AI Experts React: Elon’s Grok 4 Is Now #1 in AI — This Changes Everything w/ Emad Mostaque, Salim Ismail & Dave Blundin | EP #182

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 of Link Ventures Emad Mostaque is the founder of Intelligent Internet – Offers for my audience: Get the first lesson of my executive course for free at https://qr.diamandis.com/futureproof 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 –- Learn more from Emad: https://ii.inc/web Learn about Dave’s fund: https://www.linkventures.com/xpv-fund Join Salim's Workshop to build your ExO https://openexo.com/10x-shift?video=PeterD062625 Connect with Peter: X Instagram Listen to MOONSHOTS: Apple YouTube – *Recorded on July 10, 2025 *Views are my own thoughts; not 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?

  How impressive is Grok 4 for you?

• 0:03Speaker 01

  If you look at the AIME benchmark, which is an advanced math quiz, Grok 4 scored 100% on it. You're literally running out of benchmarks.

• 0:13Speaker 02

  It's gotta be driving Google nuts that Elon got this done in 28 months from a cold start.

• 0:20Speaker 03

  When he said he was gonna put this huge cluster together, every AI expert in the world said you cannot get power laws and coherence at that scale. You just can't do it. Every AI expert is like, "Oh, goddamn, he did it."

• 0:31Speaker 01

  The amount of compute and resources, again, are going exponential. Now it's the real quality that differentiates the top models between each other.

• 0:39Speaker 03

  My big question is, where do we go from here?

• 0:51Peter Diamandis?

  Everybody, welcome to Moonshots, an episode of WTF just happened in tech this week. Special episode today, following the release of Grok 4. It is Large Language Model Release Month. An extraordinary string of new models coming up. I'm here with my Moonshot mates, Dave London, the head of Link XPV, Salim Ismail, the CEO of OpenEXO, and a special guest to help us dissect all of this is Imad Mustak, the founder of Intelligent Internet. Guys, it was a pretty epic day yesterday. Good to see you all. Pleasure to have you. Yeah, likewise. Yeah, and this is our special Grok 4 edition. Imad, you're in London, yes?

• 1:37Peter Diamandis?

  Yep. Fantastic. And Salim, where on the planet are you, buddy? Uh, New York. Okay. Dave's in Boston, I'm in Santa Monica. All right, let's get going. So just to jump in, goal here is dissect what happened yesterday, now blow by blow. What's Grok 4 all about? And just to, you know, shadow what's coming, we've got a few new model releases coming with Gemini 3, GPT-5, you know, and probably a few others. So let's kick it off with this video.

• 2:12Speaker 04

  Like Grok 4 is postgraduate, like PhD level in everything. Better than PhD, but like most PhDs would fail. So it's better that said, I mean, at least with respect to academic questions, I want to just emphasize this point. With respect to academic questions, Grok IV is better than PhD level in every subject, no exceptions.

• 2:37Speaker 04

  Now, this doesn't mean that it's, you know, times it may lack common sense and it has not yet invented new technologies or discovered new physics, but that is just a matter of time.

• 2:52Speaker 04

  If it, I, I think it may discover new technologies as soon as later this year. And I would be shocked if it has not done so next year.

• 3:02Peter Diamandis?

  All right. Dave, you want to take the first?

• 3:04Speaker 02

  Yeah, it's awesome. This is actually a golden moment in time because it is an absolutely brilliant assistant. They can do almost anything you want it to do, but like Elon said, it's not reasoning yet. So it's not coming up with the fundamental, this is what we should build and this is why. So that's still in the hands of the creator, the human operator. And so this, this moment in time is actually really, really golden. It feels just like an Iron Man movie where you've got Jarvis. Jarvis will build the suit for you. You have to decide how you're going to save the world. It's, it's a really, really fun time to be using these brand new, like, like you said, there'll be three of these

• 3:44Speaker 02

  in the next month or so. This is the first round and he's dead right. You know, the PhD level solution, it's all measured in the, in the benchmarks we'll get into in a minute. But it, it does virtually anything, mind blowing capabilities, but it doesn't decide what to do and why.

• 4:01Peter Diamandis?

  Ahmad, I love your take on this. You've been plugged into this world, you know, intimately for a while. How impressive is Grok IV for you?

• 4:12Speaker 01

  I think it is very impressive. I think, you know, picking up what Dave said, I think it is reasoning, but it's not planning as yet. And there was a question is, when we got to this Rona flop level, I think that's the term, like 10 to 28, I think, flops. Would we continue to see improvements? And part of that is the compute and part of that is the data, as we'll get to later. And the answer is yes. And again, like Elon said, getting above graduate level in every sub postgraduate level in every subject, it can now execute and it can reason. It doesn't have planning yet.

• 4:50Peter Diamandis?

  So I mean, isn't that AGI? Isn't that the sort of like kind of definition of AGI? We passed through the Turing test without noticing. Are we going to pass through AGI without noticing too?

• 5:01Speaker 01

  It's like this hedonic adaptation. You're like, of course it's fine, you know? But already, again, if you want to get a job done, it will do the job for you of summarizing a book. Like it will do the job for you of like writing a summary of something or translating, et cetera. And life is just the same so far because you haven't got that final step that Dave said. And there's a few extra bits that we need for full agentic above that. But we're nearly there because we have that final building block now with this next level of model.

• 5:34Peter Diamandis?

  Yeah.

• 5:34Speaker 01

  Where it's reliable.

• 5:35Speaker 02

  Extinction, by the way, that it's, it is reasoning. It has to be to solve these really hard PhD level problems, but it's not planning. That's a great way to phrase it. Run a flop is 10 to the 27th. So that's the scale of these training algorithms.

• 5:49Speaker 01

  That was the, that was the level the AI act said they wanted to ban, by the way. So this would be the first ban model.

• 5:55Speaker 02

  Yeah, that's a great point.

• 5:56Speaker 03

  I think, I think one of the things that's happening is the absolute beauty of capitalism, where you've got big juggernaut companies fighting it out for supremacy and throwing, taking massive risks, choosing design paths, taking huge gambles and really, really going for it. I think it's really magical to watch this happening.

• 6:16Peter Diamandis?

  Yeah, I love this tweet from Sawyer Merritt. It says, XAI was founded in March of 2023. Just 28 months later, it's now the number one model in the world, verified by independent testing, incredible achievement. I mean, it is insanely fast compared to everything else that's being built. I remember when in May two years ago, when Elon was first raising money and I had a chance to sit in on a investor pitch in the first round for XAI. And he said, I'm gonna have 100,000 GPUs, H100s operating by the by the end of the summer. And everybody's like, no, no freaking way. And he did just that.

• 6:59Peter Diamandis?

  And he's not slowed down. So here we see in this image, Artificial Analysis Intelligence Index, Grok 3 was placing like fifth or sixth. Grok 4 leaps to the front of the line. Are we going to continue seeing this, Emad? You know, this just leapfrogging each other, leapfrogging each other? Is there is there no end in sight?

• 7:22Speaker 01

  It's getting very difficult because if you look at the benchmarks they have there, if you look at the AIME benchmark, which is an advanced math quiz, Grok 4 scored 100% on it.

