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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVPN.
Speaker 2:Today is Tuesday, 07/22/2025. We are live from the TVPN Ultradome. Temple Of Technology. The fortress Of Finance.
Speaker 1:El Capitaldi Capitaldi.
Speaker 2:Massive post from Fiji the CEO of applications at OpenAI. She is outlining what her plan is basically, and it's very, very interesting post. So in so Fiji Simo is an absolute boardroom general. Give me the Ashton call.
Speaker 1:Yeah. She's on the
Speaker 2:e Yes. Fiji Simo. OpenAI and Spotify board of directors positions. Huge runs at eBay, Facebook, and Instacart. Now she's the CEO of applications at at OpenAI.
Speaker 2:Today, she outlined how she sees OpenAI's products having the biggest impacts. High level, six things, knowledge retrieval, health, creative expression, economic freedom, time, and support. And those are kind of getting, I think, more abstract, more vague as they go along. But it's interesting. They map pretty closely to my experience.
Speaker 2:Knowledge retrieval, I use I use it as Google replacement for a lot of things. Yeah. I use deep research as a as a knowledge retrieval product. I also use it a little bit as web of the replacement. Not a ton, but I've seen a lot of people use that.
Speaker 2:But I do ask it for advice around health, fitness, recommendations for supplements, all sorts of different stuff. Often, I'll just go there and say, what is what what type of creatine does Andrew Huberman recommend? And it'll just Or
Speaker 1:complex medic medical.
Speaker 2:Fortunately, I haven't been in one of those situations recently but I if I did run one of those situations, I would definitely go to it now.
Speaker 1:Is interesting because previously when people were trying to understand maybe a small health issue Yep. They're having, they would go do a Google search, add Reddit to it and then they would look through the comments. And the comments would provide kind of like context on the symptoms or whatever they were dealing with. But you and you could technically leave a comment but I think majority of people wouldn't post about that. Yeah.
Speaker 1:So the fact that OpenAI has all that Reddit data. Yep. You can get that same type of data but then you can kind of ask a number of follow-up questions Yep. Which is very cool, very powerful. I'm certain that people are probably misusing it, maybe reading too much into the results.
Speaker 1:But again, the idea I think for a long time doctors that would say, don't don't look on Google. You're just gonna stress yourself out. And then you go into the appointment room and over there on the equivalent of Doctor. Google.
Speaker 2:Totally. It's nothing new. People used to go to WebMD and like the meme was like you go to WebMD and no matter what you type in it says cancer. Could be, like, the worst possible thing. But it might just be a cold and maybe you should just take some Advil.
Speaker 2:But, like, for whatever reason, WebMD felt the need to, like, kind of give you the full picture and all the possibilities. And then they'd, of course, say, like, go consult an expert or talk to your doctor. So but yes. I I definitely see it it it replacing that type of health experience. Also, I'm using it as a Photoshop replacement a fair amount of time.
Speaker 2:If I need to just quickly generate an image, quickly generate something that I would have normally gone to a three d rendering program or or Photoshop and kind of created a collage to kind of
Speaker 1:Huge tailwind for the meme industrial complex.
Speaker 2:Huge tailwind. Still a lot to work out there. I do find that sometimes when I go to images in ChatGPT, I'm going back and forth on the prompt for ten minutes and I'm like, I could have just done this with traditional tools. So it's not perfect, but when it gets it, it's so amazing. And the final product often looks a lot more cohesive than what I would get if I was, like, collaging and, like, the shadows didn't match and there were, rough edges and stuff.
Speaker 2:So certainly great there. The last three are a bit more vague. We'll have to read into those. But OpenAI is set up to win pretty big in all of these categories. So semi analysis, clocks, chat, GPTs, share of queries, it's 71%.
Speaker 2:Meta is in second at 12%, and that's with billions of users on products. And so OpenAI is certainly running away with consumer. So there's this question of like the it feels like the rest of consumer AI plays will be, I would say, horizontal in the sense that it won't be a new app on your home screen. Meta won't have Meta AI as
Speaker 1:a home
Speaker 2:screen app.
Speaker 1:Loses their lead and becomes the Yahoo of AI, but that doesn't feel likely.
Speaker 2:Yeah. It feels tough. Like, why did Yahoo lose to Google? It's because there was an entirely new paradigm in page rank. Like a new algorithm emerged.
Speaker 2:Sure. If that if that happens from SSI or super intelligence, meta super intelligence, there could be a leapfrog moment. But so far, they've been pretty good at staying near the frontier to the point where it's like, okay Google got them on this one or Croc got them on this one today. But there hasn't been a time when I've been like, okay. Like there is a dramatic difference in the results such that it's worth it for me to go over.
Speaker 2:There was that moment for Claude for a little bit. Everyone's like, Claude's way better. I went over and used Claude for a bit and then I went back to OpenAI just because the product was better and Yeah. And had more of an ecosystem. Product lead
Speaker 1:is very real.
Speaker 2:Yeah. I was I was thinking about this. Like, if if you played out a hypothetical scenario and you went and you had, you know, the keys to OpenAI HQ, you went and you exfiltrated all the code, everything, got an app into the App Store, Geordie GPT. You have the exact same model, the exact same inference, the exact same UI, everything. Could you win?
Speaker 2:Because people would say, well, it's not better. Real brand.
Speaker 1:We we live on a part of the internet where people are constantly debating the merits and of the leadership teams and Yep. Approaches and the philosophies. But then downstream, you have approaching a billion users that are just like, yeah, I like I like the product. I use it a lot.
Speaker 2:Yeah. And so even if you ran a Super Bowl ad saying like, we have a product that's exactly as good as ChatGPT. It is feature for feature
Speaker 3:parody.
Speaker 2:They would be like, but I already have it installed. You're asking me for two minutes to uninstall this and reinstall the new one and then I don't get any benefit. I wouldn't do it. Even if you match my even even if you match my capabilities, you got a leapfrog.
Speaker 1:It's funny. So so Jason Fried had a great post Oh, relevant yesterday. He said, feature parity is just another way to say we don't need to exist. If you That's come out
Speaker 2:good point.
Speaker 1:And you're so good Yep. At what you do that you can create it as as good of a product
Speaker 2:Yep.
Speaker 1:As OpenAI models that are as good, you still don't need to exist. Yep. And so that is the challenge Yep. For anyone competing.
Speaker 2:If you Let me tell you about ramp.com. Time is money saved both, easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place. Go to ramp.com. Really quickly, so it feels like the rest of consumer AI plays will be horizontal. There won't be a new AI app for Meta that really takes off.
Speaker 2:Instead, AI will improve everything Meta does across Facebook, Instagram, WhatsApp, Quest, etcetera. And I was thinking about the initial takeoff of Facebook. The other tech companies, they didn't really seriously get to compete in social networking. Yeah. Like, Google plus never really took off.
Speaker 2:I guess Microsoft bought LinkedIn, and that's kind of a niche social network, very profitable business, great business. But it's it is like its own thing. It doesn't directly compete. But graph databases and the idea of storing efficiently connections in in graph networks like Facebook kind of pioneered, that became really widespread and was used all over the place. Yeah.
Speaker 2:And the same thing with Google Search, like this this PageRank, just better search algorithms, those wound up manifesting in better search in all sorts of products. And so when when a new company comes out and builds, you know, a a whole paradigm or they break through in terms of a front end development or database development or some sort of structure, like, winds up it winds up improving everyone. And so I think I think AI will have these like horizontal benefits all over the ecosystem. I think it makes a ton of sense that that Meta's investing so much in super intelligence. But it's not, I don't really think the narrative should be like, they need to play catch up to ChatGPT.
Speaker 2:I think it's more like, they just need to implement LLMs in every single crack in their all of their different systems like they do with great databases, great infrastructure. Not sure.
Speaker 1:We'll see I still think I think there's I mean, remember Meta made some early experiments of making digital clones of big celebrities Yeah. On Instagram. Yeah. I still think they'll take more shots on goal around companionship. Yeah.
Speaker 1:Will they go grok waifu mode? No. I don't think I don't think they want that revenue line. But but there's a bunch of other ways in which they could kind of go after that market that I don't even think. I mean ChatGPT is is is such such an interesting product because it's designed to be a functional tool knowledge retrieval, creative expression
Speaker 2:Yep.
Speaker 1:Just unlocking consumer surplus, giving people access expertise, etcetera. And the the way in which people are using it as a companion is sort of not the sort of default. It's not like you name your ChatGPT. Right? People will give it a name.
Speaker 1:Yeah. But
Speaker 2:It doesn't really stack. It's Yeah. Not it's certainly not baked into the UI Yeah. In the way that it could be. Yeah.
Speaker 2:I know people do talk to
Speaker 1:I'm sorry. I've said it before but as as Chad GPT user hours are just or sorry user minutes still. But as they're ticking up, I do think Zuck will look at that and say, want I want some of that action.
Speaker 2:Yeah. Yeah. And and and maybe some of that. But I still I still think some of that happens inside of the platforms. I don't I don't know a net new app.
Speaker 2:It would be very difficult. And and Meta has yet to really do it. WhatsApp an acquisition, Instagram an acquisition. But Stories massively successful within Instagram. Yeah.
Speaker 2:And so I would expect, I I agree with your take that I think there's an opportunity for for a lot of AI stuff to live within those apps. And then also just on the monetization side, like they're in a very unique space where they can give great products away for free, but they can't be charged an inference cost to another company. And so, if they have their own open source model, they can inference very cheaply, they can give it away for for free, and then they leverage their massive ad network. So let's go through what Fiji Simo over at OpenAI is building. So, in a few weeks, I'll be joining OpenAI as CEO of applications.
Speaker 2:We've all been waiting for this moment. Helping to get OpenAI's technology into the hands of more people around the world. I've always considered myself a pragmatic technologist, someone who loves technology not just for its own sake, but for the direct impact it can have on people's lives. That's what makes this job exciting, since I believe AI will unlock more opportunities for more people than any other technology in history. If we get this right, AI can give everyone more power.
Speaker 2:And so, she has a fantastic career. EBay, Facebook, then Instacart, and is now at OpenAI.
Speaker 1:And she was heavily involved in building the ads engine at Instacart, correct?
Speaker 2:Yeah. Yeah. And obviously, Facebook as well. So in on knowledge, she says, empowerment starts with understanding the world around us and our place in it. When we have the right knowledge at the right time, we can make better decisions, advocate for ourselves, and change our path.
Speaker 2:But for most of history, access to expert level knowledge has been limited to those with more resources. I mean, even even after the invention of the printing press, like, you still had to be in a big city that had a library to go check out a book for free. Still had to have the time to do it. And and certainly buying every book and being able to index it was very expensive and difficult. Now it's even easier.
Speaker 2:It's already working. People who use AI tutors learn twice as much as they do from human ones, and the gains are even bigger compared to learning in a traditional classroom. In a 2024 OpenAI study, 90% of users said ChatGPT helped them understand complex ideas more easily. I agree with that. On health, she says, personally, I'm most excited about the breakthroughs that AI will generate in health care.
Speaker 2:A few years ago, I faced a complex and poorly understood chronic illness on its side, and it became painfully clear just how fragmented and inaccessible the healthcare system can be. Even with access from some of the best doctors in the world, I found myself acting as a connector, piecing together insights from multiple specialists who weren't speaking to each other. I actually had a friend who got a very, very rare form of cancer and did all of the research pre CHA2GPT, actually downloaded all the frontier science and all the different papers, figured out that it was this one very rare condition, found the expert, went to that expert, he was like, yep, you have this thing. It's the I'm the only one that studies this thing. I'm gonna help you.
Speaker 2:Did the surgery save your life? Crazy.
Speaker 1:I I had an I had an issue. I was I was 18 traveling. I was surfing in South America. Mhmm. There was flash flooding.
Speaker 1:I was in this tiny town. I got a antibiotic resistant staph infection from Oh,
Speaker 4:that's bad.
Speaker 1:And then was getting repeated infections over the next year. And the doctor kept prescribing Antibiotics. Antibiotics that were so I mean, such an intense antibiotic that doctors won't it's like a soap. They won't touch it without gloves on. Oh.
Speaker 1:And they use it pre before surgeries. And they just said, use this twice a day over your entire body. And I kept having I kept having issues and eventually found a Reddit community that was like just like obsessed over this issue and the and the thing that fixed it was avoiding gluten. Yeah. They're like actually just That's
Speaker 2:so crazy.
Speaker 1:And I just imagine if I was like even now if I was dealing with that issue, I would have been able to I would have just been able to like talk with chat GPT about it. They would be able to surface all that kind of thing, build a build a picture of it.
Speaker 2:Very interesting. Well, let me tell you about Restream. One livestream, 30 plus destinations, multi stream.
Speaker 4:That's right.
Speaker 2:And reach your audience wherever they are. We use Restream.
Speaker 1:Backbone of this show.
Speaker 2:So, she closes out health saying, AI can explain lab results, decode medical jargon, offer second opinions, and help patients understand their options in plain language. It won't won't replace doctors, but it can finally level the playing field for patients, putting them in the driver's seat of their own care. Very excited for that. And also that feels like something, I don't know, like, yeah, just like I don't know. It'll be interesting to see if that manifests itself in Like all of this is like will there be any fracturing in the actual product?
Speaker 2:Because right now all the fracturing that's happening in the ChatGPT product is in like what model you're using, you're using agent or deep research. But so far, all the different They're all chats. Products. Yeah. They're all chats and and and none of them say this one's for health, this one and I'm in like a health a safe health territory.
Speaker 2:It's like that's all driven by the prompt. I would imagine that over the long term, everything's driven by the prompt. I would love to be able to go to Chatuchipaty and just say, hey. Quickly. What's the population of Canada?
Speaker 2:And it knows to use four o for that. And then if I say, hey, I want you to give me a full report on the history of Canada. Give me a deep research report. I wouldn't need to select it. It would just know from the And
Speaker 1:go to ChatGPT agent, help me annex Canada.
Speaker 2:Then it just goes in states. Don't mistake. And then and then it just keeps working. So the third one, she says creative expression. I believe we're all born creators and that the ability to imagine something and make it real is a big part of what makes us human.
Speaker 2:The problem is that our ability to express that creativity is often limited by our skill sets. Completely agree. I can't draw at all. Not everyone has the resources, time, or training to paint, write, compose, or build. When I imagine the future, it often comes to me in images.
Speaker 2:I paint in my spare time. But the oh, we gotta find some Fiji Simo originals. Why don't I hang them on the wall? This is interesting. Bull market.
Speaker 2:It's lore. But the images in my head are much more realistic and complex than what I am able to paint today. Now, AI is collapsing the distance between imagination and execution. With AI and image generation, I can prompt and iterate until the output matches the complexity and realism of the vision in my head. Unless it's a Where's Waldo.
Speaker 2:We gotta solve the Where's Waldo challenge.
Speaker 1:We do.
Speaker 2:It's it's coming for sure. The Where's the Where's Waldo eval for image generation. Today, nearly one in three Gen Z users say AI tools have helped express themselves in ways they never could. So this is another fun, viral, obvious, valuable, like we know it, we love it, everyone's using ChatGPT for creative expression.
Speaker 1:Oh, yeah. And this presents a massive challenge if you are a a chat GP a GPT rapper that's trying to go compete in the creative expression
Speaker 2:Mhmm.
Speaker 1:Space because you have to you it's not enough to generate a cool image or generate a meme. Yeah. It used to be that if you could do text well, that would Yep. Maybe an advantage that people would use your product. But Yep.
Speaker 1:ChatGPT image generation has just gotten better and better and better. It's fantastic. If you haven't played around with it much, drop your your group chat, the the profile pictures of your most popular group chat, put them in there and say make them all Giga chats
Speaker 2:Yes. And then
Speaker 1:you can share Howdy. Back. Yeah. For
Speaker 2:sure. You start with generating an image in ChatGPT. Then when you're ready to go pro, move over to Figma. Figma.com, think bigger, build faster. Figma helps design and development teams build great products together.
Speaker 2:You can get started for free at figma.com. Fourth, she says, economic freedom. When people can independently create and capture value, they gain power over their own economic destiny. But starting a company isn't easy. The average cost to start a small business in the is around $30,000, an impossible threshold for most aspiring entrepreneurs.
Speaker 2:And until recently, building a product or launching a service required technical knowledge, especially coding. That was a problem for hundreds of millions of people who had ideas for tools, apps, platforms, etcetera, that could have made an impact, but didn't they didn't have the technical skills to bring them to life. The classic ideas guy, I just need a programmer to build it for me. Well, now you can vibe code it. AI now gives the people the the power to turn ideas into income no matter their age, credentials, or zip single person can now brainstorm, prototype, market, and launch a product with tools they control themselves.
Speaker 2:A a 2024 Shopify report showed AI enabled solopreneurs launched businesses 70% faster than peers without a tool without AI tools. I've seen it with my nine year old daughter who decided one day she wanted to be be a party planner for kids birthdays.
Speaker 1:Let's give it up for
Speaker 2:It's amazing. What a great story. In one weekend using AI tools, she created a fully functional website showcasing her party ideas, shared it with her peers and started taking on clients. Amazingly, my husband and I didn't have to help her. But we did have to intervene before the confetti cannons were ordered.
Speaker 1:Ben, good reminder, we should get some confetti cannons.
Speaker 2:We do need to.
Speaker 1:Except last time when we had confetti cannons at YC demo day Yes. My eyes were in pain days and and days. Need goggles next
Speaker 2:time. Yeah.
Speaker 1:Was there was so much dust
Speaker 2:in the
Speaker 1:in the confetti cannon.
Speaker 2:We left it all in the field.
Speaker 1:We did. We did.
Speaker 2:In the future, people will be able to build new things without waiting for permission, capital or credentials. This will, of course, will mean a meaningful shift in the workforce. Companies will hire fewer people. So you get more smaller companies. That seems pretty cool.
Speaker 1:Yeah. My first real company is skateboard company Yeah. J Man Designs. Probably, I don't know if I would have done it if my my lovely mother wasn't a graphic designer
Speaker 2:Helped
Speaker 1:and I needed a logo to print on the decks that I was getting made. And I just would sit with her and tell her, you know, do this, do that, do this, do that. And yeah, it's pretty cool that you can now just talk through that process in natural language and and Yeah. How many more people
Speaker 2:can do It's pretty crazy you ran a skateboard company without doing proper SOC two compliance.
Speaker 1:I know.
Speaker 2:You should've got on Vanta. Automate compliance, manage risk, prove trust continuously. Vanta's trust management platform takes the manual work out of your security and compliance process.
Speaker 1:Huge alpha just starting starting an extreme sports company and saying, look, none of our competitors are serious enough about this to
Speaker 2:get We take serious. To
Speaker 1:really take compliance and security Yeah. As seriously as you
Speaker 2:I mean, I do think for for for kids especially, I mean, the ability to just just use AI tools fully to go and solve problems and it's almost like your your Town's McKinsey consultant. I remember I had an early job of just like scanning photos for someone. They needed a whole bunch of photos scanned. It was like pretty manual labor, but like I I I actually wasn't that good at it. I kind of messed it up.
Speaker 2:There was like too much like the the the scanner wasn't configured properly. So a lot of us had to redo a lot of them. It was learning. It was learning process, but it's probably the first one of
Speaker 1:the first The small ones I the only thing that that's maybe boring and repetitive that that you that that I can imagine you doing is the bench press.
Speaker 2:Oh, yeah.
Speaker 1:It should basically be the same every time.
Speaker 2:But Yes.
Speaker 1:But but, yeah, those type of tasks I've always struggled with. But I don't know that we're at a point. I still think if you were using I I don't think that I think that job still exists.
Speaker 2:I think it does. I think there are bigger companies where you can just, like, send in a ton of stuff, and they'll just professionally scan it for you. But they're pretty expensive, I think. So I think the kids still have some alpha if your if your if your opportunity cost is enough. Yeah.
Speaker 1:As many as
Speaker 2:kids are. Fifth, she says, time. Regaining control of your time is one of the most liberating empowering shifts a person can experience. The ability to control how you spend your time is often what separates people who feel in charge of their lives from people who feel overwhelmed by them. Wealthy people who have always bought back their time by hiring personal assistants, household staff, private tutors, chefs and more, building full infrastructures to reduce friction in their lives.
Speaker 2:Meanwhile, the average household spends nearly twenty hours a week on domestic work, logistics and errands. While leading Instacart, I saw firsthand how technology can shift perceptions and behaviors around time. In 2012, the idea of paying someone to shop for your groceries felt like a luxury, something reserved for the ultra wealthy. But with the right product design, logistics and pricing, we made it accessible and indispensable for everyday families. Today, the Instacart user base mirrors The US population with millions of families getting hours back each week to spend on higher value activities
Speaker 1:is will OpenAI build a gig worker network where when your agent runs into a wall and needs somebody in the real world to accomplish a task, will you be able to delegate tasks like that? Feels like a stretch, but I don't know. They could plug in to the Uber network or any of these other networks.
Speaker 2:Yeah. Maybe they'll I mean, they already have like an Instacart integration. So maybe they will they will rely on other gig work Platforms. Platforms to solve those problems and actually handle that side. And they will stay in the full Like the package
Speaker 1:package delivery where you can get an Uber to just pick something up and take it across town. Yep. You could imagine that that being integrated.
