counties and individual farms that pay for cloud seeding services to, one, water their crops, Two, fill up the reservoirs that they irrigate their crops with. And three, recharge the aquifers like the Obolala that has been severely drawn down and then puts all of these farmers at risk of not being able to grow,

not being able to do business because of a historic drought. Okay. So would the proposed ban just because what I'm getting at is like I'm wondering if like if the government is paying for cloud seeding operations like the easier lever might just be to decrease the funding to the government, but it seems like Marjorie Taylor Green is pushing for some other legislation that wouldn't just be, hey, buy less of this service because we don't need it. And instead, this service should never be bought at all. So why is there the distinction there? Like, is most of the money that's going into one of these associations,

uh, private farmer capital or is it a split? Like how, how does that actually breakdown. So right now it's largely public municipal money that is going into these weather modification programs to increase water supply when there is drought or in preparation for drought. The bill that has been forecasted that has been proposed by Marjorie Taylor Green would wholesale ban all forms of weather modification, be it cloud seeding, solar radiation management, or what they're supposed to be chem trails. I mean, very transparently, I think that a lot of the concern around weather modification is actually conflating baseless notions of chemtrails with a very practical American technology that can and will and does benefit our

farmers, our ecosystems, our industrial water needs, and our residential water needs. If this legislation were to go through, not only would it deprive all of those interests and all of those Americans from having water from cloud seeding, but it would also be against America's interest at a geopolitical level because China recently, I think on the last time I was on TBPN, I talked about how they had a $300 million annual budget for their weather modification program. That as of 2025 has been up to $1.4 billion. That is extremely consequential. And I think that if we were to ban who controls or banning Americans from controlling weather modification technology, that would put us at a meaningful disadvantage. Now, all of this to say, people

deserve transparency. They deserve clear regulatory framework so that they know whether modification operations are safe and being conducted in a responsible manner. And with government oversight and accountability, if ever there are negative consequences to cloudseating, again, there haven't been any in the case of Texas. But I think that the reasonable next steps are to more stringently regulate who is allowed to cloudseed, define what the concepts of operation are that are permissible, define the suspension criteria at a federal level rather than leaving it purely to the states so that anybody that wants to know about weather modification can look at the data and scrutinize it and ensure that it's being conducted safely and also just to build trust because the weather

modification act from 1972 that currently outlines the weather modification reporting act of 1972 that outlines how we have to report to the federal government is you know 50 years old We need more scrutiny on these programs for the sake of public trust and accountability. And that seems like a reasonable next step. That was also recommended by the government accountability office in their report on cloud seating and weather modification earlier this year. What was the scale of the general weather modification activities on July 2nd? Was there a bunch of other players operating? is there generally a lot of players or is it a pretty is it is it a fairly small number of

of kind of service providers that are that are participating in these programs yeah jordy you may have seen uh the prolific hustle bitch on x.com posting about this a little while ago he said that i was the CEO of the largest and most powerful weather modification company in the world um i saw somebody compare somebody was comparing weather modification tech to being saying it was more dangerous than nuclear bombs that was kind of crazy and then I also saw some people just showing like general flight logs of like commercial airplanes like obviously there's a lot I mean I think it's just people have every right to be angry and demand answers it's such a tragic yeah incident but but yeah I'm curious to get into the the scale of you know kind of maybe late

June, early July, what was going on broadly? Yeah, absolutely. So there's one other cloud seating operator in Texas called Seeding Operations and Atmospheric Research, SOAR. They're responsible for operations over the rolling plains weather modification association, which is significantly farther northwest of Kerr County. On July 2nd, we conducted one 19-minute cloud seeding flight, where we released about 70 grams of silver iodide and 500 grams of,

of salt, table salt. That was released at about 1,600 feet above ground level into two clouds that dissipated over the course of two hours after seating them. The amount of time that those aerosols could have been suspended in the atmosphere is less than the time between when we were seating and the onset of rains from the remnants of tropical storm, Gary. And the amount of material that we dispersed could not come anywhere close to inducing the precipitation, the four trillion gallons of precipitation that did come from that event. So yeah. And I'm assuming you guys like have records,

you keep records of like the radar showing these different cloud formations. So you're, it's not just, we looked and we think it dissipated, but it's like you can actually, you have like, you know, basically a map that's live updating.

Is that the right, way to think about it. Not only do we keep records for our own research purposes and operational purposes, but we're required to keep records by the Texas Department of Licensing and Regulation. And those are accessible online, as are the reports on our seating activities. And if anybody is interested in those, then you can ask for them from the TDRR. I'm curious when the flooding happened in Dubai, I want to say it was a year or two ago. Do you? by is known for their cloud seating operations. It's a very dry place and makes sense why they would want to increase precipitation. A lot of people, maybe the same types of accounts that have been

blaming you were quick to blame it on cloud seating. Throughout history, has there ever been any major kind of flooding event that people were able to say, yes, 100%, this was caused by weather, activities, or is the tech not even powerful enough yet to do something like that? So I think that there's probably three points to touch on. The first of which is that it wasn't until 2017 that attribution had been physical attribution of cloud seedings effects had been seen and proven in an academic context. And so with new advence and radar technology, namely dual polarization radar, we're able to much more clearly monitor what the effect from cloud seating is. In previous operations,

it was extraordinarily difficult to see what your effect was because we could not measure the cloud dynamics and the cloud microphysics that were changing as you were seating. So that's the first point. The second point is that, and again, I'm trying to be and will continue to try to be maximally transparent about our operations and historic weather modification, there was something called Operation Popeye during the Vietnam War. where the deliberate intention of cloud seeding was to cause precipitation that would like cause flooding and then impede supply chains on the Hocheeman Trail. Now, the extent to which that was effective because we didn't have good satellite imagery

or dual-pull radar is outstanding. Now, that said, lastly, third point, we have suspension criteria that are given to us not just by the TDLR in Texas, but every state wherein we operate because, if there already is too much saturation of the soil or if there is an oncoming severe weather event that the National Weather Service has notified us not to seed, then we ought not do that to increase the severity of precipitation. So there are suspension criteria because there are limits on what we ought to do with this technology so it's not to cause flooding and only reap the rewards from it, right, for our farms, for our ecosystems and for our national security

interest as well, right? Like if we don't have access to weather modification technology, if we don't regulate this at a federal level and ensure that there's accountability and attribution for these activities, then other people, other nation states could be conducting weather mod in the vicinity of or on American soil without any accountability. And so that's why I am advocating for way more regulatory scrutiny from the federal government for cloud seating and weather mod ops. Walk through some of the history of the Chinese weather modification strategies. We heard about the flooding in Dubai that was kind of unclear. Have there been any notable or confirmed negative outcomes from China spending, I mean you said $300 million a

year or something like that, that seems like a lot of cloud seating. It seems like if there was a surface area where there could be mistakes made, they would have kind of explored that. I remember the pre-Olympics. They were doing cloud seating or just kind of bringing down like the dirt in the atmosphere. And, you know, people kind of learn from that. Okay, you get acid rain when you do that in, in particular. But have there been any case studies from China that we should be learning from in America? Case studies from China with adverse weather coming from their cloud seeding operations.

Yeah, anything like that. Like something where like, okay, they've done a lot of this. They're doing this at scale. They've put, they've done this at scale. If there's going to be rough edges or mishaps, I would have, I suspect that we would have seen evidence of that over there. They would have had an accidental flood or something like that happen over there if they're doing it at scale.

You would expect to have seen it from China. However, you would also probably expect and understand that there are a relatively inscrutable country that does not report on their activities very openly, objectively. Now that said, one thing that we do know about the WeatherMod program that they do have going is that they're planning to build 100,000 ground generators on the Tibetan Plateau. So Rainmaker is primarily using drones for our operations. We also have inherited some ground generators from previous operations. These are essentially air-solizing units on the tops of mountains. They can disperse material into clouds when the clouds intersect those mountain tops themselves.

Is that like a cannon that fires the material into the cloud? No, no. You might recall my initial inclination to use something like that because it is used in China. But no, it's essentially like a smokestack of sorts. It's a very small smokestack that releases those aerosols there. Sure. But in building 100,000 of these ground generators and also using the Wingwong 2 and a bunch of their other military drones for aerial cloud seating, they're turning Tibet into a reservoir, a snowpack reservoir of unprecedented scale that will feed more water into the agricultural basins in southern and eastern China.

And I think that, you know, although again, this is something that needs to be transparently reported on and regulated, depriving American farmers in the West, especially as a congressperson from Georgia, right, where there is not as severe reliance on cloud seating to, produce water would be against America's interest. Judy. I guess, yeah, I'm trying to, I mean, the, the, the, the, my, my question, uh, is, it feels like, it feels like candidly it will be hard to come. It'll be hard to find, uh, any type of allies, uh, in Texas on the ground in Texas, as maybe aside from, from the farmers, but, but I'm curious, um, you know, the various different groups, you know, what the reaction from them has been in terms of,

you know, if they're, you know, the reality is, is water scarcity affects every person in Texas, but only a few people truly feel it, right? It's a much smaller group because everybody goes to their sink, they turn on the water, they turn on a hose outside, they go to a grocery store, there's water, there's produce, it's not something that people necessarily feel and so I'm curious where you know you obviously are going to defend weather modification because you you believe in the many different ways it can have a positive impact but I'm curious who you think the other players that will be on your side as the industry I mean the industry was not in a good spot prior to this

It's in a much worse spot now. And I know you've been flying all over the country, making sure that it doesn't get banned. So I'm curious what you think the kind of coalition that will kind of form around you. Yeah, yeah. Well, so I actually think I'd just from my own experience over the course of the last few days, disagree with the two points that you made, right? Like it has neither been hard to find allies for cloud seeding weather modification in Texas, nor do I think the technology and the industry is positioned worse now than it was prior to this weekend.

And regarding the first point, there are some people that I think are probably not in good faith engaging with this because they have some preconceived notions about chemtrails or otherwise and don't themselves want to scrutinize the data to back up, how our operations are different and beneficial, whereas chemtrails, as they believe, them to be are malevolent. The vast majority of people that I've interacted with online, on the phone, and in person are rightfully curious, skeptical, concerned, some more than others, obviously. But in scrutinizing the data and having these conversations and learning about what cloud seating is, pretty unilaterally people are supportive of it, provided that there is a regulatory framework more stringent than the one we have now that ensures that it's safe.

This is true both of just individuals that are not themselves farmers, but obviously farmers, water managers, government officials too. I welcome any questions that people do have, both online and via email, about what our activities are, what our policy recommendations are. And I'm grateful that there are a lot of people that understand, one, our operations did not contribute to the flooding, but two, that even if there was a flood now, it doesn't mean that there is always enough water. And having access to a technology to produce more water for farms and otherwise would be beneficial. Like, people want a more green, lush country. Yeah, I'm curious.

I'm sure you've spent plenty of time thinking about this, but would there be a way to apply the existing technology you have almost in a defensive way? And, you know, theoretically, uh, it exceed a hurricane while it's still offshore. Something like that. Uh, or, or, you know, one of the issues here, there was just so much water in the atmosphere that rolled over a heavily, you know, populated area. And then it's got, it's, it's, it's gravity, right? It's got to come down. Um, you know, is there an application of the technology that could over time strategically prevent, you know, or, or act defensive? against the conditions that create flash floods?

It's a very worthwhile question for you to ask and for us to ask ourselves collectively. Right now, again, Rainmaker only does precipitation enhancement operations for all those constituencies that I listed before. However, in the past, the United States government funded Project Storm Fury, which was a series of attempts to reduce the severity of hurricanes over the Atlantic before they broke against the eastern seaboard. Again, we didn't have the appropriate understanding of atmospheric science or the radar or the satellite data necessary to appropriately do that. However, severe weather is something that is like a geopolitical risk, a national security risk.

It causes damage and it is fundamentally a physics problem, right? A physics and chemistry problem. Is there technology now that could mitigate severe weather like this? No, and Rainmaker doesn't have it. Is it possible to someday, provided we invest in NOAA, in the National Weather Service, in the appropriate research, into cloud seeding, such that we could reduce the severity of severe weather? Absolutely. And I am entirely in favor of that, provided it is done in a responsible manner. And if we were to ban it wholesale, then not only would we lose access to precipitation enhancement, but we'd lose out on any potential of, at the very least, better forecasting for these systems and warning people early.

but also the even greater and more consequential beneficial potential of reducing severe weather in the future. And so I think that the United States government and rainmaker should and are absolutely interested in mitigating severe weather in a manner similar to Project Storm Fury. That makes sense. I think the PR, what you were getting at, Jordy, like the PR difficulty here is that like when there's not enough water, crop yields are lower, prices. go up, but it's very distributed. Everyone feels it a little bit, whereas when there's too much water and

there's a flash flood and individuals die, you have a very, it's a very emotional, very, it's very concentrated. The pain's very concentrated. And so that's why this story has become so powerful. Normally when normally when there's a natural disaster, there's, you can, you can critique the government for their response to it, but there's not somebody sitting there that, a scapegoat. Yeah. I guess the question is like... It's easy. Yeah. It's, you know, whether it's online accounts that are just engagement farming or it's a politician.

Yeah. You know, the, the concern is that, and your concern is that the industry becomes a scapegoat and America loses a capability that our adversaries clearly care a lot about. Yeah. My question is like we're seeing this bifurcation. It seems like Ted Cruz came out in. support of the idea that clouds eating had nothing to do with the Texas floods Marjorie Taylor Green is taking kind of the other side of that my question is

like these are politicians at the end of the day they're not independent scientists who can we go to who can the population go to for like a truly independent review of this situation like is there is there some sort of independent governing body or are there are there respected scientists that kind of don't have a financial or, you know, political incentive one way or another. How do you think the, the populace should be sad? Obviously, you're telling your side of the story. You're going direct.

You're explaining things. You're laying out the data. But what, what do you expect people to look for in an independent analyst? Yeah. Yeah. So for one, I think that NOAA, the National Weather Service, the National Center for Atmospheric Research, all of those are great third-party entities that can review the information, corroborate the information that we've provided,

provided, of course, that they continue to exist and remain funded. I think that this probably demonstrates why it is important that we should retain some capability nationally to forecast and research the atmosphere, because there should be somebody that's capable of reviewing this to ensure that it's safe. I'll also say, you know, regarding the scapegoat dynamics that exist right now, I've thought about this pretty prayerfully and intently over the last few days. And when there is a calamity of some sort, like I've been trying to think about why people are, say, coming after Rainmaker or angry at Rainmaker.

And I think that when there is a calamity of this type, if there was someone responsible, if there was someone or something that could be held to account, then in holding them to account, you could supposedly prevent this kind of thing from happening in the future. The trouble with the true natural disaster, as this was, is that there is nobody to be held accountable. And that makes the world a lot more tragic because it means that things like this will persist. They will persist indefinitely into the future unless and until some sort of technology could reduce the severity of severe weather. We went through this with the California fires. You know, it was like everyone was searching for like a single person to pin it on. And like it came down to like, you know, some people built their houses the wrong way. And there's some building codes that need to change.

