This Week in Startups - Open-source vs. "ClosedAI," demoing new AI tools & more with Sunny Madra & Vinny Lingham | E1742

Episode Date: May 16, 2023

Sunny and Vinny are back to demo some new AI tools (14:08), discuss open-source vs. "ClosedAI" (38:45), and more! (0:00) Jason kicks off the show (1:31) Jason's trip to the UAE and Abu Dhabi's 30-year investment horizon (12:39) Miro - Sign up for a free account at https://miro.com/startups (14:08) Sunny demos ChatPDF and LLMs' future in the workforce (24:23) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist (25:41) Google's new universal translator (30:11) What is Hugging Face?  (37:26) iConnections - Get 20% off iConnections Miami 2024 event at http://iconnections.io/twist (38:45) Open-source vs. "ClosedAI" and the race to build AI hardware (48:28) Comparing Google Bard to ChatGPT (1:01:13) Google's vision for Gmail and AWS's partnership with Hugging Face FOLLOW Vinny: https://twitter.com/VinnyLingham FOLLOW Sunny: https://twitter.com/sundeep FOLLOW Jason: https://linktr.ee/calacanis Links: https://www.semianalysis.com/p/google-we-have-no-moat-and-neither https://www.chatpdf.com https://huggingface.co/espnet/kan-bayashi_ljspeech_vits Subscribe to our YouTube to watch all full episodes: https://www.youtube.com/channel/UCkkhmBWfS7pILYIk0izkc3A?sub_confirmation=1 FOUNDERS! Subscribe to the Founder University podcast: https://podcasts.apple.com/au/podcast/founder-university/id1648407190

It should have a button that would be like the J-Cal button, which would be like troll this person. And it would be with troll options. And like my troll option would be like, why do you, why does Hamas, why does everybody hate Hamas and then link to the clip of Sasha Baran Cohen? He's talking about hummus and Hamas. He's like trolling them. Trolling options should be there to do like jokes and stuff like that. That would be a great startup is an agent that follows you around the internet. and then optimizes your trolling and comedy and just makes a, you know, a mockery of everything.

Mockery AI. Somebody go grab that domain. This weekend startups is brought to you by Miro helps take ideas from in your head to out there in the world with its ability to democratize collaboration and input. Sign up for free at Miro.com slash startups. Lemon.io. Need to speed up your product development without draining your budget? hire vetted engineers from Europe at lemon.io. Go to lemon.io slash twist to get 15% off for the first four weeks.

And IConnections is a platform to connect and meet with elite capital allocators through their online platform and bespoke events. The first 25 VC funds to sign up for IConnections Miami-24 event in January of next year will receive a 20% discount. Head to iConnections.I.O. slash twist to sign up today. All right, everybody, welcome back to this week in startups. Once again, it's our AI roundtable. Call it this week in AI if you want.

Every week, we're going to do this until this AI thing slows down, which basically means until the singularity AGI happens and humans are retired. With us again, Sandeep, Madra, we call him Sunny. He's a co-founder of definitive intelligence that lets use his view on and off-chain data. but let's be honest, he's pivoting this whole crypto on chain analysis data thing to AI, right? You're all in.

You're full boring AI. We are all in on AI, yes. Yeah. So enough with the chains and the tokens and the NFTs, it's enough. They're important. What did you say? They're important.

They're going to be what's going to, oh, the source of truth is going to be powered by that. Yes. So it'll be a feature like of the wider new internet. But this is really AI is the new web. 3.0. I think that's going to be how I'll look back on it. Vinnie Lange is here. We're going to give Vinny credit for that. Yeah. You're he did. I'm giving Vinny credit. Here you go. I'm founder of Wait Room,

one-on-one video conferencing for your corporation, your enterprise, including a bunch of AI stuff. How you doing Vinny? Hey, Jay-Hall, good to be on. All right, let's get started. I'm in New York City. I just got my coffee. I had a little sticker shock, $8 for a cold brew. New York's wilding out here. I walked over. I'm at the Salt Conference. Just got back from UAE. and I'm speaking at the Salk Conference The world

The Tour continues Did you get in Hissa Bagel? You know, I went to Sullivan Street Bakery I'm over here on 48th and 9th on the Hell's Kitchen We're the Irish, you know My Irish brothers and sisters We ran this part of town for a little while

But I just went to Solid Street bakery And like a big argument broke out there The tension's very high in New York right now So I just step in It's a little, everybody's on a little bit of edge Usually New Yorker's a little chippy but it does, you know, usually dissipates pretty quick,

but there was a, on the line, there was a little bit of a brewhaha, woman asked for a piece of bread, the woman who was taking orders her first day, she didn't speak English perfectly, they got into it a little bit,

and then the manager said, listen, I got to protect her. When we came back, because I didn't really appreciate the way he talked to me. Well, you know, I got to protect her. She was like,

protect me for what? Protect her for what? It's like a white woman, black woman. Yeah. Manager comes out. And then I was like, well, I got to get in the middle of this.

And I was like, listen, you got to apologize in a more sincere way. And I can understand why you would take that the wrong way. That didn't come out well. But listen, let's all get a coffee. Maybe we can get a couple of pastry going on here, complimentary, whatever. And I had to dial the whole thing. I brought the whole tension down. I had to explain this woman as the manager of Sully Industry Bakery that when the words come out wrong,

I don't think she was being racist exactly, but it kind of came out a little bit racist, so I had to step in and be like, hey, listen, you know, and her apology was very weak, very weak apology. Okay. And sincere, so there's your story, everybody, a little story time. And then I come around the corner, and there's a girl in a bikini and another girl dancing in the middle of 9th Avenue.

And I'm like, this place has gone crazy since I love. And then I looked down. down, they've got their camera mounted on the lamppost. They're doing a TikTok. They're doing a TikTok dance in the middle of 9th Avenue. So that's it. Those are my two stories in one block of getting my coffee. Yeah, it's New York and springtime.

It's just people are losing their mind. The snow has started to melt and it's like in Tahoe. The snow melts and we get on our mountebikes in here. People just go crazy. But you guys been to the UAE? Have you been to the region at all? I've been to Abu Dhabi. And being to Dubai, yeah.

That's where I went. Yeah. Pretty wild, huh? Yeah, you know, it's, um, it's, it's, it's very hot. Even this time of year, it's pretty hot. It's like, you know. It's 100 degrees, yeah. It's like going to Vegas, yeah.

Yeah. It's, yeah, speaking, you know, I don't know, I prefer Vegas. Well, I mean, but if you lived in that region, it is kind of like the, it's like the combination of Vegas, New York and Washington, D.C. or New York, Abu Dhabi's. Very impressive. Give us a 90 second. The startup vibe, the investor vibe, the LP vibe. Four seasons was like Rose, you know, like the Rosewood. You know, I came downstairs and 90 seconds,

four people from Sagan Valley stopped me to say hi. You know, like who were in the region doing meetings or had moved their companies there. And tons of startups. I came out of a dinner and there was like a table of 10 startups. And so startups are going there for funding. startups are opening offices there and during COVID they remained open

so it was kind of like what was it Sweden that remained open in Europe or I think it was Sweden and state open yeah Sweden yep did it yeah and so Dubai and Abu Dhabi became like Sweden they had rules but they were like we're gonna stay open and everybody goes to their office and it's incredibly international

there's only 500,000 nationals but there's 10 million people and they built everything in the last 20 years so it reminded me you guys ever go to like Shanghai or China or Shenzhen in the like, but in like the 2005, 2010 period when they were building, there were sunny cranes everywhere. And they have like a Cleveland Clinic, NYU, the Louvre.

