Open AI Dev Day just occurred. Some of the most staggering things in human history got announced yesterday and they still undersold it. Good morning and welcome to Deb Day. The battle here is that human attention is finite. Open AI meta, everyone’s making a play for who are you talking to that then enables these MCP enabled agents to come and do the job. Everyone’s trying to be the everything app. What happens when suddenly we’re able to 5x 6x 7x the amount of broadly accessible super intelligence across the world? I I think this starts to become the foundation for transformative economic changes at a planetary scale. >> OpenI is really trying to do a global land grab, right? Going into India, going into the UK, going into Greece, and then you’ve also got all of the open- source models coming out of China. We’re just at this tipping point and the tipping point is in the next 6 months. >> Now that’s a moonshot, ladies and gentlemen.
[00:01:02] >> Everybody, welcome to Moonshots and our next episode of WTF just happened in tech. Uh we’re spinning up this episode real quick with my extraordinary moonshot mates because Open AI Dev Day just happened. Want to cover the subjects there, but there’s a lot happening across the board in robotics. you know, FSD 14.1 from Tesla just dropped, as well as other robotic updates and data center updates. Uh, we’ve got my Moonshot mates Dave London. Dave, good to see you, pal. >> Good morning. >> And of course, we have AWG live from someplace in the uh in hyperspace. And >> good to see you, Alex. Welcome back. Uh and then uh one of our other moonshot mates, Immad Mustach, coming in from London. Immad, good morning to you. >> Morning >> or good afternoon as the case may be. You know, in the rocket business in the business, there’s something called a hyperbolic fuel. Uh a hypergolic fuel is
[00:02:01] when two chemicals come together and they explode and they make a propulsive force. And I think about AWG and EMOD coming together as my hypergolic fuel this morning. So, >> better than coffee. Completely agree. Yeah. Uh, absolutely. All right. So, as always, this is the news that’s breaking that I think is impacting the global economy, impacting our mindsets, impacting, you know, how we teach our kids and run our companies. So, nothing more important uh for me and let’s jump in. The reason we spun this up uh for everybody is OpenAI Dev Day just occurred. want to hit on this and I’d like to really evaluate along the way, you know, how critical, how rapidly how is Sam sort of manipulating the future of his company and AI uh in a positive way. Um we’re going to discuss this. All right. Uh I’m going to open up with a short video clip of Sam opening up
[00:03:00] Open AI day yesterday. Let’s take a listen. Back in 2023, we had 2 million weekly developers and 100 million weekly touch BT users. We were processing about 300 million tokens per minute on our API. And that felt like a lot to us at least at the time. Today, 4 million developers have built with OpenAI. More than 800 people use ChateBT every week and we process over 6 billion tokens per minute on the API. Thanks to all of you, AI has gone from something people build play with to something people build with every day. We think this is the best time in history to be a builder. It has never been faster to go from idea to product. You can really feel the acceleration at this point. So to get started, let’s take a look at apps inside of Chat GBT. >> All right, Dave, you want to open up? >> Yeah. So you obviously Sam’s not, you know, the best. He’s not Steve Jobs on stage, but the the numbers are just staggering. You know, the 300 million to six billion tokens per minute is the one
[00:04:01] that really jumps out. And uh it’s going to explode from here forward too because, you know, I could easily consume 10,000 plus myself just coding uh and with the number of developers coming on board and the number of home users coming on board, it’s it’s just astronomical. So, as we’ve been saying, nowhere near enough compute to keep up with it. I think Johnny IV might be the guy driving the hey let’s do this Steve Jobs style have our very first big stage developer day. Uh you know their GPT5 launch was really flat. I mean really really flat. They did a much better job yesterday. I got to believe Johnny is driving that guy. Put some money and some effort behind it. Let’s let’s go. It’s but you know they some of the most staggering things in human history got announced yesterday and they still undersold it >> relative to the implications. We’ll see it in a couple other videos here. Uh, but I I don’t know if that’s deliberate slow playing because they don’t have enough compute to keep up with the demand anyway or if it’s just they’re learning how to do showbiz on the big
[00:05:01] stage. But in any event, we’ll see some more just mind-blowing capabilities that if anything are understated >> and 800 million users uh is pretty extraordinary. They’re tracking for a billion users. And I I just wonder is this a winner takemost type scenario or is there anything that can overturn them the final result let’s go to you and then we’ll go to Alex to to uh bring us home on this one. Yeah, I think to put it in context, it’s a lot, but it’s about as many weekly active users as Snapchat. And I know which one’s going to have a bigger impact upon the world between the two, you know. Um I I think there’s still so much upside to come from here, but now you’re seeing their model with Sora 2 and others moving maybe towards an advertising model as tokens get cheaper, as they get faster. >> To put the token numbers in context, 6 billion a minute is three quadrillion tokens a year. All of the humans in the world together speak 50 quadrillion tokens a year and I
[00:06:02] expect that number to go up 10 times. So next year OpenAI is probably going to be at 30 and then by themselves the year after they’ll overtake in terms of tokens all the human words spoken every single year. >> So this is the type of >> I think that moment calculated. That’s really >> I think we’re getting close to that because Google said they’re doing a quadrillion on their billion active users right now because it’s in search and things. So, I think we’re at that tipping point now where the number of AI tokens coming into the world is about to overtake humans. And maybe the we should call it a something day, right? >> Quadrillion here, quadrillion there. Yes. >> Quadrillion here, quadrillion there. >> Yeah. Alex, what’s your take on this opening commentary? >> Yeah, I think we’re really far from saturation. So um I I I would add that in addition to being call it at about 6% saturation by comparing number of open AI generated tokens versus human spoken tokens uh per minute. I I think there’s
[00:07:01] probably an even more important statistic which is that there are approximately 4 billion human users of smartphones that aren’t yet using any sort of super intelligence if you will. Now ask yourself what happens when suddenly we’re able to 5x 6x 7x the amount of broadly accessible super intelligence across the world. I I think this starts to become the foundation for transformative economic changes at a planetary scale >> and you’re limiting that to humans and of course humans might be the least significant users of super intelligence in the final result. >> Well with full autonomy super intelligence is arguably the ultimate user of super intelligence. Yeah, >> there’s a limit to the number of words we can say. You know, it’s like 20,000 a day. Our thinking tokens are 200,000 a day. AI has no limit to the number of tokens and economically valuable tokens it can do except for the GPUs. That’s the only limit. >> Well, you know, on our last podcast, we
[00:08:00] we talked about, you know, Sam was saying we’re going to have to make a trade-off between tokens used for education for our children or token used for healthcare to save lives. But we can’t. We don’t have an infinite amount of compute. and I don’t want to make those difficult decisions. But if you know FSD is coming online and all these cars are going to start driving themselves and the the quality of the driving is directly tied to the amount of compute available. So we’re imminently going to make very very difficult decisions around, you know, tolerate a very rare car crash versus give somebody the ability to build something at home using AI. I just incredible the the difficult decisions that are coming immediately after all these functions that we’re about to see get deployed. and at the same time also limited by energy which we’ll talk to um in this conversation. I’m going to move us to a few of the features the open AI day we’ll see a few things. I I didn’t show the video here but one of the primary uh you know high points was they’re talking to apps within chat GPT.
