AI Insiders Breakdown the GPT-5 Update & What it Means for the AI Race w/ Emad Mostaque, Alex Wissner-Gross, Dave Blundin & Salim Ismail | EP #186

Download this week's deck: http://diamandis.com/wtf Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends Salim Ismail is the founder of OpenExO Dave Blundin is the founder & GP of Link Ventures Alexander Wissner-Gross is a computer scientist and investor. Emad Mostaque is the founder of Intelligent Internet (https://www.ii.inc) – My companies: Test what’s going on inside your body at https://qr.diamandis.com/fountainlifepodcast Reverse the age of my skin using the same cream at https://qr.diamandis.com/oneskinpod Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding –- Connect with Peter: X Instagram Connect with Dave: X: https://x.com/davidblundin LinkedIn: https://www.linkedin.com/in/david-blundin/ Connect with Salim: X: https://x.com/salimismail Join Salim's Workshop to build your ExO https://openexo.com/10x-shift?video=PeterD062625 Connect w/ Emad: https://x.com/emostaque Connect with Alex: linkedin.com/in/alexwg Listen to MOONSHOTS: Apple YouTube – *Recorded on Aug 8th, 2025 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Peter Diamandis?

  A huge amount of expectation on GPT-5.

• 0:03Speaker 01

  The anticipation of this launch was up there with the top three product launches of all time.

• 0:10Speaker 02

  This is when you see real big things happening, either a productivity boom or the inverse. You can see you're just reaching that level now across just about everything.

• 0:19Speaker 01

  They cut the cost of AI at least in half, if not more, and they caught up to everybody else in coding. That's a big, big deal.

• 0:27Speaker 03

  When we talk about abundance in all of its many facets, taking 700 million people and suddenly giving them access to state-of-the-art AI, I think, becomes transformative.

• 0:36Speaker 04

  Just go all in and start turning your business into an AI-native business.

• 0:41Speaker 03

  This leads to Peter's abundance state, I think.

• 0:44Speaker 01

  I think what we're starting to see here is...

• 0:49Peter Diamandis?

  Now that's a moonshot, ladies and gentlemen.

• 0:54Peter Diamandis?

  Hey, everybody. Welcome to another episode of WTF, Just Happening Technology. I'm here with my moonshot mates, Salim and Dave, and two special guests, geniuses. You've met them before on WTF, if you're a listener. And Dave, would you introduce AWG? I think that'd be important.

• 1:11Speaker 01

  Alex, yes, I'd love to introduce Alex. So, he, yeah, genius is probably a good word. Math, physics, and computer science degrees from MIT. True polymath, understands everything, and we're going to talk about a lot of it today. PhD from Harvard, in addition to that, in physics, and reads literally every document, every research document, every breakthrough in AI and many other fields. So, always incredibly informative to have him.

• 1:39Peter Diamandis?

  Welcome, Alex. And Salim, would you do the honors with Imad?

• 1:44Speaker 04

  Sure. So, Imad is one of those folks where every time he says something, you have to take twice the time to parse what he just said and make sense of it. More intelligence per word density than most people you've ever met. A founder of Stability, Diffusion and Stability AI, a former hedge fund quant, brain size of several planets, and building, I think, a systemic layer for the next version of the Internet with crypto built in, which I think is really powerful. So, welcome, Imad.

• 2:12Peter Diamandis?

  So first of all, I literally just landed from a week in Portugal, so my head is still spinning after a 12-hour flight. But hey, what could possibly go wrong? Today, we are speaking about two or three special events this past week, in particular, the announcement and launch of GPT-5 and the continuation of the AI wars. But before we get there, Salim, I think you've recently gone through surgery, or is that just a...

• 2:38Speaker 04

  Yeah, I had shoulder arthroscopy, where they drill three holes in your shoulders and do kind of an oil lubin filter on it. I had a bone spur and pinging on the tendon, etc. What's incredible with the advances in technology today, I was in and out in like two hours. It's like unbelievable that they go that deep into your body and then you're just out again. It's amazing. So fascinating.

• 3:00Peter Diamandis?

  Don't forget the access homes.

• 3:02Speaker 01

  I was gonna ask you to play tennis this weekend. I guess, I guess we're not playing, huh?

• 3:06Speaker 04

  No, not for a little bit. And my right hand is, yeah, we'll leave that for another time.

• 3:11Peter Diamandis?

  And this is a special episode because I'm filming in the new Moonshot's podcast studio. So check out the background. Hope you like it. It's a real background. We'll be doing a lot of episodes from here in the future. Imad, you're in London and it's midnight or something like that.

• 3:27Speaker 02

  Yeah, it's just time for the brain to get going.

• 3:29Peter Diamandis?

  You're amazing, buddy. And Alex...

• 3:33Speaker 04

  At that time, maybe his brain slows down a little bit so we can understand everything. That's my quote.

• 3:37Speaker 02

  We'll find out.

• 3:38Peter Diamandis?

  And Alex, you're in Boston. Where are you today?

• 3:41Speaker 03

  That's right, Cambridge, Massachusetts.

• 3:43Peter Diamandis?

  Yeah, center of the known universe, at least for us MIT alums.

• 3:47Speaker 03

  Certainly the center of Cambridge.

• 3:49Peter Diamandis?

  All right, let's dive into this episode. I'm gonna start with this note. This is Sam Altman. Two days ago, he made the announcement of GPT-5. And in particular, this is the quote that stuck out. GPT-5 is a significant step on our way to AGI, which also means it isn't AGI yet. So I have a question for you guys. We also saw the day before this announcement, Sam put up this tweet showing the Death Star. And now, I have to ask, I don't get it. It's like, when he put this up, it's like, what is he trying to do? Get views? Or get people really worried?

• 4:33Speaker 01

  You know, a lot of this launch was pretty uncoordinated, but there were Kevin Wile also posted something with Elmo with the fire behind him saying, you know, it's coming. So there was a lot of sort of pre-event tweeting and buzzing or X-ing and buzzing about something huge is coming. And I don't know why a Death Star, you know, but a lot of people talked about it already.

• 4:52Speaker 04

  It feels not a great look, you know, I mean, you're trying to get people accepting and happy about the future and you show that imagery. It's kind of like, okay.

• 5:03Speaker 02

  Well, one of the Google people posted the Millennium Falcon and he said, no, we're meant to be the rebels. So he said, this is meant to be the point of view of the rebels.

• 5:11Speaker 01

  Oh, okay. There you go. That makes a lot more sense.

• 5:14Speaker 02

  And everyone's like, nah, that's not the case. That's way too subtle.

• 5:19Peter Diamandis?

  So here's my question. We go around the horn, you know, a huge amount of expectation on GPT-5. And I would love to ask each of you, what do you think of it? What'd you think of the announcement? It was a little over an hour. Let's start with, with Imad. Imad, what'd you think?

• 5:37Speaker 02

  Yeah, so it was kind of in line with what I expected because when you're doing a AI for like 700 million people, it's very difficult to do like a mega AI. And so we'd be guided to it'd be a multi routing type of thing from mini up to pro. And that's kind of what we saw. It was like basically O4, but with one front layer. So I thought the announcement was okay. It's just the expectations are so high now, particularly when you build it up, that you just have to keep on beating every time by more than a little bit. I think we all thought it would beat, but the question was how much? And it was like, eh.

• 6:15Peter Diamandis?

  Okay, was it eh? Alex, how about you, buddy?

• 6:19Speaker 03

  I tend to think the, the real net impact of a launch like this. Tends to be more about lifting hundreds of millions of users up from a model like GPT-4O to a frontier model. And I think the changing economics of a radical cost reduction of frontier models, these are going to be, I think, the long-term impacts, to the extent there were expectations that there would be an ontologically shocking moment when there would be new qualitative capabilities that would come online. I tend to think that ultimately lifting hundreds of millions of new users to frontier level and getting them to interact at scale with a frontier

• 7:00Speaker 03

  model, over the long term, that's going to be just as impactful and just as economically relevant as introducing some jaw-dropping new qualitative capability.

• 7:11Peter Diamandis?

  Yeah, I hear you, and that is true. I mean, that's what Sam's mission was, deliver a single user interface that enabled you to do quick answers or do long, detailed research and coding. You know, Salim, do you remember you and I were together up in the Bay Area with Dave in Boston when Google I/O came out? And there was so much, holy shit, holy shit, holy shit moments when Google I/O was showing their capabilities. What did you think about this, Salim?

• 7:46Speaker 04

  I have the same reaction as Iman, which was, eh, it's not 10x better than what was there before. I think I'll concur with Alex, though, in terms of, I think their real power will come in the cost drop, which will make it much more accessible to a lot of people. And I think downstream in a couple of months, as people start building applications and GPTs and special agents on top of this, then we're going to see some really big surprises, which I'm looking forward to.

• 8:10Peter Diamandis?

  Let's close it out with you, Dave. Dave, you've been thinking about this and watching all the telltale signs for a while. Were you excited, impressed, depressed? What was it?

• 8:21Speaker 01

  Well, I mean, you called it right, Peter. Compared to Google I/O, which had incredible showbiz value and a ton of video, you know, a ton of computer-generated video, for whatever reason, OpenAI decided to go folksy, make it look like a high school presentation, you know, and feel startup-y. And

• 8:40Speaker 01

  I don't know if they'll stick with that. You know, Steve Jobs did the best showbiz in the history of the world, and the anticipation of this launch was up there with the top three product launches of all time.

• 8:52Peter Diamandis?

  It really was.

• 8:53Speaker 01

  Yeah. Yeah, so you have an opportunity to really blow people's minds. Either they didn't have time to really work on it, or they don't have that staff built up yet, or they just don't care, maybe. I think, I don't think that's the case. But they really did not put a huge amount of effort into this event, and it came through. And you'll see some data that supports that. It's pretty obvious that that did come through.

• 9:17Peter Diamandis?

  Let's look at that. This is the review on Polymarket, and what we see here is answering the question, which company has the best AI model by the end of August? And coming into this, you know, OpenAI was riding high with Google, you know, coming in second, and then Anthropic in third. And then we see there the timestamp for when this release was live. Any commentary, Dave?

• 9:46Speaker 01

  Yeah, well, I mean, this is, it's great that Polymarket exists, because the feeling that I think we got, we all watched it live here in the office. We had a little, actually, Alex suggested it. It was phenomenally cool, actually. But, but watching the ticker in real time, you know, there's, there's a dip when they did their first coding demo, and then a huge plunge when they did their second coding demo. And literally, the betting markets went from 80% chance they'll have the best AI in the world, not just at the end of this month, but also at the end of the year, to completely inverting and saying, no, Google's going to have the best AI at the end of the month, month and the end of this year. And I, I think they actually showed some incredible capabilities and rolled them out at a ridiculously great price point. But the market reaction to it is, wow, I think Google's going to

• 10:31Speaker 01

  eat your lunch. So, yeah, you can't deny it. It's right there. People are putting, putting money behind this, this prediction.

• 10:37Peter Diamandis?

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• 11:22Peter Diamandis?

  To subscribe for free, go to dmandus.com/metatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode. You know, one thing I just want to point out for folks listening, and I think it's true that when you have this huge expectation of GPT-5's launch or any of these new models, you know, when Grok 4 came out, at the end of the day, I sort of feel a sense of underwhelming. And I think it's not because it's not impressive, it's because we've become so desensitized to extraordinary progress, right?

• 12:01Speaker 04

  I think there's something else here that I'm really enjoying, which is that given that the closeness of the different models, it means it's likely that we won't have one runaway success. And that means you have a very competitive market, which is just good for consumers overall for the time being. And all the models will do incrementally better over time. And so I'm excited by the fact that there's not one breakout.

• 12:23Peter Diamandis?

  Sure, but I do think it's important for folks to, you know, let's talk about the desensitization one second, because I think folks who are listening to this have to realize that our expectations are getting so high. And every time there's a new rollout that has additional capability, it's like, oh, eh, that's not so impressive. But, you know, compared to what existed a year ago, two years ago, it's extraordinary. Iman, do you agree with that? What are your thoughts?