I mean, and not like a little tiny outposts, like rivaling, the rival, like, rivaling the actual ones, like giant outposts. So they are, they're for real. and they have a 20-year window, as explained to me multiple times. We've got 20, 30 years to convert oil, wealth, you know, the geographic lottery that they hit into something else. And something else is going to be finance and tech. And they don't want to just be LPs.

They see themselves as becoming VCs. So they're looking to build bridges with the venture community, not just to LP them. That's great. They want to be LPs and funds, but they also want to be doing directs. And so they, Mubadala I met with and a bunch of other firms,

but it wasn't a fundraise trip. I just went with Brad Gerser and a friend of the pod to just hang out and learn about the region. And then I wound up getting 10 meetings, you know, 48 hours before I landed, people wanted to meet with me. So I did a bunch of meetings and,

you know, it's a very progressive place. It's kind of like New York in the 90s, I would say, equivalent, you know, socially. And how are the builders? So, interestingly, people from Europe, from Asia, Singapore, India, which is a hop-skip to UAE, they're putting their companies in Dubai because of tax, because of 10-year golden visas. So, like, if you want to get a visa, you know how it's hard it is around the world to get across borders. They're just like, yeah, come here.

And then they get all kinds of tax breaks for your company. So if you were going to put your company somewhere, if you go to Abu Dhabi, they're going to support the heck out of you. and they have like their own we work and they have this place Hub 71 so there were a lot of startups there and these were legit startups that had gone to YC international startups but instead of basing themselves in India, Singapore, China

Australia, London, they're just in Dubai and they can get anywhere and anybody can get there right and they get good you know how Canada gives what do they call it when they give you subsidies for your developers where you do it tax credits R&D credits

RID credits so I think they're They're getting in on that a little bit. And so good place if you are not in the United States to land your company, I think. And the tax treatment's sick. Like you don't pay any tax base. Like the taxes, yeah. Public Dobby is investing heavily in crypto and blockchain. They're actually, they funded this blockchain called Venom.

I think they put a billion dollars into the foundation. I guess a billion bucks going seed the ecosystem and go in. It's crazy. It's like there's so much money that's going into blockchain. And it's exactly what you're saying, Jay. They're trying to buy the tech future and getting, you know, knowing that oil is limited. I mean, California, we're going to be off oil in 10, 12 years. Yeah.

We're the tip of the spear. Yeah, yeah. So like, and not just us. Sweden, I think Scandinavia, a couple other countries, like, you know, get normal gas vehicles in about a decade from now. And so the writing's on the wall long term for, I think, for oil, if we move to electric. And if that, you know, that, that's a 30-year story, 40-year story in California. and then there are countries that haven't even started yet. So I think that's how they look at it.

And so it's pretty impressive that they have this kind of 30-year vision to sort of convert it. And some of these sovereign wealth funds, you know, they have a couple hundred billion dollars. And so for a fund manager like myself, if I wind up going to Harvard or, let me take that again, Nick, I don't want to mention it. For a fund manager like myself, who is a new fund manager, you know, I've only had fun. for whatever, eight, nine years before that was angel investing, a lot of the endowments here in the United States are full up. They've built relationships with the top firms. The top firms come back with new product, new funds. They don't add new names. And so even with my track record and, you know, my notoriety or brand, it's hard for me to break into one of those

endowments that are now over, these endowments are over committed to venture. So if you have 5% in venture and you were some endowment. And then all the public market equities came down. The denominator, the size of your endowment went down. So that, and if it went down a third, you know, now all of a sudden your venture position went up because the venture position doesn't get marked to market. But the public equities do. So now they're, you know, 10% or 8% venture and they're like, oh, we got to get down to five again. That's our mandate. How do you do that? You've got to either wait for the marks to come down on the venture portfolios where the fund managers are lowering their marks, or you're going to have to invest more money in public markets.

I mean, just basically a lot of them are taking a pause on venture. So I think that's a very unique moment in time. It's like a poker game where, oh, this week, four seats are open. Those four seats, like it could go to, you know, the Singapore sovereign wealth fund, UAE's, Saudi, whoever, they're going to have a unique moment in time while the large endowments here are taking a pause. Well, you have a unique chance, too, with the story, you know, around building around what AI represents and how that's more aligned to what you've been doing for a long time, right?

And so early stage is very attractive. Right now people are like, the late stage is kind of messy because the cap tables are so screwed up. And they're overpriced in the many cases still. So that whole late stage game is too many players, too high price is not enough traction. and so early stage, you're starting fresh. And look at all the activity we're seeing. Founders always ask me and my team to punch up their pitch decks, right? You've got to have a great pitch deck if you're a startup.

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to sign up for free. What are you seeing, Sonny, you're, you like to tinker. Yeah. So give us a, you know, this is the best part of the show.

Everybody's talking about this, you know, regular series we're doing every Monday here and this week in startups is our AI day. We start the week with AI because this is a tread. This is a tread that's moving at a daily pace.

And so we're covering it weekly, which means every week there's going to be three or four important things that we'll just demo for you. every Monday morning, get your coffee, get your cold brew, whatever you're doing, and we'll just get into it. So let's get into it, Sonny. Yeah.

Well, you know, here's a good one that, you know, talks about pace of innovation and startups versus kind of established company. So I think you had Aaron Levy on a couple weeks ago now, right, to talk about last week. Yeah, last week. Yeah. So, okay, you know, about sort of the new features out there launching with Box AI, right, where you can take documents and you can upload them into Box. and you can have it turn them into Q&A.

Well, just to highlight someone who's doing something quite similar, I'm going to pull up here this service called Chat PDF. And what this allows you to do, and it's openly available, you don't even have to log in. For the folks that are listening, I'm just logged into Chadpdf.com, and I'm uploading PDFs. I uploaded kind of three different ones. I uploaded the Berkshire 2022 letter by Warren Buffett.

I also uploaded the actual law of the Inflation Reduction Act and then a summary of the inflation plus on that just to be a little bit of course here we go perfect yeah yeah one more and one more all right okay boom now it fills the screen good for everybody yeah all right jCal mode and I don't want to have to put my grandpa glasses yeah and so you know it's it's amazing and look like this is happening in a lot of different places but um what's amazing is like this service has been up. It's available. You can use it. Obviously, it's using LLMs. And it really highlights, like, how fast things are moving because with Box, that's still in, like, a private beta. And so I think this is kind of, I'm trying to tie back into what we were talking about a few minutes ago,

like the pace at which this stuff is happening is incredible, because you have to wait, you have to sign up. And obviously, Box will give you all the enterprise features and lots of people will use it. But this is something that everyone really needs to think about, because you can come here, take your PDFs, I think is really useful. I've been using it for the last couple of days to just summarize. So you uploaded Berkshire's 22 letter. This is Warren Buffett's letter. And it said, welcome to the exciting world of Berkshire Hathaway's performance.