[00:09:01] They have an uh an apps SDK and the ability for them to say to booking.com, book me this trip or Figma, you know, diagram this or Cera, teach me this. Or, you know, just speaking to Zillow, it’s the ultimate interface with all the other apps out there. Uh what’s the significance on on this for you, Emmad? >> Well, I think attention is all they need as it were. Like the battle here is that human attention is finite and so open AI meta everyone’s making a play for who are you talking to that then enables these MCP enabled agents to come and do the job. What is the 10 cent WeChat type super app that’s coming together because everyone’s folding themselves into these nice kind of things and again that’s how they’re going to try and monetize. So you’ll see this battle between Meta via WhatsApp, Instagram, things like that, Google and Open AI to try and occupy that real estate. And then of course Elon’s going to come in with X and all
[00:10:00] sorts of interesting things coming. >> Everyone’s trying to be the everything app. >> Yeah, for sure. Dave, >> well, in a second we’re going to see actually something built by voice. Why don’t we look at it and and then we can It’s actually really cool when you see it. >> The code the codeex example. >> Yeah. Yeah. >> Yeah. All right, we’ll we’ll come to that. But before I mean, I’m just wondering, you know, when OpenAI drops this capability, are they picking winners in the final result? Are they going to be equally uh you know, sort of spreading their attention across everybody? Uh and are they basically eating away all the entrepreneurial startups? There was a there was a tweet that went out. I was trying to capture it but it said okay Open AIJ just eliminated you know a million different startups out there working on on their approach. >> Remember every platform ergonomically wants to have its own app store. So I I think that the notion of an app store being built on top of a new platform where chat GPT and then presumably other
[00:11:00] frontier models as well wanting to become the new operating system or it certainly rhymes with Facebook platform moment when Facebook launched that as well. I I think that that’s a very natural market movement. But I would also perhaps caution at at some point I think it’s reasonable to expect that every pixel is going to be generated. It’s not just going to be vector art uh or HTML type graphics. Every pixel is going to be generated. So I I would view this as almost a transitory moment where apps are floating on top of chat GPT as the new operating system environment, but it’s a passing phase. at some point every single pixel probably wants to be generated. That that was my first thought. The other thought is do you remember Peter back in 1987 when Apple without Steve Jobs launched their knowledge navigator concept? >> Yes, I do. I mean >> we’re living in that now. >> Yeah, >> we’re living in that where you know professor is having a conversation with uh basically similar type canvas that is
[00:12:01] able to pop open new apps and interact with them on demand. We caught up with the future approximately 40 years later. We’re living the knowledge navigator future. >> Every week, my team and I study the top 10 technology metat trends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI, and quantum computing to transport, energy, longevity, and more. There’s no fluff, only the most important stuff that matters that impacts our lives, our companies, and our careers. If you want me to share these meta trends with you, I write a newsletter twice a week, sending it out as a short two-minute read via email. And if you want to discover the most important meta trends 10 years before anyone else, this report’s for you. Readers include founders and CEOs from the world’s most disruptive companies and entrepreneurs building the world’s most disruptive tech. It’s not for you. If you don’t want to be informed about what’s coming, why it matters, and how you can benefit from it. To subscribe for free, go to dmmandis.com/metatrends
[00:13:00] to gain access to the trends 10 years before anyone else. All right, now back to this episode. One of the examples they had here, they on their on their demo live stage, they had an individual propose a new startup. In this case, it was a dog walking uh app. And they said, “Okay, create me an image for it. Create me a name for it.” And then they said, “Okay, Canva, turn this into a deck. I want to raise money.” At the end of the day, you know, we’re not too many steps removed from, you know, chat GPT, start this business for me and start, you know, wiring the revenues to this location. Uh, I mean, >> I I I think that’s the the the multi-t trillion dollar endgame here where at some point we see autonomous corporations. >> Mhm. >> Yeah. I literally did exactly what you just said, Peter, yesterday at a red light >> uh in Cambridge as I was sitting there, created a business plan and tried to recruit a Princeton team into it via AI at the red light. Say yes, but
[00:14:00] >> that’s like that’s like when Elon said when he was driving from SpaceX back to his home in Beverly Hills and there was traffic and he goes, “Damn it, I’m going to start, you know, an a tunneling company. I’m going to it’s going to be boring. I’ll call it boring ink. I mean, and then it’s there’s literally a future in which we’re going from mind to materialization. It’s stating what you want to do and having the universe conspire to create it for you. >> That’s crazy, ID. >> Yeah. I think, you know, he has a boring company, but then he has his even cooler name of macro hard, his new software company. >> I love that. >> Against Microsoft. >> Elon is a 13-year-old kid for sure, >> which is literally trying to do this. It’s trying to create ideas to full companies entirely digitally, right? >> And I think what you’ve seen is three phases. Consumption was expensive. It became cheap. >> Creation was expensive. It’s becoming cheap. And now the valuable thing is curation and attention. So again, the battle is who can have that value for the pixels that you see, for the noises
[00:15:00] that you hear. And then a lot of that creation element is going to be abstracted away. And I think all the big players realize this. >> And the question is where does it end up? Where does it go eventually, Dave? >> Well, know that quote that you had, I’ve heard it a hundred times. You a million startups just died because of what they rolled out yesterday. It’s absolutely not true. Show me the names of those startups that died. And this came up when we were talking to Amjad Masad a couple weeks ago on that other podcast. You know, the founder of Replet, he had to build his entire foundation model from scratch to get to market because it was before, you know, OpenAI had the op APIs. And you ask him, do you regret that? You had to throw away all that code. He’s like, “No, I absolutely don’t regret it. You constantly have to change. You know, AI is going to move at this ridiculous accelerating pace. >> You’re not reinventing your business constantly. You’re dead on arrival.” Yeah. >> Yes. Exactly. And but your team is intact. If you have a great team and you’re in AI, you will succeed every single time. Yeah. Maybe something you do gets crushed by the next iteration of Open AI, but you pivot so quickly and
[00:16:01] easily, just like we’re talking about right now. So, you show me the names of those companies, those million companies that died. They don’t exist. >> All right, let’s jump into the next demo they had at OpenAI day. It is agent builder. Creating multi-step workflows without coding. I’ll just show the first few seconds of this. >> And to make this interesting, I’m going to give myself 8 minutes to build and ship an agent right here in front of you. So, I’m starting in the workflow builder in the open platform. And instead of starting with code, we can actually wire nodes up visually. Agent Builder helps you model really complex workflows in an easy and visual way using the common patterns um that we’ve learned from building agents our >> All right. Uh Immad, you’re building agents left, right, and center right now for intelligent internet. Uh what do you think of this? >> Yeah, I think you kind of gone from the creation to the now composition and the multi-stage process for image generation and media. We built something called Comfy UI, which again is this nodebased process. But where we’re going, we don’t