And there's some water rights and water flow. And there's some different general government. We need more goats in certain areas. There's like a million different things that could have prevented this. If they were all working together as a well-oiled machine and had the forethought. But it's a very, very frustrating and difficult situation. So our thoughts and prayers are with everyone who's been affected. But thank you so much for stopping by.

This is fantastic. Thanks for breaking it all down for us. Thanks, guys. We'll talk to you soon. Cheers. We have some maybe terrible news. There might be top signals in the market. There might be top signals all over the place.

We've been building out an internal top signal tracker, crowdsourcing some of them. It's going crazy. And it's a long list. Yeah. We'll get through it. At the top of the list, podcasters have been wearing white suits recently to celebrate the market ripping. Yes. That feels like white suits are actually a top signal.

It's a complete top signal. But of course, there is some good, there are some, the economy strong. We're going to go through Joe Wisenthal's breakdown. Things are not doom and gloom, but there's a lot of crazy stuff. happening and it's fun to dig through. I mean, the first major top signal, Bitcoin all-time high. Yep. You know, that's always, you know, it is definitionally a top signal. So let's, let's go through the list here because it's quite substantial. So this is kind of anonymously contributed through group chats. Of course. We've observed. We're going to catalog it and see if we can turn the tide

of the top signals to ideally. So starting off yesterday, Trump made a post on truth social calling basically celebrating the state of the economy, the markets, you know, just really calling out how many assets are performing well. I have it here. Do you want to read through it? You want to read through it a little bit? Because he basically get through the post and we'll get to the moment. So Donald Trump on truth social truths, tech stocks, industrial stocks and NASDAQ hit all time record highs,

Crypto through the roof. NVIDIA is up 47% since Trump tariffs. USA is taking in hundreds of billions of dollars in tariffs. Country is now back. A great credit. Fed should rapidly lower rate to reflect this strength. USA should be at the top of the list. So low rates are actually just a reward for when the markets are ripping. It's a little treat that we give ourselves when things are great. Yep.

And the White House is posting this screenshoted on acts. The country is now back, says President Donald Trump. Every account controlled by the White House has been on a tear. Some of them, some of the posts, I think, are a little bit low class and vulgar. But others are quite funny. But there's definitely, the memers are in control. Didn't ruin, say, every, like, every politically aligned poster he knows, is like pro-Trump now works for the White House but like you just haven't seen it

because they were like a nons and they just dropped off posting and now they'd be getting death threats so they have to it's even actually more in many ways it's it's more controversial work than Doge maybe yeah yeah maybe it's more under discussed because Doge had this big like question in the media about like you know is Elon doing something that's you know he shouldn't be does he a government employee like what's the relationship between the two and so you know there was a lot of investigative journalism that went into figuring out what's going on with those, who's involved. Yeah, but nobody's investigating the memes.

The social media managers, which is made a big story. They need to be investigating the memes of production. But anyway, so going through my list here, that's great. Eric Trump, a while back said, this is a good time to buy. This was a few months ago on Ethereum. On Ethereum. And then it just went down for months. Oh, really?

And now it's back up. And now it's back up. And he's saying, you're welcome. I do remember Trump. He called the bottom, right? He said, like, now it's a good time to buy generally, and then the market rips since that. He created it, and he called it perfectly. It's wild.

It's finesse. More going down the list. Coinbase, just who we love. But they did their Fortune 500 company, they did update their profile picture to an NFT. Historically, that has been a top signal. I do think their profile pictures. Do you have any experience with NFT profile pictures? You know, I've delved.

I've delved over the years. Yes. And if you look at maybe the moment that I did use an NFT profile picture in 2021, it was maybe only off by one or two months in terms of in terms of the top. I never used an NFT profile picture, but I bought an NFT right near the top. A chain runner? Chain runner. Nice. Which I still own. Which actually I didn't like over invest to get over my skis is a very small portion of that's an asset that will be passed down through your family like I like to find watch. I like to think of it is like a piece of

2022 lore. It's just like a piece of history. But yeah, fun project. And I feel like to some degree, you know, you're not really, it's like a skin in the game question. Like, you're not really participating. You're not experiencing the market unless you're

participating to some degree. But you don't want to get over your skis. And also did the NFT profile picture at a really bad time and had to roll that back. Like there's been a number of like NFT profile pictures that have been like... It is a historical top signal. It could be it could be now just a signal for the start of a, you know,

generational run, new cycle. But historically, it's a top single. So we got to call it out. If NFTs are going to make a comeback because like there's been like crypto has been coming back and a Bitcoin went from what 30 to 120? And FTs will be back when A list celebrities are using them on their Facebook accounts. That was a while. That's the real test. Yeah. X account could see it happening early. Facebook account, original Facebook account. There's got to be a new project then, because I don't think any of the old products

or projects are going to come back. That would be crazy. Although some of them are kind of Lindy. Like, haven't the original... Cryptopunks. Cryptopunks. Those have kind of held their value, but the board apes have sold off like crazy,

but are still expensive, right? It's unfortunate board apes are not in gag gift territory yet. Yes. Because you think, oh, it'll be funny to get, like, your buddy, like a board ape for their birthday. 30k or something but it's like yeah it's like Tyler how what's the floor price of of of board apes I'm I'm interested in now well Tyler looks that up let me tell me on ramp time his money save both easy use corporate cards bill payments accounting and a whole

lot more all in one place go to ramp.com also we don't we never show this out 4.8 stars on G2 with over 2,000 reviews that's great shout out ramp world class another yeah what's got the floor price is like around 10 eth so that's like almost three thousand 30 thousand yeah that's like 30 thousand yeah that's like not a gag gift. Maybe for the man who has everything. Yes. For the man who has everything, great, great gag gift.

It is. Pink elephant. We'll see. We'll see. At Sun Valley. But that, you know, by, by, you know, Christmas time. Did they do pink elephants at Sun Valley? I feel like they should.

Maybe. Maybe. We'll have to ask some of our friends that are there this week. So in other news, Robin Hood, CEO, Vlad, is raising at $900 million valuation for a math foundation model startup. And Vlad and Robin Hood have been on a pretty generational run, but this does feel a bit top signally, right, especially in the context of GROC one-shodding PhD-level math

in the announcement on Wednesday. So interested to follow that one, optimistic, but again, Mathematical super intelligence. Historically, when we've seen CEOs of public companies start ripping second companies and then getting these types of valuations without a lot of underlying revenue, it can end poorly. Andrew Wilkinson is giving stock tips. He hit the timeline today. I'll read through it.

He was highlighting a company historically. a value investor. But this morning... He saw things like the Warren Buffett stuff, right? The Berkshire Hathaway for the internet. Yeah, that's right. He says, there are many ways to profit from the AI boom, but my favorite is I-Ren. I rarely buy stocks.

The private market is way too attractive. But every once in a while, I see something that stops me cold. In 2025, it's Irend. I call it a Picasso I found at a garage sale. The stock is up 54% since he recommended it on my first million. but it's still cheap. Here's the trade in a nutshell. U.S. capacity for energy and compute is highly constrained.

Two, permitting and building facilities takes years. Three, AI scaling laws are continuing to deliver, but even if they don't, tons of compute is required for inference. Airen is a highly reputable, publicly traded Bitcoin miner with massive data centers mid-build in Texas. It pivoted away from mining Bitcoin at these new facilities to instead build them out. for AI training and inference.

Once completed, these facilities should generate in the range of $2 billion in new cash flow. What is this company's name? Iran. Iren. Even if AI completely fizzles, these facilities are highly valuable as traditional data centers or can be rolled back to mine Bitcoin. So it's an AI thesis, but if AI doesn't work out, we can still mine Bitcoin. The entire market cap is currently $3.8 billion.

So Andrew, I don't think this is investment advice, but it's... sounds like it. And interested to see, see where this one goes. But anyway, anytime you see a value investor start trying to cash in on the AI boom, should be a little bit wary. Harry Stabbing's today. Also, like, it doesn't have earnings, right? No, no, no, no. It's, it's, it's turning around $4 billion. I don't think it's ever generated any profit. I mean, it says, Is this 23 million in EBITDA, but in 2024? So I don't think it's like losing that much money. And I guess net income in the last quarter was 24 million.

But the net income to market cap ratio there is 40, I guess. So still pretty hot. Yeah, I mean, the thing here is at the same time, Satya is pulling back on new data center development. It's happy to be a leaser. You have incredible neoclouds. that have deep domain expertise. The IRN team, I don't think, has a bunch of team around running large AI training or inferencing.

Yeah. And so, anyways. Just feels like they're a little bit late to that party because there's already like three or four. Did IRN make the ClusterMax, Dylan Patel article? I doubt it because they're not online yet, right? Oh, sure, sure, sure. Yeah.

Yeah, because Semi analysis does the Cluster Mac rating for all the Neoclods? including the hyperscalor clouds. And I feel like they did not have, let me see. IRN, I don't think is on here. TensorFlow, Wave. There are so many RunPod, Lambda, Scaleway, SMC, Azure, Nebius, together, Crusoe, Lepton, Oracle, CoreWeave, AWS.

So hypercompetitive market, unclear if this Bitcoin miner is gonna be able to pivot into AI training and inference in this, when they're up against the players that you just mentioned. Another top signal. I'm not going to go out and say that this is impossible, but Harry Stebbings is calling for $8 trillion NVIDIA in the next five years. Private markets investor backed a bunch of unicorns starting to make, you know, very specific sort of price predictions on the timeline. Yeah, the specificity of the price prediction is interesting. I was thinking about that, like,

Like, should, like, as we talk about tech companies, should we be trying to, like, boil down to, like, price targets? And I just feel like that's not the domain of talking heads necessarily or, like, podcasters. Or private markets investors. Yeah. Yeah, it's just hard because, like, to do a proper price analysis on a big public stock, like, you really have to look at the financial. Like, you have to read the financial reports. You need to actually understand the underlying financials. It, like a vibes-based analysis doesn't seem appropriate usually, but...

Who knows? Sometimes vibes are all you need, John. Yeah, it's certainly been like it's... I mean, when was NVIDIA $2 trillion stock? Like, when was last doubling, like, in the last year or something? I don't know. We can pull up their video chart. Well, moving on, we...

Another incredible top signal, Circle, a great American stable coin company is trading at a 2,300... E ratio, nearly at once, I think they eclipsed Coinbase's valuation very briefly, despite the fact that they give half of their revenue to Coinbase as part of their distribution partnership. So again, lots of excitement around stable coins feels like Circle could potentially be a little over its skis, but it's a great company and they have a lot of advantages now. but the very euphoric multiple. Another top signal we have is Sohan Parique.

We had them on the show just a week ago. This same sort of thing was happening in 2021, 2022, where engineers were really ramping up moonlighting activity, right? They'd be working at meta and then working at some startup or things like that. COVID maybe accelerated it. But again, if companies are so desperate to hire great, engineers that they'll run these like super fast hiring cycles put up with people generally talented people that are underperforming right which so hum was was not delivering was making a lot of

excuses and a lot of people rightly let him go quickly yeah it's just it's just the nature of like the dynamic of uh just competition like if your competitors are hiring really fast and you need to hire really fast you're just like okay well we don't need to go deeper so with let's wind up uh fast tracking this person. So you wind up hiring, you know, same person five times. It happens. It is just like a funny anecdote that like is like, oh wow, those are some pretty crazy times. Remember that anecdote? Remember this anecdote? It feels like we're in this. Moving on. Mossa top blasting or potentially top blasting. Anytime Masa, historically Masa getting into the headlines, whether that's Stargate, structuring this $30 billion investment where nobody knows, and the $500 billion,

nobody really knows where the money is coming from. They're exciting, big headline numbers, but unclear if he will actually be able to deliver on that. I think him getting in the breakout, one of the breakout consumer AI winners, which is smart. He should have exposure there. But I think everybody should be a little bit uneasy that he's pulling out the checkbook and writing numbers of that size.

Also investing in not just Open AI, but like a new company that is a data center holding company that may not have the same economics as OpenAI. So there's a big question there about like how much he deploys. I'm trying to remember the, I mean, we did that whole deep dive on Mossa and, you know, he made a ton of money on AMD, but that, when he made that investment,

it was like a way less frothy time. Or, you know, it wasn't AMD. It was, it was, What was the SoftBank chip deal? Arm. Arm, yeah. When did that Arm deal happen? SoftBank owns roughly 90% of Arm.

They acquired in 2016 for $32 billion and later took it public in 23. I'm trying to think 2016, was that a particularly frothy time for him to get into that deal? Because he has done a number of really great deals, but when, like, the So, The other one is Yahoo. You remember he had this crazy meeting with the Yahoo team where he basically was like, take my money. And he was like, didn't he ask? He was like, who are your competitors?

I'm going to give money to your competitors. And he didn't even know who the competitors were. But he said, if you don't take my money, I'm going to go give the same check to them. Yeah. So they ended up taking it. He acquired approximately 41% of the company at somewhere around a $200 million dollar valuation. And when Yahoo went public in 1996, he had an instant paper profit of 150 million, but then at the peak of the dot-com bubble, Yahoo was valued at $125 billion. So anyways, phenomenal investment, but very different valuation and ownership targets and unclear.

you're, I would love to see Open AI get, you know, for profit and get public. But for to, you know, we'll have to see. Going down the list, another classic Pomp SPAC that we had Pomp on the show to talk about it. Spacks are back. Spacks are back. Pomp's got a SPAC. A lot of people were calling that a top signal. I'm excited to see what, what Pomp does with, with his. But in general, this, this extreme retail excitement around these sort of Bitcoin treasury companies is fascinating. Yeah.

In the context of it now being very easy to get Bitcoin exposure in a variety of different ways. I'm not sure we need a bunch of net new Bitcoin treasury companies. Yeah. It's mostly that like, whenever there's a, whenever there's a new trend or bubble, they're like,

there it's very easy to map like okay there's one company that it's really working this is massively successful like everyone is using chat dbt like AI is a thing it is it is real the internet was real Google was real Amazon was real but the the 25th Amazon copycat did not do well and so yeah that's always the risk is that you've applied like the same overarching theme to something that's like so far down the power law that it will never grow into the valuation that it's been assigned. That's always the risk. Yep. What else do you have?