• 12:52Speaker 02

  Yeah, I mean, it's a demonic adaptation, right? Like, um, when you get into a Waymo for the first time, it's great. Second time, yeah. And now it's just a whole experience around this. I, I think that part of it was just the communication, though. Because as you noted, like, 4.0 was a good model, but we see people getting wireheaded and hallucinations and all sorts. Lifting that up to a better base level should have been the communication with practical examples, but they didn't really show that. Again, I think the communication was a bit off in showing that lifting of the floor. The other thing that I think is that for the first time, I think what we saw was that there's a big gap between what the consumer gets and what the lab has. We actually saw a few OpenAI people say that.

• 13:35Speaker 02

  Like, before this came out, we had Horizon and Zenith as the two models on this, um, LM Arena, where you compare secret models against each other. They chose to release Horizon, but Zenith was better. And OpenAI have admitted they have better models internally as well, even before the next cluster build out.

• 13:53Speaker 01

  So they're pulling the punches.

• 13:55Speaker 02

  Yeah, because it makes more sense, as you head towards AGI, to actually not release the best model to everyone, particularly because it's more expensive to inference. GPT 4.5 was so expensive, and that was their frontier model at the time, but it was too expensive for anyone to use for normal tasks, for the 700 million people tasks. For the genius tasks, you don't want to give someone else that AI. You just use it for yourself to outcompete everyone else. So I think we'll see that bifurcation of decent models for everyone, for everyday tasks for 700 million, and then you make 700 million dollars using the other model, because it's the only logical thing to do.

• 14:34Speaker 01

  Yeah, one of the reasons I was so disappointed by the, the lack of really compelling demos and showmanship yesterday is because I'm constantly trying to make more people aware of how much change is coming and how insanely important and imminent it is and how much they need to rethink what they're doing tomorrow. And I was hoping to get some ammunition that I can actually just forward and use. And they, they managed to make one of the biggest, you know, turning points in history, the history of humanity, make it kind of boring.

• 15:08Speaker 02

  I mean, maybe it was maybe it was deliberate because they had the chart, the charts that were completely wrong as well. Like, maybe it's just all deliberate in that, look, you don't have to worry too much about this, right?

• 15:18Speaker 01

  No, that is a theory. That is a viable theory, actually, because, you know, all the accelerationists, including me and Alex, we know that a lot of this is being used internally for self-improvement, a lot of the compute, a lot of the capabilities, and it could be that it was intentional.

• 15:33Peter Diamandis?

  Don't scare the world.

• 15:35Speaker 01

  Yeah, don't scare the world.

• 15:37Speaker 02

  Well, I mean, like, yesterday, when GPT-5 came out, so GPT-5 is a router model, so your thing goes in, and then it routes it to Thinking, or Mini, or Nano, depending on something. They said, well, it was actually broken for like 24 hours. And you're like, really? You released it, and then you just left it broken in that the routing was off? But routing being broken is also a great way to actually gather data, to do the model improvement. And they discussed this flywheel of data improvement. So again, I think we see this bifurcation now, where most of the announcements by OpenAI are likely to actually be very consumer-driven, very floor-raising. And I think we'll see less and less of the big, massive stuff, apart from the outputs, like, we've had

• 16:21Speaker 02

  a breakthrough in something or other, but not generalizing that.

• 16:25Peter Diamandis?

  I'm still waiting to see what an AGI or ASI demo would look like or feel like. And I don't know, but we're gonna find out.

• 16:36Speaker 04

  Don't get me started.

• 16:39Peter Diamandis?

  All right, let's let's let's turn for a bit to benchmarks. And when I was having the conversation before this podcast began, about, you know, should we talk about the benchmarks? Will it get old? Alex, what was your comment about the benchmarks?

• 16:56Speaker 03

  Riveting. Some of these benchmarks, Peter, are absolutely riveting. We are so spoiled. We're lifting hundreds of millions of people to the frontier level of these models. We're collapsing costs. The economics are collapsing by an order of magnitude. And here we are complaining, oh, poke it, it didn't demonstrate any ontologically shocking new capabilities. How spoiled we all are.

• 17:18Peter Diamandis?

  We are, we have gotten spoiled. And let's jump into the riveting benchmarks. So Alex, since you've got the floor, let's begin here. Debut's number one in LM Arena. So first off, what is LM Arena?

• 17:34Speaker 03

  So Ella Marina is, and I think we discussed this in the last episode a bit, is a crowdsourced benchmark wherein the community, the internet at large, is able to interact with competing frontier models in a variety of ways. The ranking that we're seeing here is focused on text-based interaction, so conversations. There are other scores that deal with web development and other modalities. And what we're seeing here is GPT-5 leapfrogging over the rest of the leaderboard to number one in text-based interaction. There's another parallel benchmark with web development where you see even larger

• 18:15Speaker 03

  margin, larger difference in Elo scores between GPT-5 and the next largest or the next strongest competitor. And this is remarkable. Again, we're so spoiled to see these leapfrogging capabilities every now three months or so, could get even faster. But this is going to be transformative in terms of everyday conversations that hundreds of millions of people have, software development, and a number of other domains.

• 18:44Speaker 01

  So can I ask you, Alex, how do you reconcile this chart with the polymarket chart? Does that mean Google will again leapfrog this before the end of the year?

• 18:53Speaker 03

  I would say to the extent that that polymarket is indicating a prediction, a rational prediction about the market, and I think that was set for end of August, I would interpret that market movement as a prediction that Google will launch a new frontier model by the end of this month.

• 19:10Peter Diamandis?

  Every expectation. And we're going to see in a little bit how much Google has done. I mean, they've been extraordinary under Demis Hassabis' leadership. Here's the next one, and I'm going to turn to you, Imad. Arc AGI 1, and we'll see Arc AGI 2 in a moment. The leaderboard here, you want to give us a dissection of this, what we're seeing here?

• 19:32Speaker 02

  Yeah, this is kind of very, very hard tasks that are meant to indicate progress towards AGI. So Grok kind of led the way there. As you can see, which one is that? It's Grok four. Grok four, Grok four thinking, right? Yeah. And so this is kind of Pareto frontier of solving these very, very complicated tasks versus the cost. And so O three was actually really, really good, but it's way out there in that it's far more expensive. GPT five has different levels, the high, the medium and the low. And it doesn't quite beat Grok, which is also the case for other ones like humanity's last exam. And so I think this was part of it in that we see better performance on GPT five for everyday stuff. And it just ekes a lead on some of these or is up there.

• 20:17Speaker 02

  And I think they wanted to blow everyone's socks off because remember they also have models that scored gold medals at the IMO. Mm hmm. You know, and Gemini, for example, recently they had Deep Think. That's a Newton model of their version that scored a gold medal. So I think apart from XAI, who are trying to do the best they can on all these benchmarks and release the best they can. We're starting to see some punches being pulled at the top of these benchmarks on the AGI side, on the super genius side. So I think we'll see a bit more clustering up there. Alex, you're in agreement?

• 20:51Speaker 03

  I, I think there are two ways to look at this chart. So one, as Inmod said, is which, which point in the scatter plot, which is plotting cost versus score is at the top of the chart. That's, that's one way to look at it. The other way is what is the cost frontier? What's the Pareto optimal frontier where you get the best score or the best performance at a given cost? And there, if you look just a bit to the left, you see the GPT five mini series. And to the lower left of that, the GPT five nano series have set, have defined a new frontier for cost performance. So I, I think the buried headline here is the, the hyper deflation that we're seeing in the cost of intelligence.

• 21:35Speaker 03

  That ultimately, I think, ends up being even more transformative than just narrow capabilities at ultra high cost. You could run the thought experiment. What would happen if we could build super intelligent computers so unaffordably that human civilization can't afford it? Compare that with what happens when intelligence is too cheap to meter that everyone can afford it. I think that's the central discussion.

• 21:57Speaker 02

  Yeah, I think you'll see you'll see Google and OpenAI compete on that left hand curve effectively.

• 22:02Peter Diamandis?

  And by the way, we're going to make all these charts available to our subscribers. You just go to diamandis.com slash WTF and you can get all the charts downloaded for you. We'll be doing this from all of our WTF episodes going forward. Just to make sure you have this so you can share it with your friends and your family. All right, here we see Arc AGI two leaderboard and Imad, why don't you lead us off on this one?

• 22:30Speaker 02

  Yeah, this is just a more complicated version of Arc AGI one because they're worried with three that it might saturate. So again, I think, as Alex said, you see the same thing with the GPT on the left hand side, kind of keeping that. But just a more complicated version of the previous one.

• 22:46Peter Diamandis?

  All right, moving along. So here's one that I think is, we discussed this, Imad, on one of our previous episodes, or I think actually it was with Alex, that, you know, how we benchmark these frontier models is going to start to saturate. And understanding how these frontier models actually become economically useful, how they're able to solve grand challenges. So here we go. This is a look at economically important tasks. Imad, do you want to take a shot?

• 23:18Speaker 02

  Yeah, I think that, you know, this is the year where you break through that line effectively. Or you reach that level of performance, especially there's another chart I think we have of Meta, which M E T R, which shows the length of tasks this can do. And GPT five is right at the top of that. Like you can do the tasks on law, logistics, sales really well for a long time without supervision and with lower hallucinations, which is the other big news that they had around this. And so they actually become genuinely useful. They released ChatGPT Agent that you've just set off and it will look up the internet and do all sorts of stuff a little while ago. It wasn't quite good enough, but soon it will be. And once that happens, this is when you see real big things happening, either a productivity boom

• 24:02Speaker 02

  or the inverse, you know, people getting laid off. And we're not sure which is those two features is going to happen. But again, you can see you're just reaching that level now across just about everything.

• 24:11Peter Diamandis?

  Who wants to plug in on this one? Salim, do you have it?

• 24:13Speaker 04

  Well, this is where I think where I mentioned, so there's two or three really big things here, right? To Alex's point, the cost drops of running these models and we can do a ton. And to Emad's point, they're kind of taking out the hallucinations and cleaning it up, even though the top line is not amazing, where there is a lot more rock solid. Therefore, the kind of agents and applications that build off these things will be very, very solid and stable going forward. And I think that's where we'll see some amazing use cases coming out where we apply them in industry.

• 24:45Peter Diamandis?

  And how should our listeners be thinking about this? Do they think a bit from a point of view?

• 24:50Speaker 04

  Well, if you're running a business, this is a time to really build, dig in, right? Before, you didn't know quite what you were going to get. Well, you're going to see now going forward now is it's pretty reliable, pretty solid, go all in. If you haven't, you should be doing that anyway. Just go all in and start turning your business into an AI native business.

• 25:09Speaker 01

  Yeah, the problem I run into all the time is as the AI is getting better and better and better, the benchmarks get harder to interpret. And also in the early days, you know, it was all just pre-training. Oh, this is 100 billion parameters. This is 500 billion. This is a trillion. It's getting bigger. As it gets bigger, it gets smarter. And then the benchmarks are nice and simple. Now, you know, the post-training became very important, but now the chain of thought reasoning is dominating. It's just such a huge factor. It makes it much harder to track what's working and what's not working. And the danger there is that people get paralyzed when they should be getting motivated, just like Salim just said. And that's a challenge, actually. And it's like a benchmark like this is vague.

• 25:53Speaker 01

  And it's a little bit difficult for people to take this benchmark and then translate it into, should I start an AI law firm? Should I, you know, should I use it to work on, you know, discovering fundamental physical properties? Is it going to be good at material science? So it's getting harder to make those predictions.

• 26:11Peter Diamandis?

  And of course, the answer to all those is yes, you should.

• 26:16Speaker 02

  I like to think, you know, in jobs, we teach people to be like machines. So obviously, the machines are going to do it better. Like, if you look at the health bench scores, for example, on the hallucinations and hallucinations in general. I think something like six to 12% of all diagnoses are incorrect. AI has just kind of dropped below that level now.

• 26:35Speaker 04

  I think it's close to 30% if you go to primary doctor, primary.

• 26:39Speaker 02

  Yeah, it kind of varies, but it's a lot. AI now makes less errors than humans.

• 26:44Speaker 04

  Yes.

• 26:45Speaker 02

  I think just now over the last month. And again, that's going to be the most errors it ever makes.

• 26:51Peter Diamandis?

  Yeah, and we'll go into this a little bit later, but you know, is the interesting study that said, you know, physicians by themselves do like 80% physicians with AI models together do like 90%, but AI models by themselves was doing like, you know, 93%, which means that the the human pulls back and enters lots of bias into the answers.