[00:17:00] need nodes and spaghetti. >> Exactly. >> You know, the future of these things, you can look at our common ground platform for example. It flips between camban and kind of workflows and gant charts and things. It will just show you what you need to show. And the way that you’ll interact with agents is like interacting with Jarvis in Iron Man. >> Like I think in a year or two, that’s what the agent build is going to be. You’ll just have a nice chat and it will show you all these things and mock them up instantly. And in fact, Claude had this with their latest release for the pro users, this instantly generating app desktop type thing that literally programmed things on the fly without code because code is just a human translation layer and that can be removed completely. >> For sure, Dave. >> Yeah. Yeah. It’s funny because the the people succeeding in AI are overwhelmingly really young, really, really smart with very limited business experience and they keep recreating the same mistakes from like 20 years ago. It’s okay because you know AI is such a
[00:18:01] great tailwind. But this this graphical programming language, those lines is the stupidest thing in the world in the age of AI where you can talk to to the AI. It’s very similar to in the cursor interface. if you want to upgrade your account and you’re talking to cursor like hey uh or or to Claud um 4.5 hey Claude upgrade my account and it says well go to the menus navigate to the settings like what are you talking about I’m talking to you right now you have MCP like just just do it so that’ll all get fixed very quickly but it’s it’s crazy the whole interface to AI is going to be voice >> voice and images >> and the idea that you’re going to design programs by drawing boxes and connecting with with lines which has been around since like 1980. No, no, no, no, no. So, it’s it’s it’ll it’ll get cleaned up very very quickly. It’s just kind of funny to see this transition phase and and all the same old same old mistakes being made. >> Alex, any uh any other points you want to make on on agent builder? >> Yeah, I’m reminded almost by analogy of
[00:19:00] the the early days of Hollywood that were shaped around vaudeville type design patterns. I think that that’s the stage that we’re at. This is the vaudeville on Hollywood screens stage of of AI for software development where it’s just sort of um on the one hand it’s great glad that it exists and glad that it provides probably a comforting safety net for enterprises that are migrating to endtoend agentic workflows on on the other hand very much feels like a passing phase I I think it’s an interesting modality for specifying for software development but really why not take a full leap and instead of specifying flowcharts for for individual individual workflows, why not just dump in an entire org chart of a human organization and rather than individual tasks or roles, just port over an entire company work chart and ask for an entire enterprise to be replicated. >> Vogill analogy is is great. You know, if you look at an old original black and white movie and the actors are on an actual stage with actual stage lights
[00:20:01] doing they’re doing a play and they’re just recording it on film. Uh very similar to when the internet took off and the newspapers just copied the exact newspaper over to the internet and said, “Oh, we just read it over here instead.” Same font, same everything. >> We humans are so stuck. We’re so stuck in the way we do stuff. We have such a high cost of switching. All right, continuing on this theme of voice mode over everything. Uh here’s a little video of controlling codecs with voice mode. Take a listen. Let’s see if we can actually control this camera now with this Xbox controller. There we go. It works. That’s pretty awesome. What’s funny is like I didn’t even specify to codeex which button should do what, but it figured that the joystick was probably a good idea. So, that’s that’s actually perfect. But let’s uh do the real test now. Let’s enter voice mode and see uh what happens. So, hello. >> Hi there. I can hear you loud and clear. Let me know what you need. Yeah. What do
[00:21:00] you see on the camera? >> I see a large audience in front of you with rows of attendees seated and ready. The room is well lit and the crowd stretches far back filling the space. >> That’s right. Could you uh shine the lights towards the audience? >> There we go. >> I’ve just lit up the audience with a nice bright water. They should be perfectly highlighted now. >> All right. So, this is a unusual demo for for Codeex to say the least. just showing our ability to control physical items in our environment. But I have to say I love this for one reason. I’ve always said I will invest in the first company that’s able to make AV foolproof, right? How many of us are uh in conversations or giving presentations and we can’t get this to connect to that. I just want to be able to say to my AI, you know, show that video on that screen, you know, connect me over Zoom to that screen. So there’s hope still >> and that’s a that’s a business plan that like that’s not hypothetical. That’s a
[00:22:01] business plan that if someone’s listening right now and they get together a team and then Peter Seed invests in it to give it credibility that will become yet another one of these massive success stories. It’s it’s really that simple. >> I’m on stage and I say you know something fails. Okay, you know AI is easy, AV is hard. Well hopefully AI can solve that. Well, but also controlling. Right now, you kind of wave to people that are backstage and they push some buttons or whatever. It’s crazy because the AI can now recognize your hand gestures and can respond to your voice and it’s much more engaging for the audience if you’re talking to the AV and it’s changing the lighting, changing the slides, you know, pulling up things from the internet in real time. >> Very doable. You could get that product out the door in like six months or less and just crush it. And of course, it self-demos and then Peter, you know, Peter will bring it into the podcast and it’s like it’s just that simple. >> There you go. Let’s let’s start with with uh with Alex. Alex, what’s your >> thinking? I think it’s it’s sort of interesting because so many facets of codeex are open source and and available for review on GitHub to actually trace
[00:23:02] where it >> appear. Tell us what tell us what Codex is in the in the first point. >> Codex is uh is a an open AI brand that seems to cover a number of different independent software tools. So it covers their code generation specific AI model backend. It’s also used as a web front end for software agentic software development. It’s also used in connection with a command line interface tool. So, so they they use it as a an umbrella branch as it were. But in in this case, at least one of the codecs associated projects is up on GitHub. You can review the source history. And so pulling the thread on the story, it was it was interesting I I think to to discover that at least some aspect of this functionality appears to have originated as a feature request from a third party from the Carnegie Melon affiliated software engineering institute back in April. That was uh where where a user was complaining or really pointing out that human prompt typing speed is increasingly become the limiting factor becoming a limiting
[00:24:01] factor for software development. So, >> by the way, I want to read I want to read a quick tweet here that came over from an open AI employee. It says, “Agent builder we released today was built end to end in under 6 weeks with codecs writing 80% of the uh the PRs. This matches the AI 2027 report uh in that was forecasted in 2026. Coding automation goes mainstream. Agents will uh work like teammates. AI R&D is 50% faster from algorithms. I mean we are seeing sort of I want to say science fiction but science predictions sort of tying much closer to reality. >> We’re close to the point of recursive self-improvement and and it can go in the other direction as well. We can get negative speed where the software is just written preemptively. >> Interesting. So, you know, we’re not smart enough to realize we need the software, but the AI is and it’s prepped for us in advance. Exactly. I love that.
