setting new records. Open AAI uh hits historic growth to 100 billion in revenue. >> I think it’s entirely possible that OpenAI could hit 100 billion AR in a couple of years. I I think the easiest path is >> Open AI. Remember, of course, one of the most important companies in the world that could give it a market cap of $1 trillion. >> But of course, this is uh an ongoing story and there are still a lot of uncertainties as well in OpenAI’s future. The big question is whether the S&P 500 is overvalued and whether the MAG7 can continue to sort of command that level of of valuation because they’re driving much of [music] the economy and much of the gains. AI is going to be huge no matter what. That’s there’s no doubt about that. But is that is that scarcity sustainable [music] or is there are there going to be many competitors and a race to the bottom and and margins will come down? With 800 million subscribers already, half this comes from subscription revenue. That’s more or less in the bag. This is really dwarfing all history. >> Now that’s a moonshot, ladies and gentlemen.
[00:01:03] >> Hey, so guys, I’m still getting up at like 3:30 in the morning coming back from Riad. How are you guys doing? >> I’m actually okay. I I’ve get back and I I I learned a trick from uh um from Rome and Raymond Macaulay and they said take a double dose of melatonin and um >> and in a couple of days you’re good. I’ve actually been surprisingly okay. >> I I actually like getting up at 3:30. It’s like I’ve got like 4 hours before anybody else wakes up [laughter] and it’s like amazing. Dave, how about you, buddy? >> No, I’m I’m back on schedule. Fantastic. >> I don’t think I ever got acclimated to Saudi actually. I don’t think I slept more than four hours straight. >> What an amazing trip it was. I mean, just to recount one second, I mean, spending time with Eric Schmidt and Fay uh on stage was awesome. Uh, hanging out with Ruth Parat, the the president of of Google of Alphabet. I mean, what an
[00:02:01] amazing woman she is. Any favorite memories from you guys? >> I have a selfie with Ray Dalio and I spent an evening late with Balaji talking about, you know, US, China, etc., etc. Oh my god, it was I I had to I had to duck out. I mean, so here we we had this uh this dinner uh in Riad that we put together uh basically with myself inviting and Dave and John from Rep. >> Uh and we had Kathy Wood and uh and uh and Bology debating China versus US. And I was like, “Oh, this is going to be a long conversation.” Bye can talk. Oh boy, can he ever talk. Yeah. [laughter] He’s got some great framings though, right? He talks about the left versus right in in the US as scribes versus vibes. >> Yeah. >> So the left is scribes and they’re like crime is down by 50%. >> And the light the right is vibes. They’re like, well, it doesn’t feel good.
[00:03:01] >> Really great framing. >> Having breakfast with Liboutan was awesome. Uh the miss the biggest miss of the week. >> Uh I know, but we’ll get him on the pod. Uh he said he wants he wants to join in the pod. We’ll talk about his time at the White House and his skyrocketing shares at Intel. I mean it’s exciting. Uh any other favorite memories? >> Uh Philip Johnston was doing it. He invited me to the SpaceX launch. I have had a wedding to go to last night which was also a lot of fun. But I would have been able to go down and see the see the launch of >> the first H100 in orbit. [clears throat] >> H100 first chip in orbit. >> Yeah. That’s uh you know not a huge amount of compute but certainly a bellweather for for humankind. if we go down the Dyson sphere path. So, that was that was really fun. He’s a he’s a sharp dude. >> Yeah. And uh for me, hanging out with Bill Aman was fun. He’s getting involved in some of the stuff that we’re doing. And uh Bob Mumgard, the uh the CEO of Commonwealth Fusion was at our dinner. So, it was great. >> Had a great time with Bob actually. He
[00:04:01] he’s deep, you know, he’s an MIT PhD in nuclear stuff. So, he uh >> he knows all the details of of sustainable fusion. There was a lot about it that I didn’t actually realize. That was that was >> there was one thing that he said that blew my mind cuz I asked him when do we have a commercially available reactor and he said it was looking like 2032. >> And I’m like that’s and I’m like how much would it generate? He’s like about 400 megawatt. I mean if we have fusion working fusion in 7 years it’s game over, right? >> Yeah. I mean I asked some of the fusion guys at Enterprise Visionering what about Helion? Right. This is the Sam Almanbacked company has a contract with Microsoft and they’re like they are so secretive. We have no idea what they’re doing and what their schedule is. But See, one of my favorite moments was our last night going out to the farm. Remember that? >> Oh, that was that was so great. We went for a mud list with uh with 20 kind of fairly senior Saudi folks. Yeah, it was >> I had I had coffee with um
