CEOInterviews.AIUrgent Update- AI Sputnik Moment: Kimi K3 Released w/ Emad Mostaque

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Peter Diamandis0:00

Today we put out the bat signal and called for an emergency pod because America just experienced an AI Sputnik moment. Kimmy K3 released yesterday shocking the AI world with the largest open model ever and it went straight to number one. This week they didn't just close the gap, they jumped the fence. Kim's always been a model that felt a bit different. That's why it was always top of the writing benchmarks for example. K3 is actually a multimodal model. So it can have all sorts of inputs and it can understand things which is one of the reasons it's so good at front end. Now it's a free-for-all between Meta and SpaceX AI on the American side and now China and Moonshot number three on that Pareto optimal frontier.

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Selma0:41

Frontier intelligence is now a totally perishable asset.

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Alex Weezer Gross0:45

What are the American frontier labs spending their money on? I think the US government starts a strategy of constraining in some fashion Chinese open models from being used in the US.

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Emad Mostaque0:56

We've had this bunch in the internet world that information wants to be free. Basically, intelligence also wants to be free.

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Peter Diamandis1:01

All we need now is some kind of a global. Now that's a moonshot. Ladies and gentlemen, welcome to Moonshots everyone. The number one podcast in all things AI and exponential. Your front row seat to the coming singularity. Maybe I should say to the singularity which is now to the present singularity to the present to the continuous singularity. Today I'm going. Today we put out the bat signal and called for an emergency pod because America just experienced an AI Sputnik moment. But more on that in just a moment. Allow me to welcome my magnificent moonshot mates. We have the full quintet with us here today. Alex Weezer Gross, Dave Blondon, Selma, and Immad Mustach. I'm Peter Diamandis, your host and abundance provocator. If your head is spinning at the pace of the singularity, good. Mine is too. And that's the point. Our mission here at Moonshots is to keep you informed, keep you up to speed on exactly what's happening. Most importantly, keep you optimistic with the extraordinary pace of change, the coming age of abundance. Gentlemen, welcome. Thanks for getting up early, wherever you might be, or ID in your case, in the afternoon. I was up at 4:00 a.m. this morning. The benefits of jet lag, but I could have used another hour of sleep.

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Alex Weezer Gross2:17

And I'm not so.

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Dave Blondon2:22

European siesta.

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Peter Diamandis2:23

Yeah, I've got a workout scheduled right after this. A lot happening, gentlemen. A lot going on and appreciate everybody's time here. Before we get started, I want to personally say thank you to all our subscribers and our viewers. I've had a chance, I don't know if you guys did recently, to watch and read the YouTube chat. All I can say is we love you guys, too. Our mission here is delivering the news. We spend an ungodly amount of time reviewing. Salem and Alex and Imad, I got your text this morning. Let's add this. Let's add that. So much going on.

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Dave Blondon3:02

I got to say also all the memes of Alex explaining JSpace are awesome. So keep memeing Alex every time you can.

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Alex Weezer Gross3:10

Yeah, for sure. And some great appreciation. See if you can figure out my JSpace.

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Dave Blondon3:15

Yeah. Well, can we look inside? We'll be able to see.

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Peter Diamandis3:21

Yeah, we're going to get a readout. And see, a lot of love for you on the comments as well. There's some wonderful people out there. What's incredible is most YouTube videos are just a flamethrowing festival and ours are completely the opposite. It's really amazing.

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Alex Weezer Gross3:41

Kudos to you, Peter.

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Peter Diamandis3:42

Well, no, I just again absolute gratitude. I appreciate the fact that everyone, all of our subscribers and viewers here take the time to listen to the pod. We constantly spend so much time with our entire team and the entire Moonshot Mates here just really trying to assess what's going on and deliver it. We have these emergency pods. So if you haven't subscribed and turned on notifications, please do. Jen, say we jump into the first story. It's a big one.

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Alex Weezer Gross4:11

I'll just note that if we do enough of these emergency pods, at some point it turns into Moonshots Daily.

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Peter Diamandis4:16

Yeah. Or continuous. I still think moving into an Airbnb together and just turning on the camera.

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Alex Weezer Gross4:23

It's going to happen.

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Peter Diamandis4:26

All right, let's jump in. We've just had a Sputnik AI moment that's waking up the US Frontier Labs like a quadruple espresso shot. Kimmy K3 released yesterday, shocking the AI world with the largest open model ever, and it went straight to number one. A little backstory here. Kimmy K3 is from Moonshots AI, a Chinese lab. Over the last year, they've climbed the leaderboard. They put out K2, K2.6, K2.7. Each one closing the gap against Anthropic and OpenAI. This week, they didn't just close the gap, they jumped the fence. Overnight, they released Kimmy K3, and it's a monster. 2.8 trillion parameters. You got to remember the context here. China is doing this while under US export controls intended to starve them of the most advanced Nvidia chips. That's a big deal I want to discuss with you guys. They've completely engineered around the compute wall and K3 jumped 17 places from the previous Kimmy model, blasting past Claude Fable 5 to land as number one on the frontend code arena. K3 has also ranked number one in six other domains: brand and marketing, reference based design, data analytics, consumer products, simulations, and content creation. The full model weights are set to drop around July 27th, which means anyone on Earth will be able to download and run this on their own prem. How big a deal is this, Alex?

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Alex Weezer Gross5:58

I think it's great for competition. Let me first as a preliminary matter point out some things that have perhaps been slightly less obvious in the coverage, the meltdown if you will over K3.

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Peter Diamandis6:08

It has been a meltdown. Yeah.

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Alex Weezer Gross6:10

The first is as Moonshot points out, they claim in nine of the past 12 months that Kimmy models have held state-of-the-art among open weight models. So if that claim is indeed true over the past year, it's been basically Kimmy all along. I think that's very interesting. Secondly, taking a look at the published architecture since we haven't actually seen the open weights yet, but they're promised later this month. There's no magic in it, and that's pretty striking. One can imagine that behind the scenes in Anthropic or OpenAI that they've somehow, Sam Altman continues to tease at this, that there's some post transformer architecture lurking behind the scenes achieving all of these performance breakthroughs. But taking a look at the published K3 architecture, there's no magic. It's still essentially a transformer. They've made obviously a number of innovations, but well understood innovations concerning how they do mixtures of experts, how they linearize attention. They have their own special Kimmy brand of linearized attention, but it's still basically a recognizable transformer. I think that the fact that a recognizable transformer-like architecture can almost match GPT 5.5 max on the task cost frontier, which we should probably throw up a slide for you. I think that's pretty striking. That does raise the question, what are the American frontier labs spending their money on? If you can just use a transformer to get this close, not like it's already on the cost frontier, but you can get close, third place on the state-of-the-art for overall AI performance. What the heck are the American labs spending all of their money on? So I derive great comfort in at minimum knowing that the transformer architecture is still alive and kicking.

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Peter Diamandis8:04

Imad, your analysis here because you've been tracking this. We've been going back and forth on WhatsApp together.

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Emad Mostaque8:11

Yeah. No, I mean I think Kimmy has been top of various benchmarks. Again, you can pick and choose. And they have had the largest open weight models out of China regularly ever since they almost kicked off a year and a bit ago. I think as Alex said, the architecture isn't anything super novel. There are improvements like their muon scaling that they did with UCLA and other things. They've actually been releasing breadcrumbs of all of these parts. I think what's key here is the underlying data. Kim's always been a model that felt a bit different. That's why it was always top of the writing benchmarks, for example. What they've done here seems to be something extraordinary. When GLM came out, it's a fantastic model. It wasn't quite up to frontier, but it was text only. K3 is actually a multimodal model. So it can have all sorts of inputs and it can understand things, which is one of the reasons it's so good at front end. Although we wouldn't have expected again it's number one in front end versus everyone. I think this comes to something which I've said before: building great solid models is cutting edge manufacturing. Again, you will have algorithmic improvements and all sorts of things coming, but why are Chinese EVs better than Fords? This actually feels like the same thing. They build it, it's engineering, but it's also like the number one car here in the UK last month was the Jaiku J7 or Temu Land Rover as it's been known. It comes out fully loaded, full spec for like 50K, a third of the price. This actually feels something very similar. They've known what the ingredients are, the raw materials. They're now putting in an incredibly consumer friendly way and they're just executing that manufacturing process with what they have. When you look at the architecture, you look internally, they're still on H800s. They're a couple of generations behind on the Nvidia chips, but then they built it to take advantage of Huawei and Alibaba's next generation chips, which you can see by the static shapes and all sorts of other things as well. They're just relentlessly going at the engineering and the usability, which is why the front end code I think is the one where they're standing out. They're just like how can we make it have the most amazing outputs, a personal website to a game to other things, whereas the US labs are maybe looking in other directions and focusing a little bit on different things.