Speaker 2:Yeah. I mean, there's there's a host of of of, you know, services and companies and APIs for shipping, mailing, moving things around, hiring someone. I mean, in theory, you could you you could hire a personal chef and be communicate your agent could be emailing with them and say, hey, you know, be here at this time. There's this party. Here's and it's kind of, you know, it doesn't need to be it doesn't even you don't even maybe need a gig work platform because the agent can go out and and scroll Instagram in theory and find someone who's advertising that service or Google it and find a listing of local people providing that
Speaker 3:Yeah.
Speaker 2:That that job and and go and retain their services directly. Interesting. I believe AI will allow for a similar shift in many areas of lifetime consuming activities like researching decisions, planning vacations, scheduling a tutor, and more can be done by an AI agent than any that anyone can access as we build new products. We have a chance to make these time saving capabilities feel not only useful, but routine. In doing so, we can empower people to regain control of their time and attention.
Speaker 2:And I I certainly feel that something that I would need to sit down fifteen minutes looking for, you know, a new studio space or something, fire off agent and come back with some interesting results. Anyway, let me tell you about graphite. Dev, code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. Get started for free.
Speaker 2:Graphite. Dev. Last one, support. For many people, the biggest barriers to progress aren't lack of access or opportunity, but self doubt, isolation, and burnout. Sometimes what's most empowering is support, someone or something that can help us reflect, feel seen, or simply move forward with clarity and confidence.
Speaker 2:My business coach Katya has been transformative in my career. I've joked with her over the years that everyone needs a Katya in their pocket. Personalized coaching has obviously been a privilege reserved for a few. But now with ChatGPT, it can be available to many. This is something I have not used.
Speaker 2:This feels like we're getting further out on the curve of like, you know, defining what the product is. Like, knowledge retrieval is, like, so concrete. Generating image, very concrete. Now support is much more and it's much more of an amorphous product, and there's some companies out there that are doing it right now. It's not a drop in replacement, and and there's much more to define about what this product looks like or how people actually use this.
Speaker 1:Yeah. It's very general. There's gonna be vertical specific companionship products.
Speaker 2:Mhmm.
Speaker 1:Right? We've seen this. What's the founder that we had on the the replica? Replica. The original one started like a decade ago.
Speaker 1:Yeah. Grok Grok Heavy four has their own There's also Specific iteration. But then but then this is also to be clear. Yeah. The area of greatest concern
Speaker 2:Sure.
Speaker 1:Right? Where it's very clear. If you have a business coach Yep. Telling you, John, you got this. You're incredible.
Speaker 1:You're Probably good. You're built different. That's great. But then when you tell them that you've discovered, know, how to break the, you know, space time continuum and
Speaker 2:they tell you the truth. Actually right. It's road right now.
Speaker 1:You're right. You're good. You're absolutely right. You
Speaker 2:can Called figure this two ones.
Speaker 1:And so I think they need to figure out the guard rails for this category and I'm sure that's top of mind for everybody at the company right now.
Speaker 2:Yeah. For sure. AI coaches on the other hand can be available throughout every day. She says, this isn't about replacing human connection, but filling a gap that often goes unfilled. Many people don't feel comfortable opening up to family or friends and most people don't have access to a therapist or coach they can call regularly.
Speaker 2:Even people who do have access often spend an hour a week or less with these professionals. At the core of philosophy and religion is the idea of self knowledge. To become who we want to be, we have to understand who we are. So very interesting. Anyway, let me tell you about Linear.
Speaker 2:Linear. App. Linear is a purpose built tool for planning and building products, meet the system for modern software development, streamline issues, projects, and product roadmaps.
Speaker 1:It is what OpenAI uses to build their products.
Speaker 2:That's true. So, yeah. I I think it's interesting to see, like, it's like, useful is it to have these six ideas in mind? Because in many ways, like, ChatGPT, the magic of it is that it's just a blank text box, and you can do anything with it, and then these properties emerge. Like, the yeah.
Speaker 2:I mean, like, Google over time had to figure out, okay. There are people that are searching for products. Let's let's surface them the Google Shopping experience. And that is a specific UI that is triggered when you search for a certain product. If you ask for, you know, like best headphones over the ear under $200, like, it will just put you in a different product more or less instead of just the 10 blue links.
Speaker 2:Same thing for if you're asking for a movie. It will pull up the pictures of this cast and the year and show you the Wikipedia page and like or news. It'll take you to the news portal. And I'm wondering like how much of this will actually bifurcate into different trees with different rules and different features? Because for something like support, I don't know that if I'm having a conversation with a coach about a strategy that I want it to wait fifteen minutes to get back to me.
Speaker 2:That might be something I wanted to do separately. But then if it's health and I'm uploading my health records or some documents, I'm like, really, really, really don't hallucinate. So, like, take as much time as possible. Again, that's something that right now I would decide as the user, but I'm wondering if this buy for
Speaker 1:you at Obviously, OpenAI, ChatGPT as a business, they when and when anybody wants to do anything, they want people to go there. Yeah. Right? When you want companionship, you wanna talk with somebody about something, you go there. When you want to, they do the book a flight demo that's overplayed but they wanna own that.
Speaker 1:When somebody's shopping, they wanna own that. When somebody's trying to diagnose a medical issue, they're trying to own that. So I just look at this this this article, this essay, whatever you wanna call it, as a as a way for people internally at OpenAI to sort themselves into what area. These are all different verticals that I can imagine people working on. Like, I wanna go to ChatGPT and work on health.
Speaker 1:Right? Giving people their time back.
Speaker 2:I was listening to Ben Thompson talk about the the flight booking agent demo and he was like, I have a personal assistant. I book my own flights. And I think that's very very common where it's like, I'm He's so specific about what he wants that he's fine to just do it. And it doesn't take that much time. And so I do wonder if I most of people
Speaker 1:have a flight booking AGI.
Speaker 2:Yeah. In your brain?
Speaker 1:First name ramp, last name travel.
Speaker 2:That's true. Yeah. I mean, it's when I use that, it's like I'm in control. It just does all it harnesses everything to bring all the data together.
Speaker 1:Yeah. Interesting thing is I've had EAs over the years. I've had remote EAs. I've had EAs that are are embodied real people Okay. That are absolute killers.
Speaker 1:Yeah. And I find that the most the Internet already makes it so easy to do so many things
Speaker 2:Yeah.
Speaker 1:That the greatest some of the greatest value that you can get from an EA is just having somebody in your city that can help you with a variety of different things. And so I think no matter how good ChatGPT agent gets, there's still I mean, there's just still so much that I think people expect out of of an EA. So
Speaker 2:Yeah. Yeah. It's very it's very particular. Like, people have all sorts of preferences and I don't know. It might be it might be more sticky.
Speaker 2:Who knows? We'll we'll we'll see. It'll certainly continue to be a good eval. Well, I wanted to just look at what's what is, you know it feels like OpenAI has a really strong lead in consumer, the product. They're thinking about the applications and actually, like, the the the the manifestation of, like, these six different categories.
Speaker 2:Polymarket has OpenAI climbing now in which company has the best AI model at the end of twenty twenty five, the December 31 rankings. OpenAI is up to 29%. Just a week ago or so Correct.
Speaker 1:July,
Speaker 2:x AI was crossing about to beat them. But Google's still in the lead. 48% chance that Google winds up with the best model. But that doesn't necessarily mean
Speaker 1:I mean, this is based on LM Arena. Exactly. It's not necessarily the most valuable model to users. Yep. It's who's dominating benchmarks.
Speaker 2:Yeah. I actually pulled up some interesting like the so do you know how there are movies that are loved by critics but disliked by audiences? So the classic example is Star Wars The Last Jedi. 91% on the Tomatometer but audiences gave it a 41% score. And then Dave Chappelle's comedy special had the opposite where the critics hated it but the fans loved it.
Speaker 2:And so these things are like controversial. And I was wondering if the same thing exists in in foundation models and it does. So Gemini 2.5 Pro has which one is this? Gemini 2.4 2.5 Pro has an MMLU score of 86% and it's the top ranked model on LM Chatbot Arena. O three, so if you summarize these, let's see.
Speaker 2:Kimi K2 illustrates how a model can excel in benchmarks and still be less preferred by users. Possible reasons include limited availability. Similarly, Claude Opus four and GPT 4.5 have high MMLU scores, yet rank lower in human preference because they may focus on careful reasoning rather than conversational ease. So you can think about it like you don't necessarily always wanna be talking to someone who's like the most rigorous or like it's almost like they're too smart maybe. And then Gemini 2.4, 2.5 Pro o three and Gemini 2.5 flash show the opposite pattern.
Speaker 2:Users love them despite modest MMLU scores. So these models have long We need
Speaker 1:Tyler to to go to a random place in America and do a man on the street interviews Yeah. And just ask people about models. I bet you 99% of respondents probably probably probably like 990 out of a thousand Yeah. Are gonna tell you, I just go to
Speaker 2:chatchat.com.
Speaker 1:Chatgbt, chat.com and I just I just opened a new chat.
Speaker 2:Yep. What is there's multiple models? Yeah. Totally. But but it's interesting that like if you wanna win with people Gemini 2.5 Pro o three, these models have long context windows.
Speaker 2:So they're staying focused a little bit longer if you're having a conversation. Multimodal features, the images and audio kind of just a better user experience. You can talk to it in different ways. Faster latency, more personable style, makes them more enjoyable. Even if they don't top academic tests, your people are happy with it.
Speaker 2:So I thought that was I thought that was an interesting Yeah. Little little anecdote. So anyway, let me tell you about numeralhq.com. Sales tax on autopilot spend less than five minutes per month on sales tax compliance. Know, You had a post today from the Wall
Speaker 1:Street Journal. This was wild. This stood out to me. We commuting in to the studio this morning and this stood out. So OpenAI has committed The Journal reported that OpenAI is committed to paying Oracle $30,000,000,000 per year Mhmm.
Speaker 1:Within three years for four and a half gigawatts of data center capacity, which will be the equivalent of two Hoover Dams worth of energy. Yep. So good time to be if you if you happen to build a Hoover Dam mega project, you know, years and years ago Yeah. This would be a good time.
Speaker 2:If you're squatting on a Hoover Dam
Speaker 1:Yeah.
Speaker 2:You could get 15 a year from that potentially.
Speaker 1:Well, it's obviously not not the entirety of
Speaker 2:the No.
Speaker 5:No. No.
Speaker 1:Of the cost. But, yeah, it's it's it's wild to think OpenAI's latest like run rate. Right? They're reporting somewhere around $10,000,000,000 run rate or they wanna end there
Speaker 2:Yep.
Speaker 1:By the end of the year. And so, they're expecting to be able to have $30,000,000,000 worth of that. And that's just with this partnership with Oracle.
Speaker 2:So Yeah. There was a So Tane, who's been on the show, says Chachi Pitita is a truly iconic product. Consumer engagement at scale, over 500,000,000 weekly active users, an estimated 7,000,000,000 ARR. And it looks like an annual chart and it's a monthly chart. So August 2024, they're at a 2,600,000,000.0 estimated consumer ARR.
Speaker 2:Then in September, they're at a 3.3. December, they're at a 4,000,000,000 ARR. Then they're accelerating. February, they're at 5,600,000,000. March, they're at 7,200,000,000.
Speaker 2:And, of course, we're all the way in July now. So they could potentially already be at 10,000,000,000 ARR. And so if you just chart this out, it 30,000,000,000 in a few years doesn't seem that crazy. And we were we were talking about, like, how bad is that? How how how how painful is that to pay a $30,000,000,000 bill?
Speaker 2:But it it is kind of the only cost is like to serve the models. And so I don't know. It it feels like it could work out. I don't know.
Speaker 1:I mean, it's certainly not the only cost. They they I mean, especially if you look at stock based comp.
Speaker 2:Yeah. Yeah. Yeah.
Speaker 1:They're spending more than
Speaker 2:And and that won't and that won't stop.
Speaker 1:119% of revenue on stock based comp over the last year. So very very significant but Yeah. This is what betting on yourself looks like. Commit. You know, if you wanna level up in life Yeah.
Speaker 1:Commit to, you know, $30,000,000,000 of of fixed costs three years from now. You gotta make it work.
Speaker 2:So For sure. So this this all comes from a Wall Street Journal report saying that OpenAI's project Stargate is struggling, which is an interesting term. We can kinda debate what constitutes a struggle. So for some context here, all the hyperscalers are generally in the high tens of billions in terms of CapEx. So Google, Microsoft, Amazon, AWS, they're all in, like, the $60.70, $80,000,000,000 range.
Speaker 2:But the majority of that is on core AI or core data center build out, so traditional data center build out because they still need to serve just, you know, relational databases. Not everything is cutting edge NVIDIA chips serving transformer based language models.
Speaker 1:Ghiblis.
Speaker 2:Ghiblis. Yeah. Not all of it's Ghiblis. But a lot of it is. And Mark Zuckerberg recently said that, you know, about half of the spend maybe going forward, something like that is going towards Gen AI versus Core AI.
Speaker 2:So he builds out a big AI data center. A lot of that's going to just serving reels, picking what ads to show you. All of that is AI as well, but it's not in this generative AI, not training these large models. So the majority of that spend is not on generative AI focused data centers. So but there's still big big numbers.
Speaker 2:You can think about all the
Speaker 1:Zac has his own Manhattan project. Yes. That's basically what what Yes. What if if you if you show that your new data center is gonna be the size of Manhattan Yes. That's one way of saying I am doing a Manhattan project for AI.
Speaker 2:And that and that that like, you know, the size of Manhattan, that particular data center, he's targeting five gigawatts
Speaker 1:Yeah.
Speaker 2:Which is right here at four and a half gigawatts in three years. And when and when Mark Zuckerberg was talking about that five gigawatt data center, he was saying this will be in a couple years. Right now, they're focused on the one gigawatt data center. And when we talked to the c the the cofounder of Core CoreWeave, he was saying, like, you don't understand how big five gigawatts is. Like, that's insane.
Speaker 2:It's such a big it's such a big data center. Like, this is a huge project. These are mega projects. And so when I hear something like, oh, it's it's struggling like a couple months in, I'm kind of like, you know, we're building something so big. Like, did we ever expect there not to be a hiccup?
Speaker 2:I'm not I'm not ready to say like, oh, this is all doom and gloom. It seems like, you know, they shot so big
Speaker 1:with 500 So so yeah. Yeah. So one, gotta give regardless of of what someone thinks about Sam. Right? He's got plenty of critics but the fact that he was able to finesse his way to getting the president to announce this project Crazy.
Speaker 1:With Masa
Speaker 2:Yeah.
Speaker 1:With a number so large that people immediately just started looking at SoftBank's balance sheet and saying, okay, cool. How happening? Is Elon quickly fired Yep. In the comments saying, they don't have the money.
Speaker 2:Yep.
Speaker 1:I do It was always unclear where the money was gonna come from But one of those things, you shoot for 500,000,000,000
Speaker 2:Yep.
Speaker 1:You land at a 100,000,000,000 Yep. You're still doing pretty well.
Speaker 2:Yeah. And it's more it feels like it's more about the corporate structure and the timing. Because if you if you go to Google, Microsoft or Amazon and you say, we're we're so in on AI. We're going to invest $500,000,000,000 over the next ten years. Like, all of a sudden, it's like, okay.
Speaker 2:Yeah. Well, you're on track to do that. That that totally maths out. So the question was always in my mind, okay, $500,000,000,000 is the goal, but what is the time frame? And and that's the one that people are pulling on right now because the immediate number was a 100,000,000,000.
Speaker 2:They said we're gonna do a 100,000,000,000 right now. That was in January when Trump, Masa, Sam Altman, and Larry Ellison were at the White House. They announced Stargate. They say, we're targeting 500,000,000,000, but we're doing a 100,000,000,000 immediately. Now that's maybe been scaled back, but it's still so huge.
Speaker 2:Like SoftBank's putting 30,000,000,000 in OpenAI, and then OpenAI is paying Oracle 30,000,000,000 per year starting within three years. So Struggles is a
Speaker 1:little Yes. Mean, Oracle's projecting 25 over 25,000,000,000 for 2020 in 2026 CapEx.
Speaker 2:Okay.
Speaker 1:Everybody's just throwing money in the pot. Yeah.
Speaker 2:Yeah. And I mean, it makes sense
Speaker 1:because all the recordings now is the the definition of Stargate is just being expanded.
Speaker 2:Sure.
Speaker 1:Sure. They're counting the the Oracle. Yep. The the sort of commitment that they're making to Oracle as part of it. Yep.
Speaker 1:So
Speaker 2:And so I I think the there there are two questions. One is, like, the super intelligence AGI pilled, like, gotta build the next greatest thing, and whoever builds that at 10 x the scale, whoever gets to the fifty fifty billion dollar, $500,000,000,000 data center, they just train, and then they win because they'll have a product that's so much better than everything else that everyone will shift over, and ChatGPT will be obsolete. The the flip side is that if we're in a little bit of an s curve, if we're in a little bit of a plateau, we'll then in order to hold on to that 71% market share, ChatGPT just needs to keep just keep delivering inference tokens reliably at a level that doesn't cause churn. And so when when if I go to ChatGPT and I'm getting a ton of errors and I just cannot get my prompts done and like my Ghibli's aren't working, I'm gonna open up the Gemini app and I'm gonna go over there and see if they have any inference tokens. And we're hearing this from the model routing companies that a lot of businesses that rely on LLMs and AI inference are seeing brownouts, intelligent brownouts in different models at different times.
Speaker 2:Yeah. And so they need to be able to reroute from
Speaker 1:Yeah. Somebody was looking at Anthropix uptime Yeah. And it's just constantly down. Like, there's so much demand and they're they're obviously doing everything in their power to deliver against it. Yeah.
Speaker 1:But they they they don't have enough GPUs yet.
Speaker 2:And so that feels like everyone's gotta build bigger data centers. Maybe there is a point where we build too big, but everything looks like, okay. It's at least worth building the one gigawatt data centers. Probably worth building the five gigawatt data centers. We might need some more research breakthroughs to justify the bigger data centers, the 10 gigawatt, the, I don't know, twenty, fifty gigawatts, something crazy.
Speaker 2:But in general, I think the main goal for OpenAI right now is just to continue serving inference at a level that avoids churn. So when someone shows up, get them the answer. I think new products like Agent are cool, but it takes months for people to really adopt these new tools in mass and seriously change inference demand. We saw this, like, agent went out Thursday. We talked to the team, and then over the weekend, I was talking to people, and smart people in tech were not using it yet.
Speaker 2:And I kind of had to, like, step up and be like, it's my job to test this thing. And now I'm using it. And now I would say I'm probably a weekly active user of of agent. I'm definitely a DAU of of four o. I'm a DAU of o three pro.
Speaker 2:I'm probably even a DAU of deep research, but I'm not a DAU of agent yet, but that will come. But I'm clearly on the early adopter side. It will be a while until they're doing so much agent, so many agent workloads that they're really
Speaker 1:Right now, just default takes fifteen minutes?
Speaker 2:It it so deep research takes fifteen minutes almost every single
Speaker 1:agent always No. Oh,
Speaker 2:it's can be shorter. It can be longer. That's part of the beauty of it is that it it sizes the inference relative to the task. And so it can it can spend a really long time. It can come back to you.
Speaker 2:It can it can interact with you. Although I haven't actually gotten a push notification. Maybe that's just because of the nature of my prompts, but I haven't had to step in, which has been surprising because when we talked to Dan Shipper from Every, he said that he did have to interact. But I think what he was prompting was a little bit more robust than what I was asking for. Yeah.
Speaker 1:What he what what what he's doing that I think will will get a lot of adoption but a bit slower is he sort of like batched tasks
Speaker 2:Yeah.
Speaker 1:That I think are really interesting. But that is expert mode
Speaker 2:Yep. For now. So that's the story in the Wall Street Journal. There's Should
Speaker 1:we flip over maybe cover this
Speaker 2:To FinAI, the number one AI agent for customer service, number one performance benchmarks, number one in competitive bake offs, number one in ranking on g two. Bake off channel. What do you wanna flip over to?
Speaker 1:I was gonna say, maybe we cover this x AI story quickly.
Speaker 2:Yeah. Yeah. Totally.
Speaker 1:And then we have actually Tyler, our very own Tyler over Fantastic. And Michael are at the Tesla diners.
Speaker 2:Oh, cool.
Speaker 1:Over to them and and get a So
Speaker 2:so Sam Altman, Larry Ellison, Trump in some ways, Masa are all working to build Stargate simultaneously. Elon Musk is trying to ramp up things at XAI. He's aiming to raise up to $12,000,000,000 for XAI chips as the startup burns through cash. And so just weeks after Musk's x AI raised 10,000,000,000 through sales of stock and debt, the startup is working with a trusted financier to secure up to 12,000,000,000 more for its ambitious expansion plans. Valor Equity Partners, Antonio Gracias, is in talks to lead with lenders to raise the capital.
Speaker 2:The money would be used to buy a massive supply of advanced NVIDIA chips. And so the number was kind of all over the place. I saw a million chips floated. That would be much bigger
Speaker 1:Sir, Elon Elon shared this morning, 230,000 GPUs including 30,000 GB two hundreds are operational for training Grok XAI in a single super cluster called Colossus one.
Speaker 2:Colossus one.
Speaker 1:And at Colossus two, the first batch of five hundred and fifty fifty thousand GB two hundreds and GB three hundreds also for training start going online in a few weeks.