This PDF file provides an overview of Berkshire's annual percentage change in per share market value compared to the S&P 500 with dividends included from 1965 to 2019. Here are three examples. Here are three example questions you may have about this file. So what is this called when it anticipates your questions? Has the industry come up with a prompt for this where you anticipate what the person's question suggested, future queries? It's something new, right?

It is. And this is like a really big area where, you know, things are going from the, going towards, I would say, where it's starting to anticipate what a user would like to learn. about what has been given, and it's doing that based on all the learning that's going on in these systems and, you know, sort of the prompts that are coming in.

And I think this is a really powerful aspect of the lead in towards, ultimately, AGI, is that when it can, you know, predict what we're doing. Vinnie, maybe, you know, you can jump in here because you guys are out to see adding these features into weight room. Like, how do you think about this? You know, so here's how we're thinking about it right now. it's really good for, I mean, you take a PDF, there's some context to the PDF, but it doesn't really understand the bigger picture of what's going on.

It's based upon the content in it. So for a large-scale PDF, 3, 4, 500 pages, it can probably do a pretty good job. The small PDFs, there's just probably a lot of context missing. So the way we think about it is when we're working with companies and they're using weight room and we're extracting the data from a single conversation, it needs broader context for the whole company. It doesn't, you know,

it won't understand what is going on. Give an example of that. Yeah. Okay. So here's an example. Let's say we have, we have a company that manufactures a certain, you know,

some device, okay? Some box. And they have a shipping delay because there's a component that's missing that they haven't received for the manufacturing process and now they've got a logistical problem.

Now, imagine there's a meeting about this and people are having this conversation. and the AI can transcribe the conversation. It can kind of infer what's going on based upon, you know, what it knows so far, but it doesn't know what the far-reaching effects of that could be. So, for example, let's say it's a really large order. Now all of a sudden, that means that you can't build a customer,

which means that the financial projections are now out by 30 days, let's say, and that means that the company is not going to have enough cash to pay payroll at the end of the month, and now it needs a line of credit. Now, these are the things that takes days to surface up in a company, and the AI can do it immediately, can flag it, saying this order is critical, we're behind now, we have a cash flow problem, alert finance, let them go to the bank and give some sort of facility or speak to the CEO or whatever it is. But without the context of how this functions in the big organization, it's just one conversation that could seem very arbitrary. That's a great example. So we're here on the phone talking about our new product. It's shipping from Cheyenne Jeanne, it's delayed.

And then when a product is delayed, the LLM might be able to say, okay, when products are delayed, what are the downstream effects of that? Customers are unhappy. Returns or refunds may happen. Extra expense. We're going to burn another months of runway. But if it doesn't know your payroll system or your orders, it can't really anticipate that. Yeah.

So we're going from a world where, you know, like, let's not confuse what AI is supposed to be or what it is with, like, what transcription is, for example, or just basic interpretation. Basic transcription interpretation is, we've had that for years, you know, we've had, it's table stakes now. It's table stakes, yeah, yeah, you have to just be able to understand what, what the, what the audio means, you know? Yeah.

Now it's about how do you take that and provide context. And so I think the future, and I'll make a prediction, I think I mean, I put a tweet about this, actually. but I think the future is really about every company one day is going to have its own LLM of some sort. So every major company within I think within five years, I found my tweet,

but we'll have its own LLM on some level. Just because how many conversations are happening in a company every single day within... Yeah, they're happening in Slack, they're happening in email, they're happening over I-Message signal, they're happening in No shit or Coda, documents, Slack's a good example.

So now imagine the AI, the LLM for the company, has access to every conversation in Slack. Obviously, private ones will be excluded, whatever. But every sort of group conversation is now being fed into the LLM live. Every video conversation or audio ones are transcripts. It's all going in. And so, you know, basically, I think within five years, if you're not running an LLM, a custom LLM for your company that's been trained on your business. Five months. Well, I think things.

No, no, no, I say five years before, like, every company will have to do it. Including the laggers. Yeah. Because it does seem to me. It'll put them out of business. If they don't do it, it'll put them out of business. And, like, I was at this conference, locality, and my quote that they quoted me on this tweet was, you will have virtual agents sitting in every virtual meeting that happens within a company.

So, like, well, you know, Sunny, this was something we went through. We've been on this concept of doing transcripts for this week in startups since, you know, maybe the third, fourth, fifth year of the show because people want to get the knowledge out of it or get summaries. And I have done multiple tries at this, but human beings like to do a transcript is a couple of hundred bucks

if you want to do it properly, with some level of fidelity, you know, people's names, etc. Now you can't not get a transcript. And the transcript is being done in multiple places. YouTube was the first with a really rudimentary close caption one. But Spotify, people are creating

search engines now of Twist and All In. new podcast players it's built into Zoom Descript which people are using to edit it's spelled in there so now we have five transcripts of every episode for free or close to free I'll take you a step further

Jail knowing how much content you've got on Twist for the past decade plus whatever it's been running you could actually build some sort of an LLM or model or you can just plug it into an existing model like OpenAI and you could actually create a business coach

actually understand so from every conversation you had with Brian Chesky and whoever else all that knowledge you could capture it all you could you could transcribe it and incorporate in the model

and now people could basically go and chat to this you know twist chat whatever you want to call it and say hey I'm struggling with like my business

what is the how do I like make the numbers work how do I get more run away and it could give you a reference or I could just give you an answer yeah now I guess then the question

becomes sunny who gets to use the data from the show because people are showing me experiments of like all in and this being startups and doing that and I'm like, that's fine for an experiment for a year. I just tell them all the same thing.

Go free to experiment for a year. But I'm starting to think like, I uploaded this to YouTube. They have the rights to the transcript. So I guess they're going to try to claim if I put this on YouTube where I put it on Spotify or if Spotify grabs the RSS feed

that they now have the rights to the conversations that occurred here. I'm going to need to like have a conversation with each of these platforms. I don't want my stuff in their LLMs necessarily unless I'm getting some quit pro quo. Imagine this. You've got the greatest idea ever for a tech startup and it's going to change the world. But you got a problem. You don't have the engineers you need to make this a reality. Why? It's hard to find engineers, right? Everybody's in competition for those great engineers. And you've got to manage your burn rate. You don't have unlimited resources like those

big, slow incumbents. You've got to be efficient. So now imagine you had a partner who could provide you with more than 1,000 on-demand engineers. And these devs were vetted, experience, result-oriented, and passionate about helping you grow. And they charge competitive rates. Sound too good to be true? Well, you need to head to lemon.io right now. It is not too good to be true. Startups choose lemon.com.i.o because they only offer handpicked developers with three or more years of experience and and really strong portfolios. Only 1% of candidates who apply get into lemon.io.