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Peter Diamandis10:38

Yeah. I mean one question real quick: we've always talked about do we need another breakthrough beyond LLMs to get to AGI? Does this give you comfort that we don't need another breakthrough to really move forward?

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Emad Mostaque10:51

Again it comes down to definition of AGI, right?

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Peter Diamandis10:53

Yeah, of course.

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Emad Mostaque10:55

Don't get me started.

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Alex Weezer Gross10:57

Six years ago, Peter. It was 6 years ago.

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Peter Diamandis11:01

I mean, I guess the question is there's plenty of headroom still to progress these models.

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Emad Mostaque11:06

Well, I think you have the base model here, right? But then you've got all these amazing harnesses that are coming out and the way that you're using the model to go back on itself. One of the things that's in the Kimmy blog post is that it actually designed a chip for itself for its next generation and it designed its own kernels for running as well. So you move from this model weight to this whole ecosystem that the model itself builds that feels AGI-ish, right? That feels like recursive self-improvement. That feels like the ability to learn and adapt new skills dynamically by changing itself. So I think for most definitions of AGI, we probably don't need something new to optimize and make it super efficient. There are various ways even what we know it could be more efficient than what we have here. We just don't have enough compute for it. New architectures could push us even further.

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Alex Weezer Gross12:02

You could say attention is still all you need.

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Peter Diamandis12:05

I like that. So, Alex, we've thrown up here the performance charts and we see Kim K3 sort of topping the charts in a multitude of places. I don't know if you want to comment on this and I want to pull you into.

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Alex Weezer Gross12:17

If we could throw up the AI scatter plot I think is probably the most instructive one. This is from the Artificial Analysis Intelligence Index and this is of all of the charts at this point. This is my favorite one because this one actually shows the cost per task as defined by AI versus performance frontier. One can sort of mentally look at this for those who can't see it. We see the frontier as a jagged frontier going from lower left to upper right where in the upper right we see maximum cost per task and maximum overall score is still Fable 5. Riding the Pareto frontier down and to the left from that we see number two on the frontier is still as of a few days ago GPT 5.6 Solve Max and now for the first time Kimmy K3 is number three. It's on the frontier. It's number three both in terms of raw capabilities and also the third point on the optimal cost performance frontier. I think that's totally striking. We went from a world where, as we mentioned a couple pods ago, there was this OpenAI Anthropic duopoly to now it's a free-for-all between Meta and SpaceX AI on the American side joining the upper end of the Pareto frontier and now China and Moonshot is number three on that Pareto optimal frontier. That's so exciting for any enterprise to the extent it's willing and able to use a Chinese open, soon to be open weight model to control more of its own destiny. I think this is just such a boon for enterprise sovereignty. It's a boon for competitiveness. We're living in the AI version of For All Mankind where the Soviets landed first on the moon and now the space race never ends. The AI race is now no longer ending with a duopoly and I think that's a total boon for the future.

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Peter Diamandis14:24

Amazing. Dave, let me pull you in here. What are your thoughts?

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Dave Blondon14:27

Well, you know, Peter, you called it a Sputnik moment. If anything, that's an understatement of the implications of this. We had that Alex Karp rant on the podcast last week where he was saying look, you can't as a large enterprise as a government just throw all of your proprietary weights, your proprietary alpha, all of your intellectual property over the wall to Anthropic and make that the basis of your whole future. But he didn't give you a road map to move forward. Here we are just a week later and it's suddenly a free-for-all. As Alex was saying, a free-for-all where anyone who reads these weights has the ability to get very close to the frontier and then fine-tune for any vertical use case beyond the frontier. So it gives everybody in the world, every corporation, every government in the world, a way to catch up to the frontier without going through the US AI models. So Sputnik, yeah, Sputnik times infinity essentially. The thing I don't like about this particular chart is because the left index goes to 100% and when you chart it out over the next two years, it looks like an S-curve. So we're in this really steep part of the curve right now, but it implies then we get to 100% and then we've achieved the end. But this is actually an exponential where intelligence goes to infinity. So the benchmark saturates, but intelligence itself goes to infinity. So now it's really clear. Just for everybody, the way this works typically is nested S-curves. One particular technology tops out, but it builds the next technology that then begins its exponential ascent and so on and so on.

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Peter Diamandis16:04

Exactly. Exactly. Right. Let me just say one other thing. Alex and I have spent a lot of time working on this Keller Jordan speedrun. We talk about it a lot. It's a way you take a GPT2 class model. You can find it online very easily. Look on GitHub. Look up Keller Jordan speedrun. It's a whole bunch of hackers and AI researchers who are continually trying to take GPT2 way back, five years ago, in the form of Andrej Karpathy's nanoGPT in particular.

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Dave Blondon16:32

Exactly. And try to recreate it faster and cheaper, faster and cheaper. If you look at the innovations in that repo, they've been able to cut the original cost of creating GPT2 by 99%. So now it's 1% of the original cost. Everyone kind of doesn't pay attention to it because it's GPT2. Up until today, it wasn't clear whether those same ideas would apply at frontier scale. Now it's really clear that when Elon Musk takes his 16 billion Colossus 2 data center and builds a 10 trillion or 20 trillion parameter model for billions of dollars, there is a 1% cost version of creating effectively the same thing. Nobody knew until Kimmy K3 whether that was going to work or not. Now it's really clear that it does work. So we're looking at 100x kind of innovations in the software stack, in the kernel optimization, in the mixture of experts, these fundamental breakthroughs that come out of China are giving them 1% cost. I think Ahmad gave a great analogy to the car where you can get a virtually identical car for about a third of the price. Here we're talking about less than 1% of the price to create the equivalent product. So Sputnik, yeah, that's the understatement of the century. That's why we're on the emergency pod today.

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Peter Diamandis17:53

Yeah, Salem, jump in.

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Selma17:55

I have three points to make. I think it's not so much that Kimmy's beaten etc. Whatever. It's the fact that frontier intelligence is now a totally perishable asset. The shelf life is weeks now for anybody that gets to the very edge. Any enterprise or government interested in that very latest cutting frontier model doesn't have time to actually evaluate it, do an RFP, look at other models, have a committee internally think about whether to deploy it, and now you're three generations ahead in the model anyway. So now all the value comes in the architecture that can swap models. That's going to be the next layer. We call that interfaces in our Exo world. That's going to be where all the value resides going forward.

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Peter Diamandis18:41

Yeah. Amazing. I love.

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Alex Weezer Gross18:43

We need a new term for that. Maybe like the Frontier Liberation Front.

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Peter Diamandis18:50

Let me say one other thing for the hypergeeks out there. Ahmad said the muon optimizer, but he said it very quickly. Anyone who's an enthusiast, look that up as well. One of the reasons this is happening is because when we built these original models, the very large scale models, we took 20, 30 trillion tokens from around the internet, every word ever written by humanity, and just dumped it into the training set and said, 'Here AI, become intelligent given all of this information.' But when you look under the covers, the vast majority of that information is Taylor Swift's concert coming up and their wedding. It's a whole bunch of stuff that doesn't actually drive the intelligence of the model significantly.

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Alex Weezer Gross19:29

The opposite in fact.

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Peter Diamandis19:31

Yeah. It's very true. A lot of those tokens actually might slow down the training, not accelerate it. So purely by pulling out the garbage and stripping down the training set to the relevant subset, you can still tax the model just as much but it reduces the number of flops, the amount of computation that the model's doing to get to the same level of intelligence. I don't think we're anywhere near done with that problem yet. So you can expect more 10x improvements to come out of just the muon optimizer process and the training data set getting stripped down process. I threw up this tweet from a guy named Allaric that I found fascinating. For those not viewing this, it says from Anthropic, quote, 'Fable is an agentic coding super weapon capable of developing cyber and bioweapons at unprecedented speed and scale. We cannot in good faith release it without guardrails.' Right? This is the conversation a month ago. And China comes back and says, 'Laughing my ass off. Here's Fable but open source. Good bleeping luck.' So I am curious how do you guys think about that fact that we were so constrained because of the guardrails and here's an open source equivalent of Fable.

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Dave Blondon20:42

Well, the Frontier Labs have a major problem. They've got three fundamental massive constraints that they can't get around. One is compute and the availability of chips and all the electricity and power that's needed. The second is frontier open source models that are as good as or in many cases substitutable without much notable difference. The third is you've got government coming down on you going, we need to check before you release anything. I'll make a thumb in the air guess. The trillion dollars that OpenAI might have been worth shrank by about 50% when the government said we have to review all these models because now it's going to take time to get things out. I think this crashes it by another 50%. I would put the finger in the air value of these Frontier Labs at about a quarter of what they were three months ago.