• 7:33Peter Diamandis?

  Yeah, so you can't go beyond that.

• 7:36Speaker 01

  I mean, so you're literally running out of benchmarks in order to do that. And the amount of compute and resources, again, are going exponential. Because you need to to squeeze that out as well as have good data, as well as have good algorithms. So before you could just chuck everything into a pot, slosh it around. Now it's the real quality that differentiates the top models between each other. And it's become more of an engineering and quality challenge than just a brute force challenge.

• 8:05Peter Diamandis?

  Insane.

• 8:06Speaker 03

  Can I please say what for a second?

• 8:07Peter Diamandis?

  Please.

• 8:09Speaker 03

  Okay, so I've got a problem. I would suggest that if I'm trying to answer that problem or get a solution to it, I could go to any of these and they're going to give me marginally roughly the same answer. So we're at a point where the the new step is I'd love to, I want to get into the details of Grok to figure out why is it so radically different from any of the others, right? And that's where I think the fun will come.

• 8:33Peter Diamandis?

  Every week I study the 10 major tech meta trends that will transform industries over the decade ahead. I cover trends ranging from humanoid robots, AGI, quantum computing, transport, energy, longevity, and more. No fluff, only the important stuff that matters, that impacts our lives and our careers. If you want me to share these 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, these reports are for you. Readers include founders and CEOs from the world's most disruptive companies and entrepreneurs building the world's most disruptive companies.

• 9:14Peter Diamandis?

  It's not for you if you don't want to be informed of what's coming, why it matters, and how you can benefit from it. To subscribe for free, go to diamandis.com/metatrends. That's diamandis.com/metatrends to gain access to trends 10-plus years before anyone else. Well, the funny thing is, we're using, you know, we're basically going to Einstein, you know, and asking him to summarize a poem for us. I mean, it's like there's such massive level of intelligence and the utilization for the general public is is de minimis. All right, let's look at what's next on this. So Grok outperforms the the highest level test humanities last exam.

• 9:57Peter Diamandis?

  Up until now, we've seen, let's see, O3 was at 21%. Grok 4 was at 25.4%, Gemini 2.5 at 26.9%. And then Grok 4, and then Grok 4 heavy comes in at 44.4%.

• 10:15Peter Diamandis?

  We were talking about this a little bit earlier, Ahmad. You know, can you speak to Humanities Last Exam for us?

• 10:21Speaker 01

  Yeah, this was come up by Scale AI and kind of a few others to have an exam that even the most polymathic people in the world would find difficult. So they estimated that like some of the smartest people in the world would score maybe 5% on it, maximum 10%, and the top models at the time, which was probably like half a year ago, nine months ago, scored 8%. Now you have a qualitative leap above to that 44% level. And I think it's interesting because as kind of Salim was referring to, like, what are these models for? They're at this super genius level. It's like having a mega liberal arts program. And then the next step is going to be to have really useful people in the workforce on one

• 11:04Speaker 01

  stream, and then the other stream will be to take the subcomponents of this and just push up to superhuman reasoning, discovering new things at a level that we could never have before. And I think this is one of the indications of that because, again, I tried to read some of the questions. I didn't even understand the questions.

• 11:22Speaker 02

  Let me give you a couple of examples. I literally just gave a presentation on this yesterday, so I have it right in front of me.

• 11:27Peter Diamandis?

  Tell me.

• 11:28Speaker 02

  Humanities Last Exam, 2,700 questions. When the slide says, for reference, humans can score 5%, that means the very best humans in any given domain can score 5% within just the domain they understand. And I'll tell you why. Like, here's an example question. Compute the reduced 12th dimensional spinboardism of the classifying space of the Lie group G2. And then it goes on from there.

• 11:55Peter Diamandis?

  Most people can't even understand one word of that.

• 11:58Speaker 02

  Exactly. Here's another one. Take a five dimensional gravitational theory compactified on a circle down to a fourth dimensional vacuum.

• 12:08Speaker 02

  So yeah, these are the hardest questions. And that's why this exam is supposed to last for a long time. A 44% score is just way outside the range of human ability because nobody has that broad knowledge that spans all these topics.

• 12:24Peter Diamandis?

  So how far, how long before we hit 100% here too? Imad, any bets?

• 12:29Speaker 01

  Two years max, I would say, probably next year.

• 12:32Peter Diamandis?

  So, you know, there was a conversation years ago about AI getting to a point where you can't understand the questions it's asking and answering. And we're not far from that. So, I mean, we're unable to actually, at some point, we're unable to measure how rapidly it's advancing. That becomes a little bit frightening.

• 12:55Speaker 02

  It's gotta be driving Google nuts that Elon got this done in 28 months from a cold start.

• 13:02Peter Diamandis?

  Absolutely.

• 13:03Speaker 02

  Largely because, you know, Elon is phenomenal at large-scale manufacturing, large-scale organizational management, and, you know, people working 4:00, 5:00 AM, sleeping in tents on the factory floor, that's his wheelhouse, and that's Tesla, that's SpaceX. And because all the intellectual property was more or less open sourced by the research community at Google and Meta, he was able to pick up all that brilliant thinking and just plow it into implementation.

• 13:32Peter Diamandis?

  Also, small teams, right? It's not large, I mean, Google's a massive organization.

• 13:38Speaker 03

  Yeah, I think there's something else here, though. Remember, we talked about this last time when Grok 3 came out, right? But when he said he was gonna put this huge cluster together, every AI expert in the world said, "You cannot get power laws and coherence at that scale. You just can't do it." And he went right back to first principles, created new kind of connections between the chips and whatever, and did it. And every AI expert was like, "Oh, god dang, he did it." And so, this is the incredible ability he has to go into a domain with a beginner's mind, go to first principles, and just re-engine a heck out of it to achieve massive performance. And I think this is an indication of that.

• 14:20Speaker 03

  My big question is, is as you mentioned earlier, Dave, where do we go from here? Right? Like, what does it mean to have a 50% versus 44% on this test?

• 14:30Speaker 01

  Yeah. Yeah, I think if I can just give a little bit of context, in 2022, Amazon built us the 10th fastest public supercomputer in the world, 4,000 A100s.

• 14:41Speaker 02

  Like me too.

• 14:43Speaker 01

  And that was 2022, that was 10th fastest in the world.

• 14:46Speaker 02

  Wow.

• 14:47Speaker 01

  Of any supercomputer that we were training on. And there was an instance where literally hundreds of the chips melted because of the scaling. Now they've managed to, by turning this into an engineering problem, scaled the hardware, but also the inside of the model, which I think is this really important thing. The reason it's above PhD level in each of these areas is that was a computation scale problem. And so what happens is that if you could scale a liberal arts person all the way up to post grad in everything, you would, and then you specialize down. And then you look at some of these things and Salim's question there. You've got the base stats.

• 15:23Peter Diamandis?

  Just for reference, everybody, it's the XAI cluster now has 340,000 GPUs.

• 15:30Speaker 02

  And they're about $30,000 or more each.

• 15:34Peter Diamandis?

  Yeah.

• 15:35Speaker 02

  Do the math. 10 billion.

• 15:37Peter Diamandis?