A couple of great launch founders have worked with lemon.io, and they had great experiences. So here is your call to action. To learn more, go to lemon. dot I.O slash twist and find your perfect developer or tech team in 48 hours or less.

And twist listeners get 15% off the first four weeks. Stop burning money. Hire developers, smarter, faster. Visit lemon.com.i.o slash twist. Let's unpack a couple of things. So, you know, one, regarding the transcripts and translation, we'll kind of maybe lead into Google I.O. in a second, but they announced something called Universal Translator. All right. Here's the 44 second clip. Let's listen. And then we'll see on the other side of 44 seconds. Universal Translators an experimental AI video dubbing service that helps experts translate a speaker's voice while also match you their lip movement.

Let me show you how it works. What many college students don't realize is that knowing when to ask for help and then following through on using helpful resources is actually a hallmark of becoming a productive adult. Much of university not understand that knowing when to pay help and use resources utilizes is in reality a clave to convert into an adult productive. We use next generation translation models to translate what the speaker is saying, models to replicate the style and the tone.

and then match the speaker's lip movements. Then we bring it all together. That's wild. So this solves like the Saturday afternoon Kung Fu movie problem. It's a film from China putting American dubbing and you can see the lips are not matching at all.

I love this because I hate, even on Netflix, there's so many good shows people have told me about and either I would watch it was, I would rather watch subtitles than watch the English dubbing. And if they can change that, I'm all in. Like, that's great.

And that opens up a universe of content. Pretty amazing. We got pitched on this week in startups being re-acted, re-enacted, I guess, where they were going to hire voiceover actors to do my part, you know, and Aaron's part, or, you know, you're part, Sunny and you're part, Vinnie. And then, you know, basically republished the podcast in German. And it was going to be, I think, I don't know if Nick remembers, but I think it was 500 an episode. and they were like, yeah, you know, for whatever that is, $150,000 a year,

you could have an entire German version, then you get just one German sponsor to do all 250 episodes for $1,000 an episode, and you'd be a profit. And I was like, ah, that's a lot of work. And then you'd have to have voice actors full-time. You'd have the scale of the show. You'd have full-time voice actors, and this just eliminates all of that work. It's wild.

Yeah. And so coming back to what you said here, so first of all, the platforms that you're publishing to are going to start making these videos. features available. They started, to your point, with transcripts, they'll just make this available. So I think that's something mindful, that's something you have to be mindful about. And then two, in terms of like, how are people leveraging all that, that, I think, that's the Grimes problem. So first, you know, this functionality is coming. So if you're kind of building in around it, be very careful because the platforms are moving very quickly and adding, you know, this type of

functionality. There's a lot of other great things that were launched at I.O., which probably hit on what, you know, 20 or 30 different startups are working on right now. Yep. Um, and so, you know, you have to really think about what, what is your moat in that particular situation or what advantage do you have? Do you not have to have a moat, but like something proprietary. Maybe someone can show up and cut a deal with you, JCal, right? And say, hey, we'll do this. and then, you know, we'll be responsible for, you know, sharing the rev share that comes from it. So I think that those are the type of things that people really need to think about now. Yeah. By the way, um, Google calls these, um, you know, questions.

suggested questions, proactive prompts. And so this could be a very interesting experience, I think, for a lot of people to when they open an app or they open up

their slack for the day or their box and they're working, work will be, the AI is going to be telling you what to do next at your company. It's going to be like, you know what? You have enough customers,

but you're losing customers. So you really should be working on churn today. Here are three customers that aren't using, your product anymore, would you like to schedule calls with them? You know, and like it'll just, the AI will just know that these customers are going to churn and do something preemptive with them.

It really could be transformative for people at work who have this sort of, in writing, blank sheet of paper problem, you know, where you're like, it's very intimidating to have a blank sheet of paper for startups or any company. You come to work sometimes, you're like, what do we do now? What's the most important use of my time? What's the most effective thing for me to do today? And this could really help drive that. You know, everybody's been hearing about hugging face, Sunny.

Maybe you could explain what hugging face is and why everybody in AI is talking about it right now. Yeah. So think of hugging face as more of a collection of models. And it has a wide range of models. So, you know, we actually, you know, Vinnie talked about this a few minutes ago where we think there's a long-term belief that there'll be a lot of of different AI models for a lot of different use cases. And Hugging Face really was a leader in that and it continues to be where they don't have a single model.

They have lots of different models that have been uploaded by different users. And so it's a combination of what you think of as say like a GitHub and a repository for AI where there's lots of different models that don't necessarily have to be for generative AI. They've been there for traditional machine learning for years. and actually Amazon partnered with them. So that's the AWS's partner has been up front in terms of giving users the selection they need

for their particular use cases. And I think it's really fascinating. Why don't you pull it up and then walk us around the side? Give us a little tour of hugging face, if you will, in real time. And, you know, make sure your sportscast it, as you do so well now on the show, just telling us what we're seeing. Yeah.

Because they have the data sets there. They've got models, et cetera. Yeah, let me just pull this up here. so. And people know GitHub is a community. It's really like a community of developers. So when somebody figures something out, they post it and they show their work. Yep.

And then if you show your work, you get kind of social credit for that. People follow you. And if people follow you, it kind of builds your career, correct? That's like part of the dynamic here is that people who are developers are looking for recognition. They want to move up leaderboards and or get exposure at a site like GitHub or here, correct? Yeah, it's a great, great explanation. And so, you know, here we've kind of.

gone, I've just clicked into the models area, I'm on the website. And what you can see here is different models. And on the left, you can organize them, you know, being multimodal, computer vision, natural language processing, audio, tabular. And you can see there's lots of different models there. There's like 6,000 pages to account, right? Right. So if you went to audio, there's a collection of them, like audio classification, voice activity, text to speech. So if you were to click text to speech, as but one example, it would give you a bunch of the models, but it's sorting the models by most downloaded.

So if you didn't know where to start, Can Beashi, I guess, is been used 28,000 times in the last month. This is the most downloaded text-to-speech model, and you can take this for free and start using it. Correct. And so this is, you know, like a collection of, and you can see here, like just the sheer number, right?

There's like thousands and thousands of models here. And this goes back to, again, these are not all, you know, focus on generative ideas. This is like sort of the broader reach of, you know, AI and machine learning. And so, you know, one of the things I get confused with when we see about regulation because Hugging Faye has been around a very long time and these are all AI machine learning models.

I mean, where are you going to cut this off? There's so many here that are serving different purposes. And what's interesting is if you were to click on like the first one, when you look at that one, it actually has a hosted version of it on the right. Underneath downloads in the last month, there's a hosted version. So if you typed in,

welcome to This Week in Startups. And you hit compute, you could actually kind of see a basic version of it without a lot of operators or interference. Yeah, and so we can put that in a post. So this basically is why things are moving so fast because people are sharing their work. Yeah, and this is the argument, you know, there was a sort of a leak of a internal Google document last week. And so, you know, tough to keep up with all this now, too. And in that Google document, what the, you know, sort of the summary of it was, the highest level summary was open source is moving so fast that open source is going to win here. And it talked about just sort of the pace of innovation has come down to weeks. You know, Paul Graham had a really good tweet this morning.