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Peter Diamandis21:33

If I don't have to spend the money for the API calls and I can just use Kimmy K3 on prem, why would I spend the money? Are they going to be hit by massive reductions in revenues?

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Emad Mostaque21:47

Yeah, I think there's a couple of things here. Number one is reduction in revenue. Why do people pay for IBM? Why do they pay for non-Chinese cars for mission critical things? I think having US on-call entities where you know things aren't going to go wrong will still sustain for a while. So I think revenues will still go up for OpenAI and others. This is why they built these forward deployed engineering companies as well. I think they've still got a way to go, but you have the substitution effect again. This is just like Chinese industrial substitution. Why can't America build industrial things? Why do you have Chinese? Sometimes you buy Chinese, sometimes you buy American. I think we'll see that at least for another year, but then it gets difficult on the cyber attack security theater kind of things. I've maintained that we would get to this point. What does it mean? It means the only form of thing that you can actually do is cyber defense. This must be the absolute biggest category in VC right now. If you're a talented Stanford MIT grad, build a cyber defense startup that goes into cutting edge and every other company and says let's use this technology to defend against what's inevitably coming. The proliferation of these capabilities is going to increase, but not quite as fast as we think. What actually happens, and we've done some tests around this, is that GPT 5.6, the cyber version, Fable etc., are trained on lots of CVE and cyber data. The Chinese models don't actually have that much of that, so they're not that great. But someone can train that data if they have it into there. So we'll probably see cyber attack capable open source emerge in a quarter or two. There'll be a bit of a lag there, but definitely for the types of big adversaries, it's going to get a bit crazy.

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Peter Diamandis23:39

Dave, you want to jump in?

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Dave Blondon23:41

Yeah, for sure. I think we glossed over recursive self-improvement there. Peter, you asked the question of is this the tipping point. The view of the US government, we always knew it was going to be too late, right? It just moves too slowly. But the view was look, when we get to a model that's capable of building itself, building the next model, we're not going to let that go out to everybody in the world so they can catch up overnight because there's never been a product in the history of manufacturing like a car. If you have your state-of-the-art car and you give it to a foreign government, they can't use it to make a better car. But AI doesn't work that way. If you have state-of-the-art AI and you give it to a foreign government, they can use it to actually catch up to you and create state-of-the-art AI. That became clear to the government a month ago, month and a half ago, that Fable 5 was over that line. So they stopped it. But the reality is that Opus 4.8 was over that line. People in China could use Opus 4.8 to create Kimmy K3. So that recursive self-improvement line was actually crossed earlier than Fable 5. That's going to be obvious to the world now because all you need to do is have an AI that's capable of improving its own kernel. It doesn't have to be Einstein level intelligence. All it has to be able to do is improve its own kernel and get a 10x step up in speed, which nobody perceives as being true AGI, but that's all it needs to accelerate itself by 10x. Then the 10x smarter or 10x higher parameter model will be some level of intelligence higher. A lot of people in academia were saying we're getting diminishing returns with the parameter count. So a 10x faster model won't natively be 10x smarter. But that turned out to be wrong. We're seeing slowing, but we're not seeing flattening of the intelligence curve. So all the evidence now is that if you boost the raw speed by another 10x, you're going to see genius level AI. Then that genius level AI will boost its speed again. So I think when we look back on this in history, we'll say right around Opus 4.8 was the point where the little spark was enough to ignite a flame, and then a flame can become a fire, and then a fire can become a sun. That's the way we'll look back on this moment in time. So the cat is definitely out of the bag. The current US policy of constrain the next model, there's no way that's going to contain global and corporate proliferation of frontier AI. Do you think the US government starts a strategy of constraining in some fashion Chinese open models from being used in the US?

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Peter Diamandis26:21

Well, you know, in two weeks these weights are supposed to be open weight, open sourced and then.

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Dave Blondon26:25

We'll see. If they're rational at the White House right now, they're spending every minute in a debate on do we negotiate with China immediately and not release those open weights. I really doubt they'll move quickly enough. I'm not sure. We'll see what happens in two weeks.

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Peter Diamandis26:44

Fascinating.

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Alex Weezer Gross26:45

Can I merge two ideas here?

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Peter Diamandis26:47

Yeah, of course, please.

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Alex Weezer Gross26:48

Peter, you talked about exponentials and the law of accelerating returns. I think it's worth drilling into that because if you connect that to what Dave just said, this is why we've been saying forever on this podcast that this is unstoppable. Ray's original observation was once you have an information based paradigm, you just keep hopping across multiple technologies. So we had vacuum tubes, relays, and then vacuum tubes in computing. At some point, you can only fit so many vacuum tubes into a room, but that architecture was used to design transistors. Transistors were used to design integrated circuits and you get these nested S-curves. What Dave is talking about is as these architectures, all the various pieces of the puzzle get all reinforcing loops inside them. Each of those is like an S-curve that starts accelerating the collective and it's unstoppable. So there's no limit to where this goes. This is why people are so freaked out about the upper end limit of this. Important to connect those two dots.

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Peter Diamandis27:51

Yeah, for sure.

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Emad Mostaque27:52

Yeah. If I just say something, Peter, I'm just following on from Dave. There was an important speech by Xi Jinping a couple of days ago, God time flies, at the World AI Conference in Shanghai where he basically said, 'We are going to fully back open source as a public good for humanity and they're not going to regulate and stop it.' This is their plan. It's great for China for a variety of reasons. From the fact they have a billion people whose IQ is about to increase by having these tools. From the fact they need robots to solve their demographic thing and the soft power from putting a Chinese educated brain, a Tsinghua graduate into every critical system in the world. But they're going to keep on doing that because they actually have a regulator. From talking to some of the Chinese labs, it used to take 60 days for a model to be approved. Now it's like a week.

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Peter Diamandis28:43

Amazing. You know, just also announced a regulatory body that they've created which includes Brazil, different parts of Asia and Africa. I don't know if you guys saw that.

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Alex Weezer Gross28:56

I saw that. It means obviously the new Belt and Road is now focused on AI coming out of China. It's a bizarre future where the Chinese Communist Party is saving American capitalism from itself.

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Dave Blondon29:08

It's so true. Let's also note that Yang Xilin was a CMU graduate and we could have given him a visa to stay.

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Peter Diamandis29:18

Yeah, we're going to get to that story in a second. This is an interesting chart here that shows the valuation. Kimmy's valuation or Moonshot AI valuation is at 20 billion as compared to Anthropic at a trillion and OpenAI basically at a trillion as well. If they were public companies today, I think you would have seen like a 30% stock valuation drop.

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Alex Weezer Gross29:43

I'll ask again, what are the American Frontier Labs doing with all of their capital?

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Peter Diamandis29:47

Yeah. What are they spending their money on?

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Dave Blondon29:49

Actually, if you go into the buildings and talk to them, they'll give you the capital. They're desperate for more smart people to help because they're trying to deploy and change the world at this insane pace no one's ever experienced before. They want to deploy that capital much more quickly than they can find smart people who have good ideas to use the capital. It's a great point, you're sort of saying it in an accusing way like what are you guys doing with your capital, but no one in the history of the world has ever had this much money pour into their building this quickly with no prior business experience. We're talking about CEOs that have never run a company before. They're trying, but can any human being really rise to the occasion of AI that quickly? My point there though is if you're smart and you have good ideas, get into those buildings and propose your ideas. This applies to XPRIZE too. They are desperate to move that money out the door into something productive that gives them a sustainable barrier to entry.

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Alex Weezer Gross30:46

I also think that the Frontier Labs are also asking themselves that question and asking the US regulatory apparatus that question. Anthropic regularly is sending out smoke signals accusing various Chinese frontier labs of distillation attacks. In Anthropic's public mind, that's how the Chinese labs are able to do it through distilling and capturing reasoning traces. But honestly, looking at the K3 performance, I'm not at all convinced that Moonshot is achieving their performance purely or even substantially through distillation attacks on Claude. It just doesn't smell right.

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Emad Mostaque31:19

No, no, I totally agree. I think there's a tendency to underweight or undervalue the existence proof. Just purely the knowledge that a highly scaled transformer running with a muon optimizer and simplified data, knowing that that works gives you a much more refined road map. You don't have to copy, you don't have to cheat, you don't have to steal every trace. You just have to know that that formula works and that cuts your R&D costs by 90-95%. So I think it's just that simple. There's nothing sneaky or cheaty about it. It's just knowing you're on the right path.