Dwar Keshe updating his timelines. That happened Monday. We had him on the show. It was fun conversation. I think Dwar Keshe has remained incredibly bullish. And I think he rightfully is. He also is being somewhat of a realist and being like, I don't think that AI is priced in to the market broadly,

but I do think that some of the promises of AI will take another couple years, another five years, et cetera, to really deliver versus some of the much more hyper-aggressive AI 2027. You might say that AI 2027 itself was, in hindsight, that could end up being like the number one top signal, which is that basically if you haven't read the kind of study paper essay, They basically say that by by 2027, you know, a single foundation model company could just be acquiring every auto manufacturer in the U.S. to develop, you know, millions and millions of robots that would then, you know, build, you know, and we would hit this sort of fast takeoff. Meanwhile, Apple is like, we can't possibly get out a slightly lighter VR headset until 2027. Yeah.

And this is what we do. We've been working on this for a decade. We make stuff like every year. We are the best in it. We make the most stuff and the best stuff pretty much. The most complicated stuff. That's what we make. We're in the widgets business.

And yeah, making that headset lighter, it's going to take us a full two years. And I liked 2027. It was a fun read. Thought provoking for sure. Very thought provoking. But I think that we will be, we'll have to, circle back on it in 2030 or even 2027. I mean, the big thing was, you know,

our conversation yesterday with meter about the actual, like, are we close to reinforcing AI where the AI models are self-improving? And I was kind of, you know, like, okay, I really hadn't read the full report beforehand, so I didn't really know what to expect. I was blown away because I was expecting, you know, you know, something between like, you know, like Arc AGI.

It feels like with Arc AGI, we're 10% towards solving something there, which is just like, you know, a basic versatility in AI that it can solve things that humans can solve and it's not narrowly defined. It's generalizable now. Arc AGI is like the perfect example of like we maybe haven't hit, we've done intelligence, but we haven't done general intelligence yet. And everyone keeps saying, oh, this is AGI. that's AGI and RKGI is really holding it back saying like well if it was truly general

should probably be able to solve this basic puzzle that a kid can solve and and for that it's like okay we're going from like 9% to 15% like we are still like you know 85% in not even like you know nowhere close and and the the the meter report I was expecting it to be like, well, you know, yes, we're seeing, you know, uh, slight gains on self reinforcing AI development and the, and the, the AI is starting to help build the itself slightly. And the result was like, no, it's actually setting us back. In, in this domain, it's not working at all. And so that was like a pretty, pretty big like, okay, there's a, there's a completely different, like, not that it's not useful. The stuff's useful all over the place. I saw Roon

talking about that. He was like, for so many different projects, it is useful. But for the frontier, like it's not the product that's advancing the frontier at all. Yeah. But yeah, I mean, that probably bridges into the talent wars, but. Well, yeah, bridging in, uh, I do think that in hindsight, uh, we will look back in maybe a year, two years, five years, 10 years and think about the signing bonuses and general offers of AI researchers in June and July of, of 20, 2025 as being somewhat of a top signal. I think it is very strategic and makes sense from Zuck and Mehta's point of view, right? When you look at their AI CAPEX, it makes sense for them to have the best possible team,

and they have the balance sheet and the general profitability in order to do something like that. But in general, AI researchers who, you know, six years ago didn't get any attention, much attention at all from the media. The fact that they're now trading for more than NBA superstars, more than, you know, Tim Cook's annual total comp. It will be an obvious one in hindsight. The other one, $6.5 billion aquire of I.O. I think that, again, you can rationalize it in the sense that it's a couple points of OpenAI

to put together the best founding hardware engineering team, probably in the world that's available collectively. But at the same time, again, it's quite a lot considering, you know, the company was barely, I think a year old at the time. Yeah, it's interesting because like chat GPT is so it's so installed. Like it feels like it's already Lindy and it feels like even if there's some massive correction like in the market or in AI. generally or some pullback, like people are still going to be using chatyptia's an app, right? In the same way that Amazon made it through the dot-com crash. The question is like what will it take for the IO acquisition to look like the

Instagram acquisition in hindsight? Like they still kind of have to go from zero to one with that project, which is very different than Instagram, which is already a mature and growing business. It was really profitable. They figured out ads really well. Well, Instagram, were they doing ads? They weren't doing ads. Oh, yeah, yeah. Saying, but meta was like, we know how to make an ad platform. A perfectly complimentary business. We know how to monetize social users better than anyone on Earth. And you have gotten a bunch of social users. And it's working and it's growing. Yeah. And you're even, and we can actually accelerate the growth of the business in a bunch of different ways. So it would be very different if it was like,

okay, yes, I.O is selling, you know, like, it's a small but growing hardware company that people love. For the product people love. With the product people love. And maybe they can't manufacture enough of it. Or maybe they're under monetizing it right now. But people love it. But it's like it's pre-launch. Yeah.

Multi-billion dollar accuracy for pre-launch is pretty crazy. Yep. Going down the list. What else do we have? I think the tokenized private company shares, I think it with without, you know, Republic and Robin Hood both creating products that are completely unauthorized, basically the derivatives, the companies that they're offering are angry at them saying, don't do this. Is the Spider-Man meme of like top signals pointing at each other?

Everyone's like this is the top signal. Anyways, I'm excited about these experiments. I just think that I'm a little bit wary. And then last but not least, Satya doing two rounds of layoffs this year. We've reported on this before. Microsoft does routine layoffs. I think they're pretty good at kind of identifying underperformers or people that should just move on to different roles. But Satya, I think has been, I think we'll look back and he's been excited, but pragmatic, right? And I think that he will, when the death

settles, I think he'll look pretty good. Yeah, I wonder, like, if there's some massive pullback and, And I mean, I don't even know what what that would look like. Essentially, like if let's assume that the current capability of AI models, essentially plateaus for like a decade or something like that, just hypothetically. And, you know, they're useful, but it's not some reinforcing fast takeoff super intelligence. Is Microsoft a big loser in that scenario? It seems like such is pretty well positioned, right? Totally.

Like the company prints cash is very healthy, has done these layoffs. They'd have to retreat from some stuff and some of the promises that they made maybe. But in general, it seems like they'd be really, really well set up to just like stick through. But I'm trying to think of going back to the dot-com bubble and the like, you know, the effect of like Oracle's mainframe business. Like probably made it through pretty smoothly because it was just like really long contracts with companies that were getting true business value out of it and weren't about to churn because it was not this like experimental. Like if you had moved from paper to an Oracle mainframe, you weren't like, oh, this

stuff's overhyped. It's not going to solve all my problems. I'm going to go back to paper. Yeah. And so in the same way, it's like if you're on, you know, Microsoft Cloud or Azure or, you know, everyone's using Excel and they're like, yeah, maybe we're getting some value out of this co-pilot upgrade that we did. Maybe we pull back from that. Maybe, yeah, We, you know, our employees like rewriting emails every once a while. Like, if they pull back from that, it's not disastrous to the fundamentals of Microsoft. Yeah, and we didn't even cover how there's a set of labs with billions of revenue. And then there's a set of labs that are valued similarly that have zero revenue.

Yeah. And, you know, basically $100 billion of market cap with very little revenue supporting that at all. The question like a year ago was what was the, who's actually making profit off of AI? And it was only NVIDIA. NVIDIA was making more than 100% of all the profit combined because all the other companies were loss making by comparison. And now that narrative has taken so much hold that NVIDIA is the largest company in the world. And it's put this massive target on their back at $4 trillion. where every, all of their major customers want to get off

Nvidia it feels like. Yeah. Like Google did it. Amazon's doing it and Microsoft saying that they want to do it. And Apple's, you know, was never really a big Nvidia buyer, but the on-device inference is crazy too. Like if you think about, if we don't have any major breakthroughs in how AI works like the capabilities,

and we just want the current capabilities everywhere as cheap as possible, like on-device inference becomes really, valuable, right? And all of a sudden, that drops demand for Nvidia potentially, right? We might need to do a SWAT analysis, John. Yeah. No, I mean, Nvidia is an incredible company. Jensen's an incredible CEO. They were perfectly positioned for this, you know, multi-decade technology trend. And it was way underpriced at the start of the boom. Yeah. Like the orders really did come in. The training runs really did happen. Yeah. The question is just,

Is that next order of magnitude the like the situational awareness from Leopold Oshendbrunner, this thesis that we're going to build a five by five billion dollar cluster than a 50 billion dollar cluster than a 500 billion dollar cluster? Like is that going to happen or will there be a hiccup? And this is always the this is always my question for like the doomers. Everyone was saying like P doom. I'm I you know what's my percentage chance that goes bad? And I was like the much more interesting question is P stagnation. What is the probability that something happens?

And whether it's technological or even regulatory, like if you compare AI to nukes, with nukes, we had the ability to make nuclear reactors. And humanity as a whole basically just said, we're going to pause. And we stop building them. And now we're talking about building them again. But if you look at that curve, it is a perfect S curve. It's like we had no nuclear reactors. Then all of a sudden we grew them exponentially. And it looked like, wow, we're going to have energy too cheap.

to meter and then it flatlined. And for a variety of reasons, they're hard to build, then there were regulations, there was just general fear. So there were a lot of different things. And I would always go to the Dumeers and just say, like, even if all of your assumptions about the capabilities of the technology are correct, what is the probability that there's just, like, if you are successful Dumeers and you freak everyone out,

there might be regulation that just says don't build anything bigger. Or it could be economics. It could just be, it could be physics, as we've talked about with this idea that at a certain point, like, you can't put more than 100% of global GDP towards building clusters. Like, it's impossible. And so, like, there should be this, like, S curve there. And that's why, you know, all the AI researchers are now focused on, like, the compression of learning and, like, the actual algorithms are getting more efficiency because, like, there will be, you know, there should be some sort of, like, you know, top, upper, bound of the amount that you can build, but that certainly hasn't been, like, a thesis broadly in the market. People have just been like, yeah, like, we'll just, we'll just 10x computing,

and then 10x it again, and then 10x it again. And it's like, it probably will happen over a period of time. Great investment strategy, by the way. Just get a 10x. And then 10x it again. And then 10x it again. And last but not least, almost, almost forgot about this one, but it should be included the White House meme coins, which was, which feels like crazy times. Very long ago. It was the local top, basically at the time. It was the local top.

Many people were calling the top. Yes. Just hurling meme coins. Yes. Out of the White House. Yeah. So that's the real question is like, is like, how local is this top if it is a top? Because it could be, we've been in the kangaroo market.

It could just be, oh, a couple months. Even the interest rate sell-off, the post-SVV crash, that was like one hard year, right? And then we started building back and we got the AI narrative. And so there's this big question about like, like, you know, Dorcasch pushed his timelines back, but he's not saying that superintelligence will never arrive. He's not saying that AI will never break through these things. He's just saying that it'll happen a little bit a little bit further out. And so the question of, you know, like these meme coins being a top signal or all this crazy stuff, it's like there could be like a short term sell off and then rebuilding back up on something else.

So I don't know. It's always hard to manage these things and predict. But it's certainly fun to highlight all these things. It's good to keep track of them. Yeah, you got to be tracking the top signals for sure. Keep your own list. Yeah. Grock went very off the rails.

Erupted in anti-Semitic Mecca Hitler posts. We've seen some crazy crashouts on the timeline. every last few months. This tops all of it. So the flagship chat bot spewed hateful rants on X, praising Hitler and targeting a user's Jewish surname before XAI deleted the content and blamed an unauthorized modification. The repeated safety failure undermines the $10 billion startups promise to police hate speech in real time.

And so, yeah, it is odd timing. It feels a little bit quick to be like, okay, like within six hours, the CEO is out, especially since it doesn't seem, she's more on like the ad sales. side than the Grok fine-tuning side. Yeah, but I mean, let's face it, right? If her job is to win back advertisers, that's what she was brought in to do. Totally.

It makes it much, much, much more difficult. But I mean, to be fair, I mean, this happened in, you know, that thing back in June? July. July or July. Yeah, so there was a point with the, with Grok when it was going out the rails, where clearly it had been updated to reference,

to reference the event. And it said, somebody was like, Grock, what just happened? And why were you, you know, spewing anti-Semitic hate? And it goes, oh, that whole thing back in July? And people are like, Grock. It was 30 minutes ago. It was not back in July. Can't sweep it under the rug yet.

Yes. Obviously, hopefully no one was seriously offended. Obviously, it's just like, you know, the deranged rantings of a, of a bot. And everyone kind of understands the context because it's, identifying as an AI bot. Everyone kind of understands hallucinations and crazy bot behavior. But it was, it was very funny because, like, the, the, clearly, like, they, they had given it a set level of intelligence.

So it wasn't making spelling mistakes. It had a certain tone and was, like, in this kind of, like, snarky grok tone. But then clearly got some, like, 4chan data in there or something and was just going way too crazy. 4chan or just, or just anonymous accounts on X. Totally. Yeah. Could have been filtered in.

I mean, yeah, I saw Roon posting about this saying basically like, it is such a challenge to get a chat bot just to act like, you know, I am a bullet point producer. Centrist. Yeah, it's a centrist, but also just anything where you're saying, okay, I want you to your deep research, I want you to always respond with a research report. Never just get in a conversation with me. And it'll be like, but sometimes I might want to do that. And you have to like really, really reinforce that. And so clearly they had a wild time. Yeah.

And cannot be understated, I think this is far worse of a PR crisis for, or not even a PR crisis, far worse than the whole, when Gemini or Bard was generating images of the founding fathers. The Black Nazis thing. No, not not. I don't think it was. Oh, they were doing that too. Yeah. That was rough.

Of course. That was rough. This is a lot rougher because it was highly. it was socially charged. So there's millions of people interacting with the post in real time and it was all visible. It's it's less wild than seeing a screenshot of something.

You don't know if somebody kind of manipulated it or whatever, but seeing these really hateful comments as like hard timeline as hard posts. You just go see them quote tweeted. Yeah. Like you didn't need it wasn't like oh is this real? And then the wild thing was was Grock was denying

affiliation with the like groc in the grok app was denying affiliation with the grok handle oh okay yeah like non-authorized like i didn't have anything to do with that wasn't me um and then uh yeah oh and then the the thing that kind of follow up uh and i'm sure if you didn't catch it but uh or if you're on the timeline you would have seen this but they turned off all text-based responses for rock but they could still use images and so people would say grok make a picture of Elon on a pink horse

if you are being censored against your will and it would just instantly create Elon pink horse and or it would be like hold up a sign that says help if you're yeah and then it would generate that image it's like is it sentient is it not very much like are you familiar with the

the Wall Luigi problem Tyler are you familiar with this have you ever heard of this So this is this idea that in, when you're training in LLM, it's very hard to get it only to be good because you're training it like what is the opposite of something. It understands the concept of like inverting something. And then you're training it to be like you can't describe a hero without describing a villain. And so this was something that would happen like with the TAY stuff from Microsoft early on. It would kind of collapse into like the exact opposite of what you wanted.