• 27:13Speaker 04

  You know, when I was when I was chatting with doctors about who's going to do my surgery, I came across a guy and I said, how many of these shoulder arthroscopies have you done? And he said about 10,000. And I said, okay, that's like, you're more like a robot than anybody. We'll go with you. We'll go with you.

• 27:29Peter Diamandis?

  By the way, that is the number one question you should ask a surgeon when you're interviewing them is, how many times have you done this surgery this morning? Right? Because you're basically training the neural net of the surgeon by seeing every possible case. And of course, we're going to end up with robotic surgeons that can see in every part of the spectrum and have had not just 10,000, but millions of cases.

• 27:51Speaker 04

  You just don't want to be the 50th one that morning. That's all.

• 27:55Peter Diamandis?

  All right, here's our next benchmark. GPT-5 sets new record in frontier math. Alex, I'm going to you on this one, buddy.

• 28:03Speaker 03

  Yeah, I think this is perhaps the most exciting benchmark to come out of GPT-5 in the past 24 to 48 hours. So what's exciting here, if you look at the performance of GPT-5 high on in the lower right hand corner, frontier math tier four. So frontier math tier four is a benchmark that measures the ability of. AIs to solve problems that would take professional mathematicians, sometimes weeks, to solve, but nonetheless, problems for which there are known answers. We're seeing, we're starting to see increments on Frontier Math Tier Four that if you extrapolate them, suggest that, and I've gone through this exercise,

• 28:44Speaker 03

  and it's a running discussion between me and the folks at Epic AI. If you project this forward, you find by, again, the law of straight lines, by the end of this year, we, Frontier AI, are starting to reach fifteen to twenty percent of hard math problems being solvable by AI. Project that forward another year, so by the end of 2026, you get to thirty-five to forty percent of math, hard math, being solved. Project it forward to 2027, end of year, you get to seventy percent. So what I think we're staring at is a slow-motion solution to math. And that's one of the reasons why I think it's just riveting.

• 29:27Speaker 03

  All math, or at least, or at least math that math has currently understood in the summer of 2025.

• 29:33Speaker 01

  Isn't that amazing? And I completely agree. And it does play into Ahmad's theory that maybe they slow-played it intentionally. Because if you, if you were to ask me, hey, what happened yesterday? They're crushing this benchmark relative to any other model. They cut the cost of AI at least in half, if not more, and they caught up to everybody else in coding. Like, if, if they just said that in like, two minutes, that would have been, you know, the epic death star moment. Yeah, just do that.

• 30:01Speaker 04

  Wait, can I, can I drill into that just for a second? Alex, when you say it can solve math, right? Can you give a specific example of what that looks like? Because, because I struggle with that, even though, you know.

• 30:13Peter Diamandis?

  Better, better than eight hundred on your SATs, I guess.

• 30:16Speaker 04

  I think, what's a specific problem or class of area that you could say that's done something interesting?

• 30:22Speaker 03

  Yeah, no, so you can, you can look at the Epic AI website for Frontier Math Tier Four, see, see lists of example problems that have been published. These are problems, hard problems in, in number theory, in analysis, in algebraic geometry, that would require a professional mathematician weeks to solve, that are being solved over the course of a short benchmark by, by GPT-5. Okay. He also asked that question like, what does this look like in practice? Say, say the dog catches the car and we actually get AI that achieves superhuman performance in in math. I think it's a profoundly different world.

• 31:03Speaker 01

  It is, and it's it's hard for not everybody's a mathematician, not everybody's an engineer. But the way a lot of things get designed and built and created in the world is you you run into problems and you immediately look up in these massive books and tables. Has anyone ever solved this before? And so if the if the AI is continually solving and archiving all of these mathematical capabilities and just making them available, then the engineering algorithms can just find it and use it, plug it in and go. And it's the same in coding, you know, huge libraries of solved problems, solved modules that can be assembled to create things very, very quickly.

• 31:40Peter Diamandis?

  I want to close on Imad here before we move on, just because we have a lot to cover still. Imad, closing thoughts on this one?

• 31:47Speaker 02

  Yeah, I mean, it's kind of an improvement over the O four mini. Again, we had the IMO gold medal from OpenAI whereby they had a verifier on the other side of their model. And they said, just by extending the RL of GPT five, they got a gold medal. So this model can get a gold medal, so it can go even higher if you push it. From the last few days of doing some pretty advanced math, I can say that GPT five high is probably the best math model out there. But the really crazy thing is I think it's getting to the point now whereby the solutions to math won't be complicated, they'll be really elegant. And that's how we typically see breakthroughs. So people are thinking giant supercomputers, lots of work.

• 32:29Speaker 02

  But most of the advances that we've had in science and math have actually been just very elegant. And if you can do a million different things at once, then you can maybe find some of that elegant theory under all of this. And that's what's going to be a big leap. And if more and more people can do that now, because the minidium and the high are actually at the same level, which is crazy. Then you might have a lot more mathematicians and the humans and the AI can figure out what that elegant theory is.

• 32:54Peter Diamandis?

  And now it's time for probably the most important segment, the health tech segment of moonshots. It was about a decade ago where a dear friend of mine, who has incredible health, goes to the hospital with a pain in his side, only to find out he's got stage four cancer. A few years later, fraternity brother of mine dies in his sleep. He was young. He dies in his sleep from a heart attack. And that's when I realized people truly have no idea what's going on inside their bodies, unless they look. We're all optimists about our health, but did you know that 70% of heart attacks happen without any precedent? No shortness of breath, no pain? Most cancers are detected way too late at stage three or stage four. And the sad fact is that we have all the technology we need to detect and prevent these diseases at scale.

• 33:39Peter Diamandis?

  And that's when I knew I had to do something. I figured everyone should have access to this tech to find and prevent disease before it's too late. So I partnered with a group of incredible entrepreneurs and friends, Tony Robbins, Bob Hury, Bill Cap, to pull together all the key tech and the best physicians and scientists to start something called Fountain Life. Annually, I go to Fountain Life to get a digital upload, 200 gigabytes of data about my body head to toe, collected in four hours. To understand what's going on, all that data is fed to our AIs, our medical team. Every year, it's a non-negotiable for me. I have nothing to ask of you other than please become the CEO of your own health, understand how good your body is at hiding disease, and have an understanding of what's going

• 34:24Peter Diamandis?

  on. You can go to fountainlife.com to talk to one of my team members there. That's fountainlife.com. All right, I'm going to dive into a bit of video here. This is labeled "Let the vibe coding begin."

• 34:38Speaker 05

  GPT-5 is clearly our best coding model yet. It will help everyone, even those who do not know how to write code, to bring their ideas to life. So I will try to show you that. I will actually try to build something that I would find useful, which is building a web app for my partner to learn how to speak French, so that she can better communicate with my family. So here I have a prompt. I will execute it. It asks exactly what I just said. Please build a web app for my partner to learn French. So I can simply press run code. So I'll do that and cross my fingers.

• 35:18Speaker 05

  Oh, nice. Voila.

• 35:22Speaker 05

  So, we have a nice, a nice website. Name is Midnight in Paris. Oh, I love that.

• 35:29Speaker 06

  Simematic.

• 35:30Speaker 05

  And we also see a few tabs, flashcards, quiz, and mouse and cheese, exactly like I asked for. I will play that, so this says Le Chat.

• 35:39Peter Diamandis?

  All right, I'm gonna pause it there. Commentary, Dave, what do you think about this?

• 35:44Speaker 01

  So, this is exactly when polymarket plummeted, so I'm so glad you captured that clip. Because, because the, the audience is looking at this and they're acting like, wow, didn't this blow your mind? There's only two types of people in the world, people who don't give a crap about this, or who already do it, but they've been doing exactly this with, probably with, with Claude 4, or, I'm sorry, with Claude Opus or Claude Sonnet 4 on Maxima. They've been doing this for like four months. And so, it completely missed the mark, even though it was the best presented part of the presentation, purely because it didn't show off the new capability or the new abilities.

• 36:22Peter Diamandis?

  But the ability to do this in, in ChatGPT, in other words, a single model that allows you to do everything.

• 36:30Speaker 01

  Yeah, I mean, if, if I'm an investor in, in the upcoming round, this is really big news, because Anthropic, you know, generally claims to be the leader in coding. Most of the people who do heavy duty encoding lead on Anthropic, and they completely caught up in this release. And that's a very, very big deal, uh, because, you know, not only are you good at everything else, but you're actually as good as Anthropic in their wheelhouse.

• 36:54Peter Diamandis?

  Yeah, the questions that were coming out was, is this an Anthropic killer, right?

• 36:58Speaker 01

  Yeah.

• 36:59Speaker 04

  Here's, here's my question about this. So, you generate this webpage, web app, right? But if, let's say I'm a language startup and I want to launch that actual product. There's a huge amount of backend stuff I have to do to make it systems integrated, integrated with Stripe, et cetera, et cetera. And we're finding that that's where all of the work is going. And therefore, this graded through up a front end and looks good like a front end prototype. Is it actually doing that much behind the scenes? Or is there still a lot of the work? And that's the question I have for the folks on the, that we have here.

• 37:33Peter Diamandis?

  Here's my question for you guys. How should someone listening to this who hasn't played with ChatGPT five, let's call it that, play with their own vibe coding on this? What's their first step? What do they do? How do they play?

• 37:47Speaker 03

  I, I would encourage everyone who has ChatGPT, ChatGPT five thinking access in particular to create a game. I, I think this is one of the simplest exercises. You've always wanted to, to create a long tail application, a game or an interactive app of some sort, and you don't have coding experience. Go and ask ChatGPT five thinking to implement a new app for you, a new game, a new something, and let it rip.

• 38:16Speaker 01

  And do it right in the canvas. There's a canvas button right down on the little, the little nav bar, search bar at the bottom. So click the canvas button. Do it right there locally. It's much more convenient. They've added a lot of capability inside the canvas. So, so you can just build an entire game for yourself right there inside the, you know, just go to, you know, go to chatgpt.com and do it right there.

• 38:39Peter Diamandis?

  Amazing.

• 38:40Speaker 02

  Yeah. Yeah. I think the performance isn't quite there yet versus Raplet, Lovable or Bolt, which do everything Salim said, the Stripe and every other integration. But again, these things will verticalize very quickly.

• 38:51Peter Diamandis?

  Um, let's move on here. And we saw, you know, the co-founder, the co-founder of Cursor come on stage and spend time with Greg Brockman, the OpenAI president. Dave, what do you think about this? How important was this?

• 39:05Speaker 01

  Well, incredibly important. So it was not just a little time. It was a huge amount of stage time in one of the biggest live streams in history. So it was very important. And of course, what happened is OpenAI was going to buy Windsurf and essentially attack Cursor with an incredibly powerful competing product that's virtually identical in functionality. Actually, people here in the office about half use Cursor, about half use Windsurf. It looks virtually identical. And so that deal fell apart. Microsoft torpedoed it because of intellectual property rights that Microsoft would have. So they torpedoed the deal. And here we are just a couple of weeks later, and OpenAI is now saying, you know what?

• 39:50Speaker 01

  We're going to work very closely with Cursor. We're going to give them a lot of stage time. And I think what we're starting to see here is the alignment between the coding companies and their LLM partners. Because previously, everything connected to everything. So any LLM is available through any coding platform. I think going forward, it's very likely that Cursor works closely with OpenAI. Windsurf is now part of Google, or sort of part of Google, half and half, half in, half out. And then, of course, Microsoft wants VS Code, and they want to build their own thing. And so you're going to see this vertical alignment. And also, already, people all over Twitter or X are saying, hey, when I use it through

• 40:31Speaker 01

  its kind of native platform, through the canvas, it works much, much better than if I try and select it through something like Lovable or Replit. And so everyone's speculating that they're doing kind of what Microsoft always used to do. They're hampering the people that aren't playing by their rules in very subtle kinds of ways. And there's no way to prove it, but it's certainly all over the internet.

• 40:54Speaker 02

  Yeah, I mean, I think if you look at this, OpenAI and Anthropic both have $3 billion in API revenue. 1.4 billion of Anthropic's API revenue, so about half is Cursor and Microsoft Copilot. And so they priced GPT-5 about 40% lower than Sonnet. So they're coming after Anthropic, basically. And they will undercut them on price. And now the performance is roughly equivalent. They're just basically trying to kill Anthropic's revenue.