  A lot. I mean, this is why, you know, this is why we're seeing a billion dollars a day going into AI and why Jensen said, you know, there'll be a trillion dollars a year by 2030. And it's not slowing down. So here's another image from the, from the little conversation Elon had yesterday. These are the benchmarks his team put up. I don't know if you want to hit on any of these, Imad or Dave or Salim? Any of the favorites for you?

• 16:04Speaker 01

  Well, my favorite one is the AIME 25, 100%. You're done, you know? GPQA, these are all hard benchmarks.

• 16:12Peter Diamandis?

  I think Elon would want, I think Elon would want to go to 110%. He likes 11 of those.

• 16:21Speaker 02

  The only one I don't recognize is on the bottom right, Imad, do you know what that is? The USAMU 25?

• 16:25Speaker 01

  I think it's the USA Mathematical Olympiad.

• 16:28Speaker 02

  Oh, right.

• 16:29Speaker 01

  So it's about to happen.

• 16:32Speaker 01

  But, but again, like, these are novel, hard benchmarks, effectively all of them. And they're being saturated because ultimately the AI can reason mathematics and science better than we can. Again, it can't plan just yet. It doesn't have the same memory capacity and the building blocks haven't been put together. But it's already superhuman narrow capability in many narrow areas. So it's inevitable, I think, what happens next.

• 17:00Speaker 02

  You know, we glossed over his quote there, "Discover new physics." Wouldn't surprise me if it's this year, certainly no later than the end of next year. Alex Wissner-Gross has been having a field day with that all day.

• 17:12Peter Diamandis?

  I bet.

• 17:13Speaker 02

  First of all, what does it mean to discover new physics? That's pretty interesting by itself.

• 17:19Peter Diamandis?

  Well, I mean, Alex has been saying, "We're going to solve all of math, and then physics comes next, chemistry and biology follow quickly." I mean, this is the most exciting, for me, this is the most exciting thing of these models are, will they literally unwrap the present of the universe before us, right here, right now, during our lives in the next five or 10 years?

• 17:41Speaker 03

  Well, there's a couple of specific applications that I think I've been watching. I want to see an AI break and solve the quandary of the wave-particle duality of light. That would be interesting, and seeing what exactly is going on in this. The second one would be molecular manufacturing, and how do we, new techniques for doing molecular manufacturing? Because you crack that, then you crack all assembly and manufacturing of all kinds. Then the cost of anything becomes about a dollar a pound per weight. A computer, a dollar a pound.

• 18:14Peter Diamandis?

  Yeah.

• 18:14Speaker 03

  And now you're in an amazing space.

• 18:16Peter Diamandis?

  I mean, listen, again, going back to Ray Kurzweil's predictions, right? How he does it, I still, you know, he's mentored you, he's mentored me, but, you know, his predictions that we're going to have nanotech in the early 2030s, where is it, where is it? Well, this is probably its parents.

• 18:36Speaker 02

  Yeah. Well, the one that's really fun to think about, you know the quantum teleportation, Peter, that you brought up at one of the press meetings? So how do you reconcile the fact that two entangled particles can be infinitely far apart, yet still communicating in real time, with the fact that the speed of light can't be transcended? So Alex's speculation is, if we can solve physics in the next year or two or three, and it turns out that you can communicate using quantum teleportation, that we instantly discover all these other intelligences around the universe?

• 19:11Peter Diamandis?

  Yeah, we've just been listening at the wrong frequency with the with the wrong codex. These are the key takeaways. I'm gonna just read these out loud and we can talk about them. They spent just as much on fine tuning, training the AI after initial phase as they did on pre-training. So that's a big change. Imad, you want to dissect that for us?

• 19:34Speaker 01

  Yeah, so it used to be that everything was basically, you take a snapshot of the internet and then you put it into this giant supercomputer mixer and it figures out all the connections, the latent spaces to guess the next word. Then you had this very weird AI that came out that was a little bit crazy. It's like a disheveled graduate student without his coffee. And then you had to tidy him up with the reinforcement learning. That was the post-training. And that was 1% of the compute. Then with DeepSeek, it was 10% of the compute. And now it's moved to equal because they figured out how to chain reasoning strips. And in fact, I think part of what they did, we've seen this with other labs, is they use their frontier model to make data for the next frontier model. So having large amounts of compute to create your own training data

• 20:21Speaker 01

  in a structured manner allows you to take that latent space, the landscape, and make it smarter and smarter and smarter, just like your brain adapts as you learn more and more reasoning, as you see more and more things. And so rather than having to have these massive scrapes of the internet or whatever, it's more and more structured data making up these models, which are making them smarter reasoners.

• 20:44Peter Diamandis?

  So the the 50% additional compute dedicated to to the the fine tuning, does that mean we have a more sane version of Grok?

• 20:58Speaker 01

  Fingers crossed. It doesn't necessarily mean that because you can still get all sorts of mode collapse within it in terms of if the latent space goes, but probably.

• 21:08Speaker 01

  Because again, you're training it just on a certain field of things as opposed to Reddit and other things. In terms of order, I'd say this is probably like $100 million each. So it probably adds up to one meta AI researcher.

• 21:23Peter Diamandis?

  A new, a new, a new unit of measure in the AI world. That's funny. So let's comment on the cost here. $3 per million tokens? $15 per million output tokens and can handle long context windows of 56,000 tokens. How does that measure up, Dave, in your mind?

• 21:44Speaker 02

  Well, it's pretty normal these days. It's the longer context. You know, a lot of the claimed context windows aren't real. Under the covers, the dimension of the neural net is much smaller than the claimed context window. So I suspect, you know, at this scale, that this is the true dimension of the network. But I don't really know. We'll have to dig in over the next couple of days and find out. But, you know, what it means is, you know, you can feed in 100 books worth of information concurrently. It instantly digests all that knowledge and then gives you an intelligent answer based on all of that information in one pass. So it's just, you know, the next step in what's been going up sequentially from model to model to model.

• 22:24Peter Diamandis?

  Ima, do you expect we're going to be constantly reducing the price per token? Is this a, is this a demonetizing curve for a while to come?

• 22:36Speaker 01

  100%. I mean, so the cost of this is about the same as the cost of Claude 4 Sonnet, which is the second model of Anthropic or O3's cost, but it's better than both. It's about 0.7 words per token, to give you an idea. And so the cost of a million very good words that are smart is $20. But next year with Vera Rubin, the next generation chip they're going to whack in there, just by the hardware, it'll be three times to four times cheaper. And they'll probably figure out some more stuff around that. So equi-intelligence, the cost probably drops by around five to 10 times a year. So it'll be a buck for a million amazing words.

• 23:20Peter Diamandis?

  It's hard to believe the most powerful technology in the world is de minimis in cost.

• 23:28Peter Diamandis?

  It's crazy.

• 23:30Speaker 03

  I want to, I want to, I want to put a comparator though here.

• 23:33Peter Diamandis?

  Yeah.

• 23:33Speaker 03

  You know, we, we, this is amazing. Like we could put hundreds of our books into the thing and it would hold all of that in real time, as Dave said. But let's note that a single human cell has several billion operations going on in it at any time, point in time, right? So we're kind of several orders, multiple orders of magnitude from modeling one cell. And so we're, we've got a long way to go try and model life or get to really big, big, big things.