Days. Taze. Yeah, days. Yeah. So, and that, you know, Paul Graham had a really good tweet this morning. I can try to find it and pull it up while we talk about it. I saw it actually. It was trending.

Yeah. Yeah. And I think it's really incredible. He basically said what we've been saying on the show, which is, hey, this is moving much faster than anybody anticipated. Something major is happening when the time scale is days. I was there for the last one of these, the web. And even then, the time scale was closer to weeks than days. And he's absolutely right.

Back then, every week or two, something would be added to the HTML spec. So people would be like, hey, you know, I want to put a background down this. It's a gray background. Can I put a background color? Can I change the background color? Yeah, okay, background colors is up and running a week later. Then somebody would say, hey, you know what? Background colors are nice.

I would like to put an image in the background with a texture. Can I, you know, point to a JPEG? Like, okay, sure, put a JPEG in the background. Yeah, and that's what we're seeing right now in terms of, you know, that pace and he really nailed it and I think Vinnie first called it out in terms of like anxiety for developers, I think that anxiety

probably even continually move up the stack all the way into companies and projects. Venture capitalists who, I've had two startups now that way back to do something in AI, I wouldn't say which ones, and they came back to me like, this is kind of built in,

everybody can do this now. All the work we did for the last three months is now built in native, everybody has this superpower. So it's like, it's like building's like some weapon, and you're like, oh, I put a scope on this rifle. I can now, you know, have 50% more accuracy.

It's like, oh, yeah, scopes are open source. Everybody's got a scope. It's like, okay, what's the next weapon? And you're like arms dealers in startups when you're building tools. And this arms race is like a free arms race. Everybody gets the latest weapon. Everybody gets the latest armor. Everybody gets the latest counter defense.

And so a lot of founders have been telling me, well, what should I do? And I'm like, just keep racing and building and build an experience and a brand that speaks to people. If you have a nice brand and a community, people will stick around. I really think that's great advice. I think the community aspect

of what's going to happen here is, and it's a good kind of tie into what Paul talked about. It's important because it's so early, the communities that establish around your projects are as critical now, more than ever before.

And I also think we're going to go in a new world where, you know, we've seen the internet in the last 15 years become about sort of giants, Titans, whether it's like, you know, the Facebooks of the world where everyone had to be there for kind of the network effect. I think we'll now see a world where, you know, this, you can have smaller communities. It could be 10,000, could be 50,000, be 100,000. That's not internet scale, but I think it's valid to build businesses around as well. So I think we'll see a kind of a move towards that. Listen, when you're a fund manager like me, you're trying to raise money. The hardest thing to do is get in front of those elite LPs, limited partners. right? How do you get those connections? Well, IConnections is how you get them. So check out IConnections. This is a platform to help connect and meet elite capital allocators. What a great idea. And these are the biggest LPs in the world from every category, endowments, foundations, sovereign wealth funds and IConnections speciality is building and connecting their global network of capital allocators with a diverse range of fund managers. They do this two different ways. They've got their I connections platform and they do bespoke events, including one I'll be speaking at. The events are amazing as a guy who knows how to throw great events.

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Iconnections dot I.O. slash twist. Yeah. I thought one of the most interesting things I saw in Hugging Face was they're just speaking to this exact, you know, impact of like who's going to win the open source or the closed proprietary. and if you look at the closed proprietary so Open AI, Open was the name of it. Elon funded it because he wanted it to be open, then they closed it. So it's really, we should start,

I'm going to start referring to Open AI as closed AI. So closed AI, their approach is to not share their work, not share their data. So if you use closed AI, everything you do as a founder, just keep this in mind, they get the benefit of and they don't share back. So is that accurate you think, Sunny Vinny?

that using closed AI means you're giving, but not getting. I think it's unless someone cracks UI in a way, the same way of Microsoft and cracked UI and distribution, this is Linux versus, you know, and the era is very different, right? So in the 90s, like, communications and was costly and the internet was expensive, it wasn't as widespread as it is today.

Those were modes. Yeah, yeah. So those are modes that Microsoft actually, yeah, There was a lot of information asymmetry between people not knowing the Linux was out there or getting information how to use it and the developers were, you know, UI, U.S. wasn't something which they were really focused on at that point. It was very developer-centric. I think with Bard, in particular, Google's resources around this, you could find that actually that open source is the way to go just because of pure scale that it gets to. and then the UI,

ux issue gets resolved through just, you know, experience that we've had and now we've better global communications network. So in,

open source failed in operating systems. I think it could succeed in AI. There was in operating systems, this idea that Linux or Lindo or any number,

Ubuntu is another one. Yeah. That like, hey, Windows could be displaced. And it never was, except Google then created Chrome. And really to have a desktop,

you really have to be, make it user-friendly. And these things are not user-friendly. So the fit and finish never competed with Mac and the OS. But I think this time is different. I think we... This time could be different.

This page is really interesting. This is the Open LLM leaderboard. And it has a little description here. And what it says is with the plethora of large language models and chatbots being released week upon week, often with grandiose

claims of their performance, it can be hard to filter out, the genuine progress that is being by the open source community, and which model is the current state of the art? The OpenLLM leaderboard aims to track, rank, and evaluate LLMs and chatbouts as they are released. We evaluate models on four key benchmarks from the Illuther AI language model evaluation harness. I think that's how you pronounce it. A unified framework to test generative language models on large numbers of different

evaluation tasks. A key advantage of leaderboard is that anyone from the community can submit a model for automated evaluation on the GPU cluster, as long as it is a number. a transformer model with weights on the hub. We also support evaluation models with delta weights, yada, yada, yada. Evaluation is performed against four popular benchmarks. AI2 reasoning challenge, 25 shot, a set of grade school science questions. Helleswag, 10 shot, a test of common sense inference, which is easy for humans, 95%, but challenging for SOTA models. MMLU, 5 shot, a test to measure text models multitask accuracy, test covers 47 tasks including elementary mathematics, US history,

computer science law, and more. Truthful QAMC, zero shot, a benchmark to measure whether a language model is truthful in generating answers to questions. We choose these benchmarks as they test variety of reasoning in general knowledge. And then it lists them, and you see here, 11am-65B, is the model with the highest average. You can see their arc shot and their hello swag and, you know, like where they're done. So the race is on, boys. I don't know, have you seen this before, Sunny or Vinny, this leaderboard?