Speaker 2:So if you compare that to what the other clusters are, Prometheus from Meta is around 500,000 ships. Stargate's supposed to be around 400,000, and I believe Anthropic's in that range too. And so it's a knockout drag out fight. Everyone's trying to build a massive cluster, do the next big training run, and XAI has been moving extremely quickly. A hundred and twenty two days for XAI to build its first giant data center in Memphis, Tennessee, Colossus.
Speaker 2:It originally housed a 100,000 NVIDIA GPUs. It was among the world's largest clusters. Just ninety two days later, XAI doubled Colossus' size to 200,000 GPUs and now he's going even bigger. So, good luck to everyone.
Speaker 1:Pulling in capital from everywhere. SpaceX had to get into the round. Quite the party round.
Speaker 2:Yep. It's all over the place. 5,000,000,000 in corporate debt included bonds in loans secured by data centers, which makes sense if you're building something CapEx intensive. You would you would use debt for that. Anyway, in other news, I wanted to talk about Adio, customer relationship magic.
Speaker 2:Adio is the AI native CRM that builds, scales, and grows your company to the next level and get started for free. No. I wanted to talk about Procter and Gamble and the and the idea of this Michelin tires question Yeah. That we have been toying with.
Speaker 1:Been toying with, to be clear, since the original deal and rippling debacle. Yes. Yes. Since the time timeline was in turmoil Yes. Our reaction was that on a long enough time horizon, people will not care Yep.
Speaker 1:That, you know, a payroll provider may have gotten a little too competitive in And the the comp that we discussed was if you went to your mother or a family member and said, hey, I saw you're driving, you know, Bridge Stone tires. Did you know that the CEO of Bridge Stone was actually, you know, spying on on Michelin?
Speaker 2:Yep.
Speaker 1:She would say, that's very sweet, honey. I'll I'll keep that in mind when I when I replace my tires in two years and then probably forget about it immediately.
Speaker 2:And it also relates to the astronomer story where the CEO was caught having an affair at a Coldplay concert. That is something that people were saying he has to go. It reflects poorly on the company. But if you look at, you know, Apache Airflow management, are you going to rip out Astronomer over this, especially when they replace the CEO so quickly? And so this question of like, what is existential?
Speaker 2:What puts you in the FTX category or the Theranos category versus a company that can come back and rebuild from what is controversial? So there's this old story from 02/2001. This is in the New York Times, and I think Fortune broke the story. So I'll I'll kind of give you the high level. So, late on a spring afternoon in April, a red flag memo landed on the desk of Procter and Gamble chairman John Pepper in Cincinnati.
Speaker 2:Internal security investigators had discovered that a handful of employees working with an outside outfit of ex US intelligence officers, I guess, like CIA guys, had been rifling through rubbish bins outside Unilever's offices and posing as market analysts to extract secrets about forthcoming forthcoming shampoo launches. The covert snooping, management learned, had been going on for months under the radar of P and G's famously buttoned down compliance system. The operation, code named The Ranch, by the company's competitive intelligence unit, first took shape in late two thousand when P and G hired Alabama based Phoenix Consulting Group, a firm led by Vietnam era clandestine veterans. So, like, CIA guys in Vietnam come back from the war. They're probably like 50 at this point.
Speaker 2:And they're like, yeah. Let's do some
Speaker 3:Not done corporate
Speaker 2:espionage as a service. So by the time the plot was exposed, the operatives had spirited away roughly 80 internal Unilever documents. So the rival consumer packaged goods company, marketing calendars, packaging mock ups, even margin analyses along with samples lifted straight from the trash dock. So they're literally digging through the trash. And if
Speaker 1:you It's think so about funny to think why this was necessary?
Speaker 2:Oh, it's incredibly valuable. So if you know someone's marketing calendar, you know that they're gonna launch this product on Tuesday. You can launch a competitive product on Monday, steal all the wind from that. Can can you can launch a counter position product. There's so much that you can do.
Speaker 1:Yeah. Know. But
Speaker 2:And margin analysis is really key because if I know that you're selling a product at low margin and I can undercut you, then you're backed into a corner. You can't lower your margin without losing money on that as opposed to if you have a high margin product, I might not want to attack that. There's a whole bunch of different things that you can do if you have good competitive intelligence. And even packaging mock ups, like understanding that, okay, they're going with a bigger size. They're gonna be on this shelf in Walmart.
Speaker 2:We should go and try and lock up Walmart, Overpay to block them out of that slot. Like, there's a lot that you can do with this stuff. So Pepper's Pepper, who is the chairman of Procter and Gamble at the time, his immediate instinct was containment by candor. He dismissed three staffers, seized the files, and telephoned the Unilever co chairman, Neil Fitzgerald, to confess. Within days, P and G couriers arrived at Unilever Chicago headquarters with bankers boxes of paperwork and a pledge that no one who had seen the material would touch hair care strategy again.
Speaker 2:This was an unfortunate incident, Pepper would later say, and we are ensuring the information has not been and will never be used. That might have been the end of it until Fortune magazine landed the scoop on, 08/30/2001 under the headline P and G's dirty little secret. The story which read like corp like a corporate John Le Carre novel who of course does Tinker Tailor Soldier Spy and a bunch of other great spy novels you should definitely read. Detailed dumpster dives, safe houses, and fake business cards, and triggered a global media pile on within a week. The Los Angeles Times, The Guardian, and newspapers from Dublin to Delhi were splashing shampoo spy puns across their business pages.
Speaker 2:Facing a reputational firestorm on the eve of the crucial back to school selling season. I didn't know that that was that big for P and G, but I guess it is. You buy
Speaker 1:Going back to school?
Speaker 2:New shampoo? I guess you need new soap. The two consumer goods goods giant struck a confidential settlement announced '6 09/07/2001. Published reports put the payment at about $10,000,000. More painful for P and G.
Speaker 2:Unilever secured an independent monitor empowered to audit new product timetables and and and the reassignment of any P and G employee tainted by the files. This agreement ensures our confidential information is protected, Unilever's US chief Charles Strauss told reporters pointedly. Regulators never filed criminal charges, dumpster diving on public property skirts US theft statutes, but the incident singed P and G's carefully cultivated Midwestern morals brand. The company rolled out mandatory ethics and competitive intelligence training worldwide, while industry groups tightened codes now that flat out now that flat out ban clandestine trash raids and pretext phone calls. Competitive intelligence textbooks and MBA ethics courses still open.
Speaker 2:Their corporate espionage chapters with the P and G Unilever saga as the moment when lawful information gathering fell head first into the dumpster of public opinion.
Speaker 1:I mean, this probably created a bull market in in paper shredding.
Speaker 2:For sure.
Speaker 1:Right?
Speaker 2:Yeah. Yeah. You don't want you don't want people diving into your dumpster. We gotta shred all of our materials when we're
Speaker 1:doing All of our all of our bags.
Speaker 2:Printed post. Can't find these anywhere on the Internet. More than two decades later, both Pantene and Suave remained grocery aisle staples. Proof that the scandal left no lasting dent in shampoo sales. What endured is the cautionary tale.
Speaker 2:The world's dullest products can tempt even the bluest chip companies into spy novel theatrics. And that in the age in the age old war for market share, the most corrosive thing you can pour over a brand is an arrivals conditioner, but the acid of public embarrassment.
Speaker 1:Very fun. Wild story. Well, we should jump over to Tyler who is at the Tesla diner. He is looking sharp on the ground.
Speaker 5:Can me.
Speaker 2:How you doing? Yeah.
Speaker 5:We can
Speaker 2:hear you.
Speaker 6:Okay. Sweet. Yeah. So I'm I'm here at the the Tesla diner. I'm on the roof.
Speaker 6:We couldn't get through. The line was was, like, extremely long. But up here on the roof, you can see it's kind of like a retro futurist, like very Americana style diner. You know, they have burgers, fries. Like, there's apple pie.
Speaker 6:But here, I can walk around.
Speaker 2:Yeah. Yeah. Sure. Yeah. Heard it's we heard
Speaker 1:it's farm to table too. Is is that is that true? They're they're partnering with local farms?
Speaker 4:It's unclear. I I I would
Speaker 6:have to ask some of the some of the cooks here, but you you can see that these two massive screens they have. Let's see if you guys see this. When they're playing what looks like, I don't know, a reality show or something. There's, like, these massive I think there's 80 Superchargers. Can you guys see this?
Speaker 2:Okay. Yeah. Are they full? People are charging their cars?
Speaker 6:I think they're almost all full. Yeah.
Speaker 2:Okay.
Speaker 6:So so I I think the way it works is you can order from your car if you have a Tesla. If you don't have a Tesla, then you gotta wait in the line. It's like thirty five minutes long probably. Okay. You can see let's see if I can find a a box.
Speaker 6:The the burger come in these little sandwich truck boxes. Let's see if I can pick it up.
Speaker 2:Oh, wow. Very cute.
Speaker 7:Very Yeah.
Speaker 6:And then if I walk over here, there's
Speaker 1:Did you just pick up a random stranger's fox,
Speaker 2:by the way? Do you know that person?
Speaker 6:Julia. Julia. It's Julia. Hey, Julia.
Speaker 2:How are you doing? If I
Speaker 6:walk over here, there's actually a an Optimus robot serving popcorn.
Speaker 2:Okay. Let's see it.
Speaker 1:Let's see here
Speaker 6:if I can walk over. Can you guys see this?
Speaker 2:Oh, wow. Yeah. There you go. Any indication then if this is teleoperated or end to end?
Speaker 6:It's unclear, but there is someone standing right next to it. Okay. Think In case something goes wrong. Security.
Speaker 2:Yeah.
Speaker 6:But, yeah, overall, it's very cool with right on Sunset Boulevard.
Speaker 2:Yeah.
Speaker 1:Okay, Tyler. It's unclear. Give you is good, but Mhmm. We're gonna give you a ramp bump on your Yeah. On your card.
Speaker 1:We're gonna make it so that you guys can start going offering 10 x the retail price of the burger. We gotta get We got You guys have to try a burger.
Speaker 2:Burger arbitrage.
Speaker 1:You can't you can't leave without a burger. So go around and just offer start offering people start bidding on people's burgers right at their tables just say, you for got $10 I'll give you a 100 right now and figure out a out a way to figure out a way to get a burger. You can't leave without a without a taste test.
Speaker 2:No. You should. Yeah. You should wait in line and and talk to people and and and actually try the food. Give us your review at the end of the show.
Speaker 6:Okay. Yeah.
Speaker 2:That'd be great.
Speaker 6:I'll I'll I'll try to find someone.
Speaker 2:Awesome.
Speaker 1:Alright. Awesome. Thanks for checking in.
Speaker 2:Very cool. Do you think this is a like a meaningful business line or a marketing stunt?
Speaker 1:Great marketing activation. Yep. I think that I can see them putting these in tier one cities. Mhmm. I do I mean, the charging stations are interesting.
Speaker 1:Right? Gas gas station convenience stores are great great businesses because you have this cap captive audience. And people that are charging their cars typically have to hang out for quite a bit longer than somebody that's filling up gas for a few minutes. Yep. So I can I can see them having a handful of these or even developing their own kind of convenience store concept over time?
Speaker 2:Yeah. It kind of harkens back to like when the soap companies Unilever P and G going back started like the soap operas to like promote soap. And it's kind of like this adjacent business that actually could grow into something. But there's a big question about like should this also be on the Tesla team's plate to manage and grow a chain of restaurants? It's like a lot of stuff to do.
Speaker 2:Yeah. But it is a very very cool like view into the future. It's a it's a it's a showcase. It feels like the world's fair. That's what it feels like.
Speaker 2:Yeah. It feels like going to a world's fair. Very cool.
Speaker 4:Well
Speaker 1:Well, we have Toly in the restream waiting room. Let's bring him in. Very excited for this conversation. There he is.
Speaker 2:How you doing?
Speaker 1:Welcome. Good to meet you. You are live.
Speaker 2:How you doing? Can you hear us?
Speaker 1:No sound yet.
Speaker 2:Let's let's ping him. Hopefully, bring him in from the restream waiting room. In the meantime, let me tell you about adquick.com. Out of home advertising make Say easy and goodbye to the headaches of out of home advertising. Only Adquick combines technology, out of home expertise and data to enable efficient seamless ad buying across the globe.
Speaker 2:And, if we are ready, we will go back
Speaker 1:We're working on it.
Speaker 2:Anatoli One from Solana. Get the full story. I I'm obsessed with the story of Solana. I made a whole YouTube video about it. Fantastic founder story, really deeply technical.
Speaker 2:I I don't know. It's just a fascinating story and he's been in it for a very long time. So very excited to talk to him about it.
Speaker 1:And he made the careers of a lot of different venture investors.
Speaker 2:For sure. For sure.
Speaker 1:Angel investors.
Speaker 2:Yeah. And just fascinating trade offs and how you design. I mean, I don't know. It just feels like like such a massive challenge to start an l one after Bitcoin, Ethereum are out there. And you're like, I'm gonna do the hardest thing in the world probably, and then I'm gonna make it through some of the most tumultuous markets ever and and kind of be at at peak awareness right during the interest rate rise and massive sell off in crypto, stuck with it, kept building, and is here today to tell us more about the story of Solana.
Speaker 2:So hopefully we can bring him in. We'll see. Okay. In the meantime, we should talk to you about MKBHD. Did you hear this story?
Speaker 2:MKBHD. In 2020, he had a video that he put on YouTube exposing this fake phone, the Escobar Fold. You saw this? I I saw this video when it went out. So it turned out some guy was scamming people by sending phones to influencers, but not to buyers.
Speaker 2:So basically what he would do is he buy a Samsung phone, give it a wrap basically, rebrand it, and then he would sell it and send it to influencers. So if you bought on the website, he would look you up and say, okay, you're an influencer, you're gonna review. I'm gonna send you the actual product. But then anyone else, he would just be like, oh, you're on the backlog. You're delayed.
Speaker 2:So in February or in June, just three months after Marques Brownlee launched that video, the FBI came to his studio and collect his collected his phone as evidence. So MKBHD keeps all the phones that he reviews, and they say, hey, we'll give it back to you. And then five years later, that guy who was scamming people pleaded guilty to fraud. He faces millions of dollars in fines and twenty years in federal prison. So what a crazy story
Speaker 1:wonder how many of these
Speaker 2:citizen journalism.
Speaker 1:Did they figure out how many how many of these fake phones he actually sold?
Speaker 2:I don't know. I mean, I imagine it's if it's millions in fines, he probably sold millions of dollars worth of phones. I it was a very expensive phone because it was it was wrapped in gold foil. And so, it was it was marked up, I believe, pretty heavily or maybe the strategy was to underprice The it or
Speaker 1:CEO said they sold over 50,000 telephones.
Speaker 2:Anyway, let me tell you about public.com investing for those who take it seriously. They got multi asset investing, industry leading yields, and they're trusted by millions. Go to
Speaker 1:public.com to get started. So just to put this into context, that means they did potentially 17 over 17,000,000 in sales of a phone that was never delivered.
Speaker 2:Yes. Yeah. Pretty crazy.
Speaker 1:And this was this was Pablo Escobar's brother?
Speaker 2:I believe he was like riding on the Escobar name and kind of a distant relative which is a funny brand to align with because it's like, trust me, I'm related to a criminal.
Speaker 1:Pablo Escobar
Speaker 2:as well.
Speaker 1:Objectively, is one of the greatest CPG entrepreneurs of all time. Right? Bootstrapped to tens of billions of revenue. Yeah. Empire
Speaker 2:Yeah.
Speaker 1:Just chose a product that happened to not be very legal.
Speaker 2:Yeah. Very rough. Mert from Helios, friend of the show, says in eight hours, Solana blocks will become 20% bigger. Put differently, you can now do more transactions per per second on the Solana blockchain. Very exciting news.
Speaker 2:And, hopefully, we'll be talking to Anatoli in just a few minutes. He is, waiting to come into the show. We are sorting out some audio stuff. In other news, BUCO Capital bloke says the people who create HR slash security slash compliance training videos and platforms without an option to two x video speed should be sent to Bukele's dungeons in El Salvador. I think that's a legal thing.
Speaker 2:Right? Like you can't you
Speaker 1:you should Should be able to do two x speed though.
Speaker 2:Yeah. What's funny is Aaron Aaron x Eckerson Erickson Erickson here says, startup idea. AI agent that watches this stuff for you. Controversial post because people have done that and gotten a lot of trouble. You're If you have to legally watch a security compliance video and you don't watch it and you have a computer do that for you, you can We got him ready.
Speaker 2:Oh, got Antoli. Welcome to the stream. Sorry for the technical difficulties. Great to have you here. Thank you so much for joining.
Speaker 2:How are you?
Speaker 4:Great. Thanks for having me.
Speaker 2:Fantastic. It's
Speaker 1:great to have you.
Speaker 2:I would love to kick off with just a little bit of the State of the Union. I know a little bit of the history, but what is what is how do you tell the story of Solana and what you built? And then I wanna go into the state of the union of all the different projects and all the different applications, and then we can kind of weave through some of those. But could you want kick us off with just a little bit of an introduction?
Speaker 3:Sure.
Speaker 4:So I'm Anatoli. I'm a cofounder of Solana Labs, CEO of and I'm the kind of the the brainchild of the Solana protocol. It's my baby. I started it around 2017, 2018 with the dream of building a high performance blockchain network. So took us about two years to launch it.
Speaker 4:I don't know if folks remember 2020, but we launched right after the double black swan. COVID was just effectively became a thing. S and P dropped 70%. Bitcoin dropped 70%, and our launch date was announced to be three days later.
Speaker 2:That's brutal. So so
Speaker 4:we launched into the abyss, but I think it was, like, a lucky timing, I would say, because we were the only next generation network out. And we're still, I think, processing more transactions than every other major blockchain combined. So not just more than every other one, but more than all of them combined, which is a pretty fun stat to have.
Speaker 2:Yeah. What gave you confidence that you needed to build a new l one? There was a narrative at the time of just like, hey. We have existing networks, big Bitcoin and Ethereum. Let's just speed up those.
Speaker 2:And that feels like I mean, you can even abstract that all the way to, hey. Like, the the the the fiat transfer rails, the the SWIFT system is slow. Let's just speed it up. We don't need an entirely new network. Like, what gave you confidence that you would have, like, an enduring advantage in speed and the other platforms, whether in fiat or crypto, wouldn't just catch up?
Speaker 4:Why do founders do things?
Speaker 2:Think The abstraction. Yeah. That's the question I'm asking. Sorry.
Speaker 4:The the real reason is because I could. I spent most of my career doing high performance, like, optimizations at Qualcomm, so I kinda knew how silicon moves data. Like Yeah. As an act that that's my expertise. And I knew the five to 10 people that I needed to hire, most of them came out of qual Qualcomm, and we were just laser focused on building something that is optimized to, like, its full potential.
Speaker 4:I didn't know if it's gonna like, how it's gonna revolutionize finance or anything like that. We we did have the idea that these systems are useful for trading because if you kinda take a step back and try to look at, like, does it mean to synchronize the state and agree in a ledger globally? It's a similar problem to, like, how Nasdaq or Nilez do price discovery. They're trying to figure out what's the price of an asset given all of this crazy information that's happening around the world that all the market makers and traders are trying to send to their machines or through their trades to to this exchange that's running in in New York or whatever. But with a blockchain and this kind of unique technology that was developed, you know, really, like, over the last two decades on the city of Byzantine fault tolerance and agreeing in a piece of state globally without a trusted third party.
Speaker 4:You can do the same thing, but you don't need to trust neither Nasdaq to do it. So I kinda had the sense that the person purpose of these systems is to do price discovery. I'm not an exchange person. I've never built a financial product before, but I knew how to move data through these systems, how to synchronize them. So we looked at it as a physics problem, and this is how we tackled it.
Speaker 4:And, you know, we thought the things that are gonna take advantage of this would be, like, real financial applications, stocks, all these things. But what happened was NFTs and meme coins were, like, the first big booms. But it's the same technology, the same infrastructure is used for those that you can now leverage for real equities and and real global price discovery without a third party in the middle.
Speaker 2:Yeah. Do you think that the that, like, the I I I see, like, this tech tree developing with all these different applications. And every few years, it check-in with crypto, and there's different there's different narratives, whether it's NFTs and meme coins. Now it's prediction markets and stablecoins. And for a while, there was gaming and metaverse.
Speaker 2:And it feels like the detractors of crypto point to that as like a failure, but I'm not sure that it's any different than what's happening in enterprise SaaS with ideas that get tried and fail or space exploration with ideas that get tried and failed. Do you think there's something, like, fundamentally different about the way the crypto community explores the possibilities and the applications in the tech tree, or do you think it's just done more transparently because everyone can see it, or there's more tension on it because of the financial element? Like, what what do think is going on?
Speaker 4:I think, you know, I grew up in the nineties, so I was there, like, in AL chat rooms and RC chat rooms. And the same kinda, like, almost religious ideas about what the Internet can accomplish were around then. You know, people were arguing about what file system they pick in their Linux kernel configuration. Configuration. Yeah.
Speaker 4:What's religious zeal on forums, like Totally. To the. Right? So I think when you have a technology that has this unforeseen stages that people can imagine could could be unlocked by this, You can almost have this, like, faith based argument to it. The difference now, I think, from the nineties is that we have the Internet.