• 24:02Peter Diamandis?

  There's a coming wave of technological convergence as AI, robots and other exponential tech transform every company and industry. And in its wake, no job or career will be left untouched. The people who are going to win in the coming era won't be the strongest, it won't even be the smartest. It'll be the people who are fastest to spot trends and to adapt. A few weeks ago, I took everything I teach to executive teams about navigating disruption, spotting exponential trends a decade out, and put them into a course designed for one purpose, to future-proof your life, your career and your company against this coming surge of AI, humanoids and exponential tech. I'm giving the first lesson out for free.

• 24:43Peter Diamandis?

  You can access this first lesson and more at dmantis.com/futureproof. That's dmantis.com/futureproof. The link is below. Let's talk about super Grok heavy. You know, gotta love Elon's terminology, right? It's, we've, we've got Falcon Heavy, now we've got Super Grok Heavy.

• 25:04Peter Diamandis?

  He loves his terms and I love them too, actually. It makes me, I smiled when I saw that.

• 25:08Speaker 03

  Why Heavy, by the way? Is there a name, reason for that?

• 25:12Peter Diamandis?

  Consistent brand across the Elonverse. Yeah, no, I mean, like, you know, Falcon Heavy was able to have, you know, three boosters to launch a heavier payload to orbit. So why not, why not talk about heavier capacity? So, I mean, in, in reality, right, Falcon Heavy had multiple boosters and this has multiple agents, so.

• 25:32Speaker 03

  So next one will be heavier and the one that will have to be.

• 25:36Peter Diamandis?

  Next one will be Grok Starship.

• 25:39Peter Diamandis?

  It'll be, it'll be BFG. BFG has.

• 25:46Speaker 02

  So the price point here is that's a new high bar and that's going to scare a lot of people.

• 25:51Peter Diamandis?

  Yeah.

• 25:51Speaker 02

  I say the same thing I said last time, you know, try it. Burn the 300 bucks for one month, you can turn off the subscription, but you got to try it to know what you're, what you're missing or not missing. A lot of the use cases, you know, the day to day use cases, it won't matter much. But if you're building something complicated, writing code or designing mechanical parts or whatever, you're going to get addicted to it. What I'm really curious about is the margin at 300 bucks a month. Are they actually chewing up all that money on compute for you? Or do they have significant margin at that price point? Cause one thing I've been predicting for a long time is inevitably going to happen soon is the use cases where you need that extra intelligence, like when you're, when you're building a software product and you're prompting it,

• 26:36Speaker 02

  you absolutely need that extra level of intelligence. It makes you dramatically more efficient in moving forward. And if you look at the cost of an engineer, software engineer's time, you can afford to go up another factor of 10 or even more in price point for this and still be glad that you paid it. And so I think the escalation of pricing is, is going to come soon. The counter argument is that the competing models will then commoditize it. But I think people will pay a lot for marginally better improvement because the, the effective product you get out the other side, it really accelerates your time to development or the quality of the design or whatever. The solution to the math problem, it was right rather than wrong, makes a big difference. My guess is they're losing money. You think so?

• 27:21Speaker 01

  That's what, that's what OpenAI said for their pro level. Whereas the level below, they make money. So I think the way that I view this is as loss leader, because if someone's paying 300 bucks, you enterprise sell them up. And then you do team things to get everyone doing it. Because basically right now, what we have is a UI problem. The reasoner is there. The way to hook it up and make it usable for as many people on your team isn't there. You know, this is what Andre Karpathy calls context engineering, you know? Like what are the new UIs that will enable us to use this most efficiently and get our data in there? If you can crack that, then 300 bucks a month for a high level knowledge worker is nothing.

• 28:01Peter Diamandis?

  Yeah, zero, right.

• 28:03Speaker 01

  Just like you used to pay a thousand, 2000 bucks a month for Bloomberg when I was a hedge fund manager, mostly for instant messaging, but you know, like again.

• 28:12Speaker 01

  It's just not quite there, but it's about to flip there.

• 28:15Speaker 02

  Yeah, like a lawyer will cost you that much per hour or even three, five times that per hour. Will this do the job of your legal document better?

• 28:25Peter Diamandis?

  I can't wait. That's the one profession I would love to replace.

• 28:30Peter Diamandis?

  Lawyers. All right, you mentioned enterprise level, Imad, let's go there right now.

• 28:35Speaker 05

  What else can Grok do? So we're actually releasing this Grok if you want to try it right now to evaluate on the same benchmark as us. It's on API, has 256K contact lens. So we already actually see some of the early adopters to try Grok for API. So our Palo Alto neighbor, R K Institute, which is a leading biomedical research center, is already using, seeing like, how can they automate their research flows with Grok for? It turned out it performs, is able to help the scientists to sniff through, you know, millions of experiments logs. And then, you know, just like pick the best hypothesis within a split of seconds.

• 29:16Speaker 05

  We see this as being used for their, like the CRISPR research and also, you know, Grok for independently evaluated scores as the best model to examine the chest X-ray. Who would know? And on the, in the financial sector, we also see, you know, the Grok for with access to all the tools, real time information is actually one of the most popular AIs out there. So, you know, our Grok is also going to be available on the hyperscalers. So the XAI enterprise sector is only, you know, started two months ago and we're open for business.

• 29:50Peter Diamandis?

  Open for business. So, Imad, you've been working on medical related AI. It's, you know, the block here isn't the tech, it's going to be the regulations. It's going to be when will an AI be able to fully replace a radiologist or fully replace a, you know, any profession of the medical world? How do you think about that?

• 30:13Speaker 01

  Well, I think it's the augmentation first, reduce errors, increase outcomes. And then eventually it's replacement because Google had their AI medical expert study, which showed that it was doctor, doctor plus Google search, doctor plus AI, and then AI by itself.

• 30:29Peter Diamandis?

  Yeah.

• 30:30Speaker 01

  But just with self-driving cars.

• 30:32Peter Diamandis?

  I just want to touch on that because it was a really important article that came out. If you, again, the physician by themselves was getting something like 80% of the cases correct. The centaur, the physician plus the AI was getting like 87%. The numbers are approximate. And then the AI without the human bias, without the human biasing the output, the AI by itself was outdoing all of them at like their early 90%. Extraordinary.

• 31:03Speaker 01

  Well, again, as we said, it's better than any post grad at the moment. But right now, I think it's about the empowering and the acceleration in terms of the integration. And you're way off the liability profile of replacement. And I think you need replacement right now. What we need is less errors in something like medicine, right?

• 31:21Speaker 03

  I think the doctor number by itself, Peter, was 70%. Because I remember Daniel Kraft saying, when you go to the doctor, you get the wrong diagnosis about 30% of the time, right? That's a staggering number of errors, by the way. But it means out of four of us, one and a half got the wrong diagnosis the last time we went to the doctor. I mean, we need to figure out who that was. That's really ridiculous. And so you need an AI to take over that whole field. Well, especially. Human bias and getting human bias out of that is also even more important, as we can see.