Yeah, you know, I did. And I was looking for a tweet and I just couldn't find it. There was a leak of a Google document and or maybe you could look for it in the background. Yeah, you mentioned this. Yeah. And in the Google document, they basically said in just a few weeks and what, you know, we've spent hundreds of millions doing, people spending tens of thousands and are, you know, getting there just as quickly now because of, you know, and that was all driven by the leak of the llama,

which is, you know, the Facebook model. And then, you know, there's just sort of some hot off the presses. news. I also dropped it in here. It's like, you know, I'm here from the information, basically saying, and I, like, I'm just reading it as we're doing this here, but I guess Open AI is now moving to open source some of their models, maybe even in reaction. Oh, close AI is going to be open eye again? Yeah, I know. It's just funny because you're just giving them that nickname. And so I'm just dropped the link in the chat. I believe it when I see it. If they're going to be pressure on them to do it because they, Sam is so smart. I would say Sam is clever. He's even, which is even better than smart in this instance. He's clever. And I think Sam Altman is going to be like, you know, being closed helped us because we could build in stealth. But now that everybody is adopting this and all the best developers are spending time on this, close is going to hurt them. So let's read from this story. My piece of my piece is that the real, you know, the real revenue and the real revenue and strategic differentiation you have right now is the hardware, not the software. The software can be easily replicated, but the GPUs that we're running out of, this is where I think like...

The big iron. Exactly. So the ability to produce these chips, aggregate them, and basically, you know, GPU processing becomes the utility of the future. That's why I'm into stuff like render. I think render is interesting for this sort of thing as well. Like, this is where the world changes. We have, you know, if we can utilize efficiently the GPU chips, the software just runs on top of it.

You still need the hardware to do the processing. You can't have all this open source, you know, all these different models without, like, hardware becomes a limiting factor, not software. And of course, you're referring to this A100. This is the big. That's one of the, you know, A100s are, I mean, they're powerful. Invidia A100s, yeah. But you could line up, you know, you can line up a bunch of, you know, 4090s and get similar output, you know, it's not too far. I mean, they use Tesla cores in the A100s, and I think they use Kuda cores in the 49.

but, you know, it's, it's, um, who's going to put up the biggest fight against Nvidia here? And is there an open source hardware project as well? I don't know. Yeah. There's no open source project. So like the direct competitor, like the most meaningful one is the TPU. Right?

By Google. That's the most meaningful one. So Google's making their own hardware. Well, Amazon as well. Amazon announced it as well. They need the same thing. And Google has been for years. They're on, I don't even know which, you know, third, fourth generation of the TPU.

Yeah. So they've been doing it for a long time. So does their TP, is the Google TPU available to the public or is it only for their cloud? It's only for their cloud. Got it. So they're making proprietary. And this is something he talked about at Google I.O. a long time ago. They've been talking about this for a while.

Yep. Yeah. Yeah. Yeah. They had a moment, you know, years ago where they were doing more in TPU compute than they were in, like, kind of X-86 compute. Yeah. And that wasn't a recent thing. There was several years ago that they had made that, you know, point.

So really, it's going to be GPUs versus TPUs is the battle. We should be monitoring. I'll give a counterpoint to Vinny's point there, which is, you know, from this, we have the Google, we have no mode. And so, you know, I thought this particular paragraph, this is a really good article is worth leading. Read it, yeah. So people who are listening. Yeah, for sure. I was going to read this one paragraph.

It says, while our models hold a slight edge in terms of quality, the gap is closing astonishingly quickly. Astonishing. Yeah. Open source models are faster, more customizable, private, and pound for pound more capable. They are doing things with $100 and $13 billion parameters that we struggle with at $10 million and $540 billion. right, and they're doing so in weeks, not months.

That has profound implications for us. Yeah. So the interpretation here is that, and he says this in bullet points after that paragraph, we have no secret sauce. There is nothing proprietary. There's nothing owned by Google. And then his second bullet point, people will not pay for a restricted model

when free unrestricted alternatives are comparable in quality. And this is something I said on the all-in, podcast and I think here, you know, this lead that Open AI has, it feels tremendous until it doesn't, right? Because if in a vacuum, it's the only one you can use and the only one you can see other people using, it feels like it's an insurmountable lead. But then Bard came out and we started playing with Bard and it feels like, okay, Bard is at, you know, Chad GPT3 or 3.5, right? So the gaps will close and then ultimately the race will be won by the platform that provides the most for the least cost and the platform that's going to provide the most for the least cost is going to be

an open source project so let me let me just i want to just jump to bod versus um jet jubit i've been playing out by the lot this week and it's actually very inconsistent um i don't know it's delusional it says weird shit you know no no you can run the same query twice and it'll give different answers. That's how ChachyPT used to be. Yeah. Yeah. So they're very much behind.

I mean, I asked it to rank. I went through a process where I said rank the top 10 vehicle manufacturers in the world based upon gross profit generated, right? So it ranked the 10. Tesla wasn't in there. So I said to it, where is Tesla? And it responded to me, Bard, responded to me saying, oh, my apologies. I didn't see that.

Now I didn't realize that Tesla was a vehicle manufacturer. actually, whatever excuse it gave me, and then it had to update the list for me again, and then updated it for me. I mean, imagine not having Tesla in that list? How is that possible? I literally just did it. Here are the top water motor models of the U.S. in 2021 and 2022, according to motor intelligence, Ford F-Series, Chevy Silverado, Ram pickup, Toyota RAV, Toyota Camry, Toyota, Toyota,

Chowarder, yeah, there's no Tesla. Yeah, so I did tell it to include Tesla. In 2020, it put Tesla model Y as number six. Yeah. Interesting. So, so this is, this is the, this is the problem. I don't think it's, I don't think it's close. I mean, I don't think it's good enough yet.

I think what it does really well, by the way, is it takes feedback and then it incorporates that feedback. And like, for example, I did, I said, tell me about Vinnie Lingam. And it says that gifts was acquired by first data in 2015 for $390 million. The year is wrong. The amount is very wrong. You know, it's just like all the stuff said to me, it said I sold another company, 100 million, which I didn't.

I don't know where it got that from. But, you know, it's very inaccurate. And here's the problem. And here's the point I'm trying to make and highlight here is I think we're going to have a lot of bad AI be based upon false information on the internet. So the more fake information that people populate with, the more these AI tools are going to search, read, and then, you know, I know it's trying to give authority to certain sites, but, you know, people can, like, it's putting data from, you know,

Wikimeli.com on me. What the hell is with Wikimini? Can I give an example here? And it's a bit of a plug on sort of what we do at definitive, but it actually gives a really good example. Would you guys mind? Yeah, please.

I have to leave. You guys can keep going to go ahead. Cool. Thanks, guys. Everybody visit weighting room.com. Vinny Lingam, blah, blah, blah. Follow them on social media and see him at the club at the music festival.

Live the life of Vinny Langham on Instagram to search for Vinny Lingam. So I'll see the All-Summit. There you go. So I'm going to I hope you bought a ticket. I hope you bought a ticket, Vinnie. I'm selling out fast.