[00:25:03] >> Immad, your thoughts on CEX here. >> Yeah, if you get enough tokens. I think this is the thing like most people are just using half a million or a million there and you know like to build something like that’s five bucks with the new Grock model. It’s 50 cents like you’re seeing a crazy thing. >> I want to come to that after we we we close on this which is you know how would you be disrupting open AI if you were going to? Um Dave, you want to comment on on controlling codecs with voice mode? >> Well, something Alex said really sparked a thought which is you know codeex when they launched it was a way to run five or 10 different coding processes in parallel and have status checks and it made you much more efficient. But now you know they use it to to kind of bundle five or 10 the different things together. >> This is going to be a real problem because we’re used to products having a very specific name and brand and doing a very limited number of things. But with AI, the explosion of capabilities is exponential and you can’t even keep up
[00:26:00] with the names. So now it’s going to be much more like these thematic branding. Like codeex is a grab bag, you know, GPT is a grab bag, but what else can you do? There’s just so much going on. So just keeping up with the names of things and naming things in general is going to be >> we had that conversation with with Kevin Wild Kevin Wheel at OpenAI that is naming protocols are kind of insane. >> Yeah. >> Yeah. this if we can add one thing um 6 months ago Dario Amadai from Anthropic said that 90% of code will be written by AI I think he meant can be written by AI and this is a really great example of that >> and so again they decided to embrace it so you see codeex the CLI the command line interface tool literally gets two updates a week which for a multi-billion dollar half a trillion dollar company is unheard of >> and so again as Alex said I think you’re going to get these self-recursive improvement cycles first with humans in the loop, but then the software might just upgrade itself and respond to what
[00:27:00] people might need. Yeah. Continuously. >> Yeah. What’s interesting is that that interacts with the interfa like like if you said my iPhone is going to update itself twice a week, you’d be confused as all hell. Like you would never know where anything is. But now that you have an AI interface on everything, it’s okay because it’s self-explaining. It’s it’s just seamless. >> I mean, I just want Jarvis. I just want an AI I talk to and it does everything I need to get done. I’m just going to assume that anything is doable and my AI is going to enable it or find the capability and I don’t need to know all the hard work it’s doing on the back end. I don’t need to know what’s calling up getting access to. It’s just making it happen. >> I’m telling you, Peter, within the virtual world, not within the physical world, but within the virtual world, that’s today. You know, no one’s productized it yet, but all the technology and capability exists right now. The robotic version of it where it makes your Iron Man suit might be a year or two or three out virtual world, you know, build me a video game, build me whatever. That’s right now. >> Yeah. >> Someone needs to go and get Paul Best voice rights, you know.
[00:28:02] >> Let’s let’s take a look at one more video from OpenAI day, which was the Sora 2 uh API and a segment I call sketch to video. And again, this is going from mind to materialization. If I can imagine something, can I make it real? Uh, take a listen. Today, we’re releasing a preview of Sora 2 in the API. [Applause] Mattel has been a great partner working with us to test Sora 2 in the API and seeing what they can do to bring product ideas to life more quickly. So, one of their designers can now start with a sketch and then turn these early concepts into something that you can see and share and react to. So let’s take a look at how this works. So if you’re listening to this podcast, what we’re seeing here uh is basically a hand sketch then being developed into a
[00:29:01] photorealistic video of a Mattel Hot Wheels toy or Matchbox toy. Uh super compelling. uh being able to go from from that and I’ve talked about in the future I’m going to be able to describe verbally what I want. I want a device that can hold a hot liquid. I want to have a handle on it. I want to have it this color. And then as I’m describing it, it’s visually materializing on my, you know, AR glasses in front of me. And I say, “No, can you make it a little bit larger? Can you stretch the dimension?” Just in in plain English. And then how much would it cost to make? It gives me a price and can you give me an alternative that’s cheaper or that has better thermal insulation and they go yeah that’s it please print it for me manufacture it for me and put it up on the web so anyone can grab it. I mean this going from again I call it mind to materialization super powerful uh you want to open up on your thoughts on this? I mean the holiday deck is getting
[00:30:01] closer, right? Not with hard lights, but as you said, that aspect is there. These models learn physics, they learn material. So in the video that just shown, the car goes down these ramps and it’s transformed it into 3D. You can have 3D extensions from it. >> One of the things you can do with these models is like you can actually do a sketchboard where you show scene by >> how every single thing changes and you have that as the input and it’ll generate that clip. >> And it doesn’t do that by thinking or breaking it apart. It literally interpolates the concept to the video. And so we’re actually only scratching the surface of how powerful these models are at the moment. And then I think as they get more and more used, you’ll see that they are genuinely world models that can create anything you can imagine and then adapt on the fly as well >> with audio to match with perfect audio to match. >> Yeah. >> I think everybody everybody has access to this, right? They just launched the API version of it yesterday for large scale use, but anyone can do this. And if you haven’t done it, you’re crazy. Do
[00:31:00] it. It’s so mindopening and compelling. Do exactly what Amad said. Do it as a series of scenes. And then right right now, you got to wait about five or six minutes to get your video back, which is really annoying. Uh, and it shows you the comput >> how quickly we are spoiled by >> Well, it shows you the compute bottleneck though. I’m sure when they do it internally, it comes back in a millisecond. You know, it is physically possible to do it very very quickly. Uh, but again, way too many users for the capability, but you got to try it because again, it’s mind opening. When I first saw this video, I I didn’t get it because I couldn’t tell. The video is actually synthetic. I thought I was like, “This guy’s sketching a toy, a Mattel toy, and here’s the toy.” Like, so what? Like, oh, wait, that’s not a that toy doesn’t even exist. That’s that’s actually been synthetically created. That it’s just so good. The video has perfect physics. You know, you just would never know that it’s synthetic. Uh, Alex, what does this mean in the final result? Where are we going here? >> This is mechanical design getting
[00:32:00] solved. MIT, the mechanical engineering department, has an entire set of courses just devoted to training the next generation of mechanical engineers how to do product design like this. We’re seeing right before our eyes an entire discipline or subd discipline get solved in bulk by generative AI. And I think maybe even more interesting than this particular instance is the API pricing. So if if you go to the the API p pricing page now for for Sora 2, it it’s 10 cents per second for the base model. You do the arithmetic that’s $360 per hour. Assume 10x year-over-year hyperdelation model costs within the next year. Suddenly, it’s far cheaper to outsource mechanical product design to an API call to Sora 2 or whatever it evolves into than a human. That’s an entire hyperdelationary field getting solved overnight. >> Okay, keep those numbers top of mind because when we start talking about compute in a minute and the cost of compute, you’ll immediately recognize what what Alex just said. you know, that