• 31:52Speaker 02

  The number of types of scans and sensors you can do is way, way outstripping any human ability to look at all the data that comes out of it. So a lot of, a lot of it isn't trying to beat a doctor. It's trying to assimilate data that never could have gotten into the diagnosis before.

• 32:06Speaker 03

  That's a great point. That's a great point.

• 32:08Speaker 02

  Yeah.

• 32:09Peter Diamandis?

  All right, let's go on to our next one. So available for an API, all right? We've covered these areas already. Let's move on. A quick aside, you've probably heard me speaking about Fountain Life before, and you're probably wishing, Peter, would you please stop talking about Fountain Life? And the answer is no, I won't, because genuinely, we're living through a healthcare crisis. You may not know this, but 70% of heart attacks have no precedent, no pain, no shortness of breath, and half of those people with a heart attack never wake up. You don't feel cancer until stage three or stage four, until it's too late. But we have all the technology required to detect and prevent these diseases early at scale.

• 32:52Peter Diamandis?

  That's why a group of us, including Tony Robbins, Bill Cap, and Bob Horry, founded Fountain Life, a one-stop center to help people understand what's going on inside their bodies before it's too late, and to gain access to the therapeutics to give them decades of extra health span. Learn more about what's going on inside your body from Fountain Life. Go to fountainlife.com/peter and tell them Peter sent you. Okay, back to the episode. All right, I love this. Elon is a gamer, and so it's not unreasonable for him to be talking about using Grok to make games. Let's take a listen.

• 33:27Speaker 05

  Yeah, so the other thing, we talked a lot about having Grok to make games, video games. So Danny is actually a video game designer on X. So we mentioned, hey, who want to try out some Grok 4 preview APIs to make games? And Danny answered the call. So this was actually just made, first-person shooting game, in a span of four hours. So some of the actually, the unappreciated hardest problem of making video games is not necessarily encoding the core logic of the game, but actually go out, source all the assets, all the textures, files, and to create a visually appealing game.

• 34:08Peter Diamandis?

  I think one of the challenges is what we do with all of our time in the future, and we may be playing a lot of video games.

• 34:18Speaker 03

  You know, this could actually light up the entire metaverse world, because building the metaverse world and building those environments was the big limiting factor. And now you can do it at a very rich level. This could be really interesting to see what comes from this.

• 34:33Peter Diamandis?

  Yeah. When did you guys first hear that Grok 4 was going to come out last night?

• 34:40Speaker 03

  Well, he said a few days ago, didn't he?

• 34:42Peter Diamandis?

  I mean, he's been...

• 34:43Speaker 03

  I think it was a week ago.

• 34:44Peter Diamandis?

  I mean, he was saying it was gonna be this weekend, and then it got pushed to yesterday.

• 34:50Speaker 02

  Yeah, because I feel like we had about 48-hour notice, plus or minus a day or two. But if you look at the presentation, the raw presentation from last night, and compare it to Google I/O, Google I/O was scripted and staged with multiple presenters and clearly planned way in advance. This last night was like, "Is it done yet, guys? Is it done? Does it work? Okay, if it works, we're launching tonight. Let's go. Get on stage, let's go." And I think that's the way it's gonna be in the future, because it seems like getting to market one day, two days sooner actually matters a lot in this horse race. So this is kind of the dynamic we should expect going forward.

• 35:29Speaker 03

  By the way, that narrator, that's the AI voice of a geek who is living and breathing it, and that's what you want in there.

• 35:37Peter Diamandis?

  That's what you want. All right, let's take a listen on Elon on video games and movie production.

• 35:44Speaker 04

  For example, for video games, you'd wanna use Unreal Engine or Unity or one of the main graphics engines, and then generate the art, apply it to a 3D model, and then create an executable that someone can run on a PC or a console or a phone. We expect that to happen probably this year. And if not this year, certainly next year. So that's... It's gonna be wild. I would expect the first really good AI video game to be next year. And probably the first...

• 36:31Speaker 04

  Half hour of watchable TV this year and probably the first watchable AI movie next year.

• 36:40Speaker 02

  It's amazing what the fragmentation of those industries is going to be incredible because, you know, normally we think of a video game coming out in a release, all of your friends get the exact same release, it's a release that's maybe good for a year or more and you're all on like FIFA twenty-three now or whatever, twenty-five. But here, because it's only four hours to create the next iteration, then you can say, well, no, I want a customized version or I want, there's going to be all this fragmentation and the version of the movie that I saw isn't the same ending that the one that Salim saw, so now we're debating on how, we're not even on the same page and how the movie ends because we saw a different, a different AI-generated version. And it's going to be great, it's going to be, it's going to be really, really cool because everything's customized.

• 37:19Peter Diamandis?

  Well, we're going to have a lot to do with our time. I mean, Iman, listen, you spent so much time as CEO of Stability in this market arena of entertainment and video production and such. When I asked you earlier whether Hollywood is, you know, going to be disrupted, you said no. Can you, can you explain that, please?

• 37:40Speaker 01

  So I think the thing that won't grow is people's attention. So if you look at Netflix, their biggest competitor is video games, which is why they're going into video games. You only have so many hours in a day and you're a consumer. Video game sector right now, I think, is four hundred and fifty billion dollars, the movie sector is seventy billion. That's how fast it's grown. Like, education around the world is like ten times larger, so it's ten percent of education in terms of size. So if you think about that, then for Hollywood Studios, this is great because the costs are coming down and it's been a dramatic shift. To give you an idea, the first video models, stable video, I think, was pretty much the first. We released that in twenty twenty-three.

• 38:21Speaker 01

  And now with VO3 from Google and others, you're pretty much at Hollywood level, close to it, but you need one more generation to get there. And the average Hollywood click length is two point five seconds. It used to be twelve seconds, now it's two point five, and we can generate eight and soon we'll be able to generate more. So you're getting to this point where you can make that, but again, people like having common stories to talk about, Barbie, Oppenheimer and things like that. So these marquee things, they can get the license of Cary Grant from back in the day and make him a star again.

• 38:54Peter Diamandis?

  You know.

• 38:54Speaker 01

  Harold Monroe.

• 38:56Peter Diamandis?

  Don't you think, don't you think that there's going to be so much supply? And if I have a chance to watch, you know, a new episode of classic Star Trek. But, you know, I'm the character playing Captain Kirk. And, and, you know, you're playing Spock and my friends are taking the roles. I mean, I don't know why I would not be buying that entertainment from a source other than, you know, outside of Hollywood.

• 39:26Speaker 01

  Well, you'll buy that too. But I think one of the things we've seen in the AI world, what's it about? Distribution, distribution, distribution. So you'll buy your interactive games and put yourself in the game, but you'll still have your marquee things. And the cost of that will decrease dramatically. And the distribution cost will decrease dramatically and the impact will increase. So again, for companies, this is all great. For the individuals working in the industry, this is terrible. And so I think this is the key thing. For the individual creators, this is great because you can finally tell the stories. So we'll see richer stories, but you've still got to distribute them. It's like one of the exams I had to give is, you know, Taylor Swift, bless her heart. It's not the best music in the world, but she still causes earthquakes, you know?