• 41:25Peter Diamandis?

  All right, the AI wars continue. Here's another one. This is an important part of the of the story from the GPT-5 announcement. And we're going to hear Sam Altman speaking about AI saving lives.

• 41:42Speaker 07

  One of the top use cases of ChatGPT is health. People use it a lot. You've all seen examples of people getting day-to-day care advice, or sometimes even a life-saving diagnosis. GPT-5 is the best model ever for health. And it empowers you to be more in control of your healthcare journey. We really prioritized improving this for GPT-5. And it scores higher than any previous model on Health Bench, an evaluation that we created with 250 physicians on real-world tasks.

• 42:10Peter Diamandis?

  So I think a lot about this, right? And and the AI models are, at this point, I think, better than most physicians. But they're only as good as the data you feed them. And that's the biggest challenge. Can you get access to the data that truly tells your story? Right? So, comments?

• 42:32Speaker 01

  So Sam did a very brief introduction to kick off the event yesterday, and then he did a much longer segment with a woman who was a cancer survivor who had really done her own self-diagnosis and completely changed the course of her own treatment by talking to ChatGPT and getting very, very good advice from ChatGPT. And I think Sam chose to do that segment himself, largely, I think, because, one, it's a very emotional, human segment. I thought, pretty well done, too. But also because it's going to prevent the regulators from ever saying, "Slow down or stop." Like, if you're going to save lives that imminently, you know, would have been ended, you cannot slow down. You have to keep moving.

• 43:16Speaker 01

  And I think that's very important as a mission for OpenAI to keep the throttle, you know. There are two drivers to keep the throttle going. One is the incredible healthcare benefits. The other is the threat from China. And so both of those are, you know, right front and center.

• 43:30Peter Diamandis?

  Celine?

• 43:34Speaker 04

  I think this felt more like PR to me than anything else because I think you could do this with many of the models rather than this. Okay, maybe incrementally better than the others. I think integrated broadly into somebody's healthcare regime is where we'll see the real value of something like this rather than this immediate thing. But I do take Dave's point. I think that's exactly right. I think they're pushing hard to kind of show they're trying to add a lot of value.

• 44:01Peter Diamandis?

  Yeah, let me let me throw in something on the personal front here. So one thing that I do, and I've talked about it openly on this, is I'm chairman of an organization called Fountain Life. And when folks come in for what we call an upload, we fully digitize them, right? We get 200 gigabytes of data about you, full body MRI.

• 44:21Speaker 04

  Didn't you just do yours?

• 44:23Peter Diamandis?

  I did it. I did it. I did it a few weeks ago. Just got my results back. I had 200 gigabytes of data. So for me, what was important was I reduced my non calcified soft plaque, which is the dangerous plaque that can give you a heart attack in the middle of the night, down by 20% to the lowest it's ever been. I got my liver fat from 6% down to 1%, which is fantastic. But what happens is in my Fountain Life app, we're running this on on Anthropic right now. But, you know, maybe we'll go to GPT-5. We're running much of the other programming on on Gemini. But here's the point. I can query all my

• 45:03Peter Diamandis?

  data. It, you know, the Fountain Life system pulls in all my wearables, right? So Apple or my continuous glucose monitor. And I can ask a question. I just asked a question the other day. I said, listen, there's a point at which my deep sleep increased significantly. What was I taking? What was the supplement or medicine that increased it? And being able to explore stuff like that is amazing, right? So the best AI, you know, healthcare models in the world are great, but they're directly a function of do you have enough deep data about your physiology over time to understand what's going on?

• 45:44Peter Diamandis?

  I mean, ultimately, that's critical. And Ema, you've been thinking a lot about this.

• 45:49Speaker 04

  I think my liver, I think my liver fat went from one to six percent last week.

• 45:54Speaker 02

  You're heading towards, you're heading towards foie gras, honey.

• 45:56Peter Diamandis?

  Well, I mean, Selene, have you come through Fountain Life yet?

• 46:00Speaker 04

  I haven't. I need to find the time to do it.

• 46:03Peter Diamandis?

  You're the godfather to my kids. You gotta come through.

• 46:05Speaker 04

  I have done the heart test where they checked if you have soft plaque in your, in your, and Lilly was like, with your diet, you must be, you must be on the verge of a thing. Go get it done. And we got it done. And they said, and they said, you're whistle clean. We got nothing.

• 46:17Peter Diamandis?

  That's great. You know, but the challenge is.

• 46:19Speaker 01

  So then you had a steak and.

• 46:22Peter Diamandis?

  You're, just one.

• 46:23Speaker 04

  I went to town.

• 46:24Peter Diamandis?

  One quick point, right? Your body is incredibly good at hiding disease. And you don't feel a cancer until stage three or stage four. Seventy percent of heart attacks have no significant precedent. So you have to look, you need to get the data.

• 46:36Speaker 04

  I have a schedule. I mean, first I want to get this shoulder sorted out. Now done. Now I can go and do other stuff.

• 46:42Peter Diamandis?

  All right. Well, for sure. And Ema, you came through, didn't you?

• 46:48Speaker 02

  I haven't been through yet. No, I nearly got there. I will, I will. We will have to get healthy and we do all the data. I think this will be really interesting, though, because the models themselves are getting good and again, better than any doctor. Like they mentioned the health benchmark, benchmark that they have. Doctors scored 20% and the latest models they have scored 60, 70% on that. So they're better than any doctor. But the really exciting thing is like, we built a healthcare model called I Medical, uh, which we released open source. So we've got a much better version coming, which outperformed every single model except for GPT five and O three. And it works on a Raspberry Pi. It works on anything. So by next year, I think we'll be at the point where the key thing is you get the right data, especially like Fountain Health has so much.

• 47:33Speaker 02

  And they just have AI just going constantly. Because what you wanted for it to figure out stuff proactively as you feed it the data. And now we're seeing these models being able to just detect breast cancer five years in advance and other things like that. Like when you talk to radiologists, they're like, we don't have any software that's actually checking all the radiological scans over time. Wouldn't it be nice if that happened? And now you have the capability of doing that, which I think will save so many lives. Before the AI makes diagnosis.

• 48:00Peter Diamandis?

  And I love having a very deep bench of data for me over the course of eight years. And every, you know, right now I go from annual upload to quarterly updates. And ultimately.

• 48:13Peter Diamandis?

  It's, you know, it is all about the data.

• 48:16Speaker 02

  Well, I think that if you just say one quick thing, like right now, everyone on this should be trying to get as much data as possible because the models are coming and the more models you data you give these models about yourself, the longer you will live and the better you will live. Before now, we didn't have the right models. Now we have the right models. And again, they'll be available via OpenAI and then also open source.

• 48:39Peter Diamandis?

  Yeah, I mean.

• 48:39Speaker 04

  So for all the folks building stuff around this, here's my ends, here's my desired end stage. I want to get it to a point where you're you're about to drink a coffee and it says, hold on, wait 10 minutes. I'm still metabolizing the donut. Give it time till I can optimize your digestion. I think that's when things get really.

• 48:58Peter Diamandis?

  Well, I want the AI to say, warning, pull up and don't eat the donut.

• 49:04Speaker 04

  Separate problem.

• 49:06Peter Diamandis?

  All right, let's continue on here. I hear you see another demo that came out at the GPT five announcement, an executive assistant for all of us. And, you know, I use Outlook right now from Microsoft and this got me thinking about moving to Google Calendar. So let's play the, let's play the demo.

• 49:23Speaker 08

  And we're giving chat GPT access to Gmail and Google Calendar. Let me show you how I've been using it. I've already given chat GPT access to my Gmail and Google Calendar. So it just works and it's easy here, but if you hadn't, chat GPT would be asking you to connect right now. Let's see what chat GPT is doing. Okay, I was pretty quick. Okay, so chat GPT has pulled in my schedule tomorrow. And oh, without even asking, chat GPT found time for my run.

• 49:53Speaker 02

  I don't think I was invited to the launch celebration.

• 49:57Speaker 08

  We'll get you on there. We'll get you on there. Chat GPT has found an email that I didn't respond to two days ago. I will get on that right after this and even pulled together a packing list for my red eye tomorrow night based on what it knows I like to have with me. It's been amazing to see that as GPT five is getting more capable, chat GPT is getting more useful and more personal.

• 50:20Peter Diamandis?

  Right. I found that impressive. I've, you know, I have an amazing chief of staff, Esther, that many of you know. And she's incredible, but I think she could use this and I could use this. Thoughts?

• 50:33Speaker 01

  It's really coming around to a Mads theory that they deliberately undersold it because this is this is cool ish, but you know, finding an email that you didn't open two days ago, you don't need AI for that. But we are using this stuff for business planning inside. I've got, you know, I'm the chairman of a couple of companies that have hundreds of employees. And knowing what everybody's doing and why they're doing it is immensely challenging. And we're having a field day with this in very high level strategic planning, in understanding, you know, performance and understanding, you know, everything going on. It's an incredible unlock at the executive management level.

• 51:09Peter Diamandis?

  Sure.

• 51:10Speaker 01

  And again, for me, as a watcher, you know, kind of frustrating to see it, you know, planning out her run when I know it can, it can actually plan entire business units. But still, the point is it's, it's very, very capable. So I don't know. I was frustrated, but I get it.

• 51:25Peter Diamandis?

  All right.

• 51:26Speaker 04

  You know, the, the opportunity to now enable, you know, Eric Brynjolfsson calls this white collar drudgery, right? There's a lot of cruft that we do just to get through. I think this solves for a lot of that. And I think this will amplify the capability of a lot of people. I think chiefs of staff rise up a whole level because you could use this effectively and do a lot more.

• 51:47Speaker 01

  Oh, my God. Well, like the standard behavior in corporate environments is individual people desperately want to help move the company forward. They want to contribute. They want to have maximum impact and they want to know that the executive team knows they're doing that. And it goes horribly wrong when either they don't know exactly what they should be doing, or they do something amazing and nobody notices. And this completely unlocks and unlocks and solves those problems.

• 52:14Peter Diamandis?

  I love that, Dave.

• 52:15Speaker 04

  So when, when Donna and Nick Ping mean go here, what dates are you available for the next WTF episode? And you're 14 that intersect figure it out with your calendar and I'll be able to get help with that.

• 52:24Peter Diamandis?

  You will. In fact, it'll get scheduled without your permission.

• 52:30Speaker 04

  Well, we're kind of dancing monkeys anywhere, right? You would just being told, okay, be here at this time.

• 52:34Peter Diamandis?

  But interesting, right? I do what's on my calendar. When it's it's very funny when I'd gotten to know Larry Page and Sergey Brin very well. Larry was on my my board at X Prize in early days. And there was a point at which they said, by the way, we fired our executive assistant. And what do you mean you fired your EA? Well, we learned that if we don't have an EA, no one could put anything on my calendar without our permission. And then like a decade later, I was scheduling a podcast with Elon. And I said, Elon, who should I schedule with? And he goes, me. I said, don't you have an EA? He goes, nope. So maybe that's a mistake we're making. All right, let's go on to the next next topic here. This is this reads AI revenue models.

• 53:18Peter Diamandis?

  So GPT five is available now for free, including its most advanced models. At the same time, Gemini is their advanced models are $249 a month. Grok heavy is at 300 bucks a month. And how do you think about the pricing situation here? Chat GPT is 700 million weekly active users on their way to a billion, probably within the next six months. Dave, thoughts?

• 53:45Speaker 01

  Yeah, no, they they really slashed the price. It shows up for the user user, but also the APIs, which I think we have on the next slide.

• 53:52Peter Diamandis?

  We do. I'm going to go ahead to that slide here.

• 53:55Speaker 01

  Yeah, here you go.

• 53:56Peter Diamandis?

  Yeah.

• 53:56Speaker 01

  This is what Ahmad was talking about earlier. They just absolutely the the cost per intelligence came way, way down. I think you said 40%. I had it about half half of where we were a week ago. That's a big, big deal. And it's, you know, it's more than you would expect on the curve. And again, they didn't really sell it yesterday in any big way, but it is a big step on that Pareto frontier. This is a huge competitive.

• 54:22Speaker 02

  GPT 4.5 was $75 input and $150 output.

• 54:30Peter Diamandis?

  Wow. As compared to a buck twenty five on input and ten dollars on output.

• 54:37Speaker 03

  Yeah.