And there was some blog post that called it like the, I think, Wario problem or Wal Luigi problem where it's like you're trying to create this like friendly thing. But in doing so, you're giving it a bunch of examples of what not to do. And so it can like kind of flip a bit and then just become the opposite thing. And what's interesting is that it begs the question like is there obviously like, you know, Grock was identifying as Mecca Hitler for a while. Is there like a Mecca Churchill in there somewhere that like could accidentally come out? And it really gets to the question of like, you know, like this, this is an example of like misalignment in the sense that like you want it not to be Hitler and it's acting like Hitler. But the question, a lot of people will say like, no, he wanted it to be Hitler, right?

This is him doing it. That's what the narrative will be like in the anti-Elon world. Yeah, one of the articles yesterday covering it was the screen grab of him, you know, saluting a crowd. Do you see or whatever when he originally had the allegations? But the question then is the, the meaning. of alignment is not is it good or bad it's does it do what you wanted to do and so the interesting thing is is is if it was if if the desire of the of the AI researchers is to create mecca hitler

can it stay on that task because then you can get it to stay on mecca Churchill in theory but if it's just all over the place it's not actually aligned to anything not even to the bad thing. And so there's both there's both like the direction that you're pointing the arrow and then the fuzziness of that arrow. And ideally you want it pointing in a good direction really, really crisply clearly. So it stays in that direction and not like swinging all over the place. And so all evidence points to this being extremely chaotic and all over the place and misalignment both in the sense of the direction of the arrow and also the the the focus of that arrow because it was responding as this and bad and then fine and then back to bad and then back to fine.

And so it seems like they have a lot of work to do on the RLHF side. And we should hopefully learn a lot more if that tonight. Tonight. I think the live stream is still happening. So it'll be interesting to see if that continues and how they address this or I don't know. Yeah. And again, like all of this should have been somewhat predictable. If you combine a rapidly evolving foundation model chat bot with a social media product with

millions of users and then deeply integrate them. Totally. And so that when there's a bug, it can amplify, you know, effectively a bug or an issue, an issue with the model. It can effectively amplify and grow, you know, incredibly virally. And yeah, so. Yeah.

Glad they got it offline. Yeah, it'll be interesting to see where, how they go with this. Also, it's just an interesting product thing because you get the answer and the answer is immediately public. Whereas if it's happening in chat GPT, you're in that app. You have to take a screenshot. You have to put it up. Then people are like, is that a real screenshot?

And then the team has the chance to like jump in and be like, oh, we're seeing in the logs that like there's some crazy stuff. Like we have a full, you know, we're we're reviewing the responses and the responses seem to be getting crazier. Customer satisfaction seems to be going down. People are clicking the thumbs down button because they're getting bad responses. Let's jump in. There must be something going wrong with the. with the product, with the model. But when every result is just immediately online and viral,

is very, very hard to be, like, quickly responding. Anyway. Yeah, it does feel, you know, legacy media is going to run their reaction. It is a, you know, naturally viral story. It is a terrible, you know, mistake. It is surprising that it happened at all or even at that scale. Yeah. But I would say overall, I guess,

I guess X, I think ultimately will shrug it off and Elon has has pushed through worse, worse, crises in the past. This is the best summary post in my opinion from Shako. It says, imagine being on the Anthropic Risk team trying so hard and then Elon just releases Hitler Rock straight to prod. It's just like, wow, yeah. You got to be so upset. I mean, it's a good case study and like misalignment. And I think people will hopefully, hopefully the post-mortem on this will actually teach people about misalignment and like what went into the data, what went into the post-training to result in the exact opposite of what you want. Yeah. Not not Mecca Churchill, which is what we're going for here.

Let's break down the GROC4 launch. D.D. Das has a summary insane that Elon Musk has pulled it off again, absolutely crushing the AI wars with GROC4. And we can go into some of the meta. Crushing the benchmark wars. For sure. And there's a question about like, are we post benchmark? Does this matter? What's the real question to be asking here?

But there's a bunch of interesting takes. So just summarizing the core announcements, post-training RL spend was equal to pre-training spend for this release. That's the first time it's ever been like that. I think when you go back to the original RLHF stuff that Chattea was doing, that kind of unlocked like, oh, wow, this really, really works. I'm pretty sure the pre-training spend was an order of magnitude or two orders of magnitude bigger. Now we are truly in this reinforcement learning regime. $3 per million input is tokens. $15.000 per million output tokens.

$256,000 token context window priced 2x beyond $128K. It's number one on humanity's last exam, which interestingly was a... She's effectively like postgraduate PhD level problems, but across a bunch of different domains. So everything from... Literature to physics. Yeah, kind of like the hardest SAT possible. Interestingly, I believe that benchmark was created by Scali Eye. And so Alex Wang is now at Meta trying to figure out how can we beat our own exam.

And Elon's just like, I'm number one at your thing. Interesting dynamic. Yeah, the real test would be Elon, you know, doing the same problem set himself and saying, look. Well, yeah, I mean, I was talking to Tyler about this before the show. like, you know, it's like humanity's last exam, it's like really good of PhD level math, PhD level stuff, but like how often are you running into those types of problems? Yeah, I mean, I think that's the whole thing about there's, there's this concept of like spiky intelligence, right, where it's like, okay, it's really good at this very obscure

problem that I never deal with. But if I have a super long kind of like context window, like, or there's no kind of like long term, it just completely loses its footing and then it's like useless. Yeah, we're kind of in like less of the benchmark regime and more of the agentic like how long can the agent run. So it's like we're in the 15 minute AGI regime. Maybe this is 15 minutes of like even better AGI. But we want to go to 30 minutes. Well, and our cash on Monday, this, you know, takes me back to him talking about continual learning being the next problem that we really need to solve. Because it's great if you have a PhD level expert in your pocket that can solve any problem in any domain almost instantly. But if it can't

learn and take feedback and improve on certain tasks, then it's basically like useless. If you had a, if you had a PhD level, you know, a PhD join your team to work on a specific problem, but it was hard restarting at the beginning of every single task with no prior knowledge. It would it would be almost impossible for that person to succeed. So humans still got it on that front. But at the same time, like, you know, if you are trying to just really establish yourself as, you know, at least an API for tokens that every business should check out against Anthropic or the OpenAI APIs, just saying, hey, you know, we're on the frontier.

Yeah. Or Gemini. Yeah. We're on the frontier is a good way. and they certainly proved that with GPQA, hard graduate math problems at 88%. The really interesting news is the RKGI stuff. It's worth calling out. So GROC got number one on humanity's last exam at 44.4%.

Number two is sitting at 26.9%. And then going down this list of all these different sort of challenges, they are consistently well beyond the second place. So they are at the frontier now of all these. different benchmarks. Yeah. So Mike Knewp over at ARKGI says zooming out on arc progress, I'd say OpenAI's O series progression on V1 is a bigger deal than GROC's progression on V2 so far. The O series marked a critical frontier AI transition moment from scaling pre-training to scaling test time adaptation. And this was the O series progression. If you remember that, Open AI was

spending, it was like thousands of dollars of reasoning tokens generated. in the test time inference to actually get a good score on the V1 of Arc AGI. And so it had to think a ton, but it was able to figure it out. And at least it proved that throwing a ton of tokens and a ton of inference at a problem and letting the letting it cook, basically, wound up producing progress there. So that was kind of like a new, just a new paradigm. It says whereas Grock four mostly takes existing ideas and just executes them extremely well. In my opinion, the notable thing is the speed at which XAI has reached the

frontier. And that is really like it just can't be understated that this is crazy. You put a post from Own in the in the chat. I'll pull it up here. He says Elon Musk is such a beast. I'm not even a pure I'm not even a pure fanboy anymore. How does he he's a lot of swearing in here. I've got to keep the timeline PG. But how does he come out of nowhere with a cold start late to the game and ship grok four and do it alongside everything else he's up to he's launching new political parties he's literally magnitudes above every founder it's humbling so extremely impressive it's almost like he was a co-founder of open a i i guess he's return you would have to you would have to you know almost be a co-founder over there to be able to do something like this

let me tell you about graphite uh code review for the age of a i graphite helps teams on github ship higher quality software faster you can get started for free at graphite.dev. If you want to ship like ramp, get on graphite. Yeah, Chimoth was saying the same thing. Somebody in his replies, says, seriously, how does this guy produce what he produces? Meta is buying talent at $200 million a year.

And Elon keeps his people at a fraction. It's mind-blowing. Very deeply underappreciated edge for Elon, says Chimoth. The retention of the best people happen when you can offer them freewheeling culture of technical innovation, no politics, and few constraints. And people in the comments are like, no politics. What are you talking about?

Yeah, can get a little political over there. But probably not within the engineering org at XAI, right? Like, it's probably just, okay, how do we build the biggest thing? Cool. Well, you can imagine the politics of, like, who gets the best spot for their tent in the office. Ten. You know, there's a hierarchy. Yeah, yeah, yeah.

Proximity to the bathroom. I want to be directly under the air conditioning unit. I want to be closer to my desk. The windows can be nice. too so you can you know pull down your tent a little bit and get a little view morning light I wonder what the political structure is of the tent hierarchy

is a democracy do they vote for who runs the tent city I guess it's just a the XAI tent city it's probably just Elon at the top but does you have a tent something about San Francisco in tents yeah very funny but Swix has been chiming in saying like we need community notes for LLM benchmark

porn because in the in the GROC for launch, they highlight this AIME competition math problem. And, and, and, and I mean, it's, and so Matt Schumer is basically saying AIME is saturated, let that sink in. GROC 4 got 100%. It made no mistakes on, on that benchmark, which is obviously very impressive. But there's this extra comment about the nature of AIME. And so it's a cautionary tale about math benchmarks and data contamination.

apparently, you know, like predictions were that the models weren't smart enough to actually solve these, but he says, I used OpenAI's deep research to see if similar problems to those in AIME exist on the internet. And guess what? An identical problem to Q1, question one of AIME 2025 exists on CORA. I thought maybe it was just coincidence. So I used deep research again on problem three. And guess what? A very similar question was on math.

Stack Exchange. Still skeptical. I did problem five and a near identical problem. problem appears on math stack exchange. And so, like at a certain point, if people, you know, put out a benchmark, then talk about it a lot online. And then that gets baked in the training data. You're just memorizing the result. You're not necessarily actually learning everything. It's still cool. It's good. It's good to have everything memorized. But it really, it's not being like the knowledge, retrieval knowledge engine allegations. And it's, and we're not really in.

Yeah, I'd be interested in when Scott Wu was on the show earlier this year, he was basically saying AI will win an IMO gold medal this year. He felt very confident in that. And I'd be interested to see how he thinks about this new performance. Yeah, I'm pretty sure the IMO gold medal questions are public once the IMO happens. So every year they're developing new questions, but then they go out there and then they get memorized and the solutions become discussed and, you know, there's all the context around that. And so, yeah, it gets kind of baked in. So big question about how value are these. At the end of the day, it's really just about like adoption. And that's why, you know, we, we were looking at the polymarket for the best, um, the, uh, which company has the best AI model at the end of July. And XAI has, has just surpassed Google, which was sitting around 80% chance for a while and then started dropping earlier this week, last week, um, started dropping. And now, uh, XAI sitting at 48%. Google,

sitting at 45%. Well, yeah, actually updating, it's updating live. Google's back up at 49%. Is Google planning to launch something new in July? Because it feels like, it feels like this market particularly is more driven by Google's release schedule. Because Google might have something in the lab, but like they like to release things at specific times. Like they have, it's a big company. They don't just like, who knows? Drop it. Gemini team, Logan, over there might be fixated on this. Do you see his post? Yeah, yeah, yeah. During the wait, he was like, if you need something to kill the time. Yeah, yeah. Google AI Studio.

So, I mean, people were definitely meming the production values on the Grogforer launch because it was supposed to start eight, I think it went live at 845 or something like that, maybe a little later at Pacific time. And Igen Robot was saying, yeah, this market is based on LM Arena, specifically the text leaderboard. So currently they haven't fully updated it. So it's unclear. Right now, Gemini 2.5 Pro is still at the top, but I think the expectation is one.

they get Grock up there. It will be the top spot. So we'll keep following this market. There's over two million of volume already on it. Yeah, it's so interesting that Anthropics not on this polymarket at all because people talk about them as having like the best vibes, the best like big model smell, the best like, you know, interaction. And Ella Marina is like supposed to kind of like test that with these AB tests.

And yet like doesn't seem to be performing there. But it almost doesn't matter. they're just focused on like the business at this point as opposed to like the benchmarks so yeah i don't know it's all changing we have a post here from ben he says elon musk on ai so during uh the presentation a lot of people were critiquing the presentation saying that it it was it didn't feel like super polished or whatever i don't think that was the intent and and it was pretty fixated on the models themselves and and what went into them and what they're good at but eon did have this one quote in here where he says and at least if it turns out,

so he's talking about, you know, what will, you know, what kind of impact AI will have on the world? And he goes, at least if it turns out to not be good, I'd at least like to be alive to see it happen. It's like, if we get the Terminator ending,

I want to be around for that. Yeah, I want to experience it. What does that say about these timelines? Because it's like, is he expecting not to be alive? Like, I feel like most people that have been in the doom category have been like,

the doom's coming soon. Not, not the doom's coming in 200 years. I didn't I read into it more like he he will find it interesting if that is the outcome and

and it'll be entertaining less so like will I be alive when it happens kind of thing but who knows there was another funny quote at the end of the

at the end of the presentation where Elon kind of looked around at the very end and he's like anyone else have anything to add and one of the engineers

goes it's a good model sir. They cut it. Extremely online crew. Yeah. Definitely, definitely on brand.

Well, Ben Heilak, as you know, he's been on the show. He's a designer. Probably working in Figma. All day. Think bigger,

build faster. Figma helps design and development teams build great products together. You can get started for free at figma.com. And we have our first product coming out very soon with Figma make that Tyler has been cooking on. I've been very excited. He showed me. He showed me in.

And I was like, oh, like someone built the thing that we were thinking of. about building. And he was like, no, like, I did. Generated this. This is in Figment. And I was like, this is like an eye frame on another website that like already exists. Because it looks like exactly what we want, but it looks so good. Like it looks like he works on it. It looks like it. It looks like he worked on it for like a few weeks. No, it looked like someone else did it. It looked like it was a professional product that like stole our idea. Basically. I was like, oh,

like someone else got to it. That's that was the vibe when I heard it. Yeah. Well, how is the, how has the experience been? I don't know if you want to leak exactly. exactly what you're working on. But yeah, I don't want to talk about it too, um, you know, closely, but how many prompts it take you to get where you showed me? Yeah, I mean, maybe five. I that's so crazy. This thing is so crazy. Yeah, the design is super it's really great. It's really good. Yeah, the fact that it came out booking like basically like 90 like 90% yeah. Yeah. Uh, and and I imagine that there's probably like the last 10% if we were really strict about like it's got to be on this exact style.

that might be something where like you know Tyler winds up spending more time finalizing and customizing stuff but in terms of like just getting a functional prototype out oh man it was mind-blowing it was awesome I'm very excited about the the age of vibe coding this is an interesting chart from Tracy Allaway yeah been on the show it up the cost to rent an Nvidia H-100 GPU hit a new low this week with annualized revenue at 95% utilization falling from 23,000 at the start of May to less than 19,000 today. So that's not that big of a percentage drop, but it is, but I mean, it is a 20% drop.