• 40:08Speaker 02

  Yeah, no, your, your point that I think the video game industry bypassed all other media combined. Yeah, I think I read that. And it's on a much faster growth trajectory as well. But I think the video games are far more compelling with AI components, AI players, AI voices, voices that are talking directly to you. And so that interactive media is going to get even more accelerated by this trend. So I, whether you call it movies or video games or other, the, the media is going to change, right? It always does. So it may not fit exactly in those swim lanes, but it's clearly the interactive talk to me part is going to grow much, much faster than passive watching part.

• 40:50Speaker 01

  Yeah, I think it's the quality part and it's the feedback for you to find flow. So the movie industry has grown from like six fifty billion to sixty billion the last ten years. Average IMDb score six point three. Video game industry has like doubled inside quadrupled. It was one hundred and seventy billion, now it's like five hundred billion. The average score has gone from sixty nine percent on Metacritic to seventy four percent. Games are good now and you need to be good to compete. And again, I think what we can see from this technology is I, as a creator, can create the best things better because I can control every pixel. This is what Jensen has said, every pixel will be generated. Exactly what's in your mind, maybe you have to use a keyboard, it just comes straight from your mind, can be on that screen, you can tell the stories you want.

• 41:35Speaker 01

  And on the other side, you've got the fast food. So you know, the general content farms get even better. So you've got your gourmet and you've got your fast food and both of the quality of those will increase.

• 41:45Peter Diamandis?

  All right. Every day I get the strangest compliment. Someone will stop me and say, Peter, you have such nice skin. Honestly, I never thought I'd hear that from anyone. And honestly, I can't take the full credit. All I do is use something called OneSkin OS one twice a day, every day. The company is built by four brilliant PhD women who have identified a peptide that effectively reverses the age of your skin. I love it and again, I use this twice a day, every day. You can go to oneskin.co and write Peter at checkout for a discount on the same product I use. That's oneskin.co and use the code Peter at checkout. All right, back to the episode. Of course, Grok for coding, let's take a quick listen.

• 42:29Speaker 05

  Right, so if you think about what are the applications out there that can really benefit from all those very intelligent, fast and smart models? And coding is actually one of them.

• 42:38Speaker 06

  Yeah, so the team is currently working very heavily on coding models. I think right now the main focus is, we actually trained recently a specialized coding model, which is going to be both fast and smart. And I believe we can share with that model with you guys, with all of you in a few weeks.

• 42:59Peter Diamandis?

  I still remember Imad when you were on stage with me like three years ago at the Abundance Summit and you said no more coders in five years. It was it was front page throughout India.

• 43:12Speaker 01

  I got I got hate mail about that, you know?

• 43:14Peter Diamandis?

  Oh, my God, you scared the daylights out of and it's true. I mean, there's I mean, it's a big issue. It's a big issue.

• 43:21Speaker 01

  Why would you be able to talk to a computer better than a computer can talk to a computer?

• 43:25Peter Diamandis?

  Yeah.

• 43:26Speaker 01

  You know?

• 43:26Speaker 03

  Well, hold on. Let me get into that just for a second. Don't you think we'll end up with really good coders just creating 100 times more code?

• 43:35Speaker 01

  No, because what you'll have is really good context engineers directing to build things. Code is an intermediate step of language because the computers and the compilers couldn't handle the complexity of what we wanted to talk about. Now you can talk to the AI all day long about anything and it understands to a reasonable degree what you actually want. And once we get the feedback loops really going, as we've seen with Cursor and other things like that, like there's a reason it's got to $500 million in revenue in a year. You know, there's a reason that Anthropic's got to $4 billion. Probably two thirds of that is code.

• 44:09Peter Diamandis?

  Hmm.

• 44:10Speaker 01

  Yeah.

• 44:10Peter Diamandis?

  Crazy.

• 44:12Speaker 02

  Yeah, disappointing that we won't have this for a couple of weeks. We'll have to get back on the pod and check it out when it's out. Somebody told me you can get to it through Cursor right now. I'm looking at Cursor as we speak and I don't see it popping up as a as an option, but I'm.

• 44:24Speaker 01

  Cursor is very much linked towards Anthropic, so probably like lobotomize it. But Grok 3 or Grok 4 already heavy is a pretty good coder. It writes clean code and the coding model I think will be even better. But again, how much better are you going to get when you can output a 3D video game like that or just about anything? And I think this comes to think, are you if you're trying to create content, the AI is good enough already for just about anything. If you're trying to create something creative, this is the final part that requires planning and coordination and multi-agent systems and the UI UX isn't there yet for the feedback loops, etc.

• 45:01Speaker 02

  Yeah, I can use all the horsepower they can give me though, because like when you're writing a little code module, it's all pretty much perfect already. But right now, I can go to the best Claude model and say, build me a dashboard for this function and just give it that prompt. And most of the time, it comes back great and even thinks of things that I wouldn't have thought of for that dashboard. And I can use another step up of capability in that area. So I'll use it up as quickly as it comes out, believe me.

• 45:30Speaker 01

  All the tokens to Dave.

• 45:33Peter Diamandis?

  Okay, let's hear from Elon about his video model training. What's coming on input? Output?

• 45:39Speaker 04

  We expect to be training our video model with over 100,000 GB 200s. And to begin that training within the next three or four weeks. So we're confident it's going to be pretty spectacular in video generation and video understanding.

• 45:56Peter Diamandis?

  So 100,000 GB 200, more than anybody's thrown at this. Ahmad, what does that, how does that, how does that hit you?

• 46:07Speaker 01

  So when we trained the state of the art first video model two years ago, two years ago.

• 46:14Speaker 02

  That's right.

• 46:15Speaker 01

  We use 700.

• 46:17Peter Diamandis?

  700.

• 46:18Speaker 01

  700 H100s. So like, let's say they're three times slower. So the equivalent of 200 of the chips that he's about to use, because these are the integrated GB chips from Nvidia. The top level models right now, if you look at the Loomers of the world, the ByteDance models of the world, the VO3s, use 2 to 4,000.

• 46:41Peter Diamandis?

  Wow.

• 46:41Speaker 01

  He's about to use 100,000 of those. And the thing about video is when you train a video model, it actually learns a representation of the world through computation. So once we made a video model, we extended it to a 3D model that could generate any 3D assets. It understands physics and more. So actually, video models are world models that can be used to do all sorts of things, like improve self-driving cars by creating whole worlds and other things like that as well. I think that's the reason why, given they've got 300,000 chips, they're putting 100,000 of these to the video model.

• 47:17Peter Diamandis?

  Well, and they're planning a million GPUs by the end of this year. You know, it's like, it's like no small dreams here.

• 47:27Speaker 02

  Ahmad, when you pioneered this just a couple of years ago, like you said, the video model was trained completely separate from the large language model because it was just too much. You couldn't put everything into one mega model. Is he going to do a monster retraining of this model with video data? Or is it a separate set of parameters and a separate model entirely?