[00:33:01] 10x deflation in price. We need that desperately because the demand for what we’re seeing here is going to be orders of magnitude bigger than the amount of compute currently available. >> What an amazing time to be a kid, right? Imagine you’re sitting down with your mom and your dad and you’re just describing what you want as a toy or what you’d like your toy to do and all of a sudden it’s materialized into a video for you and then some other enterprising company in the 3D printing world says, “I can just manufacture that for you as an end of one.” I mean, just amazing. >> Star Trek replicators aren’t 24th century. They’re they’re now just 2025. >> We are really bringing Star Trek to today. That makes me so happy. I’m so happy about that. >> Why wait a few centuries? >> Yeah, for sure. All right, so uh we’re going to wrap on the Open AI day there, but I’d like you to jump in here a second. Um you know, we’re seeing a half a trillion dollar valuation for Open AI. We’re seeing open AI really working hard
[00:34:00] to create multiple revenue flows from advertising from selling products in a multitude of other areas. What are your what are your thoughts on open AI? So I think that the core business of open AI in terms of the monthly chatt subscription is going to come under challenge because we’ve seen this breakthrough with deepseat gro 4 and others where the cost per million tokens is literally dropped 20 30 times and so the basic chat experience is not good enough anymore. So almost like you see these levels of AI that will fill. So the chat experience is basically a couple of bucks a year when you calculate now in terms of the cost down from 200 bucks just over a year ago. So now they have to think about agentic workflows. They have to think about economically valuable workflows and then even beyond because the number of tokens goes from 2,000 to 20,000 to 200,000 to 2 million. And so this is why when we see Sora, they’re doing likenesses and they’ll be doing advertising and more because how do you have the cash flows
[00:35:01] to justify that? Google and Meta both have the advertising cash flows. >> Mhm. >> How do you monetize those 800 million users? Either by delivering excess value through your $20 a month subscriptions or by having these new verticals because your competitors are going to release what was your key product at the start of this year, Chat GPT, for $20 a month for free because that’s how far and how quick token prices have dropped. >> Yeah. I mean we’ve talked about the notion that open eye is really trying to do a global land grab right going into India going into the where you are Immad in the UK going into Greece going other locations I mean and it’s interesting battle between its land grab and then you’ve also got all of the open- source models coming out of China uh which are which are going after a a land grab as well. Um, >> well, you know, Paul Graham said Sam Alman if you dropped him on an island full of cannibals and came back a year
[00:36:00] later, he would be running the island. Uh, so I mean, he’s got to be the b one of the greatest business strategists of all time. And so he’s going after India. He’s going after a massive installed base. He’s got an 800 million user installed base. He’s going after the rest of the world. And he’s also going after the data centers. And we’ll see that later in this podcast. So I think he’s narrowed in on the the two foundational points of control in this great battle are installed base of users and massive amounts of compute. If you control the end points, everything in the middle will fill in. That’s the way the way I think he sees it. >> This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and
[00:37:00] pre-ompiles code for each task. Blitzy delivers 80% or more of the development work autonomously while providing a guide for the final 20% of human development work required to complete the sprint. Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their preIDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. >> All right. Uh I call this section meanwhile in the continuing AI wars. Uh let’s hit on a few others. Anthropic nears superhuman computer use. And here we’re seeing a graphic of uh of performance as a percentage uh hitting human performance very close to it. and
[00:38:00] we’re seeing uh basically over the last year. Alex, do you want to kick us off on this one? >> Yeah. So maybe a comment first on what the benchmark is. In the past on on this podcast, I’ve beaten the drum for the importance of benchmarks more broadly for not just measuring progress, but also accelerating progress. In this case, the benchmark OS world for operating system world is really lovely benchmark that was initially developed by Salesforce and colleagues. And it’s a benchmark that measures the ability of a computer use agent and an an AI that has access to a keyboard and mouse and screenshots to be able to conduct regular everyday economically important tasks on Ubuntu, Linux, Windows, and Mac OS. Hundreds of different types of tasks. And and so what Anthropic is demonstrating with this chart is probably again by the law of straight lines perhaps by the end of this year in the next few months we’re going to see at least from Anthropic putting aside other other frontier labs superhuman performance at the ability to control
[00:39:00] computers for normal everyday tasks. >> So Alex and Ahmad I I asked uh Perplexity Comet what does this benchmark even mean? It’s really vague and it came back with some complete garbage answer. So hopefully you can you can fill me in like what are we measuring here? We’re we’re measuring the ability for an AI to literally control uh Windows type interface with mouse control and keyboard control and perform a variety of tasks. Web browser navigation that would require >> it’s ultimate ver it’s the the ultimate you know uh verbal interface, you know, do this for me >> without the verb. >> I don’t need to know. I mean, I just set up a new MacBook Pro and getting all of the settings back to where I wanted it, it just ate up a half a day of wasted time. >> Yeah. Yeah. >> Peter, you want Jarvis, this is Jarvis, albeit not in the physical world for Jarvis for controlling your computer
[00:40:00] across applications, but this is a pretty good benchmark for Jarvis for computer use. There are companies that are also setting up giant science factories controlling, you know, hundreds or thousands of experimental devices, right? Where it’s uh just basically putting an AI layer on top of all of them and running 24/7 dark experiments to ferret it out the breakthroughs of science. Um anyway, uh Immod you want to add to this? you know, it’s 360 odd tasks that take over your computer. Out of the labs and things, it’s a different kind of reinforcement learning environment. I think what this is showing is that these generalist models are getting good enough to do most human standard tasks. And again, these models have economies of scope. So now we’re seeing thinking machines and others building RL environments so they can plug into the real world even more seamlessly. And I don’t think anyone believes that that line isn’t going to
[00:41:01] break through the human level. Again, this is the takeoff point. And so when they can control anything we can control digitally and then physically, >> then it’s only a question of the number and quality of tokens behind that. And so again, this is the takeoff point. This is why we’re about to see >> and what could possibly go wrong. >> I would say what could possibly go right and quite a bit can go right. >> Yeah. Okay. Thank you for bringing me back to the world of abundance, Alex. I appreciate you. >> Anytime. >> All right. And our our next uh our next news item here is a major update to Gro imagine uh going from V 0.1 to V 0.9. I love the the numbering protocols everybody. And also uh Elon entering the gaming world or at least announcing you know Elon if anything else is a gamer and the video gaming industry is massive you know uh you know outweighing uh entertainment by you know Hollywood
[00:42:00] by a long shot. Let’s take a quick look at a video clip. Uh and the thing that’s important is Grock imagine can generate 15-second clips. Uh, and their comment is, “We’re focusing on speed and fun.” All right. Well, let’s take a look at some speed and fun. Grock launched as a truth seeking AI. >> And I love love that it says Grock launched as a truth seeeking AI. And there you see Elon as this, you know, medieval emperor, you know, in battles. It’s like, okay, this is the truth. We’re see we’re seeing this. But I I think even just t taking that line, truth seeeking and combining it with these models. I I completely buy the the notion that video as a first class modality when incorporated into chains of thought is going to help us to discover the truth.