• 54:37Peter Diamandis?

  Per million tokens.

• 54:39Speaker 03

  I would say GPT four point five was never quite on the cost frontier anyway. What I see in this with this almost an order of magnitude reduction in the cost frontier is unlocking new use cases and those I would expect to be qualitatively different. So for example, favorite use case, if tokens for L L Ms are suddenly in order of magnitude cheaper, that means that for, for example, scientific discoveries or mathematical discoveries that require searching lots of possible completions of sentences, of theorems, et cetera, then you can do ten times more searching and that makes a qualitative difference.

• 55:20Peter Diamandis?

  Yeah. You can brute force it in that sense.

• 55:24Speaker 03

  Yes.

• 55:25Speaker 01

  Exactly, exactly. I gotta give a shout out to their, you know, probably thousands and thousands of engineers out there that listen to this podcast. And if you tried writing code through any of these models, any of these really great models, either the Anthropic or the new GPT five or Gemini two point five pro, if you tried a month ago, you have to try again today. It's just night and day different in terms of being able to build something without even looking at the code, in terms of getting exactly what you asked for. I'm using mostly Gemini two point five pro deep think to do the planning, but then I'm putting it into either GPT five or Claude four sonnet max to do the coding. It's working

• 56:07Speaker 01

  like you would not believe and night and day better than just a month ago.

• 56:13Peter Diamandis?

  How many of, how many of the frontier models do you have open at a time? And are you trying the same thing on each of them, Dave?

• 56:19Speaker 01

  Yeah, I keep them all open, actually.

• 56:22Peter Diamandis?

  Of course.

• 56:22Speaker 01

  So I've got, but you know, look, it's, it's two hundred and fifty bucks a month. It's, it's not going to kill you and you can turn it off anytime. But I keep them all open and I don't usually try Grok for code. I do everything else. Not sure why, maybe I should.

• 56:37Peter Diamandis?

  Alex or Iman, how are they getting these cost reductions?

• 56:42Speaker 03

  I think a lot of it, this is based on public information shared by the Frontier Labs. A lot of it comes from optimizing the inference stack. So moving to faster blackwell GPUs, I think is one factor. Optimizations, low level optimizations in the tech stack at inference time. Distillation of smaller models with fewer parameters based on higher quality data. Algorithmic innovations, architectural innovations. These all compound. Some of them are 50% improvements, some of them are 2 to 3X improvements. But collectively, as is now the lore in the industry, we're seeing order of magnitude per year cost reductions. But are they, how much money are they losing on this per transaction?

• 57:26Speaker 03

  It's difficult to know from the outside, but I would also say that the matter is somewhat confounded by the enormous capital expenditures that are going into this space. So it's not necessarily even a reasonable question to ask how much is being lost. You have to sort of factor out the capital expenditures as, as we've discussed previously, we're in the process of tiling the earth's surface with data centers. This is an enormous capital expenditure. So it's a little bit difficult to separate out the amortization of CapEx from the OpEx of just day-to-day inference and electricity.

• 58:01Speaker 01

  I can definitely tell you they're, they're definitely not incinerating money. There's a lot of food on the internet about them. Hell, they're incinerating money, they're losing huge amount. They're not. They're, they're operating better, about break even or better. And in, you know, in the context of what Alex just said, the order of magnitude improvement in cost per compute that just came from the GB200s from, from Nvidia, that would put this way over the top. If I was talking to Gemini earlier today about, you know, what do you think they spent training GPT-5? And it came back with this insane number of billion dollars on H100s. I said, but I don't think they used H100s. He said, oh, okay. Well, if they use GB200s, it would be more like 60 million.

• 58:42Speaker 01

  Wow, okay. But yeah, it's about a factor of 10 reduction in the cost of the compute and they're passing some of that through. And you know, the GP200s are just coming off the line and starting to get into production. So it'll be a little while.

• 58:56Speaker 04

  So when I saw the pricing, I thought they were doing this for competitive advantage and taking a huge loss. What I'm hearing is saying is that's not the case. They're really running maybe about breakeven, but it passing on massive savings to the consumer.

• 59:08Speaker 03

  Yeah, Salim, this is what hyperdeflation looks like. And it's an interesting thought experiment to ask, assuming this is sustainable, and I have no reason to think that it isn't sustainable. What does hyperdeflation right now at inference time for frontier models look like once it starts to spread to the rest of the economy? This leads to Peter's abundant state, I think.

• 59:29Peter Diamandis?

  You know, I just want to say something for those listening. I feel smarter during these episodes, getting a chance to speak with Dave and Salim and Alex and Ahmad. And I hope you do too. I mean, that's the reason I do this. We put about 20 hours of deep research in per week, trying to find the most relevant content to share with you. And then how do we make it actually understandable, connect the dots and deliver sort of a distilled Cliff Notes to help you stay ahead? You know, selfishly, I do this for because it's a blast. Salim and Dave, what about you?

• 1:00:04Speaker 04

  Well, I think the curation that goes into this, right, where we are looking across the spectrum and then picking out what are the most relevant things, right? Dave talks about the actionability of it. But I think the fact that we can curate the very important bits for our viewers, I think, is the most important part and the most fun. And we get to see that first.

• 1:00:24Peter Diamandis?

  Yeah.

• 1:00:25Speaker 01

  I always, I always have my kids in the back of my mind when we're doing these podcasts because they're, they're going to live their entire lives in the post AGI world. And, you know, one of my kids was talking to one of the guys here in the office and said, all your dad ever talks about is AI. Yeah, but, but the whole time you're growing up, did I ever talk about AI once? I mean, I never mentioned it until suddenly it's going to change your life. I mean, you must get on top of this right now. You must have a plan. It's for, it's for their own good. And so I'm always thinking that in the back of my mind, how many listeners out there need this information in order to remap what they're doing?

• 1:00:59Peter Diamandis?

  And to be inspired, right? I mean, our, our goal here is to inspire one. To be in the thick of this and to find your own moonshots to understand.

• 1:01:08Speaker 04

  So if we just connect the dots on one thing, right?

• 1:01:10Peter Diamandis?

  Yeah.

• 1:01:11Speaker 04

  The fact that GPT-5 is now free.

• 1:01:14Peter Diamandis?

  It's crazy.

• 1:01:15Speaker 04

  Built into it, the best doctor in the world that can diagnose anything on a much better basis instantly for you is a profound uplift. And this, I think, Alex, the point you were making earlier.

• 1:01:28Speaker 03

  Exactly. When we talk about abundance in all of its many facets, taking 700 million people and suddenly giving them access to state-of-the-art AI, I think becomes transformative.

• 1:01:40Speaker 04

  It'd be interesting. I'm looking forward. Here's the thing I want to watch. How does OpenAI's user growth go from here, given that they've made it free?

• 1:01:49Speaker 03

  I thought you were going to go in a different direction, Sli. I agree that that's interesting. But another is, in some sense, this is the greatest A/B experiment that macroeconomists should be all over. Because prior to yesterday, the world, most of the world, didn't have access to Frontier AI. And starting yesterday, most, or a fraction of the world, call it, you know, a tenth of the world, does. What does the before and after look like? Do we see dramatically different outcomes in different dimensions?

• 1:02:16Speaker 01

  You know, Sam didn't have a huge part in the event yesterday, but he did a lot of post-game interviews, which I watched. And in one of them, one of the interviewers said, you know, imagine college and education for me in, say, 2035. And he said, 2035? Like, college in 2035? He said, if it exists, I mean.

• 1:02:37Speaker 03

  We need to coin a term for it. Maybe this is like an intelligence shock that's hitting the world.

• 1:02:43Peter Diamandis?

  Yeah.

• 1:02:43Speaker 04

  Oh, I hope so.

• 1:02:44Peter Diamandis?

  The intelligence inversion.

• 1:02:45Speaker 04

  Just for the college thing. My son is 13. My son is 13, and I'm hoping the university system implodes in the next five years before he goes.

• 1:02:54Peter Diamandis?

  You, your boy, mine.

• 1:02:57Peter Diamandis?

  And by the way, I'll make a call out as I'm talking to my son, I'm saying I'm going to go do WTF with my moonshot mates. And he goes, have you reached a million subscribers yet? And I go, why? Because, well, then you'll actually have a great podcast ad. So if those of you haven't subscribed yet, please help me get this to a million subscribers. Subscribe, share it with your friends.

• 1:03:19Speaker 04

  It's not about view count. I think it's more of a quality. And I think if a smaller set of people gets a much more value out of it, I think that's better.

• 1:03:28Peter Diamandis?

  All right. Emad, close this out on this.

• 1:03:31Speaker 01

  When I'm walking around MIT, a huge fraction of the people I bump into have actually watched the pod. So we got, we got a quality audience for sure.

• 1:03:39Speaker 02

  Yeah, I think the closing out is, you know, there's a cap on human intelligence, but there isn't on artificial intelligence. So everyone will have abundant and you can expect that next year a zero drops off here. And then the year after another zero drops off. And we're seeing that.

• 1:03:55Peter Diamandis?

  Insane.

• 1:03:55Speaker 02

  It's gonna be crazy.

• 1:03:56Speaker 01

  Crazy.

• 1:03:57Peter Diamandis?

  That's insane. So I want to hit a couple of things. OpenAI is eyeing a half a trillion dollar valuation, which is pretty extraordinary. It's one of the highest valued private companies, along with ByteDance, SpaceX and Ant Group. Wouldn't say much more here other than, you know, how will they go public? When will they go public? And will this be the largest IPO ever?

• 1:04:26Peter Diamandis?

  You know, we've seen OpenAI's GPT-5, but they also unveiled their open models. I don't want to go into this in too much detail, but Alex, do you want to lead us on this one? Actually, Emad, you're the open, open model champion around the globe.

• 1:04:42Speaker 04

  Wait, wait, wait, wait, wait. Hold on one second. Can we just go back to the previous slide just for a second?

• 1:04:48Peter Diamandis?

  Okay.

• 1:04:49Speaker 04

  So OpenAI made 10 billion, is making about 10 billion a year. Microsoft is making about 300 billion a year in revenues. And so OpenAI is valued at half of Microsoft. So I just want everybody just

• 1:05:04Peter Diamandis?

  No, Microsoft said that three trillion.

• 1:05:07Speaker 04

  No, no, I mean revenues. It's 10 billion versus 300 billion in revenues.

• 1:05:12Peter Diamandis?

  Okay.

• 1:05:13Speaker 04

  So it's a very big, it's very lofty, but that feels overpriced to me. Anyway.

• 1:05:20Speaker 01

  Well, Sam's Sam's projection is 100, 250 billion in revenue in, what is it, two years from today? Which I don't doubt that that's entirely possible. There's only two versions of the world, actually. There's a there's a version of the world where OpenAI easily hits that target. And there's a version of the world where Google destroys them and wipes them off the face of the earth. Those are the two possible outcomes.

• 1:05:43Speaker 04

  I mean, talk about capitalism at its finest, right?

• 1:05:47Speaker 02

  Look, SpaceX is 13 billion in revenue.

• 1:05:53Speaker 01

  And what's its valuation, like almost a trillion or something like that? Half a trillion?

• 1:05:56Speaker 02

  210 right now.

• 1:05:58Speaker 01

  Oh, that's right there. Okay.

• 1:05:59Peter Diamandis?

  But when they own Mars, it'll go up a little bit. So, you know,

• 1:06:05Speaker 04

  All right, next slide.

• 1:06:06Peter Diamandis?

  All right, there was an interesting note that Elon, you know, pushed out on on X, which was, when is OpenAI gonna buy Microsoft? Okay. Fascinating. All right, continue on with the open models here.

• 1:06:23Speaker 02

  I think the, I mean, it's pretty significant. A lot of people worried about Chinese open models going everywhere. And OpenAI have released a really solid model. It's a bit weird, has to be said. But the main thing is this model costs $4 million to train. And it's better than any model that we had this time last year.

• 1:06:41Peter Diamandis?

  That's extraordinary.

• 1:06:43Speaker 02

  Next year, it will cost $400,000 to train.

• 1:06:46Speaker 01

  How did you know it was 4 million to train? Did they release that?

• 1:06:50Speaker 02

  They said 2 million H100 hours. And the 20 billion parameter model that runs on your laptop was 10 times cheaper. It was 2 million. It's $2 an hour.