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Peter Diamandis31:54

I have the greatest value creation idea for ourselves ever. Okay, which is we in 9 days when they drop their open source weights, we release an open source model called Kimmy 4 under the Moonshots podcast name and IPO it.

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Alex Weezer Gross32:13

And instantly we'll be billionaires. So you're saying what's better than one moonshot? Moonshots plural.

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Dave Blondon32:20

Well, you know, why not copy the copers? Let's go.

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Peter Diamandis32:25

That's good. Actually, I think I've got a good analogy for you, Dave.

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Emad Mostaque32:29

Why do Americans pay more for drugs than everyone else? All the R&D happens in America. You pay the premium just like tokens premiums. Then what happens? You have generics elsewhere.

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Dave Blondon32:40

Yeah, that is a good analogy because that's like a 99% cost cut. It's much more akin to AI than cars. That's a great analogy. Gavin Baker, our friend, wrote a brilliant post. You can find it on X about the implications of this for businesses and essentially must read. Absolutely. But essentially all businesses, all stocks other than the Foundation AI labs are huge beneficiaries of this. Then the foundation labs are like, well, what's your future? What's your revenue model? Why are you worth a trillion dollars? I don't quite get it. So you should see a really big reshuffling of valuations in the next week based on that observation. Any corporation that has its technical act together, there aren't very many of those, but if you're a bank that happens to be a very good bank with brilliant IT and technical skills, or you have great partners and great vendors, you now have a clear road map to controlling your own destiny with your own AI, your own JP Morgan AI. So I suspect the markets will react to that if you put your hand up and say, 'Hey, we have a way to do this internally. We know how to do this with our partners or however you get it done.' This is why we call it the organizational singularity.

P

Peter Diamandis33:57

We're still seeing everybody who's using or trying to use Fable 5 getting downgraded every time they mention biology or mention something that is potentially on the edge. Why would you tolerate that? So in 9 days, what do we see? I'm as soon as it's available going to upgrade. I'm running Kimmy 2.7 on my Mac Studios. I'll upgrade it to Kimmy 3. Everybody will. So do we start to see sort of the wholesale US entrepreneurial base of capabilities on K3?

E

Emad Mostaque34:31

Well, I think I can think of an analogy of this which is stable diffusion. When we released stable diffusion, God, four years ago, time flies, you had these really restricted image generators that were a bit better but they were restricted and they had all sorts of arbitrary restrictions because obviously it's a bit dangerous to have it. You couldn't have likenesses. There was no way to get IP in there even if it's your own IP. What happened? 100 million, 200 million downloads and a whole ecosystem built around that and accelerated generative media. Why are you going to have this model? I can't even talk about philosophy with it, it downgrades me. When you can have the fully open variant of it at even a fraction of the price that you can then customize, a whole ecosystem will build around this and other models. It has already been doing so. That's a real danger versus being locked into the single vendor.

A

Alex Weezer Gross35:22

Which is why I think the labs will go vertically integrated. All their customers are now going to be their competition and they're going to be like, 'Okay, I'm going to take you all on.'

P

Peter Diamandis35:30

Well, and that directly ties to Mira Murati and Inkling. Are we going to talk about that story, too? That's huge this week.

A

Alex Weezer Gross35:36

Well, we talked about in the last pod, which was so two days ago.

P

Peter Diamandis35:40

Okay.

D

Dave Blondon35:41

I mean, and Mera just released Inkling, which is fantastic to see a US open source lab. But the question is how many more will we get?

P

Peter Diamandis35:51

You know how many more open source, shocking Sputnik moments are we going to see? We have a lot of Chinese labs pursuing beyond just Moonshot.

A

Alex Weezer Gross36:04

Yeah. So Inkling is just really telling about where things are going to go because it's designed for you to pick it up as a corporation and fine-tune it within your corporate walls to whatever your use case is. So if you're a biotech lab and you're researching and you don't want everybody to see your proprietary data, you take Inkling and you tune it internally. The reason that's telling is because Mira Murati came from OpenAI. So if she didn't believe that pathway was viable, she wouldn't start thinking machines around that thesis. So it tells you that the people that are inside the best frontier labs believe that this process can catch up to the frontier. So you combine that with Kimmy K3 proving it and it's a different world next week. The other thing that was weird in the market at the end of the week is that things started to reshuffle pretty dramatically toward the end of the week. In the downdraft, the semiconductor companies also came down, but they're actually going to go the other direction. This is the point Gavin Baker was making that this drives up the need for silicon, not down. It changes the whole software landscape tremendously. But silicon is going to be more in demand than ever before and completely sold out as we know.

P

Peter Diamandis37:18

Can we talk a second about the Nvidia embargo that we put for China? Here we see the highest performance models. Was the whole Nvidia regulatory embargo unnecessary? Did it do what we've always done before which is just spark China's need to develop their own capabilities with Huawei?

A

Alex Weezer Gross37:42

Of course that's what happened. The embargo only incentivized the Chinese frontier labs to develop and cultivate new efficiencies that by the way were always there. To Dave's point earlier about the nanoGPT speedrun, there's this enormous overhang that isn't fully exploited in terms of leveraging algorithmic and computational and hardware efficiencies to train larger and more capable models. All these export controls do, I think, is incentivize the Chinese labs, which are already feeling plenty of demand pull to compete with Western frontier models, to leverage those efficiencies sooner. Maybe on balance, although it's superficially bad for the West now that we've incentivized this new generation of much more efficient Chinese frontier models, in the end, I think it's net good for not just the world, but also for the US to have this fire lit underneath them by Chinese competition that's much more efficient, much more capital efficient, more weight efficient, probably more bit efficient. This is all a net positive as long as the US in my mind does not set up or fall into some ultimately protectionist regime of trying to prevent what may be construed as Chinese super intelligence dumping on the US. Exactly.

P

Peter Diamandis39:03

As long as we avoid that, it's great.

D

Dave Blondon39:05

Exactly what happened. That's exactly right. I think the US learned a really important lesson in the Vietnam War. That's over 50 years ago now, it's been forgotten again. You have to be reminded again. In the Vietnam War, it was really clear that either you go to war and you win quickly or you don't. What you don't do is send in a few troops and then send in a few more and then creep in. Nothing good comes of that at all. The embargo of chips on China was totally harebrained because it was enough to irritate but not enough to actually work. It's just the worst case scenario. It sparked exactly like Alex said a huge amount of quantization research which is critically important and under discussed that allows faster performance on cheaper chips. Those innovations don't go away. That's going to be around forever now.

P

Peter Diamandis39:56

Let's go to.

A

Alex Weezer Gross39:59

I think we've got a completely self-contradictory but it has some interesting outcomes. The total amount of compute used for Kimmy K3 is the same as Inkling.

P

Peter Diamandis40:12

Wow.

A

Alex Weezer Gross40:12

You can tell that because it's the amount of dense weights and roughly we assume about twice the number of tokens trained because we don't have it. But how does that work? You look at their architecture and it's a two and a half times in data to intelligence conversion through the advantages and data mix that they have because they've had to operate in these constraints. We see that because the first model isn't as good as the second model. For Inkling, you're going from a trillion parameter model to a 300 billion parameter model about to be released, which is actually better performance. So you see this with the labs and these labs have had to deal with the constraints.

E

Emad Mostaque40:45

But here's something really interesting I think. If you look at that slide Alex loves and we kind of chuck it up on the screen. So what they've had to do is they've had to optimize their inference for Huawei 910 Ascend chips, for the new Alibaba chips and others, 64 nodes in one because this is a big model. You're going to have to buy another Mac Studio or two, Peter, to serve this. It needs like two terabytes of RAM. So you see where Kimmy K3 is there, that's because they can only use Chinese silicon to run it. They don't have Blackwells, they don't have Vera Rubins. Vera Rubins and Blackwells are designed for these really large models that have really small things because it's 50 billion active parameters against 3 trillion total. American companies like Modal, like.

P

Peter Diamandis1:24:01

Forecasting capability in the markets today, you would do that. I remember having a conversation with Eric Schmidt, who said, you know, listen, if Google wanted to maximize its income, it knows exactly which companies are going to have a stock bump in the fourth quarter because everybody's googling this product or that product. We've advanced information about where the sales are going to be and which products are going to peak. But if we could only do that once and then we'd be shut down. So interesting to see if these companies and, you know, Alex, you and I have talked about the fact in Solve Everything, the notion that the greatest money, the greatest income these frontier labs are going to make is going to be as they solve scientific breakthroughs and, you know, superconducting and age reversal and so forth.