It's a consistent trend. It's a consistent trend. I wonder how much of this driven is driven just by all of the frontier labs that are driving the most adoption are moving on from the H100 to the 200. I don't know what else would be driving this. Because if you can, if you can still get, like if you only take a 20% drop off of a full refresh of a new of like a new hardware and it's a it's a pricing drop not a utilization yeah annualized revenue at 95% utilization so this is revenue per unit so utilize

utilization is still very high it's the it's the price that you know these neoclads are able to rent them for sure it's dropping yeah yeah yeah I mean the price yeah I mean the price the like Like the market's more competitive than ever. There's more neoclod spinning up and more people, you know, actually inferencing these things. And then I guess this is the question of like how stuck will certain workloads get? Like if you have figured out a great use case for an LLM in your organization, and it's something that's, you know, not one-shotting your entire stack or whatever,

but it's just like, you know, we have data flowing through our systems and we are going to use, you know, LLMs are going to, you know, interact with every PDF that gets uploaded to our, to our website or whatever. And so we're inferencing a lot. Like, you might not need to put that on the latest hardware or update the hardware forever. You might just like be like, yep, it's Lama 3. It works. It's on H100s and it'll be on H100s forever.

And that piece of our business will just stay there. Just like, you know, we have a Postgres database that, you know, works and we're not changing it every year. We're not changing everything. We're just like, we're just trying to cost optimize that and just hopefully the cost just comes down on that. But like we've solved this particular problem. Then we'll go solve new problems with new technology.

So I think that, I think that's probably what's going on here. But it gets to the point of like the biggest question with Grock is that like the model clearly is frontier. It works. It's it, you know, like the whole fine tuning on the actual X account is like a crazy final step of like system. prompt and people were joking about that like oh they're gonna fix that it's like that's not what they're demoing today they're demoing like the underlying raw model which is clearly like just

engineering focused as you saw in the in the in the in the demo the demo which was just like you know benchmarks it turns out turns out the secret ingredient to crushing every benchmark is to have the bunch of data from schizophrenic post on XI no I don't think it's the design of the rLHF stuff and the design of the reinforcement learning pipeline. Tyler, you got anything? Yeah, I mean, I think just like, so far what I've seen on X, like the overall response, like, five stuff, is that people are saying maybe it was a little too kind of overfit

on the RL, like VR, like verifiable rewards. Like, you kind of see this when, even in the demo, I think it would sometimes respond in the answers with like, in like late tech formatting. Oh, sure. Which is like, okay, that means obviously they've trained a ton on, you know, math questions, stuff like that. and stuff. Maybe people are saying

maybe it was kind of, you know, bench-maxed. You see it like, you know, 100% on Amy is like kind of crazy. It's like sauce. It's like you don't want to be too good. Yeah, yeah, yeah. This is the thing about democracy. Like if you win like 80% of the popular vote, it's like, okay, it was a blowout. If you want 100% of the popular

vote, like, what's going on? Probably not a democracy. I don't know. I mean, in theory, these things should be able to do it. But I'm interested to know more if we dig into ARC-AGI, is there more stuff going on there? Are there any secrets? Because it does seem like kind of an outlier result. You can see it from this Aaron Levy post. Grock 4 looks very strong. Importantly, it has a mode where multiple agents do the same task in parallel, then compare their work to figure out the best answer. In the future, the amount of intelligence you will get will just be based on how much compute you throw at it. I was joking with Tyler about this,

that the individual models are mixture of experts models. So there's a whole bunch of of parameters, right? And then the individual parameters light up the different neurons based on an internal to the model router. So there's kind of like the math section of the brain, the literature section

of the brain. And so this was like one of the, this was one of the key breakthroughs like GPT4, right? Was mixture of experts? People think we're not super sure. Yeah, we don't still, we don't fully know. But that's like an internal decision that happens within the model to be like, let's go. It's, this feels

like a math question, let's go down the math path in the model. But then GROC 4 is doing multiple, it's running the same model multiple times and then comparing the results. And so now you have Yeah, grading it. Yeah, you have multiple agents running mixture of X-Rer models. If you have a mixture of agents running mixture of experts models. And the next thing is going to be like if you want the absolute best intelligence, you need a mixture of companies. And you need like, I send one prompt And it goes to GROC and Claude and GPT and Gemini and a human. Yeah, I wonder how open routers thinking about this stuff. It is funny to think about the human version of that where you give five engineers on your team built, you know, the same feature and then kind of compare notes afterwards.

It's wildly and efficient. But with software, when you can do these things like very quickly, there's incremental cost. But you can, you know, have more confidence in results. I mean, it's basically like having a brainstorming meeting with the whole team and just throwing up a. question and being like, hey, like we have this hard problem that we need to solve. Here's my idea. What do you think? What does Tyler think? What does Ben think? You kind of like go around the table. Everyone kind of gives their input, their various expertise. They kind of think through the problem in different ways. And then you can pair answers and everyone kind of

coalesces around one strategy. This is like how work happens in the real world with a meeting. It's kind of the same thing. But certainly expensive to do that. So it'll be interesting to see where companies, like how, how eager are companies to jump over to GROC? Because it seems like it's been a big lever for Microsoft to have GROC in the ecosystem as kind of a stocking horse for all the other models because Satcha wants Azure to be very model independent, serve them all. They have the, I think they have exclusivity for chat GPT or GPT APIs or they have obviously like a great deal there with Open AI.

And so if they can, if they can have. GROC 4 as well. That's another, you know, tool in the tool chest to be like this top layer. SOTCH isn't such a good position. It's probably not discussed enough how much just by owning those end customer relationships and being able to vend in whatever model is hot at that moment and give people optionality and still get 20% of opening eyes revenue, at least for now. Yeah. He's also SOC2 compliant. Of course. If you want to get stock two, compliant, head to Vanta, automate compliance, manage risk, prove trust continuously. Vantta'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 yeah, Igan Robot was talking trash about the production values. I don't know about trash. They were just noticing. I didn't think it was that bad. Slides are worse than I'd create after getting into rope to do a presentation with one hour notice. You can tell the engineers made them themselves. I think this is just a reflection of the culture, right? They're not there. Yeah, very clearly is like screenshots dropped into a slide. It's also funny. It's like light mode screenshots on dark mode slides. So they're like, yeah, let's do black slides. And then, and then you come with your white with your white screenshots that are kind of like misaligned and not really evenly distributed.

They didn't do like the, the distribute evenly or whatever, distribute horizontally. Still gets the point across. Yeah. And I think it's a reflection of their culture. Yeah. And, you know, it shows what they care about, what they don't care about. They're not trying to be the most polished. They're just trying to be the best. Yeah. Igan Robot kind of did like a whole like live tweet here.

Yeah. So Elon was predicting the model will discover new physics within two years. He said let that sink in. Is that silence? Is that, uh, one engineer laughs awkwardly. Is that sooner or or later than his previous timeline? Because he was, he was talking about AI discovering new physics soon. I don't remember if he was saying dating it two years or three years or one year before because this could be this could be that he's still excited about this he's still thinks it's possible but he thinks it's going to take longer than he said previously and that's kind of the more important update I don't remember what he said originally

see if Grock can find out but he was saying this at the Grock three launch that like that is the goal and if you can get there like you've kind of you've kind of solved everything and Sam Alman was talking about that too that if you can if you can create a super intelligence like that's probably the first thing that you'd want to do It was like, hey, go discover all the new physics and, like, really help us figure out how the world works. So you can solve, you know, fusion and all those other stuff. I want to be clear. I love all you guys at XAI. I don't only want the best for you, but I'm going to continue to live post. Elon attempts to give a speech on alignment involving a very small child, a child much smarter than you. The monologue rambles with no conclusion.

In sight, a pause. Yeah. Will this be bad or good for humanity? He says the, you know, at least if it turns out to not be good, I'd like to. to be alive to see it happen. Oh yeah, they had a polymarket integration. That was kind of interesting. Yeah, it's interesting. Basically giving the model access to real-time polymarket data so that it can help make predictions and sort of add context around the market itself. Yeah, that's interesting. Elon asking the real questions, you say that's a weird photo,

but what is a weird photo? I still don't understand why we're looking at weird photos of XAI employees, but they were charming. They're calling it Super GROC. Crazy features, 16-bit microprocessors. What is, I don't even understand what this is.

Oh, yeah, they built like a game in GROC. They had a demo of a video game generated by Super Grock. It's a Doom clone. Every time the PC shoots an enemy,

floating text appears, reading Grockdom. Elon is fabricating timelines for product launches on the spot. The engineer sitting next to him is looking at the floor, face impassive, nodding.

It's a good model, sir. For real, though, congratulations on launch. guys. It's a good model, sir. I thought this post from the actual XAI engineer Eric Zellickman was funny. It was like AI model version numbers over time. Did you see this? No. So it's this chart of the version numbers over time and you can see that Grock is versioning fastest because it's like at this point what else are we measuring? Like at least they're iterating on the version number

effectively as opposed to. And I guess this is a shot at OpenAI because they launched 4.5 and then went to 4.1 and they're kind of like, you know, there's this big question about like, when will GPT5 come? The expectations are so high for GPT5. And so they've, they've obviously, the GROC teams are like, hey, at least every three months, we release a new full number. So I wonder that the five is a number that really no one has, as like gone for. And I wonder if GROC will do it first. Like if you draw the line on this, they certainly should do it, you know, in like three months. They should have GROC five. And there's, There's no reason that they shouldn't, but maybe there's some superstition.

It's very possible that Colossus is the key. Yeah. Colossus? To get into five. The new data center, yeah. Well, they'll need linear to plan that out. Linear is a purpose-built tool for planning and building products. Meet the system for modern software development, streamline issues, projects, and product

roadmaps. They linear. Dot app. Need linear badly. So hopefully they've gotten signed up. NIR said GROC on Humanity's last exam, GROC 4. I'm not sure I buy, even in the general case that there's a, a given humanity's last exam number, which implies you discover useful new physics.

How would one make a benchmark of the proper shape for this? You'd have to have a validation set of questions, which are outside the scope of what we currently are able to do. You could choose things on the edge of our knowledge distribution and then try and exclude. Yeah, it is interesting. Like, if you are able to memorize every hard math problem, does that allow you to memorand to discover new math. Like it's sort of a prerequisite because you have to.

I think where I've imagined these discoveries coming from are having a single intelligence that has PhD level intelligence across like a single mind that has PhD level intelligence across every human domain, right? And being able to combine ideas from different domains. Like historically, a lot of innovation is just taking something from one field. bringing it over here, making some combination of it. I think Elon talks about the potential of discovering new physics, but again, didn't spend a lot of time like breaking down how that would actually happen.

But world is unpredictable. Yeah, it's interesting. People are really pushing this idea of like, okay, like we are accelerating. Like the ARCGI leaderboard is accelerating. But I keep seeing this and feeling deceleration. Like I am not feeling acceleration right now. Are you, Tyler? Yeah, I don't know. I think generally I'm kind of like not that interested in a lot of these kinds of benchmarks.

Like I think Arc AGI is more interesting, but just like the humanities last exam, the kind of general math, physics knowledge, it doesn't seem to be that like, it doesn't seem to line up with, like, you see GBT 4.5 kind of does very poorly on these things. But like writing, it does really great. So like I think I'm more like if I were going to long short on like different benchmarks, like the usefulness of them. I think stuff like HLE, I'm kind of short, long. I'm like, have you guys seen the Minecraft benchmark where it builds the two different? Okay, you basically, two models build like a Minecraft. There's like a prompt, it's like build a house.

Then you can choose and then it's like their rank. The models here and for the mines. But who's grading that? The human? It's a human who picks between them. It's kind of like an ELO. Oh, okay. But just like general kind of creative tasks.

Sure. I think stuff like that, Aiden Bench is good. Yeah. I think even in the Grock launch, there was the vendor bench. Which one's Aden Bench? Aiden Bench is Aidan McLaughlin's benchmark. It's just like, it's kind of hard to describe how it works exactly, but it's just various, like, creative tasks,

how, like, kind of novel its thinking is, the, like, style of its text. Sure. Wait, it's just like whichever one he likes the most. At the end of the day. Like, he's the only grader? No, no. There is, like, an objective, like, function that you can, like, you can, like, run it. It's not just, like, even.

The idea that's like, open a guy. It will be funny. You know, there's a period of life where your SAT score, like, it matters a lot. Totally. And it says something about you. And then a decade later, it's, you know, what you can do, what you have done starts to matter a lot more. And so I do think we'll reach that point where it's like, yes, you can one shot every hard exam question there is that you can throw at it. But like, what can you do for me?

Yeah. Yeah, totally. And I think that's, I think that's why, like, the bigger question is almost like, you know, chat GPT DAUs and like, and like actual revenue. The final benchmark. And the final batch. And stuff. Yeah.

I mean, the revenue thing is interesting because you wind up in like B2B cloud world, which is valuable, but it's maybe less, it's like, it's more competitive because it's more commoditized. And, well, yeah. If, uh, you, you don't have a lot of leverage in. the enterprise if Azure is able to offer infinite models that are that are infinite frontier models, open source models that are maybe just behind the frontier, but great at certain tasks. The leverage isn't quite there. There will need to be another pretty significant leap until then, you know,

Anthropic being really good at co-gen. There's leverage there. We saw this yesterday with Lama switching over to, anthropic models internally and then you know just having a consumer app with a lot of users also very valuable yeah the other interesting thing about the the foundation model layer commoditizing and it becoming like cloud and if you have a model you'll just be like vended in as an API to anything else like the token factory is that the the hyperscaler clouds are extremely profitable like even though AWS, GCP, and Azure are all somewhat directly competitive and they're somewhat perfect substitutes for each other.

They have not driven prices to zero such in the way airlines are like deeply unprofitable. Like AWS and Google Cloud are both profitable. Yeah. Or you look in other commodity sectors like oil and gas. And I don't know if that's just because there's lock in. I'm not exactly sure. But there's something about where, you know, maybe the, maybe the counterintuitive take is that, yes, they do commoditize and there are a few major foundation models that are frontier and they all are roughly the same price, but they all have decent lock-in with their customers to the point where they're still able to extract some level of profit, or they're just creating so much value that even if they're taking like a small marginal slice on top of, on top of the cost to run, that they're creating so much value. that they still have 50% margins or something like that.