Speaker 4:Everything is global. So we're seeing the iteration cycles just to be insanely fast. And while, you know, a bunch of people tried a bunch of ideas two cycles ago, that was 2020. And now we we're starting to see those ideas get traction, I think. The fact that there's 250,000,000,000 of stablecoins that have been issued before congress took up legislation is insane.
Speaker 4:Like, there's no way I would have predicted this in 2020. Like, it it's just incomprehensible to me, and it seems like very realistic that we're gonna see over a trillion dollars in Stablecoins by the end of, you know, like, in the next four years. And people telling me that I'm bearish when I say only 1,000,000,000,000.
Speaker 2:Is that is that Stablecoin rollout I I feel like for a long time, the whole idea of, like, Bitcoin was actually in some ways a threat to the US dollar. And now it feels like with the latest White House announcement, like, it's crypto is actually strengthening the dollar in America. Like, it's like what what's actually going on?
Speaker 4:It's like saying that gold is a threat to US dollar. I actually think that's kind of the the wrong way to think about it. I'm not a finance person, but
Speaker 2:Sure.
Speaker 4:I learned through osmosis. So Bitcoin can't function as a US dollar because for you to use something for trades, like trading oil or whatever, need futures, you need a stable denominator to price those futures in. And if you're using Bitcoin, you're have to pay for shorting Bitcoin for the duration of that contract. Imagine taking out a mortgage in Bitcoin and having to pay for thirty year short position on that Bitcoin. Right?
Speaker 4:This is this just doesn't work. Yeah. And two, like, banks can you know, if when when I have, like, an oil field and I wanna buy, you know, whatever, a farm with it, I can use the oil field as collateral. The bank will create dollars up to the value of my collateral to facilitate that transaction. You can't do that with Bitcoin.
Speaker 4:You can't do that with gold, which is why these things don't function as, like, real world trading currencies. But they were great as a store of value, as a hedge against, you know, sovereign events, a whole bunch of other stuff. You know? BAT is managed by people, which is the great part and also the scary part. And gold is not managed by people.
Speaker 4:It's managed by physics. Bitcoin is managed by the rules that create you know, enshrined in this protocol, which are bounded by physics, which is what gives it these really nice properties. But I don't see a world where Bitcoin weakens the US dollar. If anything, the growth in stablecoins has been as a spot vast majority of the growth in stablecoins has been used to support spot markets for Bitcoin.
Speaker 2:Mhmm.
Speaker 4:So when those grow, do you have more stablecoin demand? More treasuries are bought. It's it's actually, if anything, has been working to benefit the US dollar.
Speaker 1:Do you do you think we do you think there's do you see any potential needs for new stablecoins? Obviously, with the new legislation, a lot of people, big institutions seeing dollar signs thinking, well, look how much, you know, look how much Tether's printing, look how much Circle's making. We should get in the game, like but
Speaker 4:They should. Competition is the best way to grow products to iterate quickly. They a 100% should. Right? Like, why wouldn't you?
Speaker 4:This is, I think, you know, a lot of The US finance was built after World War two. But when you look at India and China that has been built after the Internet, their financial infrastructure and rails are just much, much faster and more robust, which is crazy to say that, like, what we consider to be the West, the advanced economies are actually sitting on rails that are were built before the Internet.
Speaker 1:So on that note, what about, you know, the the other side of this is institutions saying we want to you know, let let's say somebody wants to tokenize securities and they think, okay, well if we wanna do this we should we should make our own l two or we should make our own chain. That feels like potentially a distraction from delivering the end value which is, you know, trustless, fast transactions globally.
Speaker 4:So, you know, I'm I have my own horse that I picked obviously, so the goal is Yeah. So not I I
Speaker 1:guess what I'm pushing on is what I what I'm pushing on a little bit is, you know, competition for for you Yeah. You know, or competition But
Speaker 2:not for me. But but at the
Speaker 1:same time, you guys you guys have faced so many competitors over the years. You've launched a new competitive market. Yeah. You're not necessarily afraid of it.
Speaker 4:You know, the worst thing would be for the government to stop innovation.
Speaker 2:Totally.
Speaker 4:Like that. So, like, if those folks think that they can outcompete us by launching an l two, let them try. My goal is to them to show that, like, hey. Everything that you wanna express in those smart contracts running in your l two, you can do it much cheaper and faster on Solana, and you'll actually grow revenues faster without needing all this info. This is what, you know, my pitch to those companies.
Speaker 4:But let them innovate and try. Like, happy to
Speaker 1:help also out. It's a if you if you choose to build on Solana, you just don't have to worry about onboarding developers, you don't have to worry about liquidity, all these things that you would have to really be, would have to be top of mind if you wanna go compete. And potentially, that's just a huge distraction from delivering the end product experience that that
Speaker 4:you want. That's that's the dream. We wanna, you know, we wanna convince people there's no point to build their own private intranets. Just use the one public giant Internet that can host everything.
Speaker 1:What about, what about developer activity? There was, I I I remember during 2021 and 2022, there was billions of of value creation, billions of of of, you know, at least in in USD terms on chain. And there were still, at some point, I remember there was like single digit thousands like true blockchain engineers. How are you sort of tracking developer growth internally?
Speaker 4:I think if you look at the reports that have been published online of developer growth, Solana is the second largest at this point and the fastest growing network. Ethereum is the largest, but I think we've been outpacing in in terms of growth the number of developers onboarded. So like everything else, you kinda we saw in the early days, there was a lot of demand for smart contract developers because there was a lot of innovation to be had in the smart contract plan. But I think given them more as drivers. Like, Windows has excellent drivers, but you don't see innovation or that being a differentiator anymore because there's only so many smart contracts that actually get built.
Speaker 4:A stablecoin is a token. So all the innovation to launch a stablecoin is happening, not on the smart contract space, but the integration with the bank, with how you handle the mint and and withdrawals and that stuff. So a lot of the work has shifted away from l one smart contract development to the higher levels. And this is where I think Solana has really excelled because a lot of the our focus has been on building reusable contracts that actually get deployed once and reused everywhere. There's really only two token standards on Solana.
Speaker 4:It's not an interface. There's one one implementation called SPL token, one implementation called token 22, and everyone uses them. So they've been effectively, through Linde, verified to be correct and bug free. And you as a organization don't have to take smart contract risk when you deploy these.
Speaker 2:Wait. Is there any hope that I I I don't know if there'll be a a new bull market, new smart contract development, but it felt like developing a secure smart contract with super high stakes, You needed an insanely good engineering team, insanely good engineers, hold all this crazy context in their head to understand all the different risk factors.
Speaker 1:You needed to reject 50 North Korean engineers.
Speaker 2:Yeah. It was not something that you just wanted to, like, you know, like hack together on Yeah. The But but I was wondering if, like, the AI code code tools would be an accelerant there. But at the same time, I've heard a lot of stuff about AI code gen tools being, like, kind of falling short when you need a huge context window. You need to hold a bunch of things.
Speaker 2:So, like, is it is smart contract development, like, the last thing that AI will be able to do in terms of code gen, or is it actually an accelerant, but we don't really need it because we have all the smart contracts we need?
Speaker 4:I think the the way that I've seen AI used effectively is augmenting an expert. So you have somebody that has deep expertise Mhmm. That can just do more work. Yeah. And where smart contracts could excel is, like, you're right.
Speaker 4:Where AI can accelerate smart contract development is you built a complicated smart contract. You need to formally verify it.
Speaker 2:Sure.
Speaker 4:The formal verification step is a huge pain for and you need a lot of expertise, but you can automate a lot of the boilerplate in generation. Generation. You have an expert guiding at AI to go do that work. But you still need, I think, your core five or six super really great smart contract engineers that can just accomplish more with that small team using AI tools.
Speaker 2:Did you read anything into the OpenAI and Google News about the IMO gold medal and the use of Lean to do complex math that feels somewhat adjacent? Yeah. Is that relevant
Speaker 4:at been, like you know, I'm you know, I've had fifteen plus years of experience as an engineer. You know, I love be I love being in IC. I love churning out code. But now my workflow is using Claude and o three and SuperHeavy to go validate each other, come up with, like, a robust plan, robust testing plan. And the jump in reasoning abilities just year over year, just from last year, has been astronomical.
Speaker 4:Like, it went from being kind of a, I'm gonna try this as a gimmick to now it's really an embedded part part of my workflow. I can't imagine myself building software without having these tools now.
Speaker 2:Do you think the I still are yeah.
Speaker 4:Yeah. I still don't trust the gen the code that it generates. I think this is where an expert that can have this big context in the in the area of expertise can quickly scan stuff over and guide the tools to go do more testing and and target more more things. You still need those people. But their their reasoning capabilities are getting stronger.
Speaker 2:Yeah.
Speaker 4:It's scary. I don't know. It's like there's kind of five years.
Speaker 2:Yeah. It feels like there's kind of two failure modes in crypto projects. One is technical. There's a bug and someone just drains the wallet or whatever and and and hacks it. Yep.
Speaker 2:And then there's another which is like, economics and people didn't realize that there was no real solid foundation. They kinda wound up with like a Ponzi and it just kind of fails that way.
Speaker 1:Well, then there's the other I mean, social engineering is the other big one. Sure.
Speaker 2:Sure. And I'm wondering, do you think that these reasoning models are are getting close to superhuman, close to, you know, amazing at at economic reasoning?
Speaker 4:Yeah. You're you're right to point at that as being a really hard problem because this is where an x you really need to have that expert that can understand the economic attacks to guide these tools to go build a simulation and actually test it. Yeah. And I wouldn't trust myself to be able to go find those given all these tools. Even if I'm aware of the problems, me just asking, o three, give me all the top 10 economic attacks and then simulate them.
Speaker 4:That's the best I can do, and it's gonna suck. Like, I can already tell you. Like, it's gonna it's gonna do maybe as good of a job as, like, a new grad. Right? But, like, I I think you really need to have an economic expert guide.
Speaker 4:They'll still similarly, like, that economic expert, if they ask all three to go generate a bunch of bug free code, I'm gonna go look at it and find a bunch of bugs. So I think you still need people in the loop there. Don't know what happens in five years given the the pace of progress of AI. Yeah. But it's remarkable of of how good that is, but but you still need people
Speaker 2:Yeah.
Speaker 4:For now. Jordy?
Speaker 1:You guys have been, really good at at at at kind of building brand through short strings of words. So Internet Capital Markets, you know, the team has really rallied around that. It's it you hear it, it makes sense and and you can think about all the ways that that evolves. With that phrase, Internet capital markets, what are you excited about on a one year timeline and and maybe what are you excited about on like a five year timeline?
Speaker 4:I think getting fully approved, regulated, boring, tradfy stuff on chain that has plans on future cash flows, like all that stuff that you read in the intelligent investor. Yeah. Having those things be tokens, I think, is really, really important, and this is kind of my dream for Internet capital markets. Getting all the you know, jumping through all the regulatory hoops, crossing out all the t's and dotting the i's, making sure that's as as compliant as the government wants it to be and, like, minimizes fraud. Because I think once you have those assets on chain, you can then use the best of DeFi, which is the purpose of it is to create transparency, right, and to run the risk engine every four hundred milliseconds instead of once a week or whatever happens in a day.
Speaker 4:Always know exactly what are the positions at risk, what collateral that particular contract is managing so everyone can see the actual risks involved, and you you don't end up with the kind of, you know, tail end failures that you see in traditional finance. That's the beauty of it. But we need real assets to do that because if you do that with just meme coins, it they don't have any value because of price. And eventually, that just doesn't work. All the risks are correlated, and and you end up with the tail amounts.
Speaker 4:That's to me the short term. The five year kinda, like, dream for me is I would want, like, a startup founder that know you know, wants to do this on their own to be able to take all this open source software and to run their own IPO, which means, you know, do all the disclosures, do the price discovery on chain, do use everything in a immutable open source smart contract, and kinda do the Linux from scratch IPO and have the SEC approve it. And that doesn't mean that every founder is gonna do that. You're gonna have a bunch of services spring up on top of it that can take advantage of all this technology, but you should see the fees of doing that basically compressed down to the actual value that they provide and no longer kinda be based on their ability to control the markets or their regulatory capture and stuff like that.
Speaker 2:Yeah. Makes more sense.
Speaker 1:Last question from my side. How how did you were were you conscious of trying to make Solana Lindy in the early days? Because I know it was like, you know, like any crypto project, was the price, you know, massive amount of volatility and then you go through these periods of insane activity. And and I think we've seen this with various companies at the product level, know, OpenAI, Pump, Pump Fun, Acxiom is the other one that's like done what, like a 170,000,000 of revenue in the last in like six months or or something Sure. Something crazy like that.
Speaker 1:And anytime you see these like massive spikes in activity or revenue, the question is like how sustainable is it? And you guys were able to kind of like navigate through the volatility and get to a point where I think everybody would have real conviction that Solana will have more activity a year from today, five five years, ten years, etcetera. But I feel like that's the number, for for crypto founders out there. It's like, how do you go from, you know, massive activity to being, durable and sort of Lindy?
Speaker 4:I don't know.
Speaker 2:It's a great answer.
Speaker 1:It's somewhat like fundamental to the technology that that when you reduce friction, when you make finance frictionless Yeah. That reduces moats.
Speaker 2:Yeah. Right?
Speaker 1:Makes it so that the things can leave as fast as they come.
Speaker 4:Yeah. I can rationally give you all those arguments, but the reality is that, like, you're just worried about surviving the next eight weeks. This is how we've operated from that launch because we simply didn't have any other option. We were, you know, we had limited runway, you know, up until, you know, for the first three, four years. And trying to get as many developers onboarded, trying to increase the bandwidth of the network, reliability, all this stuff, you're just thinking in eight week terms.
Speaker 4:And, you know, like, you read every, you know, book on startups and stuff. That's actually what you're supposed to do. You're incrementally fighting for life. Yep. And, hopefully, all those all those sprints, all those efforts, all those impulses accumulate into something sustainable.
Speaker 4:And I think we're we're starting to see that sustainability actually play out through, you know, the last cycle. But it's really hard to predict. Like, if I knew what was gonna be really important twelve months, you know, I I don't think I'd need to work.
Speaker 2:That's right. Can you place
Speaker 1:your bets?
Speaker 2:Can you give me the update on, just the the progress of decentralization, what's important to decentralize, how you increase decentralization. I remember when in maybe 2022, there was this critique, Solana is not as decentralized as the other platforms. Just judging by the performance of the company, feels like that was not a a bear case that stuck around. But but what's actually happened with the company? What plans did you put in place?
Speaker 2:And and what have you what do you feel like you've executed on properly to like, kind of satisfy the level of market demand for decentralization? Because I know that there's trade offs here.
Speaker 4:I mean, I look at it as a kind of key product, like, feature of the of the network. I'm a I grew up in the nineties. I loved Linux. This is how I learned how to code. It's hacking through Linux code.
Speaker 4:Huge believer of open source. Every part of the network, you can participate permissionlessly. This is kind of the the key part. And to me, that's really important because when you think about disrupting finance, if you disrupt settlement, you've disrupted DTCC. Like, I don't I don't you know, the number of people that can even know that what that company does Yeah.
Speaker 4:Like, you can fit them all in one elevator. But everyone can name the exchanges, the brokerages that they use, and this is where all the money is made in finance. Mhmm. So if you cannot per permission to participate in the formation of of order and price discovery, I think you haven't really just decentralized the important part of of finance. Mhmm.
Speaker 4:So Solana has always been about decentralizing how blocks are made, how transactions are ordered, the sequencer, which is in contrast to, I think, a lot of the direction that Ethereum wants where they have done an amazing job decentralizing settlement, but they've offloaded all the work of actually running the financial applications to layer twos where you now have, like, a single sequencer that runs the vast majority of layer twos. And that sequencer has the same functionality that Robinhood does or right? So to me, you haven't really decentralized the important interesting part where money is made or revenues are made. So from my perspective, Solana has been more decentralized than a lot of the networks where it counts over the last three years. Where we have taken a trade off is that the cost to run Solana validator is higher because you we are focusing on increasing throughput, making sure that anyone can participate in being a block producer and ordering transactions and all those stuff.
Speaker 4:The cost of those validators is higher. But over the last four years, we haven't had to increase the the costs around the boxes because of the software perform performance improvements.
Speaker 2:Mhmm.
Speaker 4:So if you actually look at the network, how it's run, how it's operated, I can't fire anyone that actually works on it. Like, Labs doesn't actually employ anyone that builds the protocol anymore. We're primarily focused on building a phone.
Speaker 2:Yeah. Yeah. That makes sense.
Speaker 1:I wish we had time to talk about the phone, but we'll have to have you back on Yeah. Again very soon.
Speaker 2:This is great. Thank you so much for joining. Really enjoyed this.
Speaker 1:Yeah. Appreciate it.
Speaker 4:We'll talk Thank you, guys.
Speaker 2:Have a
Speaker 1:good Bye.
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Speaker 6:So I I think it's solid. It's very similar to Shake Shack, I would say.
Speaker 2:Okay.
Speaker 6:Security. Am I gonna be going here? Is this my go to burger? Probably not.
Speaker 2:Okay.
Speaker 6:You know, I I'm more of an in and out kind of guy. I'm not very, you know, wealthy, so I gotta go cheaper sometimes.
Speaker 1:I know. Yeah.
Speaker 6:But but there's, you know, there's some cool stuff. So, apparently, the fries and the hash browns are beef tallow. Okay. Wow.
Speaker 2:Let's give
Speaker 1:it up for tallow. Very good. Generational run.
Speaker 6:So, yeah, definitely appeal there. Apparently, they're really good. I think I showed you guys this earlier, but there's, like, the little boxes. Right? Yeah.
Speaker 6:Yeah. Yeah. Cute.
Speaker 2:Are there any protests going on? Is this a controversial space? I I
Speaker 6:have I not seen any protests actually surprisingly.
Speaker 2:Seems like
Speaker 1:you need to announce some burgers. Grok integrations.
Speaker 2:Oh, yeah. Any any grok integration.
Speaker 6:I I the only AI I've seen here is the Optimist.
Speaker 2:Talk to me about the actual ordering experience. Did you order from a tablet? Did you order from a human? So
Speaker 6:yeah. I I think we ordered from a human. It was like totally normal. There was no kiosk or anything. But you can order from your Tesla.
Speaker 6:Oh, try that. Yeah. Because I think we we, you know, we had to kind of expedite the process. Yeah. But apparently, you can do that.
Speaker 6:But, yeah, honestly, I would like to see the more it's more optimistic this year. Just doing popcorn, you know, it's not super hard to do, but, I know there's, a nice bar over here.
Speaker 1:Yeah. You gotta start somewhere.
Speaker 2:Yeah. I can see it. Popcorn's hurting.
Speaker 6:Yeah. Overall, pretty good though. I'm just I'm not sure how to come back. Okay. Just, like, specifically for the burger.
Speaker 2:For the burger.
Speaker 5:But it's definitely a pull For
Speaker 1:a charge? For a charge, though?
Speaker 2:If you need to charge I wonder if the charging's free if you get the if you get the burger.
Speaker 6:I think the charging is free.
Speaker 2:Okay. That makes sense.
Speaker 5:That'll be
Speaker 6:a big drop. Yeah.
Speaker 2:That's very exciting.
Speaker 6:But, yeah, there's, 80 cars here. But, yeah, overall, solid experience.
Speaker 1:Very cool. Very cool. Alright. Well, enjoy your burgers and we'll see you back in the studio.
Speaker 2:See you back in the studio, Tyler. Thanks for joining on the ground reporting.
Speaker 1:Awesome. Well, next up, I believe we have Aaron from Box in the restream waiting room. So we can bring him in when he's ready.
Speaker 2:And in the meantime, I'll tell you about Aaron Levy from Box. Welcome to the stream. I was getting near a hard dream but you are here live. Thanks for hopping on. How are you doing?
Speaker 3:Hey. Good. How are guys doing?
Speaker 2:It's good. Been too long. It's been a month something. Yo. You were one of our first guests.
Speaker 2:Couple months.
Speaker 7:Wow. Mean, I'll take all the credit for your guys' success.
Speaker 1:You go. Take it. It.
Speaker 2:I I wanna talk about I wanna talk about AI, obviously. I wanna talk about Quickly, I mean, let's start with the consumer side and then I wanna go into into enterprise. Did you have a chance to read Fiji Simo's outline of where OpenAI is going in consumer kind of six categories, health, knowledge retrieval, creativity. What are you using personally? What's your daily driver?
Speaker 2:Are you using it with your family? Have you used it for health? What's just been your general experience with consumer AI?
Speaker 7:I think I've hit every every one of those use cases. It's I mean, it's yeah. Therapist, doctor Okay. Branding assistance.
Speaker 2:What about executive coach? I thought that was an interesting one. She says that she has a coach. Obviously, you're at a level where you can afford a full time human coach, but what what what what goes into a good coaching experience at the executive level?
Speaker 7:Yeah. I mean, that that's a fantastic use case. Probably, actually, I should be using it for that.
Speaker 1:I'm sure
Speaker 7:anybody that works with me wishes I did. But, you know, often you're you're bringing a coach a a set of problems that you're running into. I've got this org design issue. I've got these Sure. You know, people that that aren't collaborating well.