[00:43:00] I I think it it’s one of the the key modalities for understanding our universe. Okay. What what does that mean, Alex? Dive in a little bit deeper, please. >> So, when you ask a question of chat GPT or some other frontier model, now post chat GPT5, there’s thinking that goes on usually under the hood. It it thinks internally sequence of tokens before it produces a final answer. Right now, almost all of that thought takes the form of text tokens. But imagine a near future where the the agent, as it were, is able to think not just in terms of text, but in terms of video. It’s able to hallucinate a short video clip imagine, you know, basically visual imagination imagining things that you can introspect as well. You can pop open little drop down and see the little videos that it’s it’s generating as part of its chain of thought before it answers your question. Video reasoning, I think, is going to end up being a killer app for how these video models that right now are obviously largely aimed towards entertainment end up delivering transformative economic
[00:44:00] value. >> Amazing. in our you know our occipital cortex our our neoortex for visual image understanding processes much more data than our ability to to bring it in language >> yeah so open AI did $4.3 billion in revenue in the first half of the year the video game market did 200 billion in revenue last year so you can see when we think about gaming when we think about media this is a massive market to go after and you know ex Elon are going to go after it from a first principles basis whether or not the games will be any good that’s a question you know I think they’ll probably be quite addictive um and again the scarce things in the world there’s Bitcoin there’s my financial coin there’s human attention the battle for human attention is the next battle for revenue >> and everyone is basically drawing their lines getting their GPUs ready for it >> so I think we’ll see this type of thing from everyone and it’s good for consumers in many ways because the
[00:45:02] quality bar will lift and the access will expand. >> All right, I we can go so deep into that entire conversation, but before we exit, uh meanwhile in other AI wars, I wanted to play a quick clip and say a thank you to one of our subscribers, CJ Truheart, who heard our call for a Moonshot theme song and proposed one. Not saying this is it, but I was super impressed. Okay, let’s hear what he has to say or sing or produce. >> So, I recently heard you guys mention on the last podcast that you were going to create a Moonshot theme song. And for someone who’s who’s been using Sunno for two years and and uh especially since uh Moonshot’s podcast is is my favorite as far as AI and technology goes. Um I really appreciate you helping me be able to understand what’s happening and give
[00:46:01] me a perspective for my entrepreneurial creative mind to best position myself. Made you a customized um theme song for the moonshots. [Music] WHERE THE MOON SHOT ME BREAKING THROUGH THE noise just with a clarifying voice in a races disruptions never clean. We’ll show you what it means. The story between [Music] tomorrow. [Music] >> Love that. >> Thank you, CJ. I love it. I love the fact that you pulled over to shoot the shoot the video, too. That’s just awesome. Much appreciated. >> Yeah. Just I appreciate I love our
[00:47:02] subscribers. They’re just uh they’re generous. They’re intelligent. They’re creative. And just a shout out to all of you guys. Thank you. We love your feedback, your input. We read it. We consume it. All right. Uh let’s jump into our next segment. Chips and data centers. A lot going on there, but probably the single most important news. AMD and OpenAI announced strategic partnership to deploy 6 gigawatts of AMD GPUs. Uh Dave, let me go to you, buddy. Yeah, I stock moved what 30% on the news, which shows you Sam’s ability to morph the world or warp the world to his uh perspective or whatever whatever he says. Massive massive impact on a huge public company. Uh and uh you know, it’s it’s interesting. He’s going to get 10% ownership or OpenAI will get 10% ownership if they hit milestones for basically no price. Uh and how often do you get to negotiate a deal like that? Unless you’re the president of the United States, in which case you can
[00:48:00] negotiate all the time. >> Yeah, I guess that’s true. The reason this is a serious win-win, though, is um you know AMD is they have capacity to manufacture with TSMC and anyone can design inference time chips uh and and sell them out, but you have to have the manufacturing capacity. So Sam’s going to grab that capacity via AMD. Uh, I’m really curious on November 14th to look at Leopold’s 13F filing, you know, from the situational awareness hedge fund and see if he also bought AMD and got that 30 or 40%. >> He probably did. >> Probably did. Yeah. >> I mean, Dave, isn’t this I mean, we could have predicted this as well. At the end of the day, we, you know, talking about Intel uh and the criticality that capability, you could have said the exact same thing about AMD. Who else? I mean, there’s Broadcom, uh, there’s uh, Micron. which of these other chip manufacturers are going to be pulled into sort of this US- ccentric uh
[00:49:01] chips first strategy? Well, I’ll tell you what else. If you drill a layer deeper underneath the chips, there’s a whole bunch of other material that will get dragged into the vortex that no one’s quite realized yet. So if you really want to see these 30 40 50% pops, you look a layer deeper than just the chip companies into the underlying, you know, you’ve got, you know, silicon bools, you’ve got glass, you’ve got, you know, all this underlying manufacturing infrastructure that’s all just going to get sucked into this same exact vortex. And you know, a lot of those are public companies and some of them are smaller, too. So the the movement is much bigger. >> Yeah. Emmod, thoughts on this one? I mean, he’d probably just be calling everyone now and saying, “Hey, you want to give me warrants? Your stock price will go up, right? To all the companies.” >> Can you imagine that if he if he ironically did this exact deal 50 times back to back? The amount of value that would create. Oh my god. >> Just all the SAS companies. Come on, partner up with me. Right. Here’s the
[00:50:00] >> Hey, if you want to do a deal with EverQuote, I’m the chairman of that one. Just give me a call. We’ll do we’ll do this deal tomorrow. You’re right. I do I do wonder if he’s using GPT6 Pro to kind of come up with these deals, but I mean this it’s massive. >> If you look at the 10 GW that they’re doing with Nvidia and the 6 GW here, it’s about $50 billion of buildout per gawatt. >> So it’s about $800 billion of buildout, like a trillion that they’ve already got, I think. Probably more. >> Amazing. And completely sold out. Sold out years in advance. >> Sold out years in advance. And you know again the only market that can sustain this and incry the revenue that is if they’re going after the entire like all software jobs effectively. So I think in the next few years you’re going to see basically OpenAI and others replicate the whole macro hard strategy of fully autonomous workers. that is the product that they will bring to the market and they will cost like 10 20,000 30,000 $100,000
[00:51:02] and that’s the only thing I can see that will fill this particular massive amount of >> Alex are you going to stick with your efficient market hypothesis from uh two podcasts ago or are you going to just start tracking the tail number of Sam’s jet and seeing who he’s meeting with next? Well, I I one might imagine losing sleep as a public market investor that maybe the singularity as it were happens in some private company where there’s indirect at best exposure via public markets. Like what happens if Open AI and call it the the 10 other largest privately traded companies suddenly have an intelligence explosion and are worth tens of trillions of dollars overnight as a as a public retail investor. That’s perhaps a suboptimal outcome. So, so I would actually view this as through a very positive lens that through indexing, through exposure to AMD, Intel, etc., this is now an enormous jump in exposure to open AI to the extent that an intelligence explosion happens there. Let me uh hit on a couple
[00:52:02] of of these uh related stories. So, BlackRock is buying up to 78 data centers totaling 5 gawatt in a $40 billion deal. Um and then we’re also seeing here Corning uh is posed to dominate AI data centers with optics obviously for for fiber optics for connecting everything uh on these two topics of of Corning and Black Rockck. Uh let’s get some commentary there. >> Yeah, I mean that’s the war for the downstream kind of elements here, right? like Black Rockck coming in with that 40 billion. They’re coming about three times what the normal multiples are like you need to deploy capital and this feels like currently the best capital to deploy. Downstream Corning is kind of optimal here but half I think something like half of all GDP growth in the US this year is AI >> which is insane.