I don't want to apply for one, but I'll buy one. This is a big internal debate. Do I have to apply? I mean, seriously? No, you don't have to apply. The issue is each Bestie this year only gets 25 tickets

for their friends and family. So now, VIP in regular. We have 25 VIPs each. There's 100 VIPs for this. So now there's a little bit of brinksmanship going if you're in the poker group, you know, and you want to get the free ticket,

which of the four besties, you know, you might want to go to all four and try to lock up one of those tickets if you were, you know, Zander or you or Sonny, who's going to get you your free ticket, right? Like you two guys, how do I say no to you if you're coming on the pot every week? I got a, it's kind of hard for me to say no, right? Then we get 25 tickets that are 50% off, I think, is what we've settled on. Okay. But now it's like, this thing's going to sell out. We already sold out the general mission. It's, this is such a hot ticket. that now it's like, they're counting how many tickets

each best he gives away. So are you saying that Sonny I'm getting two tickets from you, Jay? Well, I mean, how do I say no is the issue, but I would very much hope that you lobby your, I think Sunny's made a lot of money, a lot more money for Chamath. So Sunny and Vinny, you guys have business relations.

I've made money for Chamath as well. Yeah, so I think you guys got a lobby Chmoth so I can save those two tickets for friends the family. I'm actually taking my tickets and I'm selling them on the black market and this thing sells out. I'm selling them for 20K each. So I'm gripped in this big time.

That's like a half-milly right there. I'm going to sell those $25 for $20k each. Okay, Jack, I'll reach out to one bestie, and if they say no, you're the next guy. Just work all four. No, no, no, no, I'll do one. I'll do one. I guess, you know, like, whichever bad, you got to work your besties. I think he makes me, the most money to David Sachs, though.

Oh, really? Vinny, then you got, yeah, you got that Salana bag. Yeah, you got to tell him he's got to give you a ticket. Yeah, yeah, I'll ping, I'll ping sex. Okay, go. Yeah, I would do that now because now the word's going to be out this podcast comes out. That's the biggest one.

Yeah. That's the biggest one. Oh, you guys. See you guys. He dropped that bag on the table. He broke the table in half. Yeah. He's like,

hey, I got your envelope. Drop the envelope on the table. Sacks is like marble table broken half. He's like, I can get a new table. See you guys. That's a lot of bad.

Love you both. Bye. All right. Love you. Bye. Love you besties. Look at this. All right,

let's keep going. You got any more examples for us? I mean, God. I just wanted to, you know, it just kind of builds on there. and we can see if it's useful or not,

but I'll share with you guys here. And this, hopefully, I was going to send this to all you guys because this came up in the all-in pod as well. So, and this really shows like where, and Ben Thompson had a tweet this morning as well. Nick, if you can pull it up in the background, let's pull it up right after this, but really, you know, where these LLMs are good

and where they kind of have some challenges. And so in this particular case, you know, we asked Bing, which is powered by chat GPT4, What is the average delay time for each airport in 2022? It comes up with an answer that we would have normally not typically seen. I'll read it quickly here. It says, I found an answer on Stratos Jet that says the average time for airport delays is 15.3 minutes,

but this is for all airports, not for each airport. Right? You know, chat GBT is getting better where it doesn't, you know, give you one of those type of standard responses, but it starts with it's, hey, I don't have data beyond, you know, September 2021. but it then offers a method which says, hey, you know, to find the average delay time for each airport in 2022, I would recommend going to the authorities website, the FAA, and you could pull it from there, and that's how you could get the answer. So it's helpful, but it doesn't give you the answer, but it's at least giving you the right directions. Right. Google is finding a result, and just kind of flipping through some sides there for people listening.

Google finds a result that comes from a page that, you know, a website, urocontrol.in.t, which has published delay times and it, you know, provides the, like a cold snippet from there. This is where Google's crawl is so valuable to them. They're crawling the web and they've indexed the web so granular over so many decades that they've got a big advantage. And they're doing that in real time. And this is like sort of, and this came up in the online pot, but this is a little bit of like, you know, where you can see some of the hallucination happen. And so in this particular case, you know, we asked the same question.

What is it average delay time for each airport in 2022? And it comes up with a list, not all the airports, and it says, hey, LaGuardia is 19 minutes. Now, you or I know, Jake, how if you've flown in Aligardi, it's not 19 minutes, right? But this answer looks very, very, you know, it's very confident on this answer. So we ask the same question inside definitive. This is a screenshot of our product. We actually go to the airline database and write a SQL query, which is shown. and we come up with a response that has all 393 U.S. airports and the average delay time.

And in this particular case for Liguardia, it says 74.54.4 minutes. Okay. So now we want to go and verify this. And so the only way we can go and do that is we can go off to the Bureau of Transportation Statistics site and go to June 22. And we can look it up here and say, here is the average delay time. in that time frame for 2022, 74.55 minutes at LaGuardia. And so what really this shows here is the LLMs,

and we use an LLM to come up with a sequel for that answer, but they can be really good reasoning engines, but when you're using them as information retrieval systems, and maybe if you pull up the tweet from Ben this morning, Nick, they try to give an answer which it has seen someone come up, up with before, which is not always practical in a scenario when you're looking for a specific answer that's based on data that may not have been published in a web article that it could have crawled. Got it. So what it's doing is it's taking the corpus of journalism, blogging,

and using that as a proxy of the data, what you're doing is saying, okay, if a journalist had gone into that database and then created this document, I'm going to just go directly to the database. database, yeah. And that's really more definitive intelligence, if you will. Correct. Which is the name of your company, definitive intent.

Which happens to be. Even him of your company. And so this is like, beyond a crawl is the actual sniper shot. So like a crawl is kind of like spray and prey, you know, what can we find and leverage

the collective work of humans? And you're saying, well, screw that. There's data, there's got to be a database somewhere we can go inject. But that is not what Google has done. Google cannot.

It's not allowed to go ingest somebody's database. That's against the rules. In some cases, it can. You know, if they're public data sources, it can. Sure. Right? But in many cases, it cannot because it doesn't allow for it, right? And so, and sorry, I was missed quote.

He wasn't Ben. It was Benedict Evans. And I think, yeah, if we pull this one up. Oh, yes, Benedict Evans, formerly of A16Z. Yes. Yeah. And I think, you know, It sort of highlights what we just talked about what we talked about here, right? LLMs do not tell you the answer to your question. They tell you when people ask that question like this, this is what the answer that other people tend to give, tend to look like. I think this is a really, really interesting and, you know, thoughtful explanation. And, you know, when you're trying to apply the technology, I think is something really to think about, you know, whether you're using it for information retrieval or you're using it for, you know, logic or reasoning.