[00:05:01] >> Let me just let me finish on Let me finish on that one. We had uh uh one of our uh our superuh subscribers and super fans uh in in Saudi has this beautiful farm right near uh MBS’s uh you know private homes and we come out there and he’s like he’s set up in this mulus for it was you me uh Eric Pulier uh Emod and Max Max song and we did a sort of a private moonshot conversation Q&A with these 20 senior uh you know Saudis over their past ministers of education and commerce and finance all all in the circle. Yeah, it was awesome. >> This is a it turns out to be a very old tradition. I remember at the UAE they used to run these and it there was the the the leader would host and anybody anybody could apply to go to this and talk directly with the leader of the
[00:06:00] country. It was kind of incredible. Very >> I loved what he pulled out. I loved when he pulled out the microphone [laughter] and he had the speakers and we were we were on stage doing Q&A, you know. It was it was great. >> I was screaming for a second. He wanted to do karaoke and I was like, “Oh.” [laughter] Um >> speaking of I thought the uh I thought the Sage uh Melus was uh the head of um president of Bermuda >> was there. I’m forgetting his name, but he was awesome. He’s an IT background, technology background guy as it turns out. So he definitely wants and he he was taking credit for being the launch point of Bitcoin. So he wanted to to eagerly make Bermuda the launch point of um of Sage, you know, of governance. >> Yeah. We had a we unveiled a top secret project that Emmad and See and Dave and I uh have been working on called the sovereign AI governance engine or SAGE >> that would allow any country in the
[00:07:00] world to be able to generate policy as these disruptive futures are coming. So that was awesome. But you guys want to jump into the episode? >> Wait, hold on. I want I just want one bit quick of feedback. So I’m I I had a coffee with Abdullah the next day. Um [snorts] Abdullah >> no Abdullah Abdullah whoost >> yeah and he said um he got feedback from the group that was what was one of the most powerful evenings they’d ever had in their lives. So that was really incredibly generous of him. >> That’s that’s awesome. Yeah. And uh and I met with Abdul Swaha who is the minister of ICT in Saudi. He’s basically the minister of AI. I said Abdullah you need to have a new title. we’re going to call you the minister of exponential technologies, much cooler than ICT. And so he’s going to be on our podcast. He basically is the lead in Saudi across all of the uh the key technologies, the commitments they’re making to AI. It’s it’s super fun. But I think we should
[00:08:01] get on with the episode. How do you guys feel about that? >> Sounds good. >> I think we should just so much so much in here. We got to >> Oh my god. I’m a little nervous because we’re trying to cram a lot into a short space of time. >> Well, hey man, it’s exponential time. Like Alex is always saying, we’re going to have to use sleep during the singularity. AWG, good to see you, buddy. Sorry we missed you in Saudi. >> Yeah, likewise. >> But uh let’s >> Every time I was having a technology conversation, Alex, I was like, “Wow, I wonder what Alex’s take on this is.” >> Yeah, no [laughter] kidding. It’s like withdrawal. Well, everybody, welcome to Moonshots, another episode of WTF just happened in technology. This is your your weekly dose of optimism and catching up with this hyperexponential world. Uh, and let’s jump in. Uh, first major chapter here is the speed of change. And here we go. So, setting new records, OpenAI uh hits historic growth to 100
[00:09:02] billion in revenue. So, here’s the chart. It’s reaching 100 billion revenue in 2 and 1/2 years compared to Nvidia which took 8 years. Uh Amazon took seven years. Google took 10 years. So it’s just speeding up. And Alex, uh what’s your prediction of when we’re going to hit 100 billion with the next company? I >> I think it’s entirely possible that OpenAI could hit 100 billion AR in a couple of years. I I think the easiest path is probably just taking agents and running them continuously 24/7. As long as they’re generating sufficient economic value, I I think it’s not that difficult to imagine OpenAI tripling revenue year-over-year for the next two 2 and 1/2 years and getting there in 2027. The the key again is just taking knowledge work and taking service economy and condensing distilling that down to agents running 24/7.