A

Alex Weezer Gross1:24:48

Exactly. And maybe just a footnote on the Google story. So I've had this conversation with Google execs many, many times over the years. Totally agree with the premise that if Google were to attempt stock trading based on arguably insider or unfiltered insider information passing through the query stream, that's a one-and-done type shutdown scenario. But there are other things that Google hypothetically could be trading besides public securities that wouldn't necessarily have the blowback. For example, again hypothetically, foreign exchange rates.

P

Peter Diamandis1:25:18

Yeah, and I think that you have to be careful here though. I think there's the market side of things and, you know, like maybe, maybe not. I will launch a hedge fund based on our own stuff, but there's the moral side of things. Maybe not. Maybe not, invest okay. Of course, but at any rate, but look, there's the moral side of these things. It's fantastic that we can optimize ourselves, but who controls these models and the advice they give can control vast waves of humanity, and there needs to be a real discussion about this because it's like the people that follow their GPS into a... You know, like you, we're going to rely on these far too much. And again, how can you debate it? In just a few years' time, like again, you will, it'll be more expensive not to do this. You will be penalized for not listening. And if we're all watched over by machines of loving grace, we need to know whose grace that is. And again, that discussion needs to start now.

A

Alex Weezer Gross1:26:13

Yeah. See, just beer. Just beer. Homer drinking beer advised by AI was not on my bingo card for this episode. That's all I'm going to say.

P

Peter Diamandis1:26:25

Welcome to the health section of Moonshots brought to you by Fountain Life. You know, my mission is to help you use the latest technologies, including AI, to not just do your work at home, teach your kids, but to help you live a long and healthy life. I'm here today with an extraordinary physician, the chief medical officer of Fountain Life, Dr. Don Mucalem. Let's talk about cancer. You know, I know from the member database that we have at Fountain, members who come in who think they're healthy, it turns out 3.3% of them have a cancer in their body they don't know about.

D

Don Mucalem1:27:00

That's right. You know, the majority of cancers that we screen for, those aren't the ones that are necessarily taking the lives when found at a late stage. We know that when cancer is found early, the chances for cure are much higher. We know it's much easier to treat a cancer when found early versus when found late. What we're finding in our members is over 3.3% were found to have these cancers that otherwise wouldn't have been found or detected.

P

Peter Diamandis1:28:00

Yeah. You know, it's interesting. People, you don't feel the cancer until stage three or stage four. And if you don't know what's going on inside your body, it's like driving your car with your eyes closed. And you can know. So when members come through, how do they detect cancers? So we're doing full body MRI and we also do early cancer detection screening. This is very, very important and these are not typical tools used in the conventional care setting when it comes to prevention. This is a hard thing because currently these are not studies that insurance would yet be covering. But the goal is to collect these numbers, do the research and work hard to democratize wellness. Yeah. So at the end of the day, you can know what's going on inside your body. It's your obligation to know. So check out Fountain Life. You can go to fountainlife.com/pater to get access to the latest technology to help you detect cancer at the very beginning at stage one when it is curable before it gets to stage three or stage four in your world of hurt. So, Selma, you sent me an article, a chart. I just put this up here right now. This is our constant debate and we're seeing this again across data center wars in the United States. Data centers are, you know, sucking up electricity, driving up the cost for consumers and also water, right? It's one of the loudest criticisms of AI right now is that data centers are guzzling drinking water to cool their servers. So this week, this particular chart that I'm showing, you know, made the rounds and it pairs two figures. On one side, every data center in the entire US, according to Lawrence Berkeley National Labs, is consuming 17 billion gallons of water on site. But what it shows is American golf courses that have soaked up 531 billion gallons of irrigation since 2024. That's 31 times as much. And so, you know, the posters I'm going to start seeing on the sides of the highways is forget data centers. We must ban golf courses immediately.

A

Alex Weezer Gross1:29:24

Yeah. Where's Peter? Where's the Chinese influence campaign to get America to shut down its golf courses? Yeah, I tell you, I don't see it any place. But here's the shocking piece of data. Besides golf courses, California almond farming alone consumes 1 trillion gallons of water, 60 times all the data centers combined. So,

D

Dave Blondon1:29:46

I have one other stat, please. Which is Amazon warehouses occupy 10 times more land in the US than all the data centers combined.

A

Alex Weezer Gross1:29:56

Yeah. So it's like such a drop in the bucket compared to everything else in terms of land usage, water usage. The human cry is such a completely non-data-driven garbage. It's unreal.

P

Peter Diamandis1:30:10

Well, exactly. That's the concern because the water use is such a nonissue. I mean, it's such a joke. But if we take that head on and say, 'Guys, don't worry about water,' you know that the angry crowd is going to move to something else equally irrational. So the underlying problem doesn't go away, which is, you know, the next issue is going to be something semi-insane. This is completely insane, but something semi-sane, but still wrong. And then that's going to create a populist movement. And you know, the word moratorium, like let's just stop. What kind of a decision, what kind of governance is 'let's just stop'? But if you look at the history of nuclear and a whole bunch of other things, that's the actual outcome we get. And so, yeah, David,

D

Dave Blondon1:30:51

I mean, this is the pandemic of fear that I keep on speaking about that I'm very concerned about. There's an underlying sense that AI and robotics are going to, you know, combat humanity, are going to be our foes. And again, I'll just go back to it. I blame to some degree Hollywood, right, of all the dystopian movies out there. And if all you see is negative visions of the future, you're going to want to shut it down. And what do you want to shut down? How can you shut down AI? Well, you can shut down the data center in your state.

A

Alex Weezer Gross1:31:24

Yeah. Also, I just that elephant in this particular room, the Dyson swarm. If the compute all moves to sun-synchronous orbit, you can do closed loop liquids including water and other coolants there, but it's not like it's going to be consuming on margin additional water. And then to Dave's point, the complaints which may or may not be in part the result of an influence operation from a foreign state actor will move to something else. It'll be very low Earth orbit, Star SpaceX, star mines and other competing Dyson swarms are polluting the atmosphere with their decay or something else. The complaint will move on to something else.

P

Peter Diamandis1:32:03

Did you hear the rant about the Starship rocket launches early? It was Falcon actually. The pollution from the Falcon launches. Elon was just like, 'Oh my god, I'm gonna vomit.' Right. Right. Yeah. Right now. It was like 0.00001% of all emissions come from any form of rocket launch. He's like, but you have to actually answer these questions. He's driving him nuts.

A

Alex Weezer Gross1:32:26

I hope those individuals who are complaining have, you know, thrown away their smartphones, don't use GPS, and are just basically going back to subsistence farming.

P

Peter Diamandis1:32:36

Yeah. As Elon likes to say, let them shake their fists at the sky.

D

Dave Blondon1:32:41

I have a fun stat. I was doing some numbers around the water thing. It's about 600 gallons of water per Big Mac and McDonald's sells 2 billion burgers a year. So it's about twice the number of golf courses, the total amount of water that McDonald's uses.

P

Peter Diamandis1:32:56

So, that I can get behind. Okay. So what you're saying, Emad, is Chinese influence op should also be shutting down American Big Macs.

E

Emad Mostaque1:33:07

That's right. Definitely improve the health of America as well.

P

Peter Diamandis1:33:11

Shall we move to one of our favorite conversations, humanoid robots?

A

Alex Weezer Gross1:33:15

This is so cool.

P

Peter Diamandis1:33:17

Yeah. So, China, as we've discussed before, has gone all in on humanoid robots. It's a national priority. Companies like Unitry and others are racing to commercialize. You know, last report and, Alex, we've talked about this, 150 humanoid robot companies in China under development and part of their strategy is spectacle and something you're trying to bring, Alex, to America. They've been staging public robot combat events, literally, you know, MMA style. And we've got a video to show. Let me just go ahead and pull this up here. Of a recent MMA that went viral on the internet. And it's a beautiful thing. Just so cool. These are only going to get better. You got to watch the full video. It's just the way the fight ends is epically awesome.

A

Alex Weezer Gross1:34:31

Yeah. One of the robots kicks the other robot's head off. You know, remember Rock 'Em Sock 'Em Robots?

P

Peter Diamandis1:34:38

As a game as kids. And so this goes viral. I mean, a lot going on in the robot world. We just saw Hyundai, all of the workers at Hyundai start to strike because they don't want robots brought in on their assembly line. That was fascinating. Alex, take it from here.