• 47:45Speaker 01

  This will be a separate model. So we took the image model and then we created the video model from that. And then we created the 3D model from that. Now they're doing from scratch training because the technology we developed for Stable Diffusion 3, the diffusion transformer matching it, is able to do that all at once. And this is similar to what VO3 and others use. And with optimizations, you can just pop that all straight in. Now, the arch that they use, like the Grok model for the image, is actually the same architecture as for the language. And they may do the same thing. I'm not sure how they're going to train this model. Because again, they're super smart. But it's a different model entirely. But they may all end up being the same model. Because if you want a model that understands

• 48:28Speaker 01

  physics and the wonders of the universe, and what's the question to get to the answer 42, you probably want to train on everything that a human sees. And more, because it'll train on everything a million humans can see, and understand, and read, and all sorts of stuff.

• 48:44Peter Diamandis?

  I mean, you know, I'm excited about the idea of, there's so many of my favorite science fiction books that have never been made into movies or TV series, right? I mean, the ability to just say, hey, you know, like, one of my favorite books is the Bob Rivers series by Dennis Taylor. And, you know, I love it. It's a four book series. It's extraordinary. Make it into a movie for me. Make it into a 20 part TV series for me. Here's 100 bucks.

• 49:16Speaker 02

  It's actually really fun, actually, if you took the best books that have ever been turned into movies already and used that as training data. So like, this book turned into this killer movie. Make the changes necessary to get from point A to point B. Okay, now here's a book that never got made into a movie. From what you learned about those patterns, make the movie that's most compelling.

• 49:36Speaker 01

  The thing is, you won't even have to do that. Like, just with the pace of chip improvements, as we go through the generations, in two years, you will have live 4K TV. So you've already seen some people do like live, low resolution stuff, interactive stuff. When Jensen says every pixel will be generated, he literally means it. Like with the next generation chips and a bit of more improvement in the algorithms and optimization of the models. You can have live streaming 3D or video where every single pixel is generated on your screen within a few years. And so you can just say, stop, try this, adjust this, and that'll be the feedback loop.

• 50:17Speaker 03

  It'd be fun to take some old movies and and make them way better. Like, take the old Conan and the Barbarian movie and make it really a proper movie. I could use.

• 50:30Peter Diamandis?

  You know what hits me, we're sitting here having this conversation in four different cities around the world where, you know, we've taken so much for granted in this video channel. And like, you know, 10 years ago, what do we have? We had just barely had Skype.

• 50:47Peter Diamandis?

  And now, it's it's crazy. So we humans adapt so rapidly to awesomeness. And we take it, we take it.

• 50:57Speaker 03

  We normalize it very fast.

• 50:59Speaker 01

  It's like your second Wayman ride, right? Your first one's like, wow, and your second one's like, okay.

• 51:07Peter Diamandis?

  Oh, for sure. So any, any closing thoughts on?

• 51:12Speaker 03

  I have a question, I have a question for Iman. You've been in the space for a while. Now we have Grok 4, right? What are the types of things that Grok 5 will be able to do?

• 51:23Speaker 01

  So Grok 5 will be a multi-agentic system, but rather than having four boosters, it'll have 60 or 600 or 6,000, depending on what you want. It'll probably have a world model plugged in and it'll have interconnectivity, and this is something that Elon mentioned yesterday, to every major type of system. So it knows how to use Maya, it knows how to use advanced physics simulators. It will write its own lean code and optimize it for mathematics. And so it's just going to be like an incredibly versatile worker. And just like he's going to unleash millions of Optimus robots, he's going to unleash billions, if not trillions of these things, GPU demand, withstanding.

• 52:02Speaker 01

  Into the economy and that's going to be a bit crazy. And I think the way that you'll interact with Grok six, probably Grok five, is you'll have a Zoom call with it, just like you have now.

• 52:13Speaker 03

  Hey folks, Salim here. Hope you're enjoying these podcasts and this one in particular was amazing. If you want to hear more from me or get involved in our EXO ecosystem, on the 23rd of July, we're doing a once a month workshop. Tickets are a hundred dollars. We limit it to a few people to make sure it's intimate and proper and we go through the EXO model. What we do there is we basically show you how to take your organization and turn it into one of these hyper growth AI type companies. And we've done this now for 10 years with thousands of companies. Many of these use the model that we have called the exponential organizations model. Peter and I co-authored the second edition a couple of years ago. So it's a hundred bucks, July 23rd. Come along, it's the best hundred dollars you'll spend. Link is below. See you there.

• 52:58Peter Diamandis?

  Gemini three and GPT five, let's talk one second about what you expect there. Are these going to just leapfrog Grok four? Are they going to be, you know, sort of diverting in different directions? Ahmad, your thoughts?

• 53:13Speaker 01

  I think they'll probably all be kind of the same plateau. Now it's really about the UI UX and then how you wrap these into agents and then multi-agent systems. And then how you make it so just easy for anyone to use like this.

• 53:26Peter Diamandis?

  So, you know, Google, in the work that they've done with their AR glasses, you know, enabling you to have a conversation with your AI and being able to have it see what you see. That's a great step forward. You know, OpenAI with their voice, their voice mode has been fantastic. Are there any versions of, you know, user interface that we haven't seen yet? I mean, BCI will be one of them for sure.

• 53:57Speaker 01

  I mean, I personally think, again, the interface is just the interface that you have with the remote worker. And all the technology is almost in place for that.

• 54:05Peter Diamandis?

  Get on a call, hit him a slack.

• 54:07Speaker 01

  Pretty much. And you just don't know. That's my AGI. My AGI is actually actually more like actually useful intelligence, right? Like, this is, I think, probably what Salim would like. Just, I don't know, it's an AI or not. It just gets the job done. And it doesn't sleep. And this final part of it as well is that the task length of these AIs has gone to like seven hours now. I think I've seen from various entities now, they're getting that up to almost arbitrary length. So you can send teams away and they have organizing AIs and others. They get the job done. They check in whenever they're unsure about something. And then this is that next step up for all these technologies. But I think the 10 to the 27 models will, as you said, all be pretty much similar because they're already above PhD and everything. Now it's

• 54:51Speaker 01

  about making them super useful and getting them out there. And the demand for that is in the billions of agents.

• 54:59Peter Diamandis?

  Dave, you know what I find interesting is Elon's got basically a limitless capital supply.

• 55:05Speaker 01

  Yeah.

• 55:07Peter Diamandis?

  You know, it's every time he's gone to raise money, you know, I've asked, well, how much can I get in the next round? And it's like, well, we're oversubscribed already.

• 55:18Speaker 02

  Yeah. Yeah. No, the constraint isn't going to be the money. It's going to be the GPUs. I have a question for you, Ahmad, about that, actually, because if you say, okay, the, you know, GPT-5 will be out soon, couple of weeks, hopefully, it'll be on the same plane, probably leaked frog, but in the same genre. And then Gemini 3 will come out and it'll be somewhere similar, maybe a little better. But the chip supply, you know, Google has huge amounts of GPU and, and a massive cloud computing platform, plus they make their own TPUs. Then, you know, you've got a million chips going to Elon. We just talked about that. Sam at OpenAI has had a little bit of trouble with Microsoft recently. There's, there's

• 56:03Speaker 02

  definitely some kind of falling out there. And the way OpenAI got ahead of everyone in the first place is getting access to the compute from Microsoft. And so is he going to have a problem getting catching up to a million concurrent GPUs, training a single massive model?