[00:10:00] >> Incredible. They’re only uh they’re only forecasting 2 and a halfx growth year-over-year. It’s a very achievable target cuz I looked at this originally and I said, “Wow, that’s a stretch.” But then you look under the covers with 800 million subscribers already. Half this comes from subscription revenue. That’s more or less in the bag. Then the other half is much more interesting. It’s where the AI gets good at commerce and recommending products and them figuring out how to monetize that. And that’s the part that attacks Google. So that part is a little more up in the air, but >> and Amazon for sure. >> For sure. But I I can’t see like it feels like it’s definitely going to happen. The only question is whether OpenAI competes effectively with Amazon or Google or Google just take it and Amazon take it back. But it’s going to happen either way. So it’s it seems like a very reasonable forecast. You know, also looking at this chart, you know, OpenAI’s number there is a projection, but Nvidia’s is in the bag. That’s a that’s a real number for Nvidia. And you know the chart starts at 10 billion but if you started at 20 billion you know
[00:11:00] Nvidia would look just like open AAI on this. So so that part is is already very very real. >> So yeah there and you know look at all the history of all other curves including the greats like Google. This is this is really dwarfing all history. Every week my team and I study the top 10 technology meta trends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI and quantum computing to transport, energy, longevity, and more. There’s no fluff, only the most important stuff that matters that impacts our lives, our companies, and our careers. If you want me to share these meta trends with you, I write a newsletter twice a week, sending it out as a short two-minute read via email. And if you want to discover the most important meta trends 10 years before anyone else, this report’s for you. Readers include founders and CEOs from the world’s most disruptive [music] companies and entrepreneurs building the world’s most disruptive tech. It’s not for you. If you don’t want to be informed about what’s coming, why it matters, and how you can benefit from it. To subscribe for free, go to dmmandis.com/tatrends
[00:12:02] to gain access to the trends 10 years before anyone else. All right, now back to this episode. You know, I read some of the user comments, some of the subscriber comments, and one of them said, “Every time Peter says incredible, should take a drink. It’s a new drinking game.” So, I’m gonna I’m gonna cut back on my Incredibles. But hey, this is incredible. All right, [laughter] let’s uh let’s move on. Uh I found this one fascinating. This is the US leading the world in data centers. So, uh in I would say incredible. Uh we have 5,426 data centers compared to the rest of the world. I mean look at that. Germany is at 529. China’s at 449. We have more data centers than the rest of the world combined. Uh >> really tried to research this Alex. I want to get your take on this Alex because it it it definitely is juxtaposed with you know China having massively more power and and massively more core manufacturing ability. This one really surprised me but I couldn’t
[00:13:00] find online any detail behind it. So what’s the understory here? >> Yeah. Now remember the internet was born here. The US has lots of available land. Uh hyperscalers are largely based here. We have access to capital. I I don’t think it’s that surprising that number of data centers. Remember this is not the number of AI data centers or the number of NeoCloud or Stargate type data centers. This is just total number of data centers would have a modality in the US. Is there a AI pedlops version of it which would be more more meaningful than just raw count of data centers? >> Almost certainly. Maybe we should cover that in the next episode. >> Yeah, I couldn’t find it. But >> our next story here is Nvidia [clears throat] reaches $5 trillion market cap. Holy cow. [laughter and gasps] Uh it’s up 1500% in the last five years. The market cap is greater than the GDP of every country in the world except US and China. Uh yeah, that that metric uh is frustrating because you’re talking about the asset value of Nvidia, the value of the
[00:14:01] company if you were to acquire it is 5 trillion. You should be comparing that to the asset value of countries, not to the GDP of countries, which is already mind-blowing enough. I I checked it out. So that makes Nvidia worth the same amount as Saudi Arabia, where we just were. What a coincidence. It’s actually a little more than Switzerland. Like in terms of if you were to try to buy Nvidia with your own money or buy Saudi Arabia if they would sell it, [laughter] the cost of buying the entire country, all the land, all the assets, all the buildings would be the same as buying Nvidia. And that that is staggering enough. You we should be comparing apples to apples because it’s already mind-blowing. It’s it’s it’s right between Switzerland and Saudi Arabia. So if you want to buy Switzerland, you or buy Saudi Arabia or buy Nvidia, those are your >> So this we’re going from nation states to corporate states in in a way that’s that’s you know uh incredible. >> A [laughter] few a few a few years ago uh we looked at uh getting a bunch of investors together and actually buying a small country on exactly that basis. In