Speaker 7:And oftentimes, it's it's most actually just helpful just the purpose of talking about the issue and then and then laying it out that gets you thinking about it. So and then seeing a set of of options. So I I think Chadjubiti would obviously make a fantastic coach for that because just the very active of just getting you to to be able to describe the the issue and then, you know, seeing a set of options would would, you know, be helpful in, like, 90% of situations. So I think those those use cases are great. I mean, the health care stuff alone has been has been extremely powerful.
Speaker 7:I seem to, like, run into, like, one new ailment per week.
Speaker 4:No. And so I'm
Speaker 7:just like and I used to just I I I I used to go into urgent care, like, way too frequently.
Speaker 2:That's brutal.
Speaker 7:Like like, oh, I I have some, like, sensitivity in my finger, and then I'd, like, go to urgent care. And so now just Chatchubiti just solves all
Speaker 2:those You are a hypochondriac. Anyway, on the on the org structure issue, like what you would go to an executive coach about. Do you feel like AI should be more of like a product team or more of like a service team? Like, do you see it like it's my infrastructure organization or it's my front end engineering packages versus it is a new product that will sit alongside other products and maybe be sold as a different SKU by the sales team? Because I've been going back and forth on this, but I'd love your take before I kind of wrestle with it.
Speaker 7:And is this in a b to b context?
Speaker 2:Or Yeah. Yeah. In your business. Like, I imagine that you're you're thinking right now there are there are LLMs, there are tools, there are APIs, there's a whole bunch of stuff. There's, you know, coding agents and and IDEs and stuff.
Speaker 2:And you wanna get this stuff into the hands of everyone in your organization. Yep. The question is is do you do I bet a lot of companies I imagine are thinking about like do we need an AI organization?
Speaker 6:Yes. Do we
Speaker 2:need an AI product? Yes. And you can think about you know, like Salesforce is launching like in Copilot is like a separate SKU almost. It sits alongside Gemini is a separate subscription. It's a separate product, separate app versus just, hey, We do x, y, and z, and all of that is made better by AI in the same way that, you know, memory caching, like Redis, the database made things better across everything, but it was not its own product.
Speaker 7:Yeah. I think in our case, and I think it so much depends on the type of product that you're you're you were in before AI happened.
Speaker 2:Yeah. Totally.
Speaker 7:In our case, what what what we did was, our chat to be team moment was, you know, same time as everybody else, but we did, you know, fortunately step back and we said, okay. If we were to found our company, in a post AI world, how would we how would we treat the very kind of business model, the the product experience, the actual value proposition? And we we started kinda laying that foundation. Now it took at least a year and a half to, like, execute in the way that that even looked like what what what you could do from a from a blank sheet of paper. But the idea was if we were to start Box in 2025, let's say we we we ran this exercise now, you know, we wouldn't think about the AI version and the not AI version.
Speaker 7:We wouldn't be like, you go over here to do AI, and everything else is sort of, like, dumb. And so we decided to bake AI into the core value proposition of the product, and that shows up in the in the kind of obvious ways you'd expect. So but you talk to your data, ask questions of documents, take a collection of content, and be able to query it and ask questions of it. And then now with in a world of agents, that's also showing up as, you know, agents being able to kind of run around and execute automated tasks for you. So a very natural one for us is a lot of customers have all of this unstructured data.
Speaker 7:It could be contracts or invoices or marketing assets, and they wanna be able to read what's in that data, and then, basically apply structure to unstructured content. So Mhmm. Take all of the variables from a contractor, from an invoice, or from a a digital asset, and then let me have effectively intelligence around that. I can ask any question of of that data now. I can automate any workflow around it.
Speaker 7:I could have a dashboard that shows me exactly when the different contracts are up for, for renewal or which ones have risky clauses in them. And so this is fundamentally changing the entire value proposition of our product. It it gets us more in line with what, you know, our holy grail was to begin with, which is, like, let you tap into all of this information that you have in the enterprise. But but yeah. So this is built directly into the core fabric of the platform.
Speaker 7:And most product managers at Box at this point are working on something AI related. There's there's sort of nobody that is is unaffected by, by AI at this point.
Speaker 2:How do you think about AI surfacing itself in the product in a, I don't know, like above the UI or below the UI? I I don't know. Front end or back end? Basically like like I feel like I love when a company I use is saying, hey, we're going all in on AI, but I don't necessarily want a chat box with every product. What I want is, hey, you guys did the hard work.
Speaker 2:You guys did the prompting and all of a sudden search just got better or or I, you know, if I want to just click a button and see it as a CSV, boom, it's there. Or it's already or, you know, it's already been transformed. It's already in a database. It's already built for me instead of me having to actually say that. But it's really hard to define those things.
Speaker 2:So how do you think about like is is this going to be the prompt is in the hands of the user or the prompt lives within the Box engineering team?
Speaker 7:Yep. You know, it's entirely case by case probably across all of software. Yeah. Even in our product, we have variants of both of those. So we have a a a product or experience where you can chat with your documents, which just means it's another, you know, chat box.
Speaker 2:Yep.
Speaker 7:We have a product that is, for all intents and purposes, you never have to even think about it as AI. It's data extraction from a document. You press the you know, extract data. You don't chat with it. And then and then the agent is, you know, a set of context, a set of tools, that that we've we've effectively tuned to that workflow.
Speaker 7:Yeah. But you don't have to think about it as being AI or not. And, it's not obvious which one wins out. I think there's a variety of of ways that people will expect to use, you know, these use cases. The the thing I'm probably most fascinated with and the thing that will have the most, you know, GDP impact is, effectively these background agent use cases.
Speaker 7:You know, when when when AI first started, you know, emerging, you know, really just due to ChatGPT, we we thought about AI as, okay, I go into a prompt window and ask a question, get an answer back. Or maybe, you know, a year prior to that, you had GitHub Copilot, which was really kind of type ahead prediction functionality. In both of those cases, the AI can only work as fast as you can. And so that means that our productivity gain was still capped by, like, how fast we could work. With background agents, you're now like, there's no there's no you're untethered in terms of the the ultimate upside of of the amount of of productivity gain because it it's just you know, if you have a well described prompt that could, you know, basically translate, you know, days or weeks worth of work into a couple minutes for the agent, then then that's, you know, obviously, like, that could be a 100 x productivity gain.
Speaker 7:And so we have a a number of features we're working on that more relate to background agent type type use cases, and that's that's, I think, where what's most exciting. So when you think about Cursor's background agent or you think about Codex, or what Replit does with its agent, that's that's way more of the future. And, and and that's, you know, probably more of what we're we're putting our efforts into.
Speaker 2:Yeah. I feel like it's like it's less flashy and it doesn't get as much attention for some reason but and it's harder. It's harder to make AI just a button and it works but when it when it when somebody can boil that down to click button, get result, like, it's just that's the original magic of software and and and I
Speaker 7:think I well, well, I but but I, you know, I think it's it's still probably click button but give some instructions to get what you But it's not as open ended as it was before which is just here's an empty chat box, do anything in the world. Yeah. And this will be an interesting, you know, tension between the, let's say, the most horizontal frontier players versus the applied more vertical specific use cases. The vertical players and and it could be industry vertical or or or some other kind of vertically integrated product. The the vertical or domain specific players will will be able to prepack in the use case.
Speaker 7:And that will actually be in for many enterprises, the the easier to adopt capability. And instead of, like, the super horizontal, we can do everything super intelligence, understanding the use case in the domain will likely improve the efficacy and ability to drive the the rollout within the enterprise.
Speaker 1:Yeah. Drew How are you thinking about Box as a is it a is it a garden that you welcome people to? Is it a walled garden? You guys are Is it building
Speaker 2:my data? Would you be okay with me taking my data data and share it
Speaker 1:with you? Well, yeah. It's just like you guys are you guys are building a bunch of workflows on top of your data but then I imagine you have you you're happy to in some cases let other companies come in and make the data more valuable.
Speaker 2:What's your stance on letting the fox in the hen house? We've been going back and forth on that. Sometimes people say, it's a friendly fox. Let it in the hen house. Let it in the hen house.
Speaker 7:We're Yeah. We're we're a public park. Yeah. Any anybody can can can build their garden here.
Speaker 2:That's great. We
Speaker 7:no. I mean, I I I I I don't wanna read between the lines too much, but I assume this is about some of the closed off data access, you know, pipe Yeah.
Speaker 2:Data walls.
Speaker 5:Yeah. Yeah.
Speaker 7:Tricky topic. So for us, I'll I'll just say our general biases, well, so first first of all, to be unbelievably clear, any any data within Box is our customer's data. So Yeah. So just, you know, get get that out of the way early. And in general, we bias toward a very heavy degree of API access into that data.
Speaker 7:Cool. There's a couple, kind of complicated issues that are the emerging topics in agent in the agent world, and this is obviously, you know, probably germane to to the origin of the of the question. There are some systems that do these kind of heavy indexing of of data tasks. And in those areas, you have a couple issues. One, you just have a cost that the that the, you know, kind of originating vendor then incurs, based on that indexing.
Speaker 7:But then also you have these open questions around security and permissions and data governance because you're trying to keep permission models in sync between multiple systems. And so all of a sudden, the brand promise of one platform can possibly be sort of mutated by another platform if there's a data leak event or whatnot because your data was indexed by that other other system. So these are gonna be more I'd I'd I'd consider them more open questions that that need to be figured out by the industry. I'm I'm more a fan of this idea that you'll have any system that today sort of wants to index all of the information from another platform. A sort of more ideal architecture would be that that that that system just talks to the the system with all the data and says, hey.
Speaker 7:I'm looking for this particular piece of information. You know, can your agent go run off and find that for me? And then and then pull that into that other agent. So, the problem is is that everybody's agents today operate differently. We all rank the information differently.
Speaker 7:There's different latency. So so that's why you kind of need indexing right now. Yeah. But I think in five years from now, it I would be I I think it would be a little bit of a architectural anomaly if if you had to index all information, like, 20 times across the Internet. I I that that seems like that would be very inefficient.
Speaker 7:And then it would lead to lots of security vulnerabilities. Because let's say, I share a set of documents or a a communication channel with you, and then that gets indexed by some AI agent system, but then I un that with you, how quickly does that propagate to the agent system that that was indexing that data? And now we have a security risk that that that that first system has no control over. So these are the the very real kind of issues that you run into an enterprise software, which is why I also think that you're just gonna continue to see so much power in the systems of record, yeah, even in a world of AI agents.
Speaker 2:I have two questions.
Speaker 1:When you, speak speaking of AI agents specifically, there's billions of dollars being poured into roll ups to acquire maybe more kind of main street style businesses. Let's say an accounting firm and the promise there is basically that we're gonna that that the investor groups gonna be able to and and operator is gonna be able to dramatically reduce head count and increase the earnings potential of the business. Do you think that there's enough excitement around agents and agentic workflows that these companies have been able to raise billions of dollars? Do you think that agents are already at a point where they're gonna be able to kind of deliver on that on that thesis or will companies like There's two paths. Like companies can leverage off the shelf agents.
Speaker 1:Maybe Yeah. Coding agents for example. Or they can build their own agents or or or workflows. But how how how ready are these businesses to be able to strip out, let's say, like 50% of of headcount?
Speaker 7:I think that depends on on do you wanna grow revenue or are you fine with the existing install base of that company and and then, you know, likely some kind of terminal value that that you can extract out of that. There's no question you you could cost you you could cut costs with with AI agents in a number of spaces. But, you know, if you had a very competitive industry where the product road map really mattered, I you know, I think you'd probably be more in the camp of using AI agents to accelerate the the work that you're doing as opposed to cutting cutting headcount. So I think it all depends on the space. I haven't I haven't, picked up on which industry people are most attracted to.
Speaker 7:Is it, like, health care, office, you know, back office firms? Is it is it law firms? Is it accounting firms? I think it'd be hard. You'd have to be really running a business very inefficiently if you could cut cut 50% of the cost with AI and then and then keep the business sort of maintaining its customer base.
Speaker 7:But, you know, private equity has found those opportunities in the past. So I I I I think it's a just a more it's the evolutionary kind of update to to probably how private equity will will will think about some of these efficiency gains. And it has a place in the economy. It's not something that is sort of, to me, the most exciting part of AI. But it could work, it could produce some degree of profit.
Speaker 2:Yeah. Makes sense. Have a friend who is running a startup and recently a hyperscaler launched a competitor. What advice would you give him for competing with someone that basically has unlimited resources and how do you think about getting through that as an entrepreneur? It must be an emotional roller coaster.
Speaker 2:We've talked to him a little bit and I've been thinking about different case studies and models and companies that have made it through and it's fascinating. But what what what would you what would you say to a founder in that space? Well capitalized, products loved but now facing fierce competition from hyperscaler.
Speaker 7:I think there's a therapist mode in Chatcha BT that apparently that you can trigger. So so sorry, is this like a known company? Can you say the company or not?
Speaker 2:Yeah. Browserbase. We we've been talking about on the show for a while. Okay. Okay.
Speaker 2:It's a computer use agent Yeah. Or it helps you, yeah, if you have an agent that needs to go browse the web. It's an API that lets you harness the computer and actually go click on things and AWS launched something and obviously that's competitive and it's something that we had him on the show a couple times. We asked, hey, this feels like something that AWS might launch. They wound up doing it.
Speaker 2:Yeah. You know, like what would your advice be to him, I guess?
Speaker 7:Yeah. So so I think actually the the first of all, the if you somebody maybe you guys could do do have like an analyst team yet? Does that does that exist?
Speaker 2:It's coming. It's coming together. We have some interns.
Speaker 7:I I think you should
Speaker 1:Deep research. Yeah. If you if you
Speaker 7:could run some analysis, I bet you in in, you know, the history of hyperscalers launching a competing capability and then you look at that that market, I bet in all cases sorry. Not in all case, but but on average, the market size kinda grows for even the independent players. I mean, think about how many times Snowflake or Databricks probably shouldn't exist based on, you know, some of the the the data sis you know, services of of the hyperscalers or, you know, Cloudflare for Matthew, you know, for probably, like, ten years running would show the market share graph of Cloudflare versus all of the other CDNs. And, you know, you would have been like, why would Amazon or Google not wipe out Cloudflare? It's like, they already have the network.
Speaker 7:It's not that hard. In fact, in many cases, Cloudflare probably runs on their networks.
Speaker 2:Yep.
Speaker 7:And yet it turns out that, like, hyperfocused teams and platforms in big markets, you know, are usually able to carve out enough enough of the space, because you're just gonna be just more wired into the customer base, the use cases, the better APIs. You're gonna, you know, jump on the next, you know, trend more quickly. In the case of Amazon, you know, I'm guessing that Amazon won't work as well with OpenAI where browser based can work with with all of the model providers. So there there tends to be, you know, with very few exceptions, plenty of of of sort of moves that you can make in these kinds of competitive situations. And in a lot of cases, it just actually, you know, again, lifts up the awareness of the market, makes it more exciting.
Speaker 7:You tend to not wanna be a market in a market by yourself, unless you're like NVIDIA or something. Like, for the most part, having, you you know, being in a dynamic market where people are comparing options and looking at SDKs and choosing things and talking about stuff, that usually actually grows the market as opposed to, you know, makes it make makes it more zero sum. So, so I would I would be I would be bullish in that, in that scenario more than anything.
Speaker 2:So Do you do you think, like, ten, fifteen years ago, you or the or, you know, the chattering class was saying that about cloud storage broadly?
Speaker 7:Oh, saying that we would be crushed?
Speaker 2:Yeah. Saying that you would be crushed, or did anyone clock it correctly? Because what actually happened was not, you know, oh, so one wins, one doesn't, one in Yeah. Like, there's multiple independent companies that are doing well. There's also hyperscalers that have That, like, it it's been this weird, like, oligopolistic positive sum market.
Speaker 2:It's been fantastic for all parties involved, basically.
Speaker 7:Yeah. No. No. Nobody nobody got it right. I mean, our our first, our our our first funding round was I think our valuation was, $240,000.
Speaker 7:That's good.
Speaker 2:I tip it on for that. Congratulations.
Speaker 7:So, so, I mean, basically, the idea was, like, storage was a commodity, but what people didn't realize was, no. It's the software above the storage that matters. And so so assuming that you're in a a market that is gonna grow again, zero some markets are very different, but there's it's hard to find zero some markets in software right now
Speaker 2:Yeah.
Speaker 7:At least you're, like, deeply legacy. Yeah. If you're if you're in a fast growing market, there's usually a move. There's there's usually some some range of motion you have to differentiate, to specialize, to go into a vertical, to build more software on top of the the commodity infrastructure. So I'm I think we're in a period right now where you can kind of be generically bullish on on just, like, categories broadly.
Speaker 7:Now maybe we don't need the twentieth, you know, kinda language model. You know, that that that is there's some asterisk to this. But if you're if you're one or two in a category right now and and a big player enters, I I think you just ride it out because because it's just too early at the moment, on what's, what's happening.
Speaker 2:Yeah. Yeah. It seems like a wildly different market dynamic in, in the enterprise in b to b than in b to c, where it's very much winner take all. And if you gave me a $100,000,000 to start a competitor, direct competitor ChatGPT
Speaker 6:Couldn't.
Speaker 2:No. Yeah. Yeah. It doesn't it just doesn't matter at this point because there's so much energy and aggregation and and network effects and all sorts of things. Anyway Yeah.
Speaker 7:Sorry. And and yet at the same time, I'd say every vertical in the enterprise is up for grabs. Yeah. I I think there's I I think there's no vertical where you can just completely call a winner. I I think there's some cases, maybe these, like, health care providers that that do transcription and and, like, maybe you can call a winner in that space.
Speaker 7:Yeah. But for the most part, you know, when I talk to CIOs, they're they're in their very earliest phases of of picking their first set of platforms for these major use cases. Yeah. And so we have a window right now where you'll have many, many names that emerge that will be, you know, a 100 times bigger in in five years from now.
Speaker 2:Totally. Yeah. And to the earlier point we were talking about where like AI can be not just a new product for a company that's existing, but just little improvements to everything that exists and that winds up being a bunch of different vendors, bunch of different internal projects, a bunch of different APIs, a bunch of different code revisions. There's so many different areas to just squeeze out percentages of of improvements. Exciting Last
Speaker 1:question I have. You've seen a number of different cycles. You started the company in 02/2005. So you've you've
Speaker 7:I I I do look I do look that tired.
Speaker 1:Yes. That's where he's going. But but I'm curious we we were joking about a week ago that there's a lot. I mean there's so many different like signals blaring that that obviously, there's a lot of excitement, a lot of new capability coming online, new intelligence being birthed. At the same time, we have Ethereum treasuries and specs for companies that maybe should be specked.
Speaker 1:NFT profile pictures coming back. How do you I'm not asking you to like call the top or call the bottom or anything but but do you have do you have any type of of outlook? Do you have any kind of concerns about about how overheated things could be right now?
Speaker 7:Weirdly, I'm I'm I'm pretty I tend to be pretty much on the conservative side in general, and it's lost me lots of money by by just, you know, not believing in, like, 80% of things that have worked out. Yeah. But for AI and then maybe this is a counter signal, actually. So maybe this is like the Jim Kramer effect.
Speaker 6:But but,
Speaker 7:in AI, I I I don't think we have reached anything close to, close to any any peak of anything. Now, sure, you might be able to point to specific categories that are that are a little inflated. But when you look at I mean, this isn't this is a an an an economy altering, technology. And if you just look at it as any percentage of labor, you know, as as as one way to to model the the potential size of these markets, we're in still the very earliest phase of of what this looks like.
Speaker 1:Any Yeah. In in 1999, if you were like, you know, these these Internet companies are are really potentially overvalued. Yeah. You maybe looked smart for a little bit, but it but over a decade, you looked pretty pretty dumb.
Speaker 7:But but if you even took '99, business if you took '9 if you did a '99, you know, kind of like, extrapolation from any of these valuations, OpenAI would probably be worth 5,000,000,000,000. Like like, these are not I mean, if you look at, like like, the those companies were valued on, you know, 100, 200, 300 x revenue Yep. For the mature companies. So that that like, we are not even in 99 territory on the amount of of of kind of, you know, hype and excitement that there is. So I I'm pretty I'm pretty bullish on on where things go from here.
Speaker 7:You know, if you look at something like the enterprise software market, it's a few $100,000,000,000 market in in just, like, let's say, The US in total spend on enterprise software. There's there's no reason why this isn't a doubling or tripling even in the conservative scenarios Yeah. When you can have AI agents go and do real work that is tied to the software, because you just have so many more categories that that the enterprise software can sell into. And there's just examples everywhere. Like, the the the enterprise software size, the category size of enterprise software for the legal industry, like, five years ago was about a couple billion dollars max.
Speaker 7:Like, that is all that that the legal industry spent on enterprise software. And in a world of AI agents, I I think you could easily underwrite $10.20, $30,000,000,000 being spent on on just AI agent automated work in the legal space. So you could have a lot of these spaces that become five or 10 times larger, than they were in the pre AI era. And, and I think you could do that across every category of of of knowledge work for the most part.
Speaker 1:Makes total sense. How, last question I have is how tolerant do you think CIOs and and executives broadly are going to be of the like, you know, if you're thinking about, know, Apple for example, thinking about implementing an LLM, it's not an app Apple's nature to have imperfection. Right? Like they're not looking for something that even one out of a thousand times is gonna say something that's offensive or or anything like that. And we were think, you know, we were talking about Grok.