• 56:19Speaker 01

  I mean, I think Stargate is in that order of magnitude when you look at the kind of gigawatts. And now Amazon's just announced poor Anthropic using Tranium for something that's even bigger than Stargate with their latest kind of chip supply. Google's the leader in this, so they have three million odd. But the thing that I come back to is OpenAI basically slowed down when everyone was making Ghibli memes.

• 56:43Speaker 01

  And so if you think about order of compute of Ghibli memes compared to order of compute for useful work, like it's that versus that, right? Google is okay because Google are actually landing millions of their own TPUs and they have the full stack and it has better interconnect for large context length. It's actually really good seventh generation hardware. Elon will get the supply because he's a beast. And I think, again, OpenAI have the capital, but they're moving more and more towards consumer with the Johnny Ive acquisition and things like that. The dark horse here is probably, again, Meta, to be honest, because Zuck is going to drop a hundred billion dollars on this. He dropped thirty billion on the glasses, on the Metaverse.

• 57:27Speaker 01

  He thinks AGI is coming and Meta is a 1.7 trillion dollar stock. He will easily drop a hundred billion.

• 57:33Peter Diamandis?

  Yeah, he's got seventy billion dollars of free cash right now to use and can pump it up.

• 57:38Speaker 02

  Well, I did an interview of Yann Le Cun at MIT not super long ago, and they had committed and already bought a million GPUs for internal use in Meta. So he, he had those on order already then. I'm sure they're in-house now, so he has the, the compute in-house.

• 57:54Speaker 01

  So basically, all the top guys can get a million. The next step is ten billion.

• 57:59Speaker 02

  Well, there's only twenty million in the world, so this is where it runs into a bottleneck. You can't even keep a straight face, can you?

• 58:04Speaker 01

  Well, but again, think about every pixel being generated and think about, again, the economic activity of actually having a single useful teammate or account. I mean, we're talking about like accountants and lawyers and other things like that on the other side of the screen. We're not even talking about super genius PhDs.

• 58:21Peter Diamandis?

  Is Nvidia just gonna just keep going, going, going? Is anybody gonna displace their their production at all?

• 58:29Speaker 01

  All of the top chip manufacturers are good enough to run these models. The only question is who has enough gating supply? So the reason for the hopper thing was actually the packaging of the chips. You know, the co-ops. So you have different supply channel constraints, just like robots. In two years, robots will be good enough to do what? Ninety percent, ninety-five percent of human labor? The only reason the entire global economy on labor isn't gonna flip over from two-dollar, one-dollar robots is supply chains. So what we've got is a complete replacement of the capital stock of the economy from GPUs for virtual workers and robots. And it's just supply constraints. So Nvidia, number one, you don't go wrong, you don't get fired for getting Nvidia.

• 59:14Speaker 01

  But you'll get chips from wherever you can get them because those chips are orders of magnitude cheaper than your team members.

• 59:23Speaker 02

  I just asked, actually, Gemini in the background here, what it costs today's market rate to train a RanaFlop. So one of these models, just the compute cost is three hundred and twelve million. So like you said, Ahmad, it's it's like one signing bonus over at OpenAI these days. So that's not, the cost is not the issue. It's it's who has access to the compute. What's amazing to me in this entire conversation, we haven't said the word Apple once.

• 59:47Speaker 01

  Yeah.

• 59:48Speaker 02

  And Apple controls about a third of the manufacturing capacity at TSMC for their M three line, M two line chips. So they could easily become a player in the the get a big data center up and running game. They'd have an incredible asset having that manufacturing toehold with TSMC. It's just incredible that they haven't done that.

• 1:00:09Speaker 01

  Well, I think this comes down to the thing. These models have economies of scope in that once you train a model that's good enough, do you really need another one?

• 1:00:19Speaker 01

  And then it becomes like electricity, it becomes a utility. So your genius models become utilities and then what matters is the model that runs on the M3 or whatever, you know, like Liquid AI just releasing edge models. Those things become even more important because the M3 has capacity, M4s have capacity.

• 1:00:38Speaker 02

  Yeah. Yeah, that's a really big deal, by the way. Liquid is, I didn't appreciate how big a deal it was until recently, but people are going to want to use this stuff immediately. It's so addictive. And the inference time compute is severely constrained. And Liquid, you know, runs fine on the edge on these M3s. It runs really, really fast. It runs on the chips in the cars. And it's about, you know, they say about 100 times more efficient than just trying to run a brute force transformer. So that could be a huge unlock for people having access to AI, you know, at least more access to keep up with the demand.

• 1:01:13Speaker 01

  Exactly, because you'll have your gated stuff and then they might increase prices because they have to, because there'll be so much competition for chips, even as you get them cheaper. And then you've just got this AI with you, but that AI will be smart enough to do your day to day. And so you'll have a whole curve of intelligence, just like sometimes you need to have steady workers and sometimes you need your geniuses.

• 1:01:33Speaker 02

  I forgot, you were the, you were actually the first guy to see Liquid, you know, when it was just a research project.

• 1:01:38Speaker 01

  Yeah, I gave them all the compute to get going.

• 1:01:40Speaker 02

  Yeah, that's right.

• 1:01:42Peter Diamandis?

  Now they're worth $2 billion valuation. So listen, Imad, when you come back and join us next week, I think we have it scheduled. I want to hear all about the intelligent internet. I'd love you to break the news on what you've been working on in secret for the last, you know, year or so. I've seen pieces of it. It's awesome, but hopefully you'll, you'll spill the whole master plan for us. Dave, Salim, my moonshot mates, thank you guys. Grok 4, special edition. See you with Grok 5.

• 1:02:14Speaker 02

  Yeah.

• 1:02:16Peter Diamandis?

  Gemini 3. In like three weeks.

• 1:02:19Speaker 02

  We'll be back online soon.

• 1:02:21Peter Diamandis?

  All right, see you all. Thank you for joining us. Take care, folks. Bye, guys. Bye. If you could have had a 10-year head start on the dot-com boom back in the 2000s, would you have taken it? Every week, I track the major tech meta-trends. These are massive, game-changing shifts that will play out over the decade ahead. From humanoid robotics to AGI, quantum computing, energy breakthroughs, and longevity, I cut through the noise and deliver only what matters to our lives and our careers. I send out a meta-trend newsletter twice a week as a quick, two-minute read over email. It's entirely free. These insights are read by founders, CEOs, and investors behind some of the world's most disruptive companies. Why? Because acting early is everything.

• 1:03:05Peter Diamandis?

  This is for you if you want to see the future before it arrives and profit from it. Sign up at dmagnus.com/metatrends and be ahead of the next tech bubble. That's dmagnus.com/metatrends.

• 1:03:32Speaker 07

  Are your ad campaigns lighting up the dashboard, but not the pipeline? That's bull spend, and marketers are calling it out in Dashboard Confessions.

• 1:03:41Speaker 08

  My boss asked for results, so I opened my dashboard for the only positive-sounding metric I had: impressions.

• 1:03:49Speaker 07

  Cut the bull spend. See revenue, not just reach. LinkedIn delivers the highest return on ad spend of major ad networks. Advertise on LinkedIn. Spend $250 on your first campaign and get a $250 credit. Go to LinkedIn.com/campaign. Terms and conditions apply.