[00:53:01] I mean, comparing to where we were even just a year ago or two years ago, >> um, it’s >> it’s an economic transformation story for the US at at a minimum. The the company that Black Rockck is purportedly considering buying many of the the campuses that they’re converting to data centers or are brownfields, including according to public reporting, uh, former coal plant in Ohio. This is what economic transformation, industrial economic transformation at scale looks like. and then it is the it’s the world it’s again we’re on a war footing we have to realize that we’re in just preWorld War II we’re converting automotive plants into aircraft plants we’re tiling uh I mean you know Santa Monica airport where I fly out of was basically build out as a secret manufacturing and uh airport hub uh it’s it’s happening and it’s >> this is programming of the entire industrial base Yeah. >> Yeah.
[00:54:00] >> Yeah. And also uh it’s another investment theme just for our investmentoriented listeners. Uh one of our best and most prolific partners Kush Bavaria is starting a new company with Alex’s help. Uh that funnels money into data centers. But it’s part of a broader theme of if you know this is half the GDP growth of the c country and accelerating there’s all this pentup capital all over the world that’s not investing in things like corning. So if you can create new conduits of the money into all the implications you know so Alex has been talking about photonix for months now and the leap from there to saying oh Corning is going to benefit is not a huge leap. So then you know the capital just needs to get into these avenues to keep this engine humming and so uh you know new entities new funds you know black rockck is obviously very very smart money pouring into this area but then all the other implications you know you know data centers and new geographies and pumped hydro and what about the equipment for pumped hydro and solar installation costs all those
[00:55:01] things all are investment opportunities I >> I mean is there I mean is this an infinite sync in other words it’s going to attract as much money and capabilities and resources. Uh, you know, is there is there any moment where the music stops and uh there’s not enough chairs for everybody who’s invested? >> It’s easy. It’s super super easy to calculate. Now, it’s an infinite demand, no doubt, but it’s limited by chip fabs. So, if it gets overbuilt or overinvested, it’s just purely because, you know, too much of X for the number of chips. But, you know, the upper bound is based on the chip fabs. And you can see those coming four years in advance. >> Mhm. >> And so, you know, it’s all bottlenecked at at Intel, TSMC, and Samsung. So, from there, you can do all the math in both directions in terms of data centers and users and everything. >> Well, we my mental model >> Go ahead. Go ahead, Alex. My my mental model continues to be that the music can continue as long as the transformative
[00:56:01] applications continue. As long as we’re driving the cost of the service economy to zero, as long as transformative discoveries and scientific inventions pour out of these super intelligent boxes, then the the music can’t continue. The the data center buildout can continue to the point of trillions of dollars of capex. We just need the transformation to continue and the revenue generation that results from that. And the transformations, you know, optical like, okay, nothing was optical, now it’s all going to be optical. Corning, huge beneficiary. Nothing was liquid cooled. Now it’s all going to be liquid cooled. The Jeff Markley told me he bought a million valves. Why’d you buy a million valves? It’s like, well, because if water starts leaking out of a pipe, you need to isolate it quickly. These are like, you know, $60,000 in a single one U. You can’t have water dripping on them. So, I need to But there aren’t enough valves in the world. So, I bought them all. >> And then there’s the under there’s the underlying problem here of energy production, right? We’re about to see energy begin to spike. We’re seeing
[00:57:02] certain communities that are voting against opening up data centers because they don’t want to have it soak up all the energy. And so are we going to get differential pricing where data centers are paying this much per kilowatt hour versus homeowners playing paying a different otherwise we’re going to have you know communities basically blaming uh you know the AI tech bros for taking their jobs and hiking up the cost of electricity and that does not bode well. I I think that the scenario where uh new data center deployments continue to be connected to to utility scale grid is probably implausible at this point. There’s there’s simply too much demand for colloccated new energy output that is completely off-rid. As long as the regulatory environment continues to be favorable, and it it does continue to be, I I think we end up it’s more likely we end up in a future that looks like Colossus where there are coll-located NAT gas and soon SMRs and fusion plants
[00:58:01] in a few years and all of that is by default disconnected from the broader utility scale grid. Yeah, I think that you you had Jeff Bezos who is a pretty smart guy saying we will have gigawatt data centers in space and when you actually do the math it actually makes sense in a few years when you look at payload costs you look at chip costs you look at again power with solar and that’s just something that’s crazy but again it just shows the demand for these things >> yes I know Eric Schmidt has a great deal of interest in that vision as Well, all right. I’m going to move us on to our last conversation topic for today, keeping this WTF episode sharp and fun, and that’s on robotics and the release of FSD 14.1. So, uh Elon has uh released as promised uh something that’s got 10x more AI parameters. I love this. Navigation and
[00:59:02] routing are now handled by Tesla’s neural net. uh can help you find detours, unexpected obstacles. You know, I’ve had my Tesla drive me into uh you know, situations that shouldn’t I should have gone into uh robo taxi style upon arrival. So, you can now select precisely your arrival option where you want to park in the street, in a garage, in a curbside. And Elon’s words, V14 feels alive. Um, of course, this is just the prelude to the entire automation of driving across every sector. Who wants to jump in here? >> Tell you one thing that’s one thing that’s new is uh, you know, with the big screen and with FSD, you can watch the podcast on screen safely while so you don’t have to have Peter describe every video to you. Anyone? >> Let us know if you’re watching this while driving. Yeah, I think that this promises to be a a big jump over 13.2.9.