Speaker 1:Grok obviously, is on a wild trajectory. They're closing, you know, they closed a massive partnership with the with the DOD, last week and that's partly I imagine like the Elon effect but how how tolerant do you think CIOs will be of just the kind of inconsistent nature of AI agents, know, being saying we're gonna make a big bet on a on a lab though even though one out of yeah, one out of 10,000 times Yeah. It's gonna say probabilistic computing And is and one out of every 10,000 times use the product it might say something that ten years ago you would have been fired for if
Speaker 4:you Right. You
Speaker 7:well, you can't, like, make Hitler jokes in, a company, setting. So so the, you know, I I would say increasingly the tolerance is going up because be because the understanding and the shared understanding of what these models are doing is is going up. And so what's happening is is companies are putting in sort of, you know, kind of informal or formal guardrails on the fact that these models are are probabilistic. And and that will that will sometimes take the form of just an internal policy that says, okay. You know, the AI agent is gonna give you your first draft, but your job and your responsibility and your liability is to ensure that what you're putting into production or the legal brief that you're writing or the marketing asset that you're creating is fully reviewed by a human.
Speaker 7:And that that is this the switch from, you know, maybe two years ago, we would have looked at a model's kind of inaccuracy as a flaw in the AI, and now we have sort of accepted that it's just a part of the workflow. Yeah. I I walked by, you know, an engineer's desk a couple weeks ago, and I've I've just said, hey. What's your now, you know, new common practice of of doing work? And, you know, he he kicks off an agent to go write a bunch of code, and then his job is to go review the code and fix its errors and, you know, clean up syntax and and whatnot that might be different.
Speaker 7:And that's just an accepted reality, whereas maybe two years ago, you would say, hey. This this model's producing a bunch of of, you know, kind of garbage code. It probably was garbage because they're just where the models were at, but but you would have seen that as a flaw as opposed to that is just an acceptant that that's an accepted reality of how these systems work now.
Speaker 1:Yeah. And
Speaker 7:so with with that, I I think evolution of the understanding, then you start to flip them the the mindset, which is, okay. I can now use AI to give me the first draft of the thing that I'm doing. I can it can make the first, you know, draft of the blog post. It can it can auto transcribe the the doctor note. It can, you know, generate the first, you know
Speaker 1:First draft of your board deck.
Speaker 7:Yes. And and then we can go through it and and review it and and clean it up. And that still saves you ten hours.
Speaker 1:Yeah. Yeah.
Speaker 7:And so that that that recognition is now kind of rippling through most organizations. This is why this idea of going AI first is is kinda picking up steam. I I talked to a lot of CEOs and CIOs in the Fortune 500 kinda universe, and this is the most easily the most exciting and animated, you know, kinda topic that has existed in twenty years in technology. Yeah.
Speaker 1:They they know they're much more likely to be fired for not Yep. Like being Yes. Like at the forefront of this wave than like having a model that goes off the rails and offends a user Yeah. Totally. On one out of every 100,000
Speaker 7:There absolutely more room for ask for permission in this phase of the of the the of the kind of excitement, you know, kind of adoption curve that we're seeing.
Speaker 2:Totally. Totally. Well, we've kept you too long. Thank you so much for joining.
Speaker 1:Great hanging.
Speaker 7:Ask for forgiveness not not permission.
Speaker 2:Yeah. Ask for forgiveness. That
Speaker 1:makes sense. And thank you for catalyzing our early success.
Speaker 2:Yes. Thank you. We appreciate it. That was very helpful.
Speaker 1:Yeah, man.
Speaker 3:We'll talk
Speaker 2:to you soon. Cheers. Bye. Really quickly, me tell you that. Bezel, get bezel.com.
Speaker 2:Your Bezel Concierge is available now to source you any watch on the planet. Seriously, any watch. And we will bring in Neil Parikh from Slingshot AI announcing Ash. Let's bring him into the studio from the Restream waiting room. How are guys
Speaker 1:on, guys?
Speaker 2:Good to meet you both. Kick us off with an introduction.
Speaker 8:Hey. I'm Neil, one of the cofounders of Slingshot.
Speaker 9:And I'm Daniel. Good
Speaker 2:to meet you guys. Introduce the company. Introduce the product.
Speaker 9:Absolutely. Yeah. So, Neil and I met about eighteen months ago. We were both chasing the same vision, AI for mental health.
Speaker 2:Mhmm.
Speaker 9:We're finally coming out of stealth. We've built the first AI designed for therapy. You probably know this mental health crisis.
Speaker 2:You might
Speaker 1:Product launch. I gotta do it.
Speaker 2:Wait. Wait. Wait. Also, did you raise some money?
Speaker 9:We're announcing our fundraise. We've raised 93,000,000 to date.
Speaker 2:Let's go. Congratulations.
Speaker 1:Almost jumped the gun there.
Speaker 2:That's a big number. Fantastic.
Speaker 9:I was just gonna share. I mean, you probably know this mental health crisis. You might not know that for every, for every 10,000 people out there who need help, there's one person to offer it.
Speaker 2:Wow.
Speaker 9:There's kinda no way that we can get past that except for AI. So, that's why we've worked quietly, carefully with, clinicians in the loop to build the first foundation model for psychology and designed it to actually help people with their mental health.
Speaker 2:Yeah. What what does that mean? First foundation model? Fine tuning, pre training? What what what's the actual tech stack that you're building?
Speaker 9:Yeah. We train in three steps. So we do continued pre training, not from scratch, but from a checkpoint.
Speaker 2:Okay.
Speaker 9:Order of magnitude is about 1% the size of a dataset that a foundation model lab would use. Interesting. So not gonna cost us $10,000,000,000, but enough to substantially change the behavior of the model and introduce completely new knowledge.
Speaker 2:Interesting.
Speaker 9:We then do alignment, which is where our clinical team adapts from the modality of human therapy to AI therapy and learns how this completely new kind of app works. Yeah. And then finally, do reinforcement learning, learning from what works at scale.
Speaker 2:That makes sense.
Speaker 1:What concerns you about people using traditional LLMs models for therapy today. Know, just basically going into their favorite app and and you know, you can't you you effectively can't stop somebody from starting to use an LLM for therapy. But we've seen over the last two weeks specifically, it seems to be some very real concerns around some of
Speaker 2:the It people feels like they're almost accidentally jailbreaking the model, winding up in sci fi territory role playing. Totally. Like what are the best case scenarios? It sounds like those three those three strategy that you outlined are part of it, but what else is going on that that that can make sure that there's always a good outcome?
Speaker 8:I I think the first thing with your knowledge is, like, ChatQPT and Clot are not made for therapy.
Speaker 2:Mhmm.
Speaker 8:Right? Like, they're not trained on clinical data. You people can end up down these very weird rabbit holes like we've seen, right, where people end up in essentially a mode collapse or somewhere that's in a very weird part of the distribution where, you know, it's bringing out psychosis and other issues and stuff. You know, they'll say that it's it's useful for support, but at the end the day, what we're building is something that's very different. Right?
Speaker 2:The
Speaker 8:first way to think about it is we're not trying to build an instruction following model. Like, if you go to ChatGPT, it's an assistant. So if you ask it, like, hey. Give me a recipe for a piece of cake, and ChatGPT were to ask you, like, so why are you hungry? He's like, what the
Speaker 2:that's so annoying. Yeah. That's the alignment by default question. Right?
Speaker 4:Sorry?
Speaker 2:Yeah. Yeah. Alignment by default. Like, the model is supposed to always help you answer the question. So if you ask it, you know, how like, prove that I am a genius, it'll just say, yeah.
Speaker 2:Okay. Of course. Let's let's Yeah. Let's do that. No problem.
Speaker 2:And that's not what a therapist does.
Speaker 9:Exactly. If you go to a therapist and you're like, hey. I feel angry. Help me. You know, they're gonna say, so why is anger a bad thing?
Speaker 9:You know? And you're gonna be like, why is anger a bad thing? Like, I don't know. And then you get into some interesting deep territory, and that's where change happens.
Speaker 4:Sure.
Speaker 9:But, yeah, chat GPT is not therapy. They're not. I actually just saw, that Sam Altman posted about this and had said, yeah. ChatGPT, a lot of people are using it for therapy, but it's not what it's built for, and we're looking forward to seeing a startup emerge in this space. So
Speaker 2:Interesting.
Speaker 1:How how excited are you guys to just like I mean, effectively, you're gonna be running them just by getting this out to more people, you're gonna be running a massive trial. I think the debate the debate among, you know high functioning people, a lot of people that listen to the show, people in Silicon Valley in general is that like like there there's almost like this question of like does therapy even work? Is it is it good? Does it put you in these kind of doom doom loops? How how are you guys, like, looking to measure results?
Speaker 1:Right? You're actually wanting to change lives, but what does that look like?
Speaker 9:Yeah. Super true. By the way, on the controversy, it's funny on on x, if you Neil posted today for our launch and, like, if you read through it, it's fascinating how how much people find this controversial. And, you know, it's interesting to see what's what's going on there, what people are really feeling when they're thinking about this.
Speaker 1:Yeah. And it's and I I feel like it's super common where I I I my parents, when I was an angry teenager in high school, were like, you should see a therapist. And they would ask me, how was the therapist? And I would say, well, I don't know how the therapist was, but it was helpful to kind of just talk through the things that were top of mind for me. So I feel like there's this question of like, you make something that's valuable and helps people better understand themselves and Yeah.
Speaker 1:The decisions they're making And but then there's all like, how do you actually be more beneficial than just having them sort of talk through a problem and actually implement change?
Speaker 9:A 100%. So we are we we built with a, beta group of 50,000 people to make sure that we're building this right, that we were able to show efficacy, safety. We are we've not yet published our results. It hasn't gone through peer review, but very exciting results so far. We've been able to show clinically effective results for symptoms of anxiety, depression, loneliness, increasing a sense of hope, achieving your goals.
Speaker 9:And I think that one of those coolest for us was actually increasing the number of people that you have in your support system in the real world.
Speaker 2:Are all those metrics are all those metrics, like, self reported? Like, I I fill out a survey and say, I'm feeling anxious. And then at the end of my therapy session, I say, okay. I'm feeling less anxious on, like, a scale of one to 10. Is that basically
Speaker 5:what you mentioned
Speaker 2:in this?
Speaker 9:The official metrics. So Yeah. PHQ nine and GAT seven are the main ones. Those are the official ones for depression and anxiety.
Speaker 2:Got it.
Speaker 9:But we use a number of others, others like the UCLA Yeah. Metric. But, essentially, we track people over time
Speaker 2:Yeah.
Speaker 9:From before they start using the app through using the app, and we measure how these symptoms change over time and to see whether or not it sustains. The interesting thing is, I mean, these are used widely across every area of psychology. They're also it has been shown, I think, interestingly, that with with normal chatbots, on average, after using it for a while, you actually reduce your connection to people in the real world. Not too surprising. Mhmm.
Speaker 9:It was amazing for us to see that with Ash, people actually did build stronger connections in the real world. And that just has to do with building something that's purpose built to help people with their mental health.
Speaker 1:Yeah. This is How how excited are you guys around, frequency? I think one of the challenges with, therapy and actually driving change is if if somebody's seeing a therapist once a week or every couple weeks, it's, like, very easy to kind of revert back into old patterns or forget what you had just talked about and we're trying to change. Is part of the potential here is like somebody can effectively have this like constant contact with a therapist or do you think or the equivalent of a therapist?
Speaker 8:Yeah. So, one thing that's important to know is that I think we're inventing a whole new modality of therapy. Right? It this this something like this hasn't really existed before, which means that with that comes you know, we can basically throw out, you know, the whole nature of, like, we have to have a forty five minute session. It happens once a week.
Speaker 8:Right? Prices or or, like, getting into a tough situation might happen at 02:00 in the morning. Right? Your therapist is gonna answer the phone at that Now that said, we also don't want people talking for six hours on one day. Like, feel it's not and it's, like, important for you to, like, work on something, probably sleep it out.
Speaker 8:Right? Think about it, process it, continue to work on it over some amount of time because, like, growth takes some amount of time. Like, very few people just snap and then overnight, you know, are completely different.
Speaker 9:Though I would say this has been like a design evolution for us as we've been with building. Like, early on, we noticed people wanted to use it, you know, until they solve their problem even if that takes ten hours. And that really doesn't work. You need to, at minimum, like, sleep. Like, most change happens when you sleep when you engage in the world.
Speaker 9:So, like, one thing that aria.ai does that's unique compared to others is at some point, it does gently push you out. It will say things like, you know, okay. You know, let me just ask you one more question, and then maybe this would be a good time to end for today. And That's right. What that does is it builds a more healthy habit where you're able to use this as something that you turn to, and people do usually engage a lot more frequently than they would with therapy.
Speaker 9:But they'll engage so that they can actually get through their problem and not create some sense of dependency. Instead, it's something that you come back to, something that you're working on in a style that makes sense and a frequency that makes sense for you and not just for your insurance company.
Speaker 2:Very cool. That's awesome. I have a bunch more questions about business model and stuff, but we are out of time. Thank you so much for hopping on. Congratulations on the launch
Speaker 1:of Why Slingshot? Oh.
Speaker 9:It's a great question. Well, we're, our product is called ASH, ASH AI Therapy. Highly recommend, checking it out. Slingshot, I think makes sense. Great as, like, a tech company.
Speaker 9:Communicate the the idea of, like, the massive change that you go through. ASH was much more, gentle
Speaker 2:Friendly. You
Speaker 9:know, not too human sounding, not not not human sounding. And so it's it's been If you're
Speaker 2:still depressed tomorrow, I will take a slingshot and hit you in the head.
Speaker 1:Hit me in the head with it.
Speaker 9:So Alright.
Speaker 2:Well shape up.
Speaker 9:Try Ash. We love
Speaker 2:your feedback. Yes. Awesome. Thanks so much for hopping on. We will talk to you soon.
Speaker 2:Have a good one.
Speaker 1:Talk soon.
Speaker 2:Up next, we have Jan Srimack from California Forever. He has some exciting news. He shared it re industrialized last week. We were slammed. We got him on the show today to break it down for us.
Speaker 2:Sorry for keeping you waiting. Jan, good to see you. How are you? Beautiful Is that a real photo or are we looking at a virtual background?
Speaker 1:He's on a hot air balloon right now. Exactly.
Speaker 3:No. That's a virtual background. Okay.
Speaker 2:It looks good.
Speaker 3:Here, there will hopefully be a a real photo.
Speaker 2:What is it? Well, what is it describing or what is it showing?
Speaker 3:It's showing the Solano Foundry. It's showing this advanced manufacturing park that we announced last week
Speaker 2:Very cool.
Speaker 3:Which is at the edge of the new city.
Speaker 2:Very cool. Yeah. Announced it re industrialized. We were confused because we were wait, California forever is building in Detroit, but you're building in in California. We're Californians.
Speaker 2:We love to see this. Take us through a little bit more of the announcement. What exactly is coming together? I imagine there's a piece of public support, some government stuff, some financial capital. There's a lot of different moving pieces to this.
Speaker 2:What is in the announcement specifically?
Speaker 3:Yeah. A few different components. So the Solano Foundry is in the new city, and it has been in the plan. We we've had a big area for basically industry and technology in the plan since the beginning. Yeah.
Speaker 3:That hasn't changed. What's changed with the announcement is we've put a lot more lot more details behind it. And so we've we've we've put forward specific master plans, the industries we would focus on. We've worked with JLL, which is probably the leader in this domain. I mean, JLL works for majority of the companies in the Valley when they decide that they need to go from 50 employees to 500.
Speaker 3:They call JLL, and they say, hey. Where we should go? And JLL has spent as they as they've told us, they've spent the last ten years moving companies out of California, and they're kind of sick of doing that. Two years. We're gonna give them another option to do it closer closer to home.
Speaker 3:So we're piling up JL. They wrote a whole 40 page white paper about why they felt that actually you could do manufacturing in California Mhmm. If you had a scale that we have and if you are an hour outside of Silicon Valley. And so we've they published a white paper. They've joined us as the exclusive leasing agent for the 2,100 acres.
Speaker 3:It's about 40,000,000 square feet of space, so it'll be the biggest advanced manufacturing park in California. And then it would work as a integrated ecosystem with both the new city that we're building and with the Solano Shipyard, which is about seven miles south of there.
Speaker 2:Okay. Tell me some historical examples that you're learning from. I wanna hear about Apple's Fremont factory. That was an example of California manufacturing in in advanced computing didn't go so well. Then we're seeing a bunch of promising stuff happen in Arizona with TSMC.
Speaker 2:What are the various lessons that you're pulling from? What are the anecdotes
Speaker 5:that Real you're
Speaker 1:real quick. Just wanted to get Yeah. So so the foundry and the shipyard, I imagine will share like have have like be heavily connected in terms of a company that's at the ship shipyard might also have a facility at the foundry. Sure. And they would obviously have talent living in the city.
Speaker 1:Like how do the how do the three kind of core Yeah. Areas?
Speaker 3:It's a great question. So city provides a place for all of these people to live, whether they work at the shipyard or whether they work at the foundry. Obviously, employee housing, huge issue in California, particularly if your people have to commute from far away. Right? That's one of the biggest drivers that makes people quit their job is they just get fed up with doing a two hour commute.
Speaker 3:And so we can basically provide a ten minute commute next to the foundry, fifteen minutes from the shipyard. People can walk to work. People could bike to work. I mean, there's very few places very few places in America where you could work in a factory and bike to work. Everyone keeps talking about are we gonna reindustrialize the country, but nobody's talking about the reality that nobody wants to work off some random freeway exit in the middle of in the middle of Texas.
Speaker 1:Hours in the desert. Yeah.
Speaker 3:Exactly. You drive to the factory an hour and a half from your house, and then you work off a freeway exit next to a Burger King and a McDonald's. Right? Like, who wants
Speaker 1:to And somehow somehow there's still traffic even though these places are in
Speaker 2:the middle of
Speaker 3:the Exactly. Exactly. Exactly. Right. And so I think if we're gonna actually try to get people to work in manufacturing again, you have to provide a quality of life that I think our generation has come to expect.
Speaker 3:Right? Which means you need to be able to go work in a factory, and then you wanna have lunch. So you meet up your friends, and you sit in an outdoor plaza, and you hang out, and you can do the same thing after work. And there's basically nowhere in America where you can get that other than this place. And so that's a component of it.
Speaker 3:And then, yes, the the the the shipyard and the foundry are very similar. The the shipyard is basically the foundry on the water. I mean, the foundry is an advanced manufacturing park, and shipyard, if you really think about what that is, that's a manufacturing park on the water that just happens to have really large parcels. And so you would have companies that build ships in the shipyard, and then their suppliers are in the foundry. And then we actually have a rail connection between the two, and so you can ship the components from the foundry to the shipyard.
Speaker 3:And so the whole thing is basically this integrated advanced manufacturing ecosystem where, in particular, we've learned a ton from how China does it. I mean, you look at the evolution of this whole thing, and we started it. I mean, we perfected it in America during the second world war. We built the global manufacturing industrial superpower. We discovered that it made a lot of sense to put these create these ecosystems.
Speaker 3:Detroit was powerful not because we made cars in Detroit, but because we made mufflers and brakes and tires and all of the components that go in the car. Right? It's the whole supply chain. And then we did the same thing in Silicon Valley. One of the things that I learned in the course of working on this, in 1965, Lockheed Martin employed 28,000 people in Sunnyvale.
Speaker 3:In Sunnyvale. 28,000 people. Can you imagine? And so you have to have the whole ecosystem. And then what happened in the nineties is China on the lesson.
Speaker 3:They basically took all of the best lessons from America, and they perfected them, and they built these tightly integrated hardware ecosystems in China where you have whole cities that focus on drones or robotics or shipbuilding or whatever it is. And that's how they've been able to outcompete us to the point where what is it? China builds 10,000,000 drones a year, and we built about a 100,000 in The US. China built more ships in one shipyard last year than we have in the entire country since the end of the Second World War. You have these entire cities that specialize in production, and our view is that if we are gonna compete, particularly in the high-tech areas, we're gonna have to replicate replicate it.
Speaker 3:It.
Speaker 2:What was the what was the number of Lockheed employees in Sunnyvale?
Speaker 1:28,000.
Speaker 3:28,000.
Speaker 2:Today, it's at 3,500. Yep. Wow. Huge fall off. Incredible.
Speaker 2:Should we do a little bit of a history question I had? Yeah. Yeah. I mean, he
Speaker 1:covered a little
Speaker 2:Yeah. Yeah. I I I'm I'm just interested to hear your take on, you know, what SpaceX is doing in in Texas, what TSMC is doing in Arizona. There's a bunch of interesting projects that you're probably pulling lessons from. What does it take to get this right?
Speaker 3:Yeah. I mean, I think we are so far behind that it it's it's gonna require kind of an all of the above approach. It's not here or Arizona or Texas. It's all of the above. I think there's an interesting question about specialization.
Speaker 3:And one of the other things that I noticed is if you look at all of the breakthrough products that we've built in America, you can go look at Boeing seven four seven Yeah. In the sixties. You can look at Tesla Model three ten years ago, or you could even look at some of the stuff that Anduril is doing in Southern California. Basically, all of the breakthrough products that we've built, they scaled between ten and twenty miles away from where they were invented. Right?