[00:15:01] that case it was about 200 million and but then you get a seat at the UN and you have all this access and you’re part of the WTO and you could really do some interesting things. So that that was an >> I looked for a historical record and what I found was General Motors in 1955 was the first company to hit $10 billion. It was during the post-war auto boom and $10 billion corrected for inflation today is 121 billion. So we’re talking about a completely different category, right? 50 times bigger than General Motors at its peak. >> Well, another I’ll take the the other side of that if I may. I mean history tells us at any given time the the market values what’s both scarce and needed. So we’ve seen uh multiple East India companies. We’ve seen various scarcities including oil pop up over the the centuries. I would argue that this is actually just a a market signal that right now compute is both scarce and
[00:16:00] needed. The way the game of capitalism works is this value wants to diffuse over many companies and and probably many countries over time and and that diffusion is going to be a net wealth creator. >> That’s very true. I mean there going to be so many additional chip manufacturers. We’ll talk about some of them here on the pod today. >> I found this chart particularly uh exciting which is the decoupling uh job openings versus S&P 500. Those of you looking on YouTube or listening, uh, here’s the chart. We see the S&P 500 and total job openings basically mirroring themselves from 2000 through 2023. I mean, exact parallel curves, right? As job openings, uh, total job openings increase, uh, S&P 500 increases or the other way around. And then in late 2023, we see this departure and the S&P 500 takes off and job openings drop from 11 million openings to 7 million openings.
[00:17:02] And so the question is, what happens in late 2023? Well, if you look at the data, it says chat GPT gets launched. Let’s dive into this one. Dave, you want to jump in? >> Yeah. Well, so I love the story lines that’ll end up in the history books as opposed to the news dour, you know, Taylor Swift type stuff. This is this is one where very likely that future history books taught in schools, if there are schools, will point to this moment in time and say, “What happened here?” Because that trend is going to continue. Now, the deniers are going to look at this chart and they’re going to say, “Well, look, that’s just COVID, you know, happening and then a big rebound from COVID and now we’re back to kind of normal job opening levels.” You know, look at kind of history here. But so what happens next is this is either a historic moment if the trends continue which I think they will or this is uh you know just sort of like a blip COVID recovery thing. But I I think you know Alex will look at this and say yeah this is this is the beginning of the inevitable.
[00:18:00] >> Alex divide by divide by zero. Actually, I I I will actually say much as I’d love to tell a just so story that this marks the beginning of the decoupling of labor and capital, I I think this is actually just garden variety uh changes in in Federal Reserve interest rate hikes in in late 2022 as interest rates started to come back down, the market goes up and as COVID starts to retreat, job openings and job displacements also start to return to 2021 levels. So again, I would love to tell a just a story. This is the the beginning of decoupling of labor and capital, but I think that this might be >> I’ll give you the opposite. We’ll know in hindsight obviously, but uh but the opposite. If you look at college graduates coming out right now, they’re massively sorted into AI people getting incredible offers and everybody else not finding a job. Uh which is very unusual with the S&P being at all-time highs like this. So that would be the counter counterargument that well no if you’re if you’re 21 22 trying to find a job right now you’re really feeling something unusual and and we’ll see it
[00:19:02] later in the deck too the layoffs at Amazon you know while record earnings um so there’s some other data points that would indicate yeah >> I I’m I’m on the plus side here I usually think this but I think this is a major mark here humans have now become optional inputs into this so into the into the economy that’s a big Yeah, I I tweeted out that uh a AI is is no longer an industry or sector. It is the economy. And Elon responded saying AI and robots are the economy and which is which is true. You know, one of the indications the S&P 500 going up is an indication of market confidence, right? Where there’s optimism about the future and people are investing and I’ve got to believe that’s that’s fundamentally true. people are excited about the Mag 7 or 8 or whatever they’re up to these days uh basically taking off and and driving the their valuations through the