A

Alex Weezer Gross1:34:57

A few thoughts on this. I have thoughts on many different levels. One is mild horror that if anyone who's seen Steven Spielberg's movie AI, where there's, without spoiling it too much, I think Steven would call it the dark sandwich at the center of the movie, the flesh fair where humanoid robots are tortured and abused for human entertainment, I think utterly horrifying. So at one level, I'm mildly horrified that humanoid robots, no matter the extent to which they're being teleoperated here, are setting an inductive prior or bias for future more autonomous embodied intelligences to be basically trying to kill each other or at least otherwise abuse, physically abuse each other for human entertainment. I'm concerned about that. But one level deeper. Now imagine that these robots are more autonomous, that they're running algorithms that are on the edge. So they're much more encapsulated. And now imagine that these humanoids are in the Chinese PLA infantry. Because I think that's the future that we are almost certain to find ourselves in. The West needs to catch up in humanoids. That's why I've supported ProRL, which Peter you were gesturing at, which ran their first humanoid robot mini marathon in America in the Boston Seaport a number of months ago. The West,

P

Peter Diamandis1:36:28

Which you helped organize, right?

A

Alex Weezer Gross1:36:30

Correct.

P

Peter Diamandis1:36:31

Yeah.

A

Alex Weezer Gross1:36:31

Yeah. So the West needs something like this. Hopefully less violent and more economically productive. I'd love to see people cheering on humanoid robots competing to iron clothing or perform some economically productive task and not just kicking each other's heads off. But

P

Peter Diamandis1:36:48

You prefer the humans to be doing that in the MMA matches.

A

Alex Weezer Gross1:36:52

I'd prefer no one to be doing it. I'm not a fan of MMA. I think it's destructive to humans and I worry about the message that we're sending to the future Light Cone by having robots doing it instead of humans. I'd rather see people in a cage competing if they must compete at all to do something that's positive, not negative.

P

Peter Diamandis1:37:08

Coding like a cage match coding.

A

Alex Weezer Gross1:37:13

Or just sitting there. Okay.

E

Emad Mostaque1:37:15

So couple of thoughts. One is my normal commentary around kickboxing is not the greatest marketing demo for humanoid robots. But I will acknowledge something here. This is unbelievably demanding engineering environment, right? You've got a stress test. It's stressing balance and impact resistance and recovery and locomotion and latency. All like there's 20 things that they're doing. And it's kind of incredible to watch them navigate that. Of course, a four-armed robot would beat the two-armed robot. So I just leave it at that. So, you know, but this is competitive, you know, we're going to see this go to competitive sports. We'll see a version of the World Cup with robotics. Question is whether people will watch that or not.

P

Peter Diamandis1:38:03

Yeah, I'll say that the real test is whether a human being can make that penalty shot under pressure at that top point of the game. Although watching England implode the other day was really devastating for me, but still, I think people much rather watch people in that environment rather than robots. But I think sports is going to thrive for many, many decades to come.

E

Emad Mostaque1:38:30

Formula racing pushes the edge and I think when we start to see robotic sports, it's pushing the edge. I think the point you just made, Selma, is important, right? That we're going to see this happening in a competitive fashion so that the top robots, and I can't wait to see Figure versus Optimus. I think that will be a fun competition, whatever form it takes. Yeah, I think that these robots are a little bit different though. I think probably you'll first see the real steel type operated robots because robots can't actually respond fast enough if you look at the latency of a VLA model. This is impressive from some pre-operated flying kicks, but why aren't they doing kung fu? When will robots do kung fu? That's when you move to things like etch silicon, when you move to teleoperation. And I think that'll be the next stage that comes next year. But I think there's a bigger issue that I have with this. Although I love fighting robots and I can't wait to see Gundams and all that. These robots are Engine AI T800s. They weigh about 70 kg and they punch four times harder than Mike Tyson.

P

Peter Diamandis1:39:32

Yeah.

E

Emad Mostaque1:39:32

So they could legitimately kill someone,

P

Peter Diamandis1:39:35

Us fleshy humans.

E

Emad Mostaque1:39:37

Robots like that should not be allowed on the streets. And there's no regulation against that. You know, like again, they could be in the PLA, People's Liberation Army, or whatever, but robots are about to enter our household. I mean, who here has a 1X robot on order? You know, like come on, it's coming. They will be walking around very soon. And we need to have regulations about safety, of what the talks are on these things, of how they operate and others, because they represent a real threat to individuals because they are machinery. Then beyond that, you will have the embodiment and others. I mean, to have the discussion of what that looks like when they are autonomous, because these things are delivering themselves by pushing a button on the door, you know, ringing your doorbell. And the final thing is

P

Peter Diamandis1:40:21

Unitry has only made 11,000 humanoid robots total. We are literally at the very start of this. A few years from now it will be 11 million a year from 11,000. So we got to have this discussion fast as well. Lots of talking to do.

E

Emad Mostaque1:40:37

Yeah. I mean, this is the work you and I were doing, you know, in terms of how do governments counsel their policy around these areas, and it's happening at a blinding speed.

P

Peter Diamandis1:40:50

Crazy. Yeah. All right. I'm going to move us to the most important conversation we always have, which is the Dyson swarm. And let's take a look at a video from our friend Sam Altman.

S

Sam Altman1:41:01

I honestly think the idea with the current landscape of putting data centers in space is ridiculous. It will make sense someday, but if you just do the very rough math of launch costs relative to the cost of power we can do on Earth, to say nothing of how you're going to fix a broken GPU in space. And they do break a lot still. Unfortunately, we are not there yet. There will come a time. Space is great for a lot of things. Orbital data centers are not something that's going to matter at scale this decade.

P

Peter Diamandis1:41:44

All right, we have the continuing MMA battle between Elon and Sam. Um, yeah, so fascinating. I'm curious of reactions here. Alex, I'll go to you first.

A

Alex Weezer Gross1:41:55

Yeah, I think there's an obvious conflict of interest. We saw similar messaging from MASA Sun regarding lack of purported promise for orbital data centers. Remember, OpenAI has retreated from its own data centers. Remember Project Stargate? Project Stargate has been rebranded from OpenAI owning and operating its own data centers to just leasing terrestrial data center capacity from others. OpenAI is delaying its own IPO. So just not even at the object level, one has to look at OpenAI's messaging here and say perhaps it's not even in a financial or operational position at the moment to lean into orbital data centers, say the way Anthropic, which in their collaboration agreement which was announced with SpaceX AI and for use of Colossus and Colossus 2, earlier to orbital data center-based compute. So I think the crossover is going to happen. Elon's messaging regarding when this crossover is going to happen is 2 to 3 years. You see other analyses that suggest that the unit economics for orbital versus terrestrial data center costs are going to cross over sometime by the early 2030s. I'm not sure which is the case, but either way, I think there is an obvious conflict of interest. And just as we were discussing with Philip Johnston, barring some surprising left turn, I expect that OpenAI's tune is very conveniently going to change on ODCs sometime in the next two to three years, right on time.

P

Peter Diamandis1:43:25

And of course, Elon's response to this is we'll be launching them in two years.

A

Alex Weezer Gross1:43:29

So, just stay tuned and watch.

P

Peter Diamandis1:43:32

Well, I think anyone listening to this video would say, okay, Sam says space data centers make no sense. Elon says they make sense. The two guys hate each other. But if you actually listen closely to Sam's words, they don't disagree at all. Sam is saying that space data centers will not be meaningful this decade. There will come a time, but this decade's only three and a half years left. And if you look at Elon's forecast of his launch rate, they agree, actually. So they're just hating on each other all the time. And it seems that way in this phrasing, but the truth is pretty clear. They both have the same numbers. So Alex is right. You know, they're going to space. It's going to take a while. I think a couple percent of all compute will be in space by the end of the decade because we're building out on land as quickly as we can, too.

A

Alex Weezer Gross1:44:18

But then the lines cross.

P

Peter Diamandis1:44:19

Yeah. You know, Alex, you and I were going back and forth texting while the Starship attempt, Starship 13 flight, was making an attempt a couple of days ago and it's been rescheduled. When this pod comes out, we'll be seeing a next launch attempt on Starship 13 on Monday of this coming week. That launch was thwarted at T minus 0 when two of... First time I've ever seen that by the way. Yeah. Here's the point. Two of the 33 Raptor engines on the booster stage of Starship did not ignite and they're going to be replaced. But here's the extraordinary point. So, by the way, SpaceX's stock dropped 5% on news of that failed launch, which is kind of ridiculous. The point people need to realize is that was an amazing demonstration of technology. The fact that you could shut down at T equals zero, safe the vehicle, unload the methane and the liquid oxygen, and that's, you know, I was part of the space industry in the '90s before it was a space industry, and those vehicles would have exploded on the spot, right? They would have failed on the spot. The ability we have to control them at that level of detail is evidence of the extraordinary engineering that SpaceX has done.