Speaker 3:The Boeing factory at Everett Field was about 20 miles from R And D. Tesla Fremont was, what, 25 miles from the HQ in Palo Alto where they designed it. I think you could make a I mean, imagine Tesla ramping up Model three production if the factory was in Texas. Mhmm. You could argue they would have gone very differently.
Speaker 3:Right? They would never have been able to figure it out if you didn't have the tight integration between the engineers and the production line. And you can actually drive there and be there in an in an hour. And so the way that we think about the Foundry is it's probably not the place where you put your factory that has 10,000 employees. It's probably not the place where you put your Gigafactory, but it is the place where you go from having 50 people in Menlo Park to having 200 people in your factory number one to having a thousand people in your factory number two, maybe 4,000 people in your factory number 3.
Speaker 3:And then if you really, really hit it big and you you you're operating at Tesla scale and you need a factory that employs 10,000 people, then, yeah, go put it in Texas or or Reno or somewhere else. But it's basically a place for all of these companies to scale from prototype to a multibillion dollar company. And then also keep some of the cutting edge development close to the r and d talent. I mean, even if you look at a lot of what Tesla and SpaceX are doing, a lot of the stuff remained in California. I mean, the engines that go on Starship are still made in California.
Speaker 1:What's what's the timeline for the foundry? Are you guys already working on, you know, are you I'm imagining you're talking with a bunch of tenants already about potential leases. How quickly do you wanna see people with actual their employees boots on the ground standing up these factories, facilities, etcetera?
Speaker 3:Yeah. I mean, the current timeline is to break ground in '28, and that's basically on track. So there's a local city called Tusun that basically came forward and said, hey. We want to look at approving the entirety of the new city by annexing it into our city. Mhmm.
Speaker 3:That happened a few months ago, and so we are now going through the environmental work. I think they're expecting to publish the draft environmental report in q one of twenty six. But since we've announced the we've announced the foundry and actually same for the shipyard, we've had a bunch of companies come to us and say, hey. We would love to build here, but we really would like to break ground in '26 or '27. We have lots of orders.
Speaker 3:We need to make a decision. And so we're gonna look at, can we work with the stakeholders around the table to accelerate it? Because it would be a shame to send another 20,000 jobs to Texas. By the way, very topical here. California just put out the put out the numbers for unemployment last month.
Speaker 3:Mhmm. We just lost another 7,000 jobs in the
Speaker 1:Bay
Speaker 3:Area. California now has the highest unemployment rate in the whole country. So you have you have this crazy juxtaposition of
Speaker 1:the greatest economy one of the greatest economies in world history, period.
Speaker 2:Bigger than most countries.
Speaker 1:And still this unemployment crisis.
Speaker 2:Wild. Wild. Well, thank you for everything you do. Good luck. It is a huge challenge but it's been fun following along and exciting to see the latest development.
Speaker 1:We're gonna have to set up our own studio.
Speaker 2:I was looking at I was looking in the background. I'm seeing studios north right there. Right behind me. Right there.
Speaker 6:Yeah. Right in
Speaker 1:the center. Exactly.
Speaker 3:Good talking to you guys.
Speaker 1:Awesome. Congratulations on all the progress.
Speaker 2:Talk to you soon. Thanks. And if you're looking to visit California find your happyplace@wander.com.
Speaker 1:Find your happy place. Find your happy place.
Speaker 2:Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and twenty four seven concierge service. It's a vacation home but better folks. And we are ready to bring in our next guest, Nathaniel Manning. Let's bring him in to the studio from the restream waiting room if we can do that. Nathaniel, how are you doing?
Speaker 10:I'm doing well. Can you hear me?
Speaker 2:Yeah. Yeah. Can hear you fine. Good to meet you. Why don't you kick us off with the introduction on yourself and the company?
Speaker 10:Yeah. Hey. I'm Nat Manning. Everyone calls me Nat. Cool.
Speaker 10:And the CEO of Legend Legend AI. What we do is essentially make Earth searchable. Mhmm. We wanna be able to query Earth over space and time. So how do you do that?
Speaker 10:Yeah. You you know, you have all these large language models out there. They're trained on language. And so if you were to wanna find all the firebreaks in the Pacific Palisades, for instance
Speaker 2:Mhmm.
Speaker 10:You can't really ask ChatGPT that because it's not in language today. It's not been marked. Right? But, the answer is that does exist. It exists in pixels that have been collected over the last twenty years, in satellite imagery or drone imagery or, low Earth flying air.
Speaker 2:Mhmm.
Speaker 10:And you can train a model, a large Earth observation model, on that dataset and be able to begin to query the pixels themselves. Yeah. So that's
Speaker 1:that's what we do.
Speaker 2:Yeah. What are the data sources? I imagine Planet Labs and some other stuff. Are you buying data? Are you just using stuff that's out there on the open open web and fine tuning or kind of putting it all in a database?
Speaker 2:Like, what what is the market for for satellite imagery look like these days?
Speaker 10:The special part about this industry is a lot of it's made free and available. It depends on how, know, how recent you want it or how high resolution. Then you have to go private. Yeah. But you can train it.
Speaker 10:We train on Sentinel, which is from the European space and then there's a bunch of NASA out there as well. And we can train on all that. So we get to train on open data. Mhmm. And then when someone wants something that's either more high resolution or more recent, we can we can run our models and easily on top of those that purchase date as well.
Speaker 2:Who's the ideal customer for this? I mean, I can imagine it being something I'm using personally, like, every once in a while, but I imagine, like, it's more of a b to b use case. So walk me through the customer workflow.
Speaker 10:Yeah. There's really three products in a stack that we're building. So the first is at the API level. Mhmm. And I would imagine the kind of similarity there is Yeah.
Speaker 10:Is like LiveKit. Right? If you wanna put audio into your into your work today in, you know, building an AI product, you can work with a a LiveKit or another one like that. It's similar that way. If you wanna be able to bring the intelligence that's in this data, which is arguably also one of the largest datasets ever collected.
Speaker 10:Right? So language is under one petabyte of data that's, you all these models are trained on. There's almost 200 petabytes now of Earth imagery. Now the amount of imagery doesn't necessarily equal value, but it does kind of create complexity and possibility, I think. So, you know, typical Earth observation market has been mostly government and defense and intelligence with agriculture and all sorts of kind of environmental climate, supply chain, logistics, finance, and insurance.
Speaker 10:Insurance is a that's a world I come from. So those are those are some of the key ones. And then as I said on the stack, it's kind of API level, which would be thinking like Google Maps, Mapbox kind of kind of tools
Speaker 2:or live deals strategy here. It feels like they have a lot of data in Google Earth and Google Maps, and there's a search box there, but it's certainly not powered by Gemini yet. But do you think it's on the road map for them, or do you think that they they're just focused more on like the consumer use case here?
Speaker 10:Yeah. I mean Google's the big
Speaker 2:800 pound big bear
Speaker 10:in the room. Yeah.
Speaker 2:Big bear in
Speaker 1:the room.
Speaker 10:Yeah. They look, they they have they have, you know, they have all the ingredients to make this stew. They also have like a lot of competition, a lot of focus. It's one of the reasons some some of the investors we took on or were the founding team of Keyhole, became Google Earth and Google Maps, you know, people who really arguably have made more from this in this space than, like, anybody else. Yeah.
Speaker 10:One of my favorite stats actually was that and and talking to them, learning that of the 200,000,000,000 in search revenue that Google makes, one third of it triages their location geospatial database. Mhmm. So it's arguably like the most successful, you know, tool in this space. Now that's location as well and and Yeah. And not just, what's called geospatial, but yeah.
Speaker 10:That does that so API level, and then we're building an enterprise product as well. And then we'll we'll put out kind of a fun consumer application as well, kind of draw people's attention to what is now really possible that everyone's kind of dreamed about for years, this idea of being able to kind of query in the earth over space and time, but the technology wasn't there until, you know, a few years ago.
Speaker 2:Jordy, you have anything? I got another question.
Speaker 1:Yeah. No. I I was curious like where where you expect the most pull from on the enterprise side. Is this like on on the site you have a bunch of different use cases that feel really tied to insurance underwriting. Is that is that an area that you're excited about?
Speaker 10:Yeah. That's where I came from as I've started a company called Kettle that focused on this is kinda how I came about to this,
Speaker 3:which was
Speaker 10:building we we train CNNs on all sorts of imagery and weather data and built our own risk models and ended up going fully verticalized and sold insurance in California. And we built kind of our own models around wildfire risk and arguably, I think built some of the best prediction models for wildfire and then wrote insurance. But our part with insurance, you need a giant balance sheet to be able to write it. And so it was hard to be in a position where you have product market fit so clearly. Like, so clearly saw that, like, there was gonna be a breakage in the California market, that you could do a better job using AI to predict this risk, And then and then just be kind of hampered by conservative mindsets.
Speaker 10:So
Speaker 1:wasn't there also wasn't we John John and I live in two areas that were impacted by the LA fire. Fortunately, our our homes were okay. But I had read that California had effectively had price controls by not allowing you to price based on risk but only price based on historical loss rate And then that changed in December. Do you like I don't I don't wanna go on a tangent but I'm No. No.
Speaker 5:We could
Speaker 10:I can I can talk about insurance all day long? How do you expect that?
Speaker 6:One of the
Speaker 10:main the main the main verticals we're focused on because it's it's one of the most kind of important datasets for underwriting property underwriting. But in short, yes, the admitted market in California using prop one zero three because the prop one zero three basically says you cannot yeah. Yeah. You you have to kinda use historical risk, which in the world of climate change or any other kind of the how fast everything's moving right now, the last, you know, hundred years does not predict the next five years nearly as well as it used to. Right.
Speaker 10:And so but there is this thing called the excess and surplus market. So once you're have three denials from the admitted market, you can go to the excess and surplus market and those rules don't apply. And so that market has grown at a I think a 17% CAGR year over year for the last eight years in California. Wow. Pretty cool.
Speaker 10:Because essentially the mid market's on strike, saying like, hey. And and and fairly so. They're like, I need to be able to raise my rates. I need to be able to use models that actually work, and and they they struggled to do so. So I I got a lot of sympathy for for them.
Speaker 10:It's hard to be in that business.
Speaker 2:How much how much demand are you seeing from people that just want to use AI tools to get cleaner and more data into a traditional geospatial database versus more of like an end to end AI solution where you're training on like the raw satellite images and then trying to kind of query that directly?
Speaker 10:Yeah. A a fair number. I mean, what what were the the first customers and the people kind of doing this today, what you're essentially offering what we offer is the ability to create Aaron actually was kind of talking about this earlier on your show. Like, the ability to create information out of or structured data out of unstructured data. Yeah.
Speaker 10:So imagery is unstructured data. Yeah. And kind of historically, you'd have a you know, stage one is you have an an analyst look at it. Yes. You know, looking human eyes are pretty good at looking at this picture and saying, ah, that's a firebreak and this is a neighborhood and and that's a fire on the other side of etcetera, or a or a forest on the other side.
Speaker 10:And then you would train a the kind of stage two is you'd train a specific model, convolutional neural net.
Speaker 2:Detect all the trees. Detect all the roads.
Speaker 10:And that's how And give it hundreds of thousands of images Yeah. And teach it how to do that specific and we spent millions of dollars a kilo doing that. And, that's that's kind of the norm today. There are tons of teams and it takes multiple data scientists and an ML ops person and, you know, a quarter or two to do one of these. So you're spending, like, half a million bucks kind of per query.
Speaker 10:And it because, again, it's just like convolute convoluted data, and it's across all those kind of industries we talked about. But what happened when you have the attention is all you need, you know, a paper that came out, the transformer model, when you apply transformer model architecture to data, the output is embeddings. Right? So you have these vector embeddings for language. And what happened over the last twenty five years you know, for twenty five years, keywords were the first order data object for making sense of language.
Speaker 10:And in the last two and a half years, we've seen the process of it changing from that to language embeddings, and it's one of the biggest stories sort of in the world. And our take is the same thing is gonna happen in in geospatial data. For twenty five years, it was map tiles or or the pure raster data, the pixels themselves, and that we're in the process of that changing to geo embeddings. And so our whole thesis, what Legend really is, is the the stack for managing embeddings, creating tuning and storing them, which is the output of these models on the raw data itself. And just that's the wave we think is is gonna happen for the same reason that because it's happening in language.
Speaker 2:Very exciting. Thank you so much for stopping by.
Speaker 10:Quick hit. Happy to be here.
Speaker 2:Do you have any news for us? You raised
Speaker 10:money We from raised a $9,000,000 round.
Speaker 1:Oh, here we go. Very
Speaker 10:excited. We have some great guys on it. Know, Kareem, your buddy, Ryan Delk was kind of our first check-in so Fantastic. A lot of Yeah. I've known Ryan Amazing.
Speaker 4:He's the best.
Speaker 1:Amazing. Thanks guys. Congratulations. Congratulations to you and the team.
Speaker 3:Appreciate it.
Speaker 10:Thanks for having We'll
Speaker 1:have you back on soon.
Speaker 2:And we'll see you soon.
Speaker 1:Have a good one. Cheers. Cheers. We have to pull a video up Okay. And react to it.
Speaker 1:Apparently some guys were
Speaker 2:What's this?
Speaker 1:Made a video this morning that I will drop into for the production team to pull up. Here we go. They made a launch video. I think they're a company called Composio. Okay.
Speaker 1:And apparently, we were featured in it. Oh, really?
Speaker 2:That's good.
Speaker 1:Well, well, they they they violated the derivative works clause. So they anyway, so let's watch Let's
Speaker 2:watch this. This is the first time seeing this. They were reacting to this. There we go.
Speaker 11:Hello. My name is Jonathan Liu. Today, I'm launching Cupidly, the cursor for dating. Let me show you how it works. So when you visit the site, you first enter your type.
Speaker 11:So let's enter my type.
Speaker 2:Oh, this is HingeBench. We've been talking about this.
Speaker 1:This is not the video that I pulled up.
Speaker 11:And connect your profile.
Speaker 2:This is this is a this is AI agent for hinge dates.
Speaker 1:Okay.
Speaker 2:It scrapes your hinge profile and it tries to does do matter Not
Speaker 1:video not the video that I was referencing. So can you guys look in the in the tab? Getting some audio.
Speaker 2:Sound effects in that video.
Speaker 1:Yeah. Here it is. It is. No. Not this one.
Speaker 1:Not this one. This one? Second. The first one, there there's two videos.
Speaker 2:Okay.
Speaker 1:So first, they violate the derivative clause and I guess they tap out.
Speaker 2:Okay. Okay.
Speaker 1:Let's see. Let's pull up the first one. I We're gonna have to find out what that other video was.
Speaker 2:Oh, yeah. That that that's a big viral launch. So someone launched AI agents. We should definitely talk to
Speaker 1:guys.
Speaker 6:I mean, how could it go wrong? We got into fucking YC.
Speaker 1:Alright. Here we go. Yeah. That was useful, but eventually becoming nothing, just like the agents we built. Fuck, Julie.
Speaker 1:I
Speaker 11:wish our agents just worked. Beautiful cinematography.
Speaker 6:I sometimes wonder what it'd be like if we had agents that actually were useful.
Speaker 7:You're watching TPPS.
Speaker 2:There we go. We have some crazy founders on our show. They literally went from almost going homeless to an AI agent unicorn. Oh, tap on it. Our
Speaker 5:agents keep breaking. How'd you fix that?
Speaker 6:We started using this new tool.
Speaker 8:I saw this agent AI thing on Facebook, but it made no sense to me.
Speaker 1:Your new agents are amazing. They just work.
Speaker 8:So how did you grow so fast?
Speaker 6:Honestly, our agents sort of sucked before. We tried to build everything ourselves.
Speaker 10:Then we started using the friend of the show, Composio. They're fucking great. They allowed us to build these incredible agents.
Speaker 6:Last year, we got reliable agents. Ones you could trust to code, test, and ship.
Speaker 4:This year,
Speaker 2:the ship gets bigger.
Speaker 5:Agents. Agents. Agents. Teams aren't
Speaker 1:just working with agents. They're managing swarms.
Speaker 9:Dozens of them. Splitting work.
Speaker 6:Handing off context.
Speaker 1:Stop correcting.
Speaker 2:This is very Very
Speaker 1:drawn out. Okay. Fix your agents before it's too late. So composeo.
Speaker 2:Very cool.
Speaker 1:I'm pulling it up the skill layer of AI.
Speaker 2:There was so much in that video. Yeah.
Speaker 1:There was a lot going on in there. So much going on. Second Pull up video now because it sounds like they respect our
Speaker 2:They respected it in the video.
Speaker 1:I saw Tapware in the I
Speaker 2:don't I don't even need to do a second video, but they did. So thank you to them for respecting the derivative works clause and paying homage homage.
Speaker 1:I love how the team is able to deliver twenty hours of cinematic content a week. Yeah. But if you get them, try to get them to pull
Speaker 2:up the video. We go. Let's see this. Look at this cinematography. So many cuts.
Speaker 2:Wow. This is fantastic editing. Congratulations. I can't fucking believe it. You already tapped out.
Speaker 2:There we go. You'll love it. That's fantastic. Full golden. Congratulations to that.
Speaker 1:Love it.
Speaker 2:So We have to have
Speaker 1:more on show. Yeah.
Speaker 2:Gotta have
Speaker 1:them on. They raised 29,000,000 to build skills that evolve with your agents.
Speaker 2:Okay. Tomorrow, we're having them on. We have slots. We will reach out. We'll make it happen.
Speaker 2:We have one more guest. I think Chris is still in the restream waiting room. Is that correct? Is that right? Chris, sorry to keep you waiting.
Speaker 2:There was a viral video. We had to react to it.
Speaker 5:No worries.
Speaker 2:Thanks so much for hopping on. Thanks so much for the patience. Kick us off with the introduction. How do you know TJ Parker?
Speaker 5:Yeah. TJ Parker. Man, we went to Sunday school together
Speaker 2:I think so.
Speaker 5:Twenty five, thirty years ago. That's a good start.
Speaker 2:That's great. But I
Speaker 5:know TJ's a dear friend.
Speaker 2:That's great.
Speaker 5:We're both based out in Park City, Utah.
Speaker 2:Oh, amazing. Amazing. And, well, yeah, give us the introduction on the company, the news. What else is going on in your world.
Speaker 5:Yeah. So I'm Chris Andrew, co founder and CEO for Scrunch AI.
Speaker 11:K.
Speaker 5:We've built a customer experience platform for the AI buyer journey. Yep. Today, we're announcing a $15,000,000 series a. Congratulations. Bet by Decibel.
Speaker 5:Thanks. Had to hit the gun. And I mean, very simply, our belief eighteen months ago was that all of search was moving to be AI search.
Speaker 2:Yep.
Speaker 5:Really, like, outsourced we browsing without talking about the fact that we never wanted to browse the Internet. Was inefficient. We outsourced it. AI does it for us and it means that AI visits websites instead of humans. And so we're building a company around that shift.
Speaker 2:Okay. Talk to me about the the AI shopping journey recently. We're looking for gear for our studio basically always. I wanted to build a mobile camera rig. I needed certain features.
Speaker 2:There's HDMI ports, this much battery life, this much all the camera kind of describe what I want. It puts together a little shopping list. I send it to the production team. We kinda go back and forth. There are some links there.
Speaker 2:I don't think those are affiliate links yet. I feel like in the future there will be ads, but but what else is important in terms of actually positioning if you're selling a particular camera? How do you make sure that you show up and you beat it out? Because I kinda knew I wanted a Sony camera, but it they could have sold me on Blackmagic there. Blackmagic should have been hand wring me.
Speaker 2:They should have been paying OpenAI to be like, hey, have you considered this Blackmagic one? And, you know, the team likes Blackmagic too. So talk to me about all the different nuances that go into AI shopping.
Speaker 5:Yeah. I think, really, ultimately, all that top of funnel top of funnel discovery, kind of the 90% of the buyer journey, which used to be you curating research from Reddit Yep. Reviews Yep. Sites based on pricing. We've trusted OpenAI and Perplexity to do that for us.
Speaker 5:So, you know, they're basically running a search over a search index, which is increasingly GPT's own search index.
Speaker 11:Yep.
Speaker 5:Prior, that was based on Bing or Google or Brave. But they're looking at a list of websites, identifying title, description, snippet, visiting the website, deciding if it's relevant based on the prompt that you asked. So it's basically trying to match the intent of a human prompt to content on websites to cite the sources that it deems relevant. So what we're seeing in the end is buyer journeys that are massively reduced. People are arriving on a website and buying the first time they're there.
Speaker 5:Lot of our customers are seeing two to four x conversion from AI search visitors compared to organic search visitors. And I think search and shopping will keep changing. Right? I I just heard that GPT is, you know, embedding Shopify checkout in their feed. They're taking a cut of that checkout.
Speaker 5:I think it's, you know, 4% or something in terms of, like, another cut off the top. But today, what's happening is AI is doing the research, citing sources, and we as humans are clicking out to purchase and engage.
Speaker 2:So how important is it if you run an e commerce website to go into Cloudflare and turn off that AI default because that seemed like Matthew Prince came on the show, a great entrepreneur. He's certainly working in favor of content producers who might not want to be scraped and have their their their, you know, the harder work to blogs that they've developed automatically generated in in AI search results. But if I'm just selling a product, I definitely want to be in search. So how is that landscape shaping up these days?