• 1:07:01Speaker 01

  And that's like from scratch, or was there a distilling from a big model?

• 1:07:05Speaker 02

  No, it's from scratch. It's 80 trillion tokens, 80 trillion words. So when we back it up.

• 1:07:11Speaker 03

  Dave, to your point, I think the footnote there is, is where do those tokens come from? And I think it's reasonable to assume in the style of, say, Microsoft phi models, that these are tokens that were generated through some synthetic process from a much larger, much more expensive in terms of fixed costs model, in which case whether you call the total pre-training cost just the marginal cost for training on the back of a much larger parent model or teacher model, I think that's the key distinction.

• 1:07:43Speaker 01

  We should do a whole podcast on just that topic because in the broader sense, AI that helps create the next AI is an incredible force multiplier for just humanity. And it's a good example because when you, when you just distill the training data and create some synthetic data using the prior model, you knock 90 to 99% off the cost of creating the next iteration. It's just, it's just crazy economics how it feeds back. Like no technology previously, other than maybe robots building robots someday. But there's nothing that feeds back like that.

• 1:08:14Peter Diamandis?

  We need, we need a new term, you know, that supersedes Moore's law here because the speed of this is extraordinary. And we're witnessing the evolution of, of something that I think we're going to look back as.

• 1:08:29Speaker 01

  I can tell Alex is about to say something brilliant. I always know that look.

• 1:08:32Speaker 03

  Point out a couple of things here. One, we do have this already. It's called education. Distillation is, is what humans use to, to take years and years that researchers and teachers spend accumulating and then convey this in a concise lesson to, to a student. So, so we as humans do distillation as well. It's very efficient, very economical. And so it's perhaps not that surprising to, to see distillation give us radical economic efficiencies in, in, in these open weight models. That's first point. Second point, just to go back, Peter, to your earlier comment, having these. Supply chain safe, if you want to call them that.

• 1:09:13Speaker 03

  Open weight models is transformative for so many applications that are highly regulated, that are very sensitive to supply chain risks in finance, in healthcare, in government. Now we have American trained models that can be embedded in all sorts of mission critical internet disconnected systems, and that is going to be transformative.

• 1:09:34Speaker 02

  Yeah, I think I think that just one final thing on this. This model only has five billion active parameters. And so it runs like faster than you can read even on a MacBook. And I think the big thing is everyone's talking about billion dollar training runs. I actually don't think that's true at all. I think you will have a GPT five level model by two years max that will cost under a million dollars to train end to end.

• 1:10:01Speaker 02

  And nobody's got that in their numbers. Or they will run on anything.

• 1:10:05Speaker 03

  The the the expensive part was the journey to get there. I I completely agree that at some point we're we're going to discover the made this point previously, the perfect architecture, the the perfect sort of micro kernel version of a foundation model that's relatively small parameter count that's fully multimodal. And if we knew what that were today, we could radically collapse training costs.

• 1:10:26Speaker 02

  I think what this actually shows is we don't even need that. We need to have a trillion good tokens. And if we've got a trillion good tokens, then you can train a frontier model for less than a million dollars next year. And so I think that's where we go.

• 1:10:39Speaker 04

  Do you then embed that into all sorts of devices and humanoid robots and moving cars?

• 1:10:44Speaker 02

  Anything, yeah.

• 1:10:45Speaker 03

  Everything everywhere.

• 1:10:47Speaker 04

  You embed everything. You do everything.

• 1:10:49Speaker 03

  Everything becomes intelligent.

• 1:10:51Speaker 04

  With a built in.

• 1:10:52Speaker 03

  I think that's where that's where this all goes.

• 1:10:54Speaker 01

  Yeah, so your question exactly defines the future entrepreneur. What am I going to do with all that? If I get for a a million, which is seed money. I can build a GPT-5 level model. What else can I build? And in the, this is going to be the age of abundance where it's limited by people's imagination. If you can imagine something genuinely useful that people want, the cost of creating it is near zero.

• 1:11:17Speaker 02

  Well, you didn't have to create the model. One entity needs to create that model open source once and the economies of scope means it can be used anywhere.

• 1:11:25Speaker 04

  Maybe I can stop arranging the room for the damn Roomba. That would be a great starting point.

• 1:11:32Peter Diamandis?

  Let's not go there, Salim. Everybody, there's not a week that goes by when I don't get the strangest of compliments. Someone will stop me and say, Peter, you've got such nice skin. Honestly, I never thought, especially at age 64, I'd be hearing anyone say that I have great skin. And honestly, I can't take any credit. I use an amazing product called OneSkin OS01 twice a day, every day. The company was built by four brilliant PhD women who have identified a 10 amino acid peptide that effectively reverses the age of your skin. I love it and like I say, I use it every day, twice a day. There you have it. That's my secret. You go to onescan.co and write Peter at checkout for a discount on the same product I use. Okay, now back to the episode.

• 1:12:16Peter Diamandis?

  All right, we have a backend of this WTF episode, which is to look at all the other companies in the AI wars that continue. Grok, Gemini, Meta, Nvidia, Apple. I'm going to try and move us through this. There is some important data we need to share with everybody. Just, you know, this is what we're watching and what we're keeping in tune with. Hopefully you are too. Let's jump in. The first is again, a quick look at humanity's last exam, HLE benchmarks. Alex.

• 1:12:48Speaker 03

  Yeah, I think what we're really seeing here, so we see two models, Grok with extensions and derivatives of various sorts and GPT-5 and its derivatives, leading the pack. I think if you pull back that headline, what you're actually seeing here is the power of tool use and the power of parallelism with GPT-5 leaning heavily on search. And and other tools and Grok for heavy leaning on the power of having multiple parallel agents collaborating and zooming out 10,000 meter perspective. I think what this points to is what we were just discussing, a world in which it's not just the the core

• 1:13:28Speaker 03

  foundation model, but arrangements, not even necessarily scaffolding, but the ability to integrate both these micro kernel type foundation models with each other in teams of agents and the ability to integrate them with powerful tools in their environment. That's going to turn out to be one of the the next big shocks in terms of how we're able to to challenge the frontier for HLE and other hard benchmarks.

• 1:13:56Peter Diamandis?

  By the way, people listening, our subscribers listening, if you get a second, you want to do something fun, just get onto onto ChatGPT five or Grok or wherever and just ask it to give you 10 example questions from humanity's last example.

• 1:14:12Speaker 04

  Yes.

• 1:14:12Peter Diamandis?

  I mean, I I I'm going to share a couple of them here that I asked for. And so here's one of the classics, category classics. Here's a representation of a Roman inscription originally found on a tombstone provided provided translation for the Palmyreni script. A transliteration of the text is the following, and then you have to transcribe that. Here's another one. What is the rarest noble gas on earth as a percentage of all terrestrial matter in 2002? Okay. All right. Here's one. I'm going to ask our our geniuses here. In physics, a point mass is attached to a spring. Spring constant is K. It oscillates on a frictional

• 1:14:55Peter Diamandis?

  surface, on a frictionless surface. If its amplitude of motion is doubled, what happens to its total mechanical energy? A, it doubles, B, quadruples, C, it triples, or D, it remains the same. I'm not going to ask you to answer that.

• 1:15:11Speaker 04

  Should hopefully quadruple, I would expect.

• 1:15:13Speaker 03

  Yeah.

• 1:15:13Peter Diamandis?

  It does quadruple, yes, correct. Okay, we got.

• 1:15:19Speaker 04

  Shivers flashing back to my physics courses. Please, for God's sakes, let's not do that.

• 1:15:24Peter Diamandis?

  All right, last one. Consider a balanced binary search tree, like a red-black tree, with N nodes. What is the worst-case time complexity for searching a given key?

• 1:15:37Peter Diamandis?

  And the answer is zero log n. Okay.

• 1:15:41Speaker 03

  Oh, order login.

• 1:15:43Peter Diamandis?

  Oh, yeah.

• 1:15:47Peter Diamandis?

  There you go.

• 1:15:48Speaker 02

  I'd like to point out on this one, the open source models OpenAI just released scored nineteen percent and seventeen percent. And the seventeen percent is the twenty billion parameter model that will run on anyone's laptop.

• 1:16:00Peter Diamandis?

  Crazy. Amazing. Bring that into your college exams, everybody. All right.

• 1:16:08Peter Diamandis?

  We had Elon pipe up. He said, great work. So here was the tweet he's referring to. Very proud of us at XAI after seeing the GPT-5 release. With a much smaller team, we are ahead in many. Grok four, world's first unified model and crushing GPT-5 in benchmarks like Arc AGI. So we're going to have this continuous, if it's an ego battle, a financial battle, whatever it might be, where everybody just, just trying to one up each other. And of course, his next tweet was Grok five will be out before the end of the year, and it will be crushingly good. So comments on Grok.

• 1:16:54Speaker 02

  He just tweeted, he just tweeted saying Grok four point two oh before the end of this month, number one.

• 1:17:02Speaker 03

  Four point two oh. I think Peter, one of the take homes here is that whoever's defining the benchmarks wins. It's like, you know, you create the evals and humanity wins. It's, it's amazing how starved the research community is for compelling new evals as discussed previously. And, and so to the extent that we can create more evals that as, as I think your community has also chimed in historically with some wonderful ideas for abundance oriented benchmarks or evals, the frontier labs will, I think, race to achieve them.

• 1:17:37Peter Diamandis?

  All right. Most of the poly market, you know, predictions have Google winning by the end of the year. And for good reason, what we've seen is extraordinary. And here's the title of the slide, Demis Hassabis, in a word relentless. In only two weeks, they've shipped or achieved, and I'll read the list here, Gemini 3, we'll see an example of that, Gemini 2.5 Pro, Deep Think, Gemini Pro, free for university students, Alpha Earth, amazing, we'll see a demo of that, Enius, Deciphering Ancient Text, Gemini won the gold medal in the International Math Olympiad, Storybook, Kaggle Game Arena, Jules, Notebook

• 1:18:22Peter Diamandis?

  LM Video, Overviews, and Gemma, which passed 200 million downloads. And this is Google's lightweight, open source, open weights model. I mean, really impressive work.

• 1:18:35Speaker 01

  Yeah, well, so Dennis has, Dennis has 6,000 people in AI R and D. OpenAI is up to a little under 2,000 now, but these guys at Google have been working on it for years. So they've got about a factor of 10 more person hours put into it so far, and they're all operating on things in parallel. So they're, they're now unleashing it all. Yeah, it was all just kind of sitting there in the lab until OpenAI put the competitive pressure on them.

• 1:19:02Peter Diamandis?

  Yeah.

• 1:19:03Speaker 01

  Now something has shifted in a big way at Google and a couple of fronts. You know, one, they're unleashing all the things they've been working on. The other is they proactively reached out to a bunch of our companies, including Blitzy, which is, you know, Blitzy is a particularly hot company. But I don't know how they found it, probably through all their big data. But the Gemini people came over to our office proactively and said, we need to meet with you. So they're really reaching out, trying to get the businesses to move over to using Gemini. And that was also really evident in the GPT-5 rollout yesterday is the call to companies saying, we're here, we're open, we want to partner with you. And we're cutting the price point to make it easier to do. And, you know, we're

• 1:19:47Speaker 01

  open for business. So I think, I think that's a new thing. I hadn't seen anyone proactively reach out to our companies until this week.

• 1:19:56Peter Diamandis?

  Amazing. All right, let's take a look at a few of these examples coming out of Google. This is Google's Genie 3. It's world models for gaming. Let's play the video. I was blown away by this. I found this probably one of the most impressive things I've seen in the last week.

• 1:20:13Speaker 09

  What you're seeing are not games or videos. They're worlds. Each one of these is an interactive environment generated by Genie 3, a new frontier for world models. With Genie 3, you can use natural language to generate a variety of worlds and explore them interactively, all with a single text prompt.

• 1:20:41Speaker 09

  Let's see what it's like to spend some time in a world. Genie 3 has real-time interactivity, meaning that the environment reacts to your movements and actions. You're not walking through a pre-built simulation. Everything you see here is being generated live as you explore it. And Genie 3 has world memory. That's why environments like this one stay consistent. World memory even carries over into your actions. For example, when I'm painting on this wall, my actions persist. I can look away and generate other parts of the world. But when I look back, the actions I took are still there. And Genie 3 enables promptable events,

• 1:21:25Speaker 09

  so you can add new events into your world on the fly. Something like another person, or transportation, or even something totally unexpected. You can use Genie to explore real-world physics and movement, and all kinds of unique environments. You can generate worlds with distinct geographies, historical settings, fictional environments, and even other characters. We're excited to see how Genie 3 can be used for next-generation gaming and entertainment. And that's just the beginning. Worlds could help with embodied research, training robotic agents before working in the real world, or simulating dangerous scenarios for disaster preparedness and emergency training.