A

Alex Weezer Gross1:45:39

I thought that was the most interesting part, which is how quickly the system diagnoses the problem and returns. It would have taken months and months to do this and fix it and recover everything and replan another launch, and you're like, 'Yeah, problem. Shut it down, redo it. Oh, we're starting Monday.' I mean, it's amazing.

P

Peter Diamandis1:45:56

Yeah. Extraordinary. Yeah. Because I think if you're serious about spending in intelligence with what we know, you have to have a space play. OpenAI is going to buy Planet Labs or something like that, you know, like then the tune will change. All right, I'm going to go to some AMA questions. So, Emad, you had suggested I post questions to X and we have a number of questions coming about Kimmy from our X audience. Let me go ahead and show these and let's dive in. So, Emad, I'm going to give you first crack. Which of these questions do you want to answer?

E

Emad Mostaque1:46:33

I think probably number four is an interesting one. Given Kimmy K3's lower token efficiency, is it actually as cost effective as advertised compared with Solo Fable? So Kimmy K3 is an expensive model relative to the other Chinese models like DeepSeek is now a dollar per million tokens. Kimmy K3 is $15. Sonnet is $20 or Opus is $40 and I think Fable is $60. But that's because they're actually making money. When you back out the numbers from the Chinese models and the chips they're running on, they're probably making 80-90% margins now. And that's with their Chinese chips which aren't that efficient for running this. We will see the cost of K3 drop by 10 to 50 times I think in the next few months as it gets optimized. And right now it uses twice the number of tokens for the same task versus GPT 5.6. Again, a frontier model that uses 37% less tokens in 5.5 or Fable. Again, we're going to see that drop because everyone and their dog is going to optimize the crap out of this. Like you've seen Fireworks just raise at a $17 billion valuation. Others like Modal at $10 billion, Base 10 at $10 billion. These are the inference providers of open source models. They've all raised a billion dollars that they're now going to spend to optimize the Chinese model and make it more efficient and run it. And so American labs who do the inference side of things are going to optimize the crap out of this. So we will see it catch up.

P

Peter Diamandis1:48:05

All right. And by the way, I welcome the mates to lean in on these questions. But Selma, you want to go next?

S

Selma1:48:11

Given that I made the comment about number one, how much could Kimmy K3 devalue US frontier models? I'll stick with my original estimate of about 75%. 50% from the US regulating the front end, and then you've got lack of compute on the supply side plus the front open-source models kind of within a release barely of where you are. That bleeding edge is such a perishable thing. I would say 75% drop. So if OpenAI's worth a trillion bucks, I'd put it at $250 billion. You still have a very valuable business because now the competitiveness you have to compete on reliability, security, integrated tools, ease of deployment. But the actual frontier cutting edge becomes one ingredient amongst the whole thing.

P

Peter Diamandis1:49:06

You know, I would not want to be inside these frontier labs right now. It must be a frenetic code red 24/7.

A

Alex Weezer Gross1:49:13

It is a total rat race. I have so many friends at the frontier labs, friends who are jumping hypothetically from one frontier lab, Google, which is nowhere at this point, missing the action, to other frontier labs. It is a total rat race.

P

Peter Diamandis1:49:28

Yeah, it's crazy. Dave,

D

Dave Blondon1:49:32

You have a choice for me.

P

Peter Diamandis1:49:34

No, pick one. You got two and three, I think.

D

Dave Blondon1:49:37

Okay, I'll take two. What does the release of Kimmy K3 do to the open source versus closed source race? Will this force the large companies to provide more product? I think they're implying more open-source product. Yeah, it's a total game changer in the sense that anyone with resources can build an internal model that's tailored to a specific use case and then use it as a defensive moat. I don't think the large US model providers will go open source. I think they're committed to their pathway. So if you were talking to Anthropic right now, they would say, 'Look, Kimmy has caught up for a week, but Fable 5.1 is coming out in just a few weeks.' When you look at the all-important enterprise use cases, so you know, white collar automation, drug discovery, people are going to use the best model no matter what. And you know, it's like if you're using an AI to design a car or a rocket, a slight improvement in the design has massive payoff. So you're going to use the best of the best of the best model. So the Anthropic guys are going to scramble to stay a step ahead and keep their price point nice and high. The cost of the model itself is so small compared to the benefit that people will pay the price.

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Peter Diamandis1:50:51

So it does create, like Alex was saying, the rat race is incredible, but people aren't going to switch to Kimmy unless it's proprietary data they want to keep in house and they want to tune their own, or Kimmy actually bypasses Anthropic, which it hasn't done. You know, it's only caught up or not even quite caught up. All right, Alex, number three.

A

Alex Weezer Gross1:51:12

All right, number three asks, and these are I think these questions seem to all be variations on a theme, but it asks, 'How can US models, I think this means US frontier model providers, continue to justify their massive valuations if China can leapfrog with an open-weight model at less than half the token cost?' So I don't think the premise is quite accurate. There are so many elements, so many layers to superintelligence, and quite frankly superintelligence itself is, as it fully develops, I think far larger than the total GDP of the entire world anyway. There's an enormous amount of pie that can be sliced. But to the extent we're talking about say Google, which as I was mentioning earlier seems to be MIA at this point on the frontier, I can't find a single top Google model at this point on the cost frontier for capabilities. What does Google do? Well, they can continue to race obviously in terms of capabilities, but if I'm Google, I'm thinking, yeah, I want to become a hyperscaler. I mean, Google obviously is a hyperscaler, but a hyperscaler provider to other frontier labs. That's one obvious venue of differentiation. And we've seen that approach vector from SpaceX AI itself, which has now signed deals with Anthropic. We're seeing it with Meta, interestingly, which on the one hand is offering Spark 1.1 and on the other hand in the past two days, just as we were going to air, it was announced that Meta is exploring selling $10 billion of compute to Anthropic. So differentiating by going downstack and offering your compute up to other more competitive providers, whether western, usually Anthropic, sometimes OpenAI, or Chinese models in a self-hosting model, that's one area. You can also go upstack, you can try to vertically integrate and offer applications that are benefiting from the commoditization of their complement, namely the model layer. You can also, I think the premise that valuations somehow are going to net shrink just because Kimmy K3 exists now is completely fallacious. We saw that incorrect thinking happen with the original DeepSeek shock, which was at the time also branded as a Sputnik moment. So we saw a bit of a hiccup in capital markets at the time. But as always, Jevons paradox kicks in and we see the value of chip stocks ultimately increase, not deflate. And we also see it's open. It's open weight. So there's absolutely nothing in Kimmy K3 that OpenAI and Anthropic and other western frontier labs can't just immediately reappropriate for their own internal models.

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Peter Diamandis1:53:59

You don't think that the amount of revenue these labs are going to make gets reduced as people start to use Kimmy K3 for their work instead of the API calls? No, for example, so I spend at, and my portfolio companies spend an extraordinary amount on let's say Anthropic and OpenAI, and to my knowledge, my expectation is Moonshot would have to release like a 2x, 3x, 10x better model than say Fable 5 to have a massive diversion of that spend. Right now, what K3 buys at the moment, to the extent it's legal, query how much longer K3 will be legal to host within the US, but assuming it remains legal and regulatory uninhibited, all it results in is greater in-house self-hosting, but it's not at the top of the frontier. To Dave's earlier point, Fable 5 at the moment is, so if you're trying to solve the frontier of problems, K3 is not causing you to divert your spend. Well, let me hit that point you just made, Alex, and ask you and the other mates a question here, which is, do you think it's possible that some legal policy in the United States prevents US companies from downloading K3? It's going to be on the open internet. It's going to be available through a multitude of sources beyond Hugging Face. Can it be shut down in the US? It can effectively be shut. This is not prescriptive and I'm not a fan of this policy, but I think it can effectively be shut down by requiring that every public corporation disclose any use of Chinese open-weight models and subjecting them to scrutiny. As we were going to air the latest, we talked in the last pod about Demis' proposal to create a FINRA-like entity that would regulate the frontier. Well, guess what? The reports are that the present administration is actually running with a proposal like that and is planning to or at least exploring creating a FINRA-like agency to regulate frontier AI that would live under the SEC, because the SEC already has statutory authority to operate FINRA-like industry advised and funded entities. So it's a natural place. Yeah.

A

Alex Weezer Gross1:56:19

Yeah. Self-regulated governance, aka regulatory capture cartels under the SEC. And so I think it's completely plausible, albeit I think highly undesirable, that we get sometime in the future an SEC suborg that looks like FINRA that basically makes it completely economically infeasible for corporations of any size, especially public corporations, to actively use Chinese open-weight models.