Speaker 5:Yeah. Matthew Prince, another great Park City local. We've all Oh, yeah. Crossed he can buy the mountain. We're pulling
Speaker 2:for him
Speaker 5:and also pulling for him that, you know, content creators can get paid in Yeah. In AI crawling. I think that model makes a lot of sense for Cloudflare. Our customers, on the other hand, I think the 50 to 60% of the Internet that has a product or service to sell is desperate to bring content online to help AI understand their products and services. So we still come across Fortune 500 brands who have their site blocked.
Speaker 5:And so when I ask a question about that brand, what's the price? What's the product description? Compare it to x y z. It's going out to the open web to represent your products.
Speaker 10:So our
Speaker 5:customers are like, my product and service is no longer what I say it is. It's what ChatGPT says it is. Yeah. And if GPT can't access or can't effectively utilize your content on your website, it's gonna pull from every other source that it can find on the Internet. It's it's part of why we've launched what we call our agent experience platform today, which is essentially an optimized version of your website.
Speaker 5:So we take your website, we scrunch it, called our brand scrunch, because we literally wanna strip away everything on a site that is confusing to AI. These models don't read JavaScript. They struggle with carousels. They're not converting your multimedia into text. Large language models want language.
Speaker 5:So it's critical for businesses to be enabling the crawling on their site and making that content rich and accurate for the crawlers to access and pull through.
Speaker 2:How is that actually different from just generic SEO? I feel like if I had a video, I'd want subtitles and text and like an HTML tag or something that that that just Google search could pull up anyway. There was kind of like that keyword stuffing era, dump a bunch of words in white text on a white background at the bottom Yeah. One point font or whatever like Yeah. It is that.
Speaker 2:Are we going back to that?
Speaker 5:No. I mean, I think we're actually moving more towards human language and intent. I mean, the keyword stuffing is a great example. If you if you pull up a recipe site, go Google chicken noodle soup, you're gonna find the word chicken 60 times on that page. Right?
Speaker 5:So it gets absolutely manic. Yeah. AI wants the intent of the query. So, like, if you ask GPT for a recipe, it gives you the answer. Right?
Speaker 5:It kind of strips everything away and reduces it to what you want. So I do think we're actually returning to a lot of core SEO principles. You need language. Large language models want language. They're struggling with carousels and multimedia.
Speaker 5:They need that text. And so I think best practices in SEO ultimately, hope is we just call this search. We get rid of g e o, a e o, a I o. I ultimately think all of search is gonna be AI search and its agents retrieving content for
Speaker 2:us. Mhmm. Anything else, Jordy?
Speaker 1:No. This is great. Thank you for joining. Congratulations on the waves.
Speaker 5:Will Thanks talk you
Speaker 1:guys. Appreciate it. Out there in Park City give our best to TJ.
Speaker 2:TJ. Yeah. We'll talk to
Speaker 4:you soon.
Speaker 2:A good Cheers. Let's rip through some timeline. Did you see the medieval knight raising a seed round of 500 gold ducats at 3,000 ducats post and they already have their first LOI signed with the holy Roman empire.
Speaker 1:Hard not to be bullish.
Speaker 2:Must beat the Ming dynasty in the gunpowder race from
Speaker 1:What is this what is this video by
Speaker 2:the way? We gotta pull up this video.
Speaker 1:Pull up the video.
Speaker 2:I don't know if we can. This is gonna be hard.
Speaker 1:It's gonna be a big challenge.
Speaker 2:Damage right now, but it is in the tabs. You might have to scroll way back. Loosely modified after the Tannenberg Castle gun. Mine is loaded with around 50 to 60 grains of two f black powder and fires a point seven five caliber lead ball. Heavy.
Speaker 2:Do we have the video? Can we pull it up? One second.
Speaker 1:This is an OG two a enthusiast right here.
Speaker 2:Yeah. Indeed. And I love that some founders all Edward is just like completely transposing this to the defense tech meme of like we must beat the Ming dynasty in the gunpowder race. Like you know I've invented defense tech and this guy is firing some sort of a castle gun. I've never heard of this before.
Speaker 2:Apparently from 1400.
Speaker 1:So We should get one. They had studio.
Speaker 2:They had guns six hundred years ago? Wow. I thought that was more modern. I thought that was like maybe three hundred years ago.
Speaker 1:But When was the first gun created?
Speaker 2:Let's figure it out.
Speaker 1:Appeared in China. The earliest firearms known as fire lances appeared in China around the tenth century. They were essentially tubes often bamboo filled with gunpowder and shrapnel mounted on spears. Mhmm. So they were just made a lot of sense.
Speaker 1:You got a spear, you wanna point it, you want some range, throw on some gunpowder. Fantastic. More news, Nudge raised a $100,000,000.
Speaker 2:There we go. We got the video.
Speaker 1:I think we got What are these guys doing by the way? This is incredible. Is this operation?
Speaker 2:Who are these guys? Legends. That is so crazy. It is bamboo. It looks like it's bamboo.
Speaker 2:I don't know if it is.
Speaker 1:Insane. A crazy thing. Ben, get one of these for the studio. I need one.
Speaker 2:Yeah. Yeah. Yeah. For our next confetti cannon, we'll load up
Speaker 1:that Yeah. With gun real confetti cannon with which Boom.
Speaker 2:We're like shaking
Speaker 1:the whole thing
Speaker 2:every time someone announces a closed seed round. Yes. Nudge, the brain computer interface company co founded by Fred Ursim, the co founder of Coinbase says half the world will experience a brain disorder in their lifetime. At Nudge, we're building brain interfaces that are a safe precise, and noninvasive to solve that problem. They raised a $100,000,000 in series a led by Thrive Capital and Green Oaks to go faster.
Speaker 2:We're hiring. Join us. Very exciting. Nudge, kind of the noninvasive Neuralink. There's other news in here in the deck.
Speaker 2:Neuralink just did two implantations in the same day. So they're scaling the actual implantation of the Neuralink device. That of course requires invasive surgery. Nudge does not. It's a kind of a helmet that you put on but then can can stimulate the brain in different ways and solve a whole bunch of different brain disorders very
Speaker 1:likely could be the key to scaling from three to to six hours a day.
Speaker 2:I think so.
Speaker 3:Live.
Speaker 2:Put one of these on. I mean you can actually turn off sleepiness basically. Mean, the the the like once you get the the the different it's literally like a tinfoil hat. Put it on and and it can just be like turn off fear. Up regulate risk taking.
Speaker 2:Go turbo long.
Speaker 1:Yeah. Mitigate you want you want capital alligators to to be super risk on but still get the weight loss benefits of GOP.
Speaker 2:Yes. Exactly. This is a wild leak memo from Yes. And probably see Dario.
Speaker 1:Dario is basically justifying to the team why they're gonna go directly to The Gulf to raise capital. And this is not something that probably should have ever been in a memo. He says, unfortunately, I think no bad person should ever benefit from our success. It's a pretty difficult principle to run a business on. Just blanket putting The Gulf States in the
Speaker 2:bad It's so it's such a weird thing because it you'd think you'd just be like, I met them. I dug in. I don't think they're bad people. And so I'm doing business with them and let's debate that. And I think it's a Pareto improvement.
Speaker 2:Everyone has made it better off by Anthropic working with The Gulf. That's the argument he should be making, but he's not, I guess. And so Dylan Patel says Anthropic has been a series of ideological decisions later defeated by business realities. We've talked about this before where, you know, it was like, all the all the idealistic AI scientists were like let's try doing this without capitalism and then and then the AI god was just like
Speaker 1:I actually enjoy capitalism.
Speaker 2:I enjoy
Speaker 1:It's thrilling to me.
Speaker 2:Thrilling and I like 500,000,000,000 You're
Speaker 1:exactly right. The right way to do something like this is say, went, we visited
Speaker 2:I dug you.
Speaker 1:We spent a few days together. Yes. We have a shared vision for how AI can increase human prosperity.
Speaker 2:Totally. Whatever the critiques are. I don't even know what the critiques are of The UAE. I I that I'm sure there's a bunch of of both The UAE and Qatar. Like there are of all governments and every company and every person ever.
Speaker 2:Yeah. But you dig in, you figure out like, oh yeah, how can we work together to resolve any lingering problems? Should we have a different perception here? Know, just be like, I'm going into business with someone I think is bad. Wild wild choice.
Speaker 2:Wild. Anyway.
Speaker 1:Choice of words.
Speaker 2:In better news, Blake Scholl says, at Mach 1.7, Overture out flies Earth's rotation. That's cool. So you can have breakfast in London, fly to New York for breakfast, and then to San Francisco just in time for breakfast.
Speaker 1:This is gonna be huge for the breakfast folks. Yes. You ever been breakfast for dinner guy?
Speaker 2:Pancake dinner. Yeah. Pancake dinner. Kind insane.
Speaker 1:A kid that was mind blowing. Yes. We do that maybe once
Speaker 2:a month. Cereal for breakfast.
Speaker 7:Waffles. My
Speaker 2:dad would die laughing at the concept of eating cereal for
Speaker 1:It really is.
Speaker 2:Oh, it was the funniest thing
Speaker 1:you Breakfast could is so good.
Speaker 2:It is.
Speaker 1:And when
Speaker 2:It's not my favorite.
Speaker 1:Really?
Speaker 2:Yeah. I'm not a big breakfast guy.
Speaker 1:I think I think it's my favorite.
Speaker 2:Even even my default breakfast is like a breakfast burrito which is really like lunch or dinner masquerading as breakfast. You know? Yeah. It's kind of like
Speaker 1:That's true.
Speaker 2:They've just kind of like swapped out stuff I just remember as a kid. Breakfast y.
Speaker 1:My dad making waffles for dinner was so awesome.
Speaker 2:Yeah. Oh, it's amazing. Do we have the Tyler cam working? Can we can we check-in with the final review Yeah. Of the Tesla cafe?
Speaker 2:How was the experience? How far how far how long did it take you to get there from here?
Speaker 10:It's like five months away.
Speaker 2:Oh, it's really close.
Speaker 3:Super close. Oh, wow.
Speaker 6:Okay. Like we could probably walk there.
Speaker 2:Okay.
Speaker 1:Yeah. Did they? I wonder if they did that on purpose.
Speaker 2:We didn't get the invite to the opening. There's some other influencers there yesterday. We're behind the ball. Had to go
Speaker 1:They know we're always live.
Speaker 2:Yeah. Yeah.
Speaker 10:It's definitely cool like the building is super cool. Yeah. There's a ton of stuff on the menu. It's just like a a diner.
Speaker 2:So That's cool.
Speaker 10:I mean, there was like I don't know. There's like hundreds of not hundreds. There's a lot of things on the menu Yeah.
Speaker 6:Yeah. For like every kind of meal.
Speaker 2:Yeah. So like
Speaker 10:a think dozen it's open twenty four hours.
Speaker 2:Twenty four hours.
Speaker 4:That's cool. Maybe, you know, we go back later.
Speaker 1:Do they have steak? They have steak?
Speaker 2:Do have dinner?
Speaker 10:I don't know if
Speaker 4:they have steak.
Speaker 2:I guess you just get a burger whenever. Yeah.
Speaker 10:But so we took a Tesla like to get there and then so when we parked, you could see on the menu.
Speaker 2:Wait. How did you take a Tesla to get there?
Speaker 4:Adam. Adam has a Tesla.
Speaker 2:Okay. He just owns one. Yeah. Got it. Okay.
Speaker 2:Wasn't a
Speaker 6:It didn't
Speaker 2:It wasn't like a robotaxi because the robotaxi is rolling out really aggressively but it's not in LA yet but this feels like kind of tied. They're teasing. They're they're they're testing the waters.
Speaker 4:Anyway. Yeah. Think the burger was
Speaker 2:How's food setting? Are you feeling still good or any upset Tommy?
Speaker 10:I feel pretty good right now.
Speaker 2:Feel pretty good.
Speaker 6:We'll see. Okay.
Speaker 4:Yeah. It was cool.
Speaker 10:I I'm I'm not I wouldn't go back just for the burger. Okay. But maybe I would go back for Would
Speaker 2:you go back and do a mukbang and eat every item on the menu in exchange for an iPhone.
Speaker 1:That would in exchange for an iPhone.
Speaker 2:Yeah. I would
Speaker 1:do that.
Speaker 2:You would eat every item on you would try and eat every item on the menu during three hours every every item you have to eat them all. Yeah. Like 7,000. What would
Speaker 6:you eat
Speaker 5:by every item?
Speaker 10:Do you like is it a burger and a burger with bacon?
Speaker 2:What what what I saw I saw a graphic that had like 12 different items on it and so it'd be it'd be 12 different meals basically.
Speaker 1:Yeah. He's a growing he's a growing boy. He's a growing boy.
Speaker 2:Never been in the competitive eating. I think it's a little vulture. I think we'll come up with a better better challenge for you. You will win the iPhone within the next few weeks. But we gotta come up
Speaker 1:with It's gonna happen.
Speaker 2:I wouldn't wanna put you through the muck bang. I think it's probably a little bit too aggressive too hardcore on your body to try and eat all that food.
Speaker 1:Yeah. Three
Speaker 5:hours though?
Speaker 1:Three hours? Three hour show?
Speaker 2:Maybe you it. You do the muckbang.
Speaker 1:I gotta be here.
Speaker 2:Yeah. Exactly.
Speaker 1:Anyways, we have a post here from Jira tickets. He's been an absolute regular recently.
Speaker 2:Yes.
Speaker 1:Feels like he's on every other day.
Speaker 2:Love Jira tickets.
Speaker 1:He says, ah yes. Good morning. Let's open up the Infinite Information River for a nice twenty minutes before getting out of bed or thinking any original thoughts at all. I love it. So real.
Speaker 2:I because I wake up so early and I race over to your place and then get in the car. I haven't been opening the Infinite Information River first thing in the morning. I haven't been doing anything other than just get Actually I go outside. I go outside and I get sun. Who were we talking about that with?
Speaker 2:Maybe Huberman or something? Rob. But Rob. So I've been doing that and I don't know if it's really been that much better. Sometimes
Speaker 1:the the light that blasts your eyes from your phone is Sweep it up. Best alarm clock.
Speaker 2:It's the best. And and when you open up your phone and you're greeted with a post like this, just kicks you off to like a great start of the day. Yeah. You're just laughing.
Speaker 1:If pin this to the top of the feed that
Speaker 2:would You're having a You're having a great time. What else is in here? Oh yeah. I mean we do have the post about somebody built cursor for dating. We gotta talk to this this fellow.
Speaker 2:Spent his life
Speaker 4:Can we
Speaker 1:pull up the video now? Was super confused earlier but we
Speaker 2:Spent my life savings on this cinematic video because I have no VC money to burn. Did one shot, very funny and then digs into AI agents for Hinge. The AI agent goes and scrolls your Hinge profile does all the swiping all the talking and then surfaces matches that it thinks you're actually interested in matching with. Kind of like a layer on top of Hinge I suppose. Yeah.
Speaker 1:Let's pull
Speaker 2:it up. Let's see it. Let let let's see it. I mean, the cinematography, fantastic for the first couple seconds and then it gets a little silly.
Speaker 11:Hello. My name is Jonathan Liu.
Speaker 2:It's a cool shot. Cool shot. He says he ran
Speaker 11:Today, my interview watching the with Cursor for Dating. Let me show you how it works. So when you visit the site, you first enter your type. So let's enter my type.
Speaker 2:What does he say? I can't read that. Then
Speaker 11:you would go ahead and connect your profile.
Speaker 2:Does he does he it's funny that he's censoring Hinge because it's obviously hinge and and hinges
Speaker 11:black button
Speaker 2:to start searching for
Speaker 11:people your type. And this launches an AI agent that swipes for you on Hinge filtering for people
Speaker 2:Why is he censoring it? Everyone knows. And then also Boom. Just like that. He's harnessing Hinge in some weird way because I don't think Hinge has an API.
Speaker 2:Tyler, do you know if Hinge has an API?
Speaker 10:Not that I've looked, but I
Speaker 6:don't think there is.
Speaker 2:Okay. Because I imagine that they would not want this to happen. They don't want bots in their network whatsoever.
Speaker 11:Thinks you're a good match. And, oh, this picture's pretty cute. Let's go ahead and send
Speaker 2:it back. The OY is really coming back.
Speaker 11:Either send a message using AI Yeah.
Speaker 1:It was a real throwback.
Speaker 2:Yeah. And then you send a message using AI. That's wild. I don't know what this is done for. I don't know how serious he is about this.
Speaker 2:But, I mean AI dating clearly gonna be something there. This is an interesting go to market. Maybe it's controversial. I mean, you got 10,000 likes, million views.
Speaker 1:Yeah. Think the Probably
Speaker 2:a bunch of
Speaker 1:It's it's very clear the dating apps don't want people building experiences on top of them. Yeah. And they will try to own this type of experience but but we're talking about it.
Speaker 2:We're
Speaker 1:talking So about
Speaker 2:it sounds
Speaker 1:like a successful launch.
Speaker 2:Well, we gotta jump. We gotta film an ad. I'll close it out with Mike Krueger, co founder of Instagram at Anthropic. He says, today I'm excited to share that I'm joining Figma's board of directors having known Dylan for years and watched him build the platform that's become essential for design teams. I'm looking forward to partnering with him and the Figma team on what's Fantastic.
Speaker 1:Heading into the IPO. Could have found a better person
Speaker 2:to So join the congratulations to everyone involved in that.
Speaker 1:Last one. Please. Close close so investments. Oh, Not calling a top here because of AI yada yada yada. But White House eliminates day trading regulation, poly market returns to The US.
Speaker 1:Robinhood enables twenty four seven EU gambling. The architects of the twenty twenty two SPAC bubble are posting. CNBC guys have a crypto treasury play. Wall Street bets meme crashes 40% and almost closes negative.
Speaker 2:I don't understand that one.
Speaker 1:If we blow up later this summer, can't say there weren't signs.
Speaker 2:I mean, the benefit of of like, you
Speaker 1:know, what is going on is pretty crazy.
Speaker 2:Yes. I mean the benefit is that if no one's saying this, then you need to be really worried. Because at least people are saying this and then they're thinking it and then hopefully people are pulling back before you get to a feeling press I
Speaker 1:feel like in 2021, 2020 people were saying this crazy. Yeah. I see saying all I'm saying is what's going on pretty crazy.
Speaker 2:Pretty crazy. Pretty crazy.
Speaker 1:Hyper capitalism.
Speaker 2:We'll see. We'll see. Gotta love it. Anyway, thank you
Speaker 1:so much. Last last but not least.
Speaker 2:What you got? Hope hope Oh yeah. Hope's revenge.
Speaker 1:One of the top posters in the world.
Speaker 2:Hope's revenge. Tipping the
Speaker 1:power ranking. Originally said my g f is upset because her favorite albino alligator was bought by Anthropic and ruined. And then he actually has a picture here and it says, the care of Claude the alligator is generously supported by Anthropic.
Speaker 2:Think this is great. I don't see why it's ruined.
Speaker 1:I love to see big AI supporting alligators.
Speaker 2:Yes. I
Speaker 1:actually wanna get, I'm really excited for BCI's brain computer interfaces to get into the alligator category. So can talk They're to pretty wild.
Speaker 10:For I
Speaker 1:mean, just pull up a picture of an alligator. These things are insane. Yeah. The fact that they're just cruising around.
Speaker 2:One's working on humanoid alligators, like robotic alligators.
Speaker 1:We've seen Maybe
Speaker 2:that's Maybe that's the killer form factor.
Speaker 1:Maybe everybody's saying, Oh, you guys could do incubations.
Speaker 2:I like robotic alligator would be a good defense play too.
Speaker 1:Yeah. I mean, there's a lot of investment in bears. Yeah. Robotic bears.
Speaker 2:Yeah. You let the robotic alligator can sneak under stuff and
Speaker 1:Swim. Jump up Run.
Speaker 2:Attack the terrorists
Speaker 1:Yep.
Speaker 2:Attack the enemy. Seems like
Speaker 1:An alligator, a robotic alligator with drone based wings so it could actually fly while snapping.
Speaker 2:Could reshape the modern battlefield. Could be looking at billion dollars
Speaker 1:Home defense play too. If you had some robo alligators on the roof Yeah. And you had somebody breaking
Speaker 2:I'm big into moats. I'm big into moats. What am I gonna put in the moats?
Speaker 1:That's right. Alligators. Yeah. And there's gonna be some upkeep costs with maintaining a fleet of robotic alligators but probably less than how many how many chickens or cows you gotta throw in the moat Exactly. Exactly.
Speaker 1:If they're real alligators. So yeah, we're trying to I think more single family homes should have moats.
Speaker 2:Yep.
Speaker 1:Right? Always talking about businesses, talking to founders. What's your moat? What's your moat? Yep.
Speaker 1:Meanwhile, we're sitting in houses that don't have moats. Yeah. And I think that should change. So lots of lots of opportunity in alpha here at the end of the show.
Speaker 2:Fantastic. Have a great day. We will see you tomorrow.
Speaker 1:Cannot wait.
Speaker 2:Have a
Speaker 1:great evening.
Speaker 2:Cheers. Bye.