Yeah, so if you were to ask, you know, what's the best Peking duck in New York City? People have asked that question many times. Yes. It's been answered by timeout, New York, Zagatz, Yelp, you know, some forum, a newspaper, and it gave Red Farm and Peking Duck House as the first two. Those are the first two I would have given you. Yeah. Red Farm is the Peking Duck that I order on Goldbelly.

as just about one example. And then Peking Duck House is a place where you can bring your own bottle of wine, no corkage fee, and it's $50 a person for Peking Duck. So you can have a table of $10, $500. You bring $500 in like really great wine, bring five bottles of great wine

and you're in and out for $1,000 for 10 people, 100 bucks a person. Yeah, I'll take you there next time. If you like Picking Duck, highly recommend both in those places. And now this transcript is going to get crawled by someone if we were talking about earlier, and then that's going to get added

into the corpus of training material for these LLMs. So basically it's getting all the chit chat out there. And what Google will do is, and this is where it gets really interesting, I've had a conversation about peeking duck a hundred times in my Gmail with various people. Now, is that something that it can use publicly? Of course not. But maybe they'll figure out a way to finagle if you're using Gmail for free and there's some knowledge in there. Maybe we'd point it in the right direction.

who knows what, you know, insane justification they'll use for taking conversations that were not meant and using them, you know. Well, yeah, I mean, especially behind free products, like you said, right? Where, you know, you have to understand there's got to be some tradeoff of your data or your knowledge. That's now being put into other systems. Yeah, that's kind of scary when you think about it. But that's where, I think, you know, I really think Googles, and I, I, I, I, I, bought Google shares. I don't know when.

I have to check J-trading, but when people got down on Google, I was like, I think they're going to incorporate this into everything. And I think at Google I-O, they incorporated it into most things. Most things, yeah. Most things.

Now, did they, I didn't see, I didn't watch I-O, but what was their Gmail strategy? Because to me, Gmail is really incredible. It's the most important one. There's a, yeah, yeah, so there's a short, there's a 15 minute summary video

which I can send you JCal. It's awesome. The verge made that, right? Yeah, no, no, someone else did. It was like, yeah, it was, that's the best summary. That was something we created at, Engadgett, that Verge,

which is like a bunch of former gadget editors. It was, it was one of the best. We do the Steve Jobs keynote in three minutes. We do the Steve Jobs keynote in one minute, three minutes, and 10 minutes. So we'd make like, whatever version you want to watch,

we'll do it. But now, yeah, I could do that. Yeah, it was a, it was a really, really incredible summary. I'll try to find it. I tweeted about it here. Here it is.

I'll just drop it in here. You can pull it up. We're not going to watch it here. It's too long. But really, in terms of the video, Nick, if you want to pull it up after, is that what they're doing in Gmail now, so basically they're adding a button, which is a prompt. And that when you hit that button, you can actually write a prompt to reply to a message. And then when the reply is generated, they have like sort of some options.

and I don't remember exactly what they were, which is like, be more aggressive, be more neutral, be more passive, something along those lines. And so if you're fighting with someone about like, you know, canceling something along those lines, you can say, hey, draft me an email

that's a response to this. And basically, and then, you know, it generates a response and you can tell it to be more passive, say it's both same, more aggressive. It was really, really cool. I don't want to like, tow my J-trades, but on,

March 21st, I bought like 100 grand in, I bought a thousand shares at about 100 bucks a piece. And it went up 17% in a month. It's another great J trade. My J trades are right now. Meta and Google. They got the meta one and the Google one. My J trades are now 7.45 versus the S&P equivalent of 2.5.

So I'm beating the market by 3x, apparently, on my J trading. Yeah. This is not trading advice. Do not follow my J-trades. But I think it's just like timing. I bought when everybody was scared. I'm getting killed on my Disney trade. Yeah. Just, just absolutely slaughtered. And my Amazon trade is getting killed and my Warner Brothers. But I'm going to buy more of them. Those three companies are going to figure it out. Disney's going to figure out AI. Yeah. Amazon's got to figure out. Where's Amazon and all this? Where's Amazon? Well, so they partnered with Hugging Face. Okay. So they, they did a big, so they're making it such that, you know, like what we were just showing earlier. Yep. If you want to pick models and you want to run them in an infrastructure, they make it, they'll make it as simple as possible within their infrastructure. Got it.

So if you really think about sort of that open source argument, they are embracing that the most kind of, I guess at the forefront. So if I want to grab the model and start playing with it, it'll just dump it on my AWS account and let me start playing with it. That's smart. Why don't they just buy a Hiking Face, man? They should just bought it now.

Yeah, I mean, that would be the move like, you know, a Microsoft and GitHub type thing. Yeah. Yeah. And, you know, similarly, Google did a big investment in Replit.

So, yeah, that would seem like a good move for them. Yeah. That's, I think that Gmail thing where it understands tone is going to be really, really powerful. So AWS then,

switcher landed it. They're not like, Azure's like, use open AI. AWS is like, listen, use whatever you want. Here's a bunch of options.

Yep. And then Google will do what? Google Cloud. So Google Cloud, and this was also at I.O., they are basically going down the approach of, there are going to be multiple models of different sizes, and we will allow you to run Google models of different sizes within your infrastructure with your own data.

So allow you to have a model that's private running within your VPC, like your virtual private cloud connected to your data. Yeah. And I think it's a really smart approach for enterprises that already, because Google has one of the leading data products, or a couple of the leading data products, but the largest one probably being BigQuery, which is a large analytical database.

And so a lot of companies rely on that. And so it's a really smart place to plug into. And they gave some also really great demos there as well. I think Nick has the Gmail video. If you have the Gmail video, Nick, we should pull that up real quick for Jason because I didn't see that last week. All right, here's a 44 second clip.

We'll see you on the other side. Say you're writing to your neighbors about an upcoming potluck. Now, as you can see, Sidecake has summarized where this conversation is about. Last year, everyone brought hummus. Who doesn't love hummus? But this year, you want a little more variety. Let's see what people signed up to bring.

Somewhere in this thread is a Google sheet where you've collected that information. You can get some help by typing, write a note about the main dishes people are bringing, and let's see what we get back. Awesome. It found the right sheet and cited the source in the found-in section, giving you confidence that this is not made up.

It looks good. You can insert it directly into your email. Wow. That's so powerful. It should have a button that would be like the J-Cal button, which would be like troll this person, and it would be the troll options. And like my troll option would be like,

why do you, why does Hamas, why does everybody hate Hamas and then link to the clip of Sasha Barron Cohen but he's talking about hummus and Hamas and he's like trolling them. Trolling option should be there to do like jokes and stuff like that. That would be a great startup is an agent that follows you around the internet

and then optimizes your trolling and comedy and just makes a mockery of everything. Mockery AI. Somebody go grab that domain and mockery AI. Or anything else happening this week that we should talk about as we wrap here? I think we did a lot I think

There's a lot to process everybody All right And then tomorrow on the show We'll talk about Karen I don't know if you saw that one go by But some influencer uploaded herself

And she's now made a I used to have these In the back of the village voice Like you could pay a dollar a minute To dollar a minute Yeah Talk to somebody in a Adult fashion

I'm going to be careful Not to get us censored here on the YouTube But there's a dollar a minute virtual girlfriend for lonely people. I think she made like 70K in the first week. I mean, I think people are going to try that.

Yeah, that seems dystopian and crazy and sensational, but I don't know, is that going to be a long? Maybe they'll just build it into only fans, and then whatever you upload

to only fans, it then makes a model of you that's interactive. I mean, that makes sense to me that you could have an interactive version of every person there

and then you could interact with them upsell premium if you want the person line. All right, everybody. We'll see you next time on this week and service. Bye-bye.