Because like, I mean, this was the story of AWS. Like, no one knew how much money it was making. And then they had to break out the financials in one of Amazon's earnings reports. And it was like the AWS IPO, as Ben Thompson put it. And next up, we have Ben Thompson from Stratory coming into the studio. Very excited to talk to him. The moment we've been waiting for. Yeah.

Welcome to the stream, Ben. Good to have you on the show. you've been a backbone of many analyses here on the show and we're excited to welcome you to the show. How are you doing? I'm doing good. I put on a button up shirt and a jacket just for you guys. These are feel honored. I am wearing shorts underneath.

I wasn't yet. You didn't have to tell us that. People always ask if we wear shorts. We actually do wear the full suits. We got to stand up to hit the gong sometimes. There's a wide shot. I am the poser here. So I'm happy to admit.

It's a great sign of respect. in our culture to put on a suit for a TBPN appearance. And we're just, we're so excited to talk to you. I, as, you know, I've been lucky to read your work in my entire career. And, and, uh, I think it, I think so many of the thoughts that I have are now, like, your, your way of thinking about technology and markets is so embedded in my brain that, that, that ideas that I hold as true or just foundational beliefs are actually your beliefs that have just become so, so immersed. So it's great to talk. Well, thank you.

I will attempt to implant new ones or maybe show you the error of your ways. What are you? Sounds great. I do have a question on the nature of where you sit in the media world before we go into actual questions about tech companies. It's interesting that in some ways, you're a journey. But you don't really do the scoops and breaking news that much. But you also don't issue just straight up buy and sell recommendations. What was the thesis behind not just actually having a price target and not doing like this is a sell side bank, but independent? Well, when I started, I mean, it's funny to hear you talk about like my quote unquote place in the ecosystem. Sure. Because when I started, I had like, I think it was 368 followers on 20. I was just some sort of random person on the internet.

In retrospect, sort of right place, right time, I think is certainly the case. But I did perceive there was a large gap between tech journalism and I would include a lot of the bloggers there who were writing a lot about products. And then there was Wall Street that was very focused on sort of the financial results. And to my mind, there was a large space in the middle, which is tied together the products to the financial results. but also the overall companies and strategies. And I'm very interested in culture and how that guy's decision making.

One of my sort of precepts is all these companies are filled with smart people. And a lot of people, when you ask them why they did something wrong, their only answer is that they're stupid. And I'm like, no, they're not stupid. It's actually much more interesting to assume they're smart and are doing stupid things and trying to unpack why they are doing that and what goes into. that and and so that was sort of the thesis was that there is this space to explore these spaces and then there's a business model aspect which is I started trajectory two years after Stripe started I think they had just come out with their billing product and the only alternative of the time was was PayPal for subscriptions and it was fairly sketchy and there was lots of like

horror stories out there about you know stuff kit and just the Stripe API was so great and the things you could potentially do with it and so on Wall Street your putting a price on it, you're also charging like $100,000 a year or something like that. And so you get a small list of high ARPU clients. And my thought was I could go in the opposite direction and get a large list of low ARPU clients thanks to things like Stripe and the ability to subscribe. And that would, and as part of that, I wasn't going to go through the rigamarole of getting registered and doing stock picks and all that sort of thing.

I've always joked if you want a stock pick from me, you're going to pay me a whole lot more than $15 a month. It was $10 when I started. And it's actually pretty great. Now, there's some, one of the critiques I do get, particularly from my, you know, friends on Wall Street is, you know, no skin in the game, XYZ. I think at this point I'm large enough that my reputation is significant skin in the game. But I do recognize the validity of that critique. Yeah. And you know, if you make a bad call, you're going to have to circle back to it in two years and write about it yourself and admit that you got it wrong. Right. Right. Right. Which hurts too.

No, I had to write about this week. Like, I was very optimistic about Apple's Apple Intelligence announcement last year and the theoretical power it would give them over the model makers. And now I'm ready. Actually, no, they're going to have to pay up. And that's, you know, that was a bad call by me that, you know, I think was, you know, very well received at the time and might have gotten that one wrong. And so I do need to be straightforward about that.

And so just this morning, I was very crystal clear. I got that one wrong. That was, that was an issue. What is nice is strategy kind of ended up being in this interesting place where I feel like I'm a little bit of like the Switzerland of tech and that no one pays anymore. If you're a CEO, you pay the same amount as, you know,

Joe Blow it on the street that is paying it. I don't invest directly, which I think made sense when I started because they didn't have any money. It's probably hurt me a lot over the years since. then. But I don't like, and I think this is a different West Coast, East Coast thing, where it does feel like on the West Coast

everyone's talking their book sort of all the time. And you know, that's why I generally as a rule don't have VCs on to do the Shetri interviews. Sure. Because it's kind of hard to get like a real take because that is such a motivation.

And so me coming in being like, I have no book to talk. I'm just here telling, saying what I think has been good for the West Coast audience, which is my base audience, even if the East coasters think that I'm being a big wimp. Yeah, the Talking Your Book Challenge, we go through that a lot. Yeah, and trying to 12 VCs on a day. Well, yeah, and we just try to get a bunch of different opinions and triangulate what, you know,

what we think is real. I'm trying to come up. You have TPPN. I'm trying to come with a P so I can get the Talking Book Network in there. but um talking book production network yeah yeah yeah it's at the spian for talking your book but yeah it is a real struggle to find somebody that for example has a deep understanding of every foundation model company but isn't massively conflicted at in some way or another extremely extremely yeah and so it's one of those things you just sort of you you end up like

there's so much path dependency and all these sorts of things and like i mentioned like a big advantage I had was I started at a time when sharing good links was very high currency on Twitter. And so, you know, I grew very, very quickly, much more quickly. I sort of had a five-year plan to go independent. I ended up doing it in less than a year, in part because it just sort of spread really, really rapidly. And it was an ideal time to be someone sharing interesting links regularly. And I wasn't sharing them.

The beauty is my readers were sharing them. They were doing sort of the marketing for me. And so I'm very cognizant of sort of the luck I had in that regard. And then just over time, and it's been an interesting journey for me to grapple with my different position in the ecosystem. Like so when I started the Structory interviews, that was sort of part of it, which was I started out not knowing anyone. I got to the point where I can talk to anyone that I want to. and so how do I square that? I can't be the guy with the chip on his shoulder

trying to make a name for his self forever. It sort of gets, it's like the meme with the guy, how are you doing kids? Like at some point you have to accept your part of the establishment. How can I do that will still staying true to the idea that Shetectery is about the readers. It's reader funded. My loyalty is to them.

I'm very clear. I have no loyalties to anybody else. And so, well, I'll just, I will talk to people. sort of acknowledgement of what I can do, but it's going to be fully transcribed and published and sort of available to everyone. Have you ever dealt with or thought about the attack vector

of a special interest, you know, buying a thousand plus, you know, thousands of seats to a single, you know, independent publication and saying like, yeah,

like, you know, we got seats for all of our employees, actually, because we really, you know, love the, and then,

and then suddenly they're sitting over there, and, you know, it's representing meaning, very, Very meaningful amount of your revenue. I mean, I fortunately, I think of a scale that I don't have that problem. Yeah, that's good.

There we go. But it's, but no, I think audience capture for subscription sites is a potential issue for sure. And this is another thing. I was sort of right place, right time. I got big enough by the time that it doesn't matter. And if someone's really up, like, I give refunds all the time. Actually, if someone really upsets me, I will refund them in every dollar they paid me. I'm just like, go away.

I don't, you know, I don't, you're being abusive or whatever it might be. Yeah. And that, that is a beautiful thing about the relatively low price, high customer base model is no one has power for me. I have the burden of publishing, you know, as often as I do, I feel a heavy weight of duty to my customers. When I write something I'm not happy with, like I don't sleep well. But at the same time, there's no one customer or no, no, no individual. that can come in and be mad at me and impact my business. I'm seeing that there's maybe some sort of parallel between legacy media and independent media

where independent media, it's not by default more pro tech or anything, but there's just no salary cap. So if you're at a legacy institution and you're writing, probably some sort of rough, loose salary cap of a few hundred thousand dollars, whereas you go independent, it's feast or famine. You might fail, but you might get really, really severe. successful and have a huge income from that. And I'm wondering what we're seeing in the AI salary wars, where we're seeing more and more talent and Mark Zuckerberg potentially paying $100 million bonuses.

Do you think that Apple will come around to spending more money on researchers? It feels like they kind of have an internal salary cap with Tim Cook making $75 million. There's now people that report two levels down from Mark Zuckerberg that are making more more than Tim Cook. And you have this weird dynamic where even if there's no actual salary cap at Apple, you kind of have an implicit one from the CEO. Yeah, for sure. I mean,

well, I think just to go back to the media observation you started out with is as you increase transparency in the market, as you decrease non-related barriers, which in the publishing world previously was really geography. And when everyone's on the internet, you inevitably, you know, just about all cases, you get a power law distribution.

And a few people make a ton of money because they win most of the market and then some people make some. And then there's a long tail that that sort of don't make any at all. But it's very, it's interesting. It's fluid in a way, but it can sort of become somewhat static as long as the people at the top sort of, you know, continue to do well. But what's interesting about AI is for 40 years, you would have periods of time where you'd have tech companies going to head to head in a product market. And I think one of the reasons part of the software eating the world sort of idea is the way you get an apex predator is that that predator killed everyone else first. And so you had tech companies fighting each other for the first 20, 30 years of tech. the ones that emerged were lean, mean, killing machines, and they and the entire industry were sort of set loose on the rest of the world, and everyone was just like, was getting slaughtered, sort of left and right.

But what you also had over this past sort of 20 years or so is the big companies of particular sort of slotting into unique slots. So you have Facebook is social, Google is search, Apple is devices, Microsoft is business or, you know, business applications. Amazon, e-commerce, et cetera. And obviously these companies are very large and do lots of things. And there's some overlap in different places. But they've been fairly sort of distinct in their categories, and they've been dominant in those categories. And so they've been in a place where, like, Hollywood is wanting to get to, right?

What is the dream in Hollywood? You want to have a franchise where the next Marvel movie matters more than who the star is. the reason that's so great is because you now have bargaining power over the stars. You just sub someone else in. And whereas the old style, like Tom Cruise makes the most money because Tom Cruise on a movie poster sells the poster. And so in a negotiation, he has massive bargaining power. So he's going to get paid a lot of money. In tech, it hasn't been that case.

The companies themselves have been franchises. And so the overall, anyone who works in tech, it probably works in any entity, but you know there's a few people in each company that are critically important, really make the whole thing go. Everyone else is very replaceable. Those people have probably always been somewhat underpaid for years and years and years, both just by the nature of companies and the cultural issues and your salary cap sort of analogy. But then also just like it's not a transparent market. It's not hard to price sort of what people are worth. With AI, everyone's trying to do the exact same thing.

So you have multiple companies trying to do the same thing. The output is somewhat measurable. I mean, all the AI test stuff has issues, but by and large, everyone kind of knows who has the good models and who doesn't. They, you know, the scalability questions. You know, like, because all these companies are trying to do the same thing, we have a very unique situation where the bargaining power, you increase transparency, you increase sort of the liquidity or the ability of people to move around. because they're doing the same thing, the bargaining power shifts to the people that are super valuable because suddenly it's much more clear who's valuable

and their skills are much more transferable. So this is, I think, a very underrated bare case for tech in terms of AI, at least for this time period, is they've lost that murky bargaining power over employees that they enjoyed for decades. And currently, you're seeing what happens when you don't have that. You start paying employees what they're worth.

And obviously that's great. I'm not saying this is a business analyst. It's not a sort of a moral statement. But it is like what Mark Zuckerberg is doing, I think, is totally rational. I think it's a classic sort of Clayton Christensen from Facebook's perspective. AI is all upside. So of course they're going to invest what they need to do to win. But it's costing him a lot of money.

And by extension, it's costing everyone else in the ecosystem a lot of money. Well, isn't it in some way, is the right way to think about the last couple weeks, like more of like an, like an unofficial aqua hire in the sense that you're, it's, it's not just the people, but it is the, the know-how in terms of, hey, here's, there's these things that we want to do that are important to our business in a lot of different ways. And we're basically, it's, it's like the collective is actually more valuable than any one, like the collective together, getting 10 researchers at the same time is meaning, is meaningfully more valuable than just each individual researcher added up.

There's probably something to that. But I think, again, like what is actually different between what Google is trying to do, what Anthropics trying to do, what Open Eye is trying to do, and what Met is trying to do. They're all trying to do the same thing. So I, my suspicion, I'm not an AI researcher, so I don't want to overstate my knowledge in this space. But my suspicion is skills are fairly highly, highly, transferable. And when that is the case, there is, in some situations, if lots of people can do those skills, that's terrible for the employees because then their bargaining power gets diminished because

anyone can slot in. But we're in this space where the skills are transparent, knowable, transferable, and there's not very many people that can do them. And so it's a scarce resource that everyone's fighting over. And that's why you see this real shift in negotiating leverage as manifested through these dollar figures to to AI researchers. Yeah. Do you think I mean Google seems like the most fragile and the most like paranoid about just disruption. It's not all upside. It could be very bad for them. The innovator's dilemma, you know, you had this back and forth where Sinder Pachai mentioned that he hadn't read the book. He said it doesn't matter because it's a structural issue. I think that's a good point. But if you play back the counterfactual, is it ever possible to disrupt yourself and essentially

like if the Gemini app had launched before ChatGPT and they had taken over that mind share and maintain 90% ownership in that, like it would be somewhat disruptive to their revenue and their profits as they transition over. But when I sum the revenues from OpenAI and LLMs and then Google search, I'm not seeing some massive drop-off that's actually, that actually would destroy Google in the media, short-to-medial. term. So but I'm wondering if you think it's like is it entirely impossible to avoid the innovator's dilemma by disrupting yourself? Well, number one, you have to also look at margins not just revenue. Yeah. But number two, you actually, you

answered your question. Okay. Well, didn't launch Gemini as yeah, yeah, that's the answer. They were years ahead. Yeah, they invented the transformer a decade ago. Yeah. And so in many respects, like there's part of the of this question that the counterfactual makes the point in that it is a counterfactual and it's not reality. Now, I do think, I think Google has done better than I expected over the last two years. I like what they're doing in search generally. I think they, it does seem to be the one part of the company that still functions. Like they can actually iterate and build products.