[00:20:00] roof. >> Just just to flip that side though, let’s note that that most of the gains are just the AI companies, right? And the tech companies. >> Yeah. >> The rest of the market is really really not in great shape. >> Yeah. So a lot of a lot of the job cutting is actually in anticipation of AI coming. So it’s not it’s not full automation yet. But if you look at Amazon as a bellweather for that, Amazon’s right in the middle of the AI fray. They have huge amounts of labor in their delivery business, yet they have this massive data center and AI business. So that’ll be the bell weather on whether the true automation kicks in. And I think it’s very real if you look at their the numbers coming up in the slides here. I mean, the big question is whether the S&P 500 is overvalued and whether the MAG7 can continue to sort of command that level of of valuation because they’re driving much of the economy and much of the gains. Dave, what do you think? >> Well, you know, Leopold actually, you know, he went long Intel and long long um Broadcom, but he shorted the semiconductor index as a whole. And I
[00:21:02] didn’t dig in on that until yesterday, but that’s mo that’s 20% of that is in Nvidia that he shorted when when you short the whole sector. So that would be the argument that look if the whole thing is going to is going to collapse it’s because Nvidia in particular is valued like you know Switzerland more than more than Switzerland. [laughter] Um and is that rational? Uh, and and I think Alex is dead right. You know, right now Nvidia is right at the crosshairs of the true scarcity. AI is going to be huge no matter what. That’s there’s no doubt about that. But is that is that scarcity sustainable or is there are there going to be many competitors and a race to the bottom? >> It’s going to diffuse, right? We’re going to go it’s going to be Broadcom, it’s going to be AMD, it’s going to be Qualcomm, and it’s going to be a whole bunch of uh chip manufacturers. So it will diffuse but we’ll see sort of the peaks perhaps of Nvidia. Well, really specifically too, Nvidia is, you know, Melanox is interconnect is a million
[00:22:00] coherent GPUs operating on one big problem, but most of the industry is inference time. Inference time doesn’t need any of that. >> And so, you know, we’ll get we’ll get to that later actually, but that’s the >> I found this clip by Jeffrey Hinton, right? Jeff uh Nobel Prize winner Jeffrey Hinton was on stage in my abundance summit. I’ve invited him back to join us on a podcast. Let’s see if he takes it up. And all of a sudden, you know, he has been so concerned about digital super intelligence and he put forward an optimistic view of AI. Let’s play this clip uh from Dr. Hinton and then let’s chat about it. >> More optimistic than I was a few weeks ago. >> Really? >> Yes. And it’s because I think there is a way that we can coexist with things that are smarter and more powerful than ourselves that we built. Because we’re building them as well as making them very intelligent,
[00:23:00] we can try and build in something like a maternal instinct. The mother can’t bear the baby crying. The mother really, really, really wants that baby to succeed and will do more or less anything she can to make sure her baby succeeds. We want AI to be like that. >> All right, Salem. Uh, a mothering [clears throat] in a mothering instinct in our in our super intelligence. I mean, I buy it. I’d love that. I I want this, you know, this digital god to be sort of loving and warm and supportive and uplifting of all of humanity. How do you feel? >> You know what what you often find when something brand new comes along, the first instinct is to freak out, right? Um, and remember, you identified this in your abundance book, Peter. We have this amydala that goes nuts because it’s for on a survival bias, we are geared for 4 billion years to scan for danger and then run, right? And when we see something new like an autonomous car, the first reaction is, “Oh my god, that my car might kill somebody. Let’s ban the car until we figure it out.” >> And Brad Templeton used to joke, we we
[00:24:00] don’t want to be killed by robots. We’d much rather be killed by drunk people, which is what’s happening today. And so, you have to get over that curve and let the evidentiary basis of the the elegance of an autonomous car come to you. And often also people that are very focused on technology, folks like um a certain that have spent most of their lives focusing on the technology and they ignore their emotional side, right? And little by little the emotional side comes into play, freaks out initially and then little by little warms up to the task because people forget the unbelievable benefits that AI is delivering and will deliver. That’s the part that they only see the dark side and we don’t see the unbelievable benefits. So I’m really thrilled to see this. I think we’re going to see a lot more of this as time goes by. I don’t really buy the maternal instinct. AI is a maternal thing. It seems a little kind of really off to me. It’s such a visceral subjective experience to parenting or whatever that I’m not sure how that >> we have to give. We’ll see. >> We have