• 1:22:10Peter Diamandis?

  All right, I'm gonna pause there, but holy cow. I mean, I don't see, I mean, first of all, the simulation theory just took a huge jump forward.

• 1:22:22Speaker 04

  Boom.

• 1:22:23Peter Diamandis?

  I mean, you know.

• 1:22:24Speaker 04

  This blew my mind. I actually showed this to a friend who spent the last two, three years building metaverses. And, and he was literally had his jaw dropped and he said, I, I, I don't even know where to start. The fact that you can have a responsive environment that tailors depending on where you look, and all that's generated on the fly in real time. He couldn't cope. I've just never seen his mind broken like that.

• 1:22:49Speaker 02

  Yeah, it's a master fusion transformer, similar to a lot of the video models like VO and others. And again, we're kind of seeing the breakthroughs coming in this, especially as Google has such an amazing data set. I think that you'll see a video like this, a video model like this as well from XAI. This is what Elon's going to be putting those 10,000 black wells on his video model towards. But the fact that it's real time now gives you a real idea about that. Similarly, we've seen real time video generation from WAN and others now. So every pixel will be generated in a few years, which is gonna be cool.

• 1:23:21Peter Diamandis?

  That progression has been made. And what if, you know, meta, you know, Zuck has wanted the metaverse forever. And of course, this is delivering the metaverse.

• 1:23:31Speaker 03

  On the one hand, on the other hand, this is billions of dollars of capex that's, that's been allocated to video gaming or to, to metaverse software that suddenly is in danger of having been rendered irrelevant. If this can all be just the output of a, a single model, a thousand voices in the video gaming industry just cried out in anguish if this is all just a prompt away.

• 1:23:54Speaker 04

  That's the response I got.

• 1:23:56Peter Diamandis?

  Yeah. I mean, with, with VO, with, with VO3 potentially crushing Hollywood and, and this potentially crushing the video game industry, or reinventing it, accelerating it, making it possible for anybody to create magically compelling video games.

• 1:24:10Speaker 03

  This is the Star Trek holodeck, that this is the Matrix. That this is the, the keynote potentially in, in the tech tree of our civilization that unlocks general purpose robotics and general purpose autonomous vehicles.

• 1:24:24Peter Diamandis?

  Yeah, because they can train inside of that.

• 1:24:26Speaker 03

  That's right.

• 1:24:27Peter Diamandis?

  Extraordinary. Absolutely extraordinary. All right, here's another extraordinary gift from Google, and this is Google's Alpha Earth Maps in real time. This turns massive satellite data into unified global maps, views of land and coastal areas on 10 by 10 meter precision, tracking deforestation, crop, wealth, water use, and urban growth. Let's take a quick look at this video.

• 1:24:52Speaker 10

  This is how our new AI model, Alpha Earth Foundations, interprets the planet.

• 1:24:56Speaker 11

  Different colors in this map show how different parts of the world are similar in their surface conditions.

• 1:25:02Speaker 10

  So similar colors mean similar things, like two deserts, two forests.

• 1:25:07Speaker 11

  The model understands the unique patterns that distinguish any ecosystem, so it's able to use those learned patterns and quickly find matching patterns in other places in the world. This allows it to tell the difference between, say, a sandy dune on a beach and the deserts of the Sahara.

• 1:25:22Speaker 10

  It used to take months to years for scientists to accurately map the world.

• 1:25:26Speaker 11

  But with our dataset, they can do it in minutes.

• 1:25:29Speaker 10

  Much like Google Search has indexed the web, with Alpha Earth Foundations, we've indexed the surface of the planet.

• 1:25:34Speaker 11

  And we're making this available through Google Earth Engine for the year's 2017.

• 1:25:38Peter Diamandis?

  All I can say is, just in time. Thoughts?

• 1:25:41Speaker 03

  What's interesting here, I think, is this is what's called an encoder-only model. It takes 10-meter by 10-meter patches of Earth's surface and converts them to high-dimensional vector representations. Encoder-only models were very popular in natural language processing prior to the advent of so-called decoder-only models, like the GPT series. I think the elephant in the room here is, once we have encoder models that are, or encoder-only models that are, that cover the Earth's surface, we're about to get decoder-only models. And what that'll enable in practice is, so right now with these encoder models, you can convert arbitrary land masses or ocean masses to vectors and do a bit of regression on them

• 1:26:25Speaker 03

  and maybe a bit of light prediction. With decoder-only models, you'll be able to take Few square kilometers of land and extrapolate out visually what does the future of this land look like? And you'll be able to do searches of interventions. If I put a parking lot here, or I put a hospital here, what's going to happen in all likelihood to development in the area? You'll be able to do urban planning as a matter of a tree search in the same way in which AlphaGo or AlphaZero or MuZero are able to play chess. That's, I think, going to be the real economic unlock.

• 1:27:00Peter Diamandis?

  Amazing.

• 1:27:00Speaker 04

  See, this is the application usage where I think all these things start to really shine, where you can take all that capability and apply it to something like this. It'll completely transform how we look at the world. My mind is kind of blown with this one.

• 1:27:15Speaker 01

  Yeah, I'm really glad you said that, Alex, because I really did not get the implications of this until you explained it just now. I do appreciate that. You know, on the prior slide too, I had a meeting earlier today with Satya Mahaja, the CEO of Dateline here, who, you know, all these companies are thinking, what's my moat? What's my moat? What's defensible? What's going to give me recurring revenue for the next 20 years? And like, it's just not a way to think anymore. If you look at the rate of change, it's all about small, nimble teams and great team dynamics. Overall, there'll be far, far more company success than ever before. But you can't expect to sit still. You have to reinvent yourself all the time.

• 1:27:56Peter Diamandis?

  Amen. Amen. I think agility and passion-driven building and understanding the root cause problems that you want to go solve, those are the fuel for the future. It's not setting up regulatory, you know, blockage. All right, next up is a video of Zuck on Meta Superintelligence Labs. Superintelligence for everyone. Let's take a look.

• 1:28:21Speaker 06

  I want to talk about our new effort, Meta Superintelligence Labs, and our vision to build personal superintelligence for everyone. I think an even more meaningful impact in our lives is going to come from everyone having a personal superintelligence that helps you achieve your goals, create what you want to see in the world, be a better friend, and grow to become the person that you aspire to be. This vision is different from others in the industry who want to direct AI at automating all of the valuable work. This is going to be a new era in some ways, but in others, it's just a continuation of historical trends. About 200 years ago, 90% of people were farmers growing food to survive. Today, fewer than 2% grow all of our food.

• 1:29:04Speaker 06

  Advances in technology have freed much of humanity to focus less on subsistence and more on the pursuits that we choose. And at each step along the way, most people have decided to use their newfound productivity to spend more time on

• 1:29:18Peter Diamandis?

  All right, so he's out pitching hard. He wants to get to superintelligence first. What could possibly go wrong? He is, the poaching continues, and I love this. So Zuck contacted over 100 OpenAI employees. 90% of them turned him down. Why? Because they think OpenAI is closer to AGI than Meta. That's got to sting. Imad, what do you think about that?

• 1:29:47Speaker 02

  I think he has a very different definition than Sam Altman does. I think one of the reports was that he was talking about how AI could make Reels a better product. So I think it's a very different view to the type of ASI that we're talking to. They should just call it Meta Intelligence. But, you know, I think it shows, like, you see the billion-dollar offers. People still don't move. I think everyone feels that we're getting close to that AGI point. And you want to be where it's going to happen, you know? Because what even is money after that? We're going to find out soon.

• 1:30:18Peter Diamandis?

  I mean, that's a very important point. I mean, in this, in this post-abundance world, we're living in a post-capitalist world as well. Money has very little meaning. Imad, you and I, and Alex, you and I have spoken about that at length.

• 1:30:32Speaker 03

  That's right. And I, I think, Peter, as the cost of talent is increasing, and it would appear that it certainly is, that that's going to force Frontier Labs to start competing based on algorithmic insights and ideas. And I think that's a net positive for the economy and the world.

• 1:30:49Peter Diamandis?

  Amazing. All right. I love this next one. The Zuck poaching effect. So Sam just announced $1.5 million bonuses for every employee over two years. He's now officially made every employee at OpenAI a millionaire by giving them over $1 million. That compares to 78% of Nvidia employees who are also millionaires.

• 1:31:14Speaker 04

  David asked if that included the baristas. Do we answer that?

• 1:31:17Peter Diamandis?

  I don't know, but we'll be at OpenAI in a couple of weeks, and we'll ask.

• 1:31:24Speaker 01

  Okay, it'll affect your tipping at the coffee counter, I guess.

• 1:31:28Peter Diamandis?

  Oh, my God.

• 1:31:29Speaker 03

  Peter, I would expect this to create a bloom of seed funding of startups in the next year or two. It's just going to be absolutely enormous. I'm already starting with some of the startups I advise, starting to see the beginnings of an absolutely enormous.

• 1:31:43Peter Diamandis?

  That is such an important point, right? This is something that America does so well. We create, you know, these, these deck a billion and cent a billion dollar companies and trillion dollar companies and we make because of stock options and stock distribution, we make all the employees super wealthy and they turn around and invest in other individuals. And that doesn't exist in a lot of countries. Dave, you've spoken about this.

• 1:32:07Speaker 01

  Well, there's two things that are different this time, but you're right. That is the engine of America and it works really, really well. This time around, it's so fast and the teams are so young. So that's unprecedented and I could see some things that go wrong with that, but it's, you know, it's a field day right now. So might as well, might as well savor it. Also, it's much clearer now how you're supposed to work with either OpenAI, Anthropic, or Google.

• 1:32:31Peter Diamandis?

  How's that?

• 1:32:31Speaker 01

  It's not, well, I mean, they've made it very, very clear that they want partners in all these categories, especially complicated, regulated categories or categories that have proprietary data. They, here's the API, here's how we want to work with you. The pricing is going to be super low. We want you. For those three companies, it's really clear. It's not as clear with Grok yet, and I don't think anyone knows how to work with Meta, if there is any way. But, but for the three other big guys, it's, it's just a field day for here's how we want to partner. And please just bring in the revenue, change the world, we're all happy. So I really am cheering for Sam in this battle too, because, you know, Marc Andreessen built Netscape, coolest company ever, got absolutely obliterated when

• 1:33:15Speaker 01

  Microsoft woke up. They just annihilated him and changed the course of his life. He did well in the end. Anyway, but complete life change. So now Sam is that guy. He woke up Google. He's got a little shaky relationship with Microsoft right now.

• 1:33:28Peter Diamandis?

  I think he pushed Google over the edge. I think they were awake already in that regard.

• 1:33:33Speaker 01

  Yeah, yeah. Well, so now he's got them all coming after him concurrently and he's got to out race them. And it'd be a great American success story if he can stay ahead of that and survive.

• 1:33:43Peter Diamandis?

  Can't wait for the Hollywood movies that are coming out all on these subjects.

• 1:33:47Speaker 02

  Yeah, I think one of the really interesting things is that crypto has basically been legalized in America almost fully with the lot in the last week. And so I think next year crypto XAI is going to be the most ridiculous thing you've ever seen. Because these startups will go with a few smart people, they'll get massive traction by leveraging these models, and anyone will be able to buy them pretty much instantly. And so we're just at the start still of the bubble, I think, versus what we're gonna see. It's gonna be the biggest bubble of all time.

• 1:34:17Peter Diamandis?

  Well, bubble has a negative connotation to it, Iman.

• 1:34:21Speaker 02

  Of course, but you know, we're just at the start now. Like, this is the final hurrah of the current financial system.

• 1:34:28Peter Diamandis?

  Well, or societal system as well.

• 1:34:33Speaker 01

  I really, I really think that if you just take a step back and try and visualize Sam's life for real, the biggest companies in the world are offering your direct reports $1 billion to walk out the door. You have to fight. At the same time, Mira Maroti, Ilya Sutskever, two of your founders are trying to raise $10, $20 billion to compete directly with the thing they built at OpenAI.