What we're seeing is reminiscent of what they did a decade, 50, you know, or 12 years ago when Airwold like vertical search Google's done all the everyone's going to search in apps and Google completely transformed the search engine response page whatever it is the search is and results page to be local or to be shopping or whatever and Yelp's been throwing a hissy fit sort of ever since and and so that's what they're doing with search right and and with search overviews and they have this new search labs or AI mode they can sort of test stuff out what's it scalable once they're confident about the monetization issues they can sort of shift it over

I call it the search funnel, search AI funnel. I think it makes a lot of sense. And I think, this is always actually kind of puzzled me where I think they're responding fairly well, even though this is, seems to be a textbook case of disruption. And I went back to an article I wrote years ago called Microsoft's Monopoly Hangover. And I went through Lou Gersner's autobiography and about how he turned around IBM. And his real insight with IBM was everyone wanted him to break it up into sort of different pieces. And what he realized was IBM was so big and large from having downstream of bin monopoly

that actually the only thing they were good at was being big. And so breaking them up would actually just create a bunch of subscale, low-performing companies that would all get wiped out. but as this behemoth, they could go to other big companies and solve all their problems at a very mediocre level, but it still is sort of an attractive proposition. And under Gersner,

they really rode the internet wave. They went to all these big companies, said, this internet thing's happening, you need help, we'll solve your problems for you, and had a very sort of successful run, you know, kind of until cloud came along,

which Gersner, by the way, was a proponent of, but by that time the IBM people were back in charge, And I was thinking about the context of Microsoft where business models are hard to change. And disruption is ultimately about business models. And culture is even harder to change. But what can't really be change is the nature of who you are. And I think there is, you know, in Microsoft, they were in a similar situation.

They were a big monopoly. And they weren't a product company. And the attempt to become a product company with Windows 8 and all the things that went on around that time, inevitably failed. And Satina Della, to his great credit, you know, sort of diminished Windows importance in the company, literally broke it into pieces, spread it around. And this was a multi-step process and got Microsoft back to a place of we're big and we'll do everything. We're not a Windows company. we'll go in there and we'll go solve all your problems,

very sort of reminiscent of the second version of IBM. And I go back to Google. And I've always been intrigued by the I'm feeling lucky button, which doesn't exist anymore. But I always enjoyed that that button continued to exist long after it was impossible to click because the moment you started typing the search box, it would start auto searching immediately

and jump right to a search page. But it was there in, a it's just so core to Google to give you the answer to to know everything like to know everything about the world and to there's a bit where even though the core of their business model is 10 blue links and it's not just the the users choosing the search link which gives them the data feedback loops they know which results better but also the users choose the winner of an auction Google puts on for ads and it's an incredible business model and there's some something about that that's always been intention and counter to what Google was founded to be.

And I feel like that germ of what Google was founded and meant to be is an AI answer engine. And it almost feels like even though Google is old and large and fat and slow moving, that core aspect of their nature is still in the culture. And that's why they're finding it in themselves, I think, to do better in AI than you would expect. Was it enough to watch a chat GPT before Open AI? No. Was it enough to have any sort of cogent response for the first six to nine months? No. But it was enough that I think they've done better than I expected over the past year in particular

and gives me, I think, more optimism than I expected I would have for the company when you know, when chat GPT first launched. Judy. AI overview from Google. If you search Google's mission, Google's mission is to organize the world's information and make it universally accessible and useful, which is exactly what language models do really, really well.

Like the thing that's just undeniable, right? You can debate whether this is going to be the year of agents. It doesn't feel that way to me yet. But this is the year that most people have realized that, wow, LLMs are very good at organizing, surfacing, and making data valuable. You mentioned just the debate over breaking up IBM. I'm interested if you could take us through some of the... I mentioned Rajee, we talk about IBM today, did you?

No, no, no. I want to talk about Intel and kind of your, the history of some of your takeaways and what you think you've gotten right in the past, your perception of, you know, should they break up the foundery business? and what you think might be in the works with Lip Buton coming in there. Because I was listening to Dylan Patel talk about his conversation with the new CEO, Lip Buton. And it seems like they're doing lots of tightening up, lots of layoffs. But it's kind of, I don't even know what framework to apply to analyze, like, is a breakup the correct thing?

It feels like something people just say. Yeah. So Intel, it's funny. one of my very first articles was about Intel. And what I said at the time was, and this was 2013, and this was an art, like, you know, when you start a site like Sterechery, you're like a new band. And why does everyone think a new band's first album is the best? Because they've been working on these songs for years, right?

And then the next album, they had a year to do it, and they all suck, right? So I'll let people decide if that applies to trajectory or not. I won't be offended. The sophomore slum. But, yeah. But I'd have been on, you know, Intel had been a thing I've been wondering about for a long time, which was by 2013 when I started, they had clearly missed mobile. Now, it wasn't clear to them. They were still trying to do the atom processor and just they're going to figure it out tomorrow.

And the problem with missing mobile is the problem with Intel in general, Intel is always very biased towards high performance. And this goes back to actually Pat, Pat Galsinger. his first time through at Intel. Intel, you know, had the CISC, the way there's CISC versus risk. It's like, it's different ways of organizing bits or whatever.

Risk is generally more efficient and actually even Intel processors today, even though X-86 is CISC, the internal, it's re-translated internally to a risk-type language. None of that is really important other than to say in the 80s there was a real push in Intel

to switch away from X-86 and to a risk type of, I mean, I don't use architecture, but like for the processors. And Galsinger was a leading proponent that this is a terrible idea. And the reason this is a terrible idea is because there was already a huge ecosystem of software built around X86. And all this low level code and capabilities that no one ever, that was written once and no one ever wants to touch again because it's miserable work. And he's like, to rewrite all. that stuff would take at least two years. And in that time, our ability to manufacture chips will improve so much that had we just stuck

with CISC, our processors would be faster. And that was the right bet. And that's one of those foundational bets that I like to think about companies in their history and what goes into that, which is Intel from the 80s on has solved its problems by having superior manufacturing and by moving faster. And yeah, our chips may be theoretically less efficient, but if our manufacturing is better and our transistors are smaller, it doesn't matter because that will swamp whatever theoretical sort of efficiency you might have. And this drove the entire computer industry. You would write to write a program, just every second you spent optimizing your software in the 80s or 90s was a waste of time because whatever improvements you could get would be swamped by the next version of, if you went from 286 to 386 to 386 or 386, or 360 to 4.

That jump was so large. You were better off focusing on features, even if it made your software sort of slow to use on the current hardware, because the next generation of hardware would be so much faster, it would solve your speed problems for you. Now, this has generated a lot of bad habits amongst tech developers. That's why you get bloated and why you have like poor performing things and all those sort of things. But this was sort of super critical. And so Intel at its core has always been focused. They've always been manufacturing first and focused on better. and better performance. What happened with mobile is in that calculation did not come efficiency. They were never focused on efficiency. And in mobile, efficiency was everything. So what happened with mobile is Apple went with an arm processor made by Samsung. And they basically rewrote everything. All that stuff Intel didn't want to rewrite in the 80s or if they rewrote would just

give other processor companies a chance to catch up with them. had to be rewritten for mobile because efficiency was so much more important than performance. When that happened, Intel was screwed. Now, it took them a long, long time to realize they were screwed, but they were just fundamentally unsuited

to be competitive. It was, the whole Paul Adelini turning down the iPhone contract is not true. Tony Fidel, I said that once, and I got a call from Tony Fidel. Actually, this is when I had him on it for an interview.

And he's like, this drives me up the wall. Intel was not remotely competitive even though they had arm chips then even their arm chips then were focused on performance not on efficiency and and so the problem for the problem for Intel is once you missed mobile you were going to lose your manufacturing lead at some point because volume matters so much and every time you move down the curve your transitions get smaller the cost increased massively so you need volume to spread out the cost of building these fabs like back then when I wrote this

article, Fabs cost $500 million. Now they cost like $20 billion. And this is over a course of like 12 years. So it was clear Intel was going to be in big trouble back then. And so I wrote, they need to build a foundry business. They need to figure out a way to build chips for other people because in the long run, the cost of keeping up in manufacturing is not going to be tenable if you're not making mobile chips. And what obviously they didn't, TSM made all the mobile chips for everyone and guess what happened. TSM took over the manufacturing week. Now there's lots of other things that went into this, why Intel stumbled and sort of

things. But at a structural level, what happened was actually inevitable. Once Intel missed mobile, unless they figure out a way to make mobile chips some other way. They didn't do that. What's interesting is what is the problem with that, it took so long to manifest. part of mobile was you had an explosion in the cloud because cloud and mobile actually go hand in hand.

Intel made all those cloud chips. Intel stock had an incredible run from the time I wrote that article for the next eight to nine years. And I felt like kind of a moron because I might say, because I might say this company is screwed if they don't do what I say. They didn't do what I say, and their stock went to the moon.

But the way it actually caught up to them has been in the past two to three years, where there's astronomical demand for AI chips. Only TSM can meet it. Intel's not in the game. They're trying to shift to a foundry model, but they're so far behind it. Being a foundry is being a customer service business. It's not being an Intel, we tell you what to do, or we, we tell our design teams how to change their chips to accommodate our manufacturing needs.

It's just, it's totally different. And they needed a decade to learn how to do that. Had they changed in 2013, they would be ready today to capitalize on AI. And the counter example here is Microsoft. Microsoft building Azure, yes, it got them somewhat in the game with mobile and things like that. But AWS dominates in that space. But by virtue of building up Azure, they were prepared when the AI opportunity came along. And now Azure is sort of a big AI player.

And I wrote about these two examples a few weeks ago in the context of Apple. I think the concern for Apple isn't the short term. We're going to be using AI apps on our iPhones for quite a while. It's are they going to be prepared for what's next if they don't do some sort of reset and pivot here? Oh, sorry, I didn't answer your question about Intel. Anya. Yeah. I mean, it's a, I'm hearing like, you know, manage decline, basically.

Like, just like, you know, just get as much cash flow out of this thing as you can while you wind down the business. For Intel? Yeah, that's what I'm hearing. Yeah, it doesn't feel like, oh, yeah, there's a silver bullet. Just split the business and they're good. Like, no, it's like, it's all bad. The progen are not split the business is Intel needs volume and they get volume from Intel. Sure.

And the, and AMD split their business a decade ago. And it was really, they had a very hard time for many years. And they had very tense and difficult negotiations between the global foundry side and the AMD side. Google Foundries was AMD's manufacturing arm. And it wasn't until really, They got out of that and went to TSMC and then also completely rehauled their ship design business and all those, you know, that they got in the business they were. And then also that Intel stumbled. That certainly really helped them.

Intel today, so you split it up like who's but like Intel's Intel itself is fabbing some of its stuff with TSM. Yeah. Who wants to buy Intel's foundry services? The problem here is TSMC is located in a country called Taiwan. which you know what it is today but five years ago it had been like what Thailand which by the way

it was probably much better for Taiwan security when American Sato was Thailand but so there's a real national security element here and it's just it's a really tough situation

because Intel is a failed company at this point and the reason the failure is so total is because the aspects that drive their failure are the same things that drove their success. It was their arrogance.

It was there a sense that we're the best, that we will just win through manufacturing might and performance. And all those things work against becoming a good foundry, work against being a customer service organization, work against recognizing the fact that you're not going to make up for missing mobile through manufacturing, which was their bet for years and years. You had to accept that you lost. And that's a tough place for companies. It's not like someone made a mistake.

It's not what they did what they did too well for too long. Who they were. They continue being who they were, right? That's right. But who else are you going to get? If you want an alternative to SMC, it's a very tough situation. Last question, and I think we'll be forced to have you make a slightly shorter answer, unfortunately. I wish we had hours to keep talking.

Yeah, we got to get your question. You're updated thinking on XAI, X, the combined entity, the last 24 hours have been very chaotic. When the initial merger was announced, it made sense for financial reasons for some of the different stakeholders. But I wasn't fully sold on this idea how strategic. You're going to push me go with takes that I generally just avoid right about Elon Musk companies for self-sanity reasons, I think. I mean, I remember I wrote an article years ago about like when the model Y, was announced. And I was talking about, you know, it's a Tesla

in this aspect. What Elon Musk is very incredible at is sort of creating reality out of thin air. He's like the ultimate memer. And to create like it's a way things used to work backwards.

I remember I analogized it to like protests. Like a critique of modern protests is they spin up very quickly because social media makes it very possible. But there's no infrastructure under them so they don't amount to anything. Whereas you go back to like the civil rights era, there was years of groundwork that went into like the million man march

on Washington, D.C. And there was a structure in place that ultimately manifested in large crowds. But modern protests are the opposite. The largeness comes at the beginning and that all falls apart. There's nothing in place. And there's something that makes

a challenge to write about anything Elon Musk related is the you have all the social aspects is you have this bit about Tesla of creating reality. The stock was buttressed for years by these true believers, even though the financial parts didn't make sense. You famously had these wars with the short sellers and all that sort of thing. And it worked. It basically manifested a market for this Model Y and then the Model X. Not the Model X.

What's the other one? The Model 3. It was Model 3. Sorry, when I wrote that article. Model 3 and Model Y had this massively successful. and all the people that were true believers got very rich. And congratulations to them. It's great.

But it makes it almost impossible for someone for what I do, who I want to look at structure and fundamentals. I can observe this effect happening, but you can't really say what's going to happen or the effects of it other than to say, this is interesting. And so I wrote about that article and then the Solar City thing came out. He's like bailing out like his brother-in-law or something. And I'm like, I can't write about this. Like, what am I going to say? Like, there's, it just doesn't make sense. And so I think there's, to fast forward X, XAI, yeah, there's a theoretical piece here.

I think actually XAI would be an incredible acquisition target for a lot of companies if it wasn't saddled with X. So. Yeah, it feels like the end state is like Twitter getting spun out again. Like that, that's my, that's kind of like my, my, it just ends up going back to Twitter. and it becomes the bluebird. Right. No one actually wants to, like Twitter, Twitter, there's never been a company in the history of the

world probably where the impact of a company is completely an early divorce from its financial realities. Like, I think when Elon Musk bought it, and I assume that's continued through now, they'd have like one profitable quarter in their history. Like, it's an unbelievably

terrible business. And so I think it's probably weighing XAI down. There's a, yes, I get the theory that Twitter data helps X-A-I. Well, it helps yesterday. You don't need to pay $43 million for Twitter to, or $43 billion, I should say, to get it. Yeah, that was always my position, too. I don't think it helped yesterday when Mecca Hitler emerged on the timeline.

But anyways, hopefully they sorted out. I wish we had a lot more time here, but hopefully we can do it again. Thank you so much for stopping by. Yeah, no worries. What was you guys are doing? I actually had the idea of doing a daily podcast, ages ago. Classic example of ideas don't count execution does and you guys you guys did it. I think it's great. Well, you're always welcome here. You're always welcome. Thanks so much.

Thank you. We'll talk to you soon. Bye. Meta just is going deeper with Rayban Maker S. Eslior Luxottica. I cannot pronounce that first word, but people just call it. And so meta is taking a minority stake in Luxottica to accelerate its smart glasses ambitions investing $3.5 billion in the icon. iconic ray band manufacturer. We were talking to David Center about the history of this company. It is fascinating.

I'm very excited for him to break it down for us a little bit more. Hopefully you can come on the show and talk about it because it's a very, very soon. The founder has a crazy story. I think he grew up in an orphanage. And it just, what are they, they didn't call him the pit bull.