[01:00:02] And I I think aspirationally also represents the beginning of several different forms of convergence. The convergence between obviously robo taxi tech stacks and human driven or supervised driven autonomy tech stacks. obviously less obviously I I think we’re I I would expect we’re going to see over the next few years maybe 2 to 3 years a sequence of subsequent conversions I uh convergences I would expect to see for example the Optimus tech stack converge with FSD maybe in in some future version and what what the at the core I think what we’re what we’re seeing is the emergence of a vision language action model VLA model from Tesla that’s just endto-end embodiment it it works in cars. Hopefully, it works in in Optimus robots as well. I would expect to see from all of the other major frontier labs also singular consolidated VLA models that work across a variety of different embodiment. Amazing. Um, speaking about VA models,
[01:01:02] uh, so out of Google, we’re seeing the next gen of physical agents, Gemini’s Robotics ER15, play a little video. If you’re watching this on YouTube, you can see the model is identifying everything on your desk. And so it helps robots think through complex realw world tasks. Uh reasons like a human model outperforms GPT5 on embodied reasoning and pointing accuracy. Uh Emod, you want to comment on this one? >> Yeah, I mean what are the brains of robots? is these joint vision language models um that can basically think and reason. And the crazy thing about this is like to do this a couple of years ago, you really need to have very high performance chips with a thousand W of electricity. If you look at how efficient models like this are, you can extrapolate out. You can see they’re actually going to be possible on edge compute, which just opens up the
[01:02:00] opportunity so much. And again, I think as Alex said, this is why you’re standardizing around specific stacks, just like Dojo was stopped in favor of the edge compute at X, for example. So, I think we’ll see these very specialist chips and these very specialist models for them with tremendous capabilities that can then act as a basis to learn any given task effectively. >> So, I mean, is everything becomes smart? Everything understands its context where it is and you can speak to anything and have it understand what you mean. Alex, where does this go? >> It gets even better than that. I I just in in line with what we were discussing a few minutes ago about our living in the sci-fi future. You you can’t make this stuff up. The the safety benchmark for for Deep Mind Gemini’s robotics VLA model is named Azimov. And it it’s a of course and it it’s a benchmark that’s uh semi-ynthetic but it’s based on lots of different visual/ language/action scenarios uh and the relative safety
[01:03:02] thereof. And the beauty is if you actually go and read the Azimov paper, Gemini, the Gemini team in Deep Mind are benchmarking the safety of Isaac Azimov’s three laws of robotics against better constitutions for safety of these embodied robotic models. And turns out that there are in fact better constitutions for constitutional AI that one can come up with beyond those three laws. But the very fact that we’re now at a point in in our future history where we’re benchmarking the three laws of robotics against other better models, it’s amazing. >> I I I love the I love the group at at Deep Mind and Google. Thank you for uh for what you’re doing. >> Um >> well, Alex, this week we’ll close our investment in uh the I don’t know if I Yeah, Andy Systems. Who know who cares if that leaks out? But, uh, incredible company, uh, that, you know, picks through all the recycling using this exact technology you just saw in the video, pulls out the precious and rare
[01:04:01] and valuable metals, the rare earth metals, uh, and then gets them back into recycling for the next generation of chips and computers, uh, right out of Wall-E. I mean just the and and it shows you how this human paradise is possible where you know everything can be cleaned, sorted, fixed, repaired using this exact vision capability you saw in that video. >> Love it. Love it. >> Alex, your your investment picks so far are still 100%. So add this to the >> no investment advice for me. >> These are private. That’s okay. >> I’m going to show this video of of Tesla’s optimist learning kung fu just because it’s so cool. Let’s take a quick look.
[01:05:03] Now, if you’re listening rather than watching on YouTube, we just saw Optimus with a kung fu sparring partner making some impressive moves. And I’ve got to imagine just for it to actually be impressive. That was not a human controlling optimist that that was its uh its AI model in the world. Anybody have any counterveailing evidence of that? Elon has actually said in connection with this that it was autonomous. It was not teleoperated. >> Fantastic. uh you know, we’ve seen we’ve seen our friends from uh uh from Unitry, you know, doing impressive work, but Optimus towers over the the G1 from Unitry. So, you know, it’s we’re not too far from mech bots fighting in the ring train by imitation learning. We’re we’re we’re so painfully close, I think, at this point to unlocking physical labor and solving physical labor. Remember in
[01:06:01] in the services economy approximately 2/3 of of all of the the service labor ultimately is connected to some sort of physical task. So think of of how in the future so many tasks that no human would ever want to perform for which there there aren’t any jobs even can just be automated. Yeah, I think I think the fact that it’s all neural network based and imitation learning, that’s a really important point because people who’ve been working in robotics, you know, I had dinner with the founder of I I robot and he’s all cynical about, you know, robots are slow, robots, what it’s just it’s not true because it’s all neural network driven now. The pace of development and that the smoothness of the mo movement and the the dexterity is going to skyrocket because it’s all neural net based. >> Yeah. And so >> I need to jump shortly, but some some closing thoughts here, pal. >> It’s again the most exciting sci-fi times to learn kung fu is going to be like a couple of megabytes. And to do any task, it’s probably not going to be more than another couple.
[01:07:00] >> But models once again, >> you’re going to have to wait for the neural link to get better for that. I think again we’re just at this tipping point and the tipping point is in the next like six months across just about all of these. >> Yeah, Alex, you’re >> we’re going to we’re going to need these capabilities for data center construction. If we’re going to achieve 250 gawatts by the early 2030s, we may not have the the human labor to to accomplish that. So, one, as you know, Peter, I’m always looking for what the innermost loop of of the tech tree is. in in this case mixing metaphors and it it increasingly to me at least looks like the innermost loop is going to look something like a recursive self-improvement of robots building data centers training better robots >> robots robots building robots first that are then building data centers uh that are then putting out the you know digital super intelligence to increase the efficiency of the materials that the robots are built out of and the
[01:08:01] efficiency of the energy used to pump into data centers. It’s It’s a hyper exponential. I can feel the singularity coming. >> You’re feeling the AGI. >> I’m feeling the ASI. Oh my god. >> Right. >> Yeah. Dave, thoughts to close us out. >> Well, my final thought, tomorrow’s my 25th wedding anniversary, >> and so when Mora sees this podcast, she’ll see I I bought two tickets to Bermuda for the weekend, so we’re gonna spend a ton of money and she should see that. It’ll be concurrent with the podcast. So, uh, go ahead and open it. >> Yeah. And my question ultimately is, as we hit longevity, escape velocity, uh, does till death do us part hold out for hundreds of years? We’re going to find out. >> That’ be awesome. That would be awesome. >> Uh, so I went to Tiffany’s and and I bought something. I swear it’s made of vibranium and and set with infinity stones given the pricing it, but dealing with people in a physical store is the worst form of torture for me that I can
[01:09:01] possibly endure. Uh so that’s the that’s the real gift. >> My god, amazing. >> Immod and Alex, uh grateful for your brilliance as always and uh see you guys next time. Everybody listening, thank you for subscribing. Thank you for being part of our community. Uh super pumped the speed of uh of this these breakthroughs. I mean, I don’t know how you asmtoically approach infinity, but we’re we’re going to watch it happen. All right, take care, guys. Every week, my team and I study the top 10 technology meta trends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI, and quantum computing to transport, energy, longevity, and more. There’s no fluff, only the most important stuff that matters, that impacts our lives, our companies, and our careers. If you want me to share these meta trends with you, I write a newsletter twice a week, sending it out as a short two-minute read via email. And if you want to discover the most important meta trends 10 years before anyone else, this
[01:10:00] report’s for you. Readers include founders and CEOs from the world’s most disruptive companies and entrepreneurs building the world’s most disruptive tech. It’s not for you if you don’t want to be informed about what’s coming, why it matters, and how you can benefit from it. To subscribe for free, go to dmandis.com/tatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode. [Music]