• 1:35:00Peter Diamandis?

  Well, they don't try. They did raise.

• 1:35:02Speaker 01

  They did. Does it get any harder for an entrepreneur than where Sam is right now? And he's, he's like bulletproof. He's just fighting his way through it. It's, it's something that the movie will be really cool, I think. There's so much to work with.

• 1:35:16Speaker 04

  This is a great testament to the fact that if you keep pushing product, right, and keep doing, or launching new things and keep innovating, you can stay ahead. And Facebook showed us that, Yahoo showed us that, Google showed us that, all in their era, they just kept breaking boundaries. And so the only thing now is, can you break those boundaries and break the status quo and relentlessly keep doing that?

• 1:35:40Peter Diamandis?

  And differentiate yourself from the competition?

• 1:35:42Speaker 03

  Yeah, I think it's sort of an interesting economic experiment. In the past, I've compared the AI build out that's happening in the US to 1939 and the prelude to the Manhattan Project. It's sort of an interesting thought experiment to ask, what would have happened if nuclearization and the Manhattan Project hadn't been a nationalized effort, but instead had been a private sector effort where blue chip companies were all competing with each other to see who could build the first atomic weapon? And how much would they be spending to poach the top scientists from each other to build that first atomic bomb that has such strategic import over the future light cone?

• 1:36:24Speaker 03

  I think we're living in some sense a civilian version of that thought experiment.

• 1:36:28Peter Diamandis?

  Hmm, amazing.

• 1:36:30Speaker 02

  It's actually, the really interesting thing is, it's not hard to know how to build the models if you know how. The if you know how is really, really rare. And so that's why they're willing to splash these billions on top of that. And it'll be interesting to see what they come up with now as these things get commoditized.

• 1:36:47Peter Diamandis?

  All right, on the OpenAI train, Nvidia and OpenAI announced their first European Norway data center. This is $2 billion OpenAI data center, 100,000 Nvidia GB 300 superchips. They'll host 230 megawatts of capacity, expandable to 520 megawatts, so half a gigawatt of capacity, powered 100% by renewable energy out of Norway. Let's take a quick look at this video.

• 1:37:14Speaker 12

  The launch of Stargate Norway marks a new chapter for AI infrastructure in Europe. We're entering a new industrial era. Just as electricity and the internet became foundational to modern life, AI will become essential infrastructure. Every country will build it, every industry will depend on it. AI is no longer hand-coded. It is trained. It is refined with massive compute. It is deployed into factories, research labs, and digital services. Stargate Norway will be powered by GB300 superchips and connected with MVLink. It is designed to scale to hundreds of thousands of GPUs and support the most advanced

• 1:37:59Speaker 12

  models in training, reasoning, and real-time inference.

• 1:38:03Peter Diamandis?

  All right, there you got it. Emad, analysis, please.

• 1:38:08Speaker 02

  Yeah, I mean, I think this is part of the big sovereign AI strategy because your comparative advantage as a country will be how many chips you got and how much intelligence you have when most of your workers are digital. We've seen OpenAI go very aggressively on this front. In fact, this week, they announced that they're going to be rolling out ChatGPT to all federal workers in the US at the cost of $1 per agency per year. So I think the land grab has really begun.

• 1:38:35Peter Diamandis?

  They couldn't say, they couldn't have said free, huh?

• 1:38:37Speaker 02

  Yeah.

• 1:38:39Speaker 03

  I'd add, Peter, there's, I think, a less obvious angle here, which is pulling back the details on the announcement. This new data center is planned to be powered with hydropower, which is intrinsically scarce. You either have access to it or you don't. You don't necessarily. It's not that ergonomic as a nation-state to create a lot more hydropower. So that means there is very literally a land grab here. And this is Stargate planting its flag in that hydropower to the extent that Europe has a policy of bounding power to certain energy sources. There's only a finite amount that's available to reprogram to AI. So real land grab.

• 1:39:25Peter Diamandis?

  And we'll see geothermal energy as a land grab, and we'll see other areas. I want to move this forward here. We saw a couple of interesting announcements coming out of the White House. So Apple announced $100 billion US investment. This is increasing their total investment to $600 billion. And I don't know, this is, finally, we're seeing Apple come back to the US. How much of Apple's products are overseas manufactured right now? Anybody have an idea?

• 1:40:00Speaker 01

  It's gotta be overwhelming majority, like 90-plus percent. Yeah, huge.

• 1:40:06Peter Diamandis?

  Comments, Dave?

• 1:40:07Speaker 01

  Well, look, you know, we've been, most of the countries that have like a Samsung in Korea or they're, the government industrial integration is very, very tight. The US has never really had that before. This is the first time, but, uh, I mean, obviously works really, really well. It got Japan on the map and then it got Korea on the map and now it's gotten China beyond on the map. Um, and so, you know, Trump is the first president to really take this to its limit. He's a business guy, so he knows how to do it. Um, and it's obviously going to work really, really well. It's, it's not super hard to figure out. You just need to do it.

• 1:40:43Speaker 03

  I would also maybe add that I think there's, again, going back to this idea of a tech tree existing for civilization. It seems clear that there's an innermost loop to the tech tree that's at the intersection of fabs and electricity sources and drones and rare earths. And to the extent that it's possible to co-locate as high a density as possible, talent and infrastructure for building all of these, I, I think that has the potential to lead to an economic explosion for the US, for the world.

• 1:41:13Peter Diamandis?

  Amazing. One more article coming out of the White House here on AI, and that is Trump Demands Intel CEO Resignation Over China Ties. Trump Labels CEO Highly Conflicted Over $200 Million Plus In Past Investments In Chinese Tech Firms And Relationship With The Defense Department. For me, this has echoes of the J. Edgar Hoover anti-communist campaigns from the FBI.

• 1:41:40Peter Diamandis?

  Iman, do you have any opinion on this, being a non-American?

• 1:41:45Speaker 02

  Yeah, well, I mean, look, it's just posturing, right? Like, I think that this whole US versus China AI thing is completely overblown because everything gets commoditized soon anyway. Actually, to be honest, we should have had the push for open source being that China wants to get into all our systems. Then they would have actually put proper money behind it.

• 1:42:07Speaker 02

  It's completely wrong, though, because, again, the correct view is this is abundant and it's going to come to everyone everywhere. You can't keep a lid on it at all. And how do you keep a lid on math?

• 1:42:18Speaker 01

  I threw this into the deck, actually, just to spark the conversation around, you know, right now, the chips that are driving this entire AI revolution, two-thirds, 66% market share through TSMC, a single manufacturer.

• 1:42:31Peter Diamandis?

  Crazy.

• 1:42:32Speaker 01

  That's utterly insane and not sustainable. So my guess is that the White House is thinking about this and talking about Intel every day. There's, it's not coincidence that Trump decided to tweet about, you know, one CEO. The China thing, I don't know what, what, what he's thinking about there. But, but, you know, Lippo's a 65-year-old guy. Intel must succeed for, it's just an incredible national priority.

• 1:42:57Peter Diamandis?

  It's an incredible asset, right? I mean, it defined the last 50 years.

• 1:43:00Speaker 01

  Mm-hmm.

• 1:43:01Peter Diamandis?

  And, uh, yeah.

• 1:43:02Speaker 01

  So, so anyway, the, the point is, the White House is talking about it. We need balance in chip manufacturing desperately, and we need a lot more volume of chip manufacturing, so.

• 1:43:12Speaker 04

  I mean, if you're at Intel, what you should be thinking about is, where do you, how do you leapfrog?

• 1:43:16Speaker 01

  Well, they have, they, you know, their tech, their 18 nanometer, or 1.8 nanometer, 18 Angstrom tech is absolutely fine. They need to, to get the yields up, and then they need to build more fabs, and which means federal help. And so I, I just think that if someone running that company can, can get friendly with the current administration, that it's all unlocked and it'll explode and succeed wildly, which is what America needs. And, I don't know, I, I hope they figure out the relationship between Lippo and Donald Trump quickly.

• 1:43:49Peter Diamandis?

  Yeah.

• 1:43:50Speaker 02

  I mean, actually, actually, part of this was because Intel were trying to sell their fabs to TSMC.

• 1:43:55Speaker 01

  Yeah.

• 1:43:56Speaker 02

  So, again, it gets complicated.

• 1:43:58Speaker 01

  I mean, that would be devastating for the world, you know, really. There's no way that can get through. But, but I get it, right? It's, it, because all the losses at Intel come from the fabs. They would immediately monetize a huge asset. The remaining Intel would be hugely profitable the next day. So that's the allure of that transaction. But then you have one company controlling the entire destiny. Yeah, there's no way. That makes sense.

• 1:44:20Peter Diamandis?

  All right. I want to close out with this slide, which is, I find telling, especially on the backside of the Intel conversation, that we're still early in terms of build-out. So here we see a slide showing infrastructure capex as a percent of the US GDP. So the railroads were 6% of the GDP back in the 1880s. Telecom was 1% back in 2020 and today our AI data centers in 2025 is 1.2%. We're still early and and you know Alex, we've talked about and Imad that we're about to turn planet into Computronia and we're building data centers every place. And maybe the solar system, we'll see.

• 1:45:02Peter Diamandis?

  And maybe the solar system. So Liam, you've got an event coming up soon. Talk to me about it.

• 1:45:08Speaker 04

  On August 20th, we have our next monthly EXO workshop. The last one, the last two or three have sold out. People are absolutely loving them. It's a hundred bucks to come, bring your company and we'll teach you how to build an EXO. We actually have a great ad, which we'll get a link to and post in here, which is they created an ad where the AI reads out a real review by a real person, but it's an AI reading it out. Super funny. So it's fun.

• 1:45:34Peter Diamandis?

  And for those interested, I've got some comments interested in the Abundance Summit in March. Applications are closed at this moment. They'll be reopening in September, but you can get on the waitlist by going to www-abundance360.com and let us know that you're interested. We'll have all of our Moonshot mates at the Abundance Summit as well. Let's take a quick look around the horn. Dave, what's happening for you in the next few weeks?

• 1:46:03Speaker 01

  Well, the biggest thing by far is we'll be together at OpenAI in what 11 days, 12 days? They'll be there the whole week actually. And I, God, there's so much going on in that building. So really looking forward to that.

• 1:46:16Peter Diamandis?

  We're having a fun podcast with the Chief Product Officer, Kevin Wile at OpenAI. Looking forward to that conversation. Imad, it's 2 AM. Do you know where your children are? You're a nuclear power source, buddy. Thank you for sticking with us through the wee hours of the UK.

• 1:46:35Speaker 02

  It's too much fun to sleep.

• 1:46:37Peter Diamandis?

  It is. And what's what's on your plate over the next month?

• 1:46:41Speaker 02

  We've got some big releases coming up, in particular, I've been looking at the economics of the AI age. So it's going to be wild. I'm going to be releasing a bunch of stuff around that.

• 1:46:50Peter Diamandis?

  I'm seeing what you're going to release, and it is stunning. You know, dare I say, you know, just earth shattering. Alex, how about yourself, pal?

• 1:47:01Speaker 03

  Oh, my goodness. Well, I think we're in a time, although on an exponential curve, every point looks like the knee in the curve or the inflection point. So one has to be careful of such anthropic bias. I spend most of my time advising tech startups and making sure that the benefits of AI are evenly distributed throughout the economy. And every day is an adventure and an opportunity to smooth out the singularity, as it were.

• 1:47:31Peter Diamandis?

  All right. Well, everybody, thank you for joining us on this episode of WTF and the GPT-5 announcement. We'll be coming back to you with an episode again next week. Please tell your friends about what we do. Our mission here is to help you understand how fast the world is going, to inspire you, to give you the motivation to create your own moonshots, and to make this understandable. And actually, what was the word you used, Alex? Riveting.

• 1:47:56Speaker 03

  Riveting. I'm at the edge of my seat.

• 1:48:00Peter Diamandis?

  An amazing time. The most amazing time ever to be alive. All right, to all of you, thank you for a fantastic conversation. 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 report's for you. Readers include founders and CEOs from the world's most disruptive companies, and entrepreneurs

• 1:48:43Peter Diamandis?

  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 dmantis.com/metatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode.

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