E

Emad Mostaque1:56:46

Any other comments on this? I've got comment on this. I mean, this is ridiculous in terms of trying to limit the use here because once you release the weights, right, stopping them, you can mirror them across jurisdiction. You can use peer-to-peer networks, VPNs. All you're going to do is deny American researchers and startups access to those models and security experts. The rest of the world goes ahead building on those models. I don't think there's a viable approach. I mean, this is the same.

P

Peter Diamandis1:57:16

Yeah, please.

E

Emad Mostaque1:57:17

This is the same as denying Americans cheap insulin.

A

Alex Weezer Gross1:57:21

I mean, it's again regulatory capture, right? Like, why can't you have generics? Because again, you have the regulatory capture point. There's operation, I think they're calling it Gold Eagle to approve access to frontier models. You will have anti-token laundering regulations. You will have know-your-prompter regulations. Like the US government has really realized that this technology is about to break through and I think that they're a lot more worried about it than China is. You know, like China again, you look at that Xi Jinping speech. I would urge everyone to check it out. They're like full on open source. We're going to do this. America doesn't know what it's going to do, but as you said, there's a real chance that they might hobble American capitalism. And oddly, China's encouraging capitalism. It's going to

P

Peter Diamandis1:58:13

All right. Let's go back to you, Selma, on next question.

S

Selma1:58:18

Okay. Which one?

P

Peter Diamandis1:58:20

Some of these are a little bit duplicative. Yeah.

S

Selma1:58:23

Yeah. I'll take number five. Would you trust Kimmy K3 to write your code for you without oversight or review? The answer is no. But I wouldn't trust a human being to put consequential untested code into production either, right? The question is not whether we trust the model, it's whether we trust the development system around it. So AI-generated code needs to be run in a sandbox and pass automated test and security scanning and all sorts of things before it goes into production. And then you do proportionate permissions based on the use case and the potential impact. This is the same thing we talk about. Whatever the workflow is that AI is running, you're still going to need human review at the highest level and at the highest consequential inputs. A lot of the routine can be automated, but the scalable model is not AI with no oversight, it's machine generated plus verification plus human accountability combined. That's going to give you the real power.

P

Peter Diamandis1:59:33

All right. Emad,

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Emad Mostaque1:59:36

Yeah. I think what role, if any, did distillation play in K3 development? They distilled data clearly from Opus and others. But to be honest, using Kimmy K2.5 and Kimmy K3 now quite intensely, it feels different. So I think they did a lot of their own data creation based in part from distillation, but everyone's distilling from each other right now. The one area that it's clear that they've had a big leap ahead is in the front-end development. Again, this isn't the best mathematician in the world, although it's quite a good general model. It's not the best cyber attacker from our benchmarks, but they've kind of done something original and new on the front end, game consumer/entertainment side of things, which I think is really interesting. Although that might be also because it's a multimodal model.

P

Peter Diamandis2:00:25

Dave,

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Dave Blondon2:00:28

Number seven. What are the reasons why Kimmy K3 might not be as good as advertised or we shouldn't use it? The scenario where it's not as good as advertised is if it's benchmaxed and, you know, in two weeks the open source will be out. We'll have beaten it to death. We'll know the answer if they benchmaxed. So we're going to find out. I think it's unlikely that it's benchmaxed to the point where every company in America right now should be, in the world right now should be saying we need a crash program with our best possible advisor to decide: are we going to do our own model on our own on-prem hardware, or are we going to use Anthropic or OpenAI or Google and just trust that API? But we need to decide whether tuning and training on our own proprietary data gives us a long-term competitive advantage. And so there's going to be a desperate shortage of good advice on this. Vendors and McKinsey consultants, you got to grab those resources quickly. Exo consultants, make seed-stage investments, get your network together, find out who can answer that question for you internally on your business and your use case quickly, and then commit to the path. And you know, you can do something internally and still use the APIs, but if you don't start down the path of evaluating Kimmy K3 on your own, you can't really come back to it later. So I think everybody's got to just get going on this question. We'll know in a couple weeks though whether it was benchmaxed to hell or not. But I think it's very, very likely that the open source path is a viable path for every US and world company and government. Now,

E

Emad Mostaque2:02:07

Can I just add to that real quick? Yes, of course. Very simple suggestion for every company. Implement two installations: Kimmy K3 and Inkling. Fine-tune your own internal data because that learning loop is going to be the proprietary gold that you don't want to lose. And start there.

P

Peter Diamandis2:02:27

Alex, why don't you close us out here? You've sort of answered number six already, but perhaps you could expand on it.

A

Alex Weezer Gross2:02:32

Yeah, I'll say something new. So question six asks, should the US move to block loading the weights of the next Kimmy release onto Hugging Face? I'll give a conditional answer. I think that if some party, presumably in the US, can prove to a cognizant court that the next Kimmy release, presumably a reference to this Kimmy release, was somehow obtained or derived illegally, maybe through copyright infringement or illegal distillation of traces or something like that, that would probably be grounds for blocking its release in the US. But if no one can prove that Kimmy's parent, Moonshot, did anything otherwise wrong in creating it, no, I don't think the US should be blocking its release in the process. I think if anything, quite the opposite. I think every US frontier lab should be closely scrutinizing it and learning whatever they can so that we can leapfrog it. And I would like to see far more outward pressure from US labs creating the best in world open-weight and open-source models so that it's not the CCP with their new Belt and Road for AI initiative blanketing the world, some would even say dumping superintelligence on the rest of the world or the so-called global south. It should be the US, the arsenal of freedom, that's also the arsenal of superintelligence, showering the rest of the world with open-weight and open-source superintelligence, not China.

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Peter Diamandis2:04:04

Showering the rest of the world. I love that. And remember, we're moving towards intelligence too cheap to meter, but a million times more available and more powerful than ever before. Everybody listening, I'm grateful on behalf of the Moonshot Mates here for your time. If you haven't subscribed, please do. We're going to be putting this out more and more often as we're starting to see the release dates move from months and weeks to days. And there's no time to sleep during the singularity. Gentlemen, what's in store for the week ahead? Emad, I'll go to you next. Yeah, Emad, what's news in your life?

E

Emad Mostaque2:04:42

Yeah, just getting a whole bunch of research papers ready to release. So finally, it's going to be exciting.

P

Peter Diamandis2:04:52

Incredible. Selma, please.

S

Selma2:04:55

Tuesday I have my next Meaning of Life session, 7:00 PM Eastern, for those that are interested.

P

Peter Diamandis2:05:00

Where do they go to find out?

S

Selma2:05:01

We'll have the link below, but it's openexoexo.com.

P

Peter Diamandis2:05:07

So anytime I'm doing, if you've not participated in one of Selma's Meaning of Life sessions, they are extraordinary. They will take you beyond the AI into the realm of philosophy and theology. Alex, are you coming up? What's going on with you?

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Alex Weezer Gross2:05:24

I'm so focused at this point on literally solving everything. I'll say large swaths of the sciences at this point, I'm convinced, are so thoroughly cooked. More to come on that subject. Peter, you and I wrote Solve Everything about it, but now it's actually coming true.

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Peter Diamandis2:05:41

I'm excited. You're going to be doing an AMA with my Abundance community coming up. That's going to be a fun deep dive. And of course, we're going to have you during the Moonshots gathering in September 25th, doing an in fact all of us will be here. Emad, you're joining us in LA in September. Yeah, it's going to be fun to have all of us together again for the full day. Dave, you know, this has got to be the most exciting time to be in Link Studios.

D

Dave Blondon2:06:07

Oh my god. Yeah. I think that discussion we had of quantization on this podcast that Emad kicked off, I think that now vaulted to my new best piece of media ever recorded, passing Leopold to Ashen Brunner. I got to go back and listen to that again in slow-mo. And also, you know, we had Vlad Bullovich from MIT Nano in this week. He's going to advise and help us on our new startup working on photonic computing. And he gave us a whole roadmap of people I need to meet next week. So we were looking to add two MIT people with our Princeton team to work on just the photonics, quantized photonics side of the equation. So I'll be working on that next week. But I think I can take that video we shot earlier and use it as a recruiting tool. It was just so freaking brilliant. You guys are incredible.

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Peter Diamandis2:06:55

I love you guys so much. What a great week. Awesome conversation. We'll see what breaks tomorrow. Yeah. Over the weekend. Emergency pod. We need emergency pods every day by January. All right, be well everybody. Thank you for tuning in to Moonshot, your front row seat to the Singularity. Take care, guys.

A

Alex Weezer Gross2:07:14

Peter, awesome job as always. Thanks, Peter.

Urgent Update- AI Sputnik Moment: Kimi K3 Released w/ Emad Mostaque | Ep. 272

About Emad Mostaque