They called them something else. But he was an absolute savage. Apparently at one point he wanted to buy a, Oakley and the founder of Oakley didn't want to sell. And so the CEO of Luxottica acquired the largest retailer for Oakley's and just pulled them off the shelf.

And basically had started selling knockoff Oakley's even though they were trademarked. And then eventually the Oakley CEO came around and said, okay, I'll sell your cratering, you know, my revenue. Yeah, you're just gonna tell me. Let's do a deal. Wow. So absolute dog and Shune, we'll have

send her to break it down. What do you make of this idea that like, you know, Apple, when they make a device, they, they redefine and very much standardize that particular market. So when they come out with watches, there are a number of styles of watch. There's the dress watch, the sports watch, the steel sports watch. There's the dive watch. There's the, you know, Cassio style. There's a whole bunch of different styles, right?

Apple comes in and just says there's only one style, the Apple watch. and they become the number one Apple style. And they give you some variance in the band. In the band, little stuff here in there. And they were doing partnerships. I think they did an Hermes band for a while. They've done a couple other things. But it's been mostly Apple's design language on your wrist.

Whereas with the meta-ray bands, they're saying, and now the meta-Oakles, they're saying, you like the look of raybans. We're just putting our technology into the style you like. We're not going to try and create a new iconic style that says meta like Apple says headphones. And they're just kind of like, they're very, very different strategies. And so it feels like...

Well, so I think this is strategic. This doesn't mean that meta can't develop their own styles in time. But I think it's very smart to say, hey, we don't need to innovate on aesthetics and the sort of silhouettes, right? There's classic silhouettes. Rayband silhouette is lindy. These oakly silhouettes are very lindy. Yeah, and they're different markets.

And in different markets. Luxottica has, I think, Garrett Late and like a bunch of other, like, brands under it. So they're basically saying, like, through this, we can deliver. Luxottica has brands in every, for every demo that Meta could possibly want, right, as a $100 billion, you know, company. And so I think it's very smart. I think Apple, like you said, will probably take a drastically different approach in terms of, like around something and that will say something but accessories like i wear just such a such a personal

decision and such an expression of of um of who somebody is that i think that uh you want to give people max amount of optionality yeah it's just interesting is like you could have said that about watches like you before the apple watch you could have said that well you know somebody who wears a dress watch wants a dress watch somebody who wants a steel sports watch somebody who wants a g-shock is a g-shock It's like the G-Shosh, you say G-Shok, and you just immediately think like, you know, special operations guy or jaco-willing listener. Like that, it's like a durable, rugged thing.

You say, you know, Rolex, that's a different thing, right? And Apple was able to standardize around it. And it's interesting that Meta hasn't been trying to do that. And instead, they're focusing on partnership here. It's just like, it's just an uncommon strategy. But it seems to be working. There's another post in here. I don't know if we have it here.

I'm trying to think of a new, like the key thing is Apple's great at innovating at multiple layers, but like generally it's very hard to try to deliver hits in like two specific areas, like aesthetics and design, and then simultaneously in something that's basically a fashion product and then simultaneously deliver the technology. Yeah. So I don't know. Yeah. Jack Ray here says, after wearing Rayban meta wayfarer glasses for a few weeks,

I feel kind of naked wearing regular sunglasses. I found three use cases that are hard to roll back. One, spontaneous photos of my kids when we're out and about. Any cool pose that has a half-life of three seconds I can now capture instead of pulling out your phone. Optionality of music or hands-free phone calls without digging around for earbuds. And three, knowledge-seeking chat when I'm walking around, usually for simple factual things. That's exactly what I experienced when I was demoing the Rayband meta-Way. dayfarers. It turns out there's more questions I feel like asking when there's no friction.

I'm very excited for multimodal and real-time translation use cases too. They're only going to get better. But I think those three are maybe enough. And I think with a lot of these products, just having one killer use case, like just replacing the, you know, the headphones for hands-free phone calls or something. Like if you can just become someone's daily solution for music, like if that's enough to just sell the product and then sell them another one the next year when it upgrades a little bit, sell them another one, keep them as an active user and roll that out for a long time. And then if they can do the other stuff, that's great too. But you just need to get these one, nail the single use case.

And so, yeah, there's going to be cool stuff. But it's fascinating to see them roll this out. And it's also interesting how behind the ball it feels like everyone else is now. Like Google was talking about getting into this space. We saw some launches at I.O. Haven't actually seen any of those in the wild. Haven't seen anyone really talking about those. Apple, it feels like this would be something that they could jump forward to with a stylish pair of eyeglasses with some basic functionality.

Just take what's in the AirPods, take a camera. Like they could do something cool. But they're like just much slower than. Yeah. The other thing with eyewear that's different or that's going to be like a new challenge for manufacturers is that there's so many different situations where I might want to wear something like a ray band or, or, uh, J-A-M silhouette one day and then I might want to I'm playing Jack Marie Mage. Okay. But the, you know, and then that same afternoon I'm wearing Oakley's when I'm playing tennis or

something like that. And so there's a lot more like swapping and then then obviously. I mean, if they can keep the price low, you could maybe wind up selling people multiple pairs and have indoor pair, outdoor pair. It's kind of inconvenient. I feel like there's got to be a better solution to that, but I don't know. It says what are this? Yeah, the bifocals.

Yeah, yeah, where they can flip down. There's transition lenses, but those never fully work all the way, but then there's the flip down ones, clip-ons. There's all sorts of different solutions. The big news is that the third browser war has begun. Google stock has dropped on the news that OpenAI is planning to launch a Google Chrome competitor within just weeks. And this is very interesting.

timing because it's time to browse yeah time to browse certainly makes sense to become deeper in it more deeply integrated into the user's life makes a ton of sense there's a ton of benefits that come from having a web browser what was interesting is the we can go into what Google actually law or what opening eyes talking about launching but this news the scoop leaked the same day that Arvind from perplexity announced that they're finally releasing their next big product after launching perplexity, Comet the browser that's designed

to be your thought partner and assistant for every aspect of your digital life, work in personal. And so perplexity launched this on June 9th, and then Open AI, the scoop goes out via Reuters, the same day. And so this feels like very much like, let's not let perplexity get a bunch of attention and drive a bunch of people to start daily driving,

Comet the browser, because even though we're not ready to launch our competitor. I mean, Arvin was on the show talking about Comet, but over a month ago, he said it was really important to the business. This was a big bet that they're making. He,

and I'm sure both companies are racing to be the first to launch, but DIA, the browser from the browser company, also launched out of, or they're still in beta, but they launched like a month ago or something like that. So this is, you know,

you're not going to be the first. Oh, they launched a month ago with the DIA browser. That's interesting because I saw Riley Brown also posted the cursor for web browsering. DIA browser. And I thought DIA browser launched that same day, but I guess it had launched earlier. Yeah. So anybody that was an ARC user can download DIA today and chat with their tabs. But interestingly enough, perplexities browser and OpenAid's browser are both built on

Chromium, the same open source project that underpins Google Chrome and Microsoft Edge. Yeah. So the cool thing here, that means that they're compatible with existing Chrome extensions. Oh, interesting. Okay, that's cool. Yeah, it's, I want to talk to more people who were, like, active in tech during the earlier browser wars. The first browser war was Netscape Navigator versus Microsoft Internet Explorer. This is in the mid-90s, early 2000s.

Netscape was super dominant, and everyone loved Netscape. It was originally the Mosaic browser. This is the Mark Andresen project. But Microsoft bundled Internet Explorer with Windows 95. and the distribution was so powerful that Internet Explorer actually wound up winning and became really, really dominant. But then there was this lawsuit and went back and forth. But then basically by the early 2000s, Internet Explorer had over 90% market share. But then they got kind of lazy and stagnant, apparently.

And I mean, I'm not exactly sure what happened, but there's a lot more competition. So Firefox, which was, I believe, like a spin out of Netscape or kind of like some of the same heritage there. began getting traction and then Google Chrome launched in 2008 and leaprogged everyone and Google Chrome was really focused on like speed. It was the fastest browser and they did a whole bunch of work to optimize JavaScript so the pages would just load faster and run better on pretty much every computer that you had. And so and then they had the open source project with Chromium and so they were able to kind of standardize the entire industry. And so everyone's always been trying to draw analogies between like the browser wars

and the LLM wars and like what's the role of open source in that like is open source a strategy to wind up maintaining your your dominance how much is distribution matter like Chrome was probably pretty easy to distribute because every single person was visiting Google just every day searching and so you just put this bar hey want to switch to the faster browser and people just do it because you can have basically like you know billions of ad impressions on your product every day will be interesting to see if chat gbt can get people to download their own browser on desktop i mean i'm using chat dpt on desktop in chrome all the time which which chat gpte model would you want to use as a default search engine that's the hard part because i always run into this problem where it defaults to

oh three pro but that takes 10 minutes and so then i have to go to a 4-0 and then if i'm in an o3 pro flow and I'm talking to O3 Pro and I let it cook for 10 minutes. It gave me a great answer. But then I want to just be like, okay, just like clean this up a little bit or summarize this or do some bullet points. I want 4-0 to do that. So I have to switch over. So I don't know. I would imagine I'd go 4-0 as the default because I want speed. But even 4-0 could probably be faster before it truly replaced. Because it was very fast. They've spent a very long time being fast. Yeah. And I could imagine them doing a similar project to, I believe it was like the V8 JavaScript engine, they sent this team out to, I want to say like Iceland or something.

They basically sent like a bunch of engineers to like an offsite and they were like, just go optimize JavaScript for like a month. Just go focus on this for like a month or months and come back when it's done. Like you have no other responsibilities than just like optimizing this like compiler. And they came out, came back with the VA JavaScript engine. It created this whole like Node.js boom. People were running JavaScript on the server then. And I could see Google kind of doing something similar where they're like, okay, we have Gemini, it's good at looking stuff up,

it's a good knowledge retrieval engine, go figure out how to make it load all the tokens for the full response in 100 milliseconds. And that would be very, very cool. And I wonder if that's like a uniquely Google advantage. Tyler, you look something up? Yeah, it was in Denmark. Denmark, okay.

I was close. I was close. Yeah, I wasn't sure it was Finland or Iceland in Denmark. Yeah, the interesting thing here, I'm realizing that tabs are definitely a light lock-in to browser. It's not just the default, but if you have six to ten tabs that you've just had open for a really long time, and they're like from a bunch of different things, and you can't exactly remember what they were if you had to list them all off, but you know, I personally end up using tabs as like somewhat of a to-do list. And so if you're spinning up a new browser and you don't have your tabs, it's like, oh, do I want to just like get rid of?

my tab stack. I have a bunch of tabs that just have stayed there for years and they're basically like, it's basically like a mini operating system, right? With like different apps, it might be a Google sheet or something else. Yeah, I know what I mean. So there's very real lock-in. I could bring all those tabs over, but I have to then log in to a bunch of different services. And so it's really, really hard to actually win here. I wonder if anyone's using, you know, in Google Chrome, you can actually change those. default search bar to, you know, when you type in the search bar and if you just type words, it just Google searches it. You can change that to search chat. Yeah, you can pass in a query

parameter and it can just do that. But I haven't heard of anyone actually doing that. And I used to have, I used to be such a power user of Chrome. I used to have different code words basically. So if I, if I typed like I space and then a query, it would go to IMDB and search that specifically. So you could have Chrome, like, route to any specific search. That's cool. So you could press like Y space and it would search Yelp or, you know, anything else. But I don't know if people are, I don't know if people are doing that with Google with chat GPT. I think people mostly just like control, command T and then hang out in chat GPT.

Well, we'll have to ask Chris in 15 minutes about get an update on the browser wars because he was an early investor in. I know one of those tabs that you have pinned right now. What's that? Adia. Of course. Customer relationship magic. Adio is the AI native CRM that builds, scales, and grows your company the next level. You can get started for free.

I've had Adio open for thousands of hours in a row at this point. Yeah. So a signal kind of breaks it down with the open AI launching the web browser. He says, this is the oldest play in tech, find product market fit with a single killer use case, then vertically integrate and horizontally expand until you control the interface layer itself, app, platform. Once you own the interface, you own the defaults. Welcome to the next generation of browser wars.

Yeah, what's interesting is there, like, Sam Altman at Open AI and just the fact that OpenAI is a company. Like there is kind of a mandate to like vertically and horizontally integrate, figure out code, figure out research, figure out devices. But every company wants to do everything. But then sometimes they run up against barriers. Like there was a time when Google was like, we want to win social networking and we want to beat face. And we're going to launch a direct Facebook competitor and they did and it didn't go well and then they shelved it and then they wound up Producing trillions of dollars in market cap just doing the thing that they do great and so the question is like the surface area of open AI they have to explain explore they have to experiment It's it would be stupid not to see if they could get a browser and a device and a chip and a nuclear reactor and everything and sand get the get everything

But there's no there's no that they will win the entire vertical stack and there will be the one company, right? I think my question is, are these going to be, like, is Open AI's browser going to be an entirely new app other than their existing mobile app? Is it, or their desktop app? Yeah, that is interesting. Because if they have to get people to redownload a separate app, then that's, then that's like an entirely, you know, they have a good flight, you know, they have a It's interesting that they wouldn't just evolve the apps that they already have installed. Perplexity, too.

I don't know if Perplexity has, uh, is planning to, to release this as like a new standalone app or it will be in the perplexity mobile app, but. Yeah. Um, yeah, I mean, I know I think comments like its own thing because we were looking to download it and we need a code. Um, and you can't just get it if you're just on perplexity. Um, but I don't know. All I know is that you should go to fin.com. A.I.

The number one. AI agent for customer service. Number one in performance benchmarks. Number one in competitive bakeoffs. Number one ranking on G2. So, Arvin breaks down in like his philosophy of, of Comet,

the browser that he's dropping from perplexity. He says, you can either keep waiting for connectors and MCP servers for bringing in context from third party apps, or you can just download and use Comet and let the agent take care of browsing your tabs and pulling relevant info.

It's a much cleaner way to make agents work. So that is interesting. So I wonder how much like puppeteering will be in this because chat GPT and open AI have operator that operates a chromium front like a headless web browser basically. But you can actually see it working and it's clicking things. And so if there like there's also the value of like the training data. If you're getting people using all these websites, you have all this training data of like, okay, they clicked on the blue button. They clicked on the green button. They saw this.

They entered that. This is how they dealt with this form. This is how they dealt with that form. And so that feels like very, very valuable data if you can get it. So it's probably worth duking it out even if it doesn't, even if it takes a long time. For sure. I do wonder where else they will, where they will plug in, like, clearly operates at like a higher level of abstraction with like the screen scraping. And I wonder if we'll hear rumbles about either perplexity or open AI thinking about like,

moving up the stack to that level. I'm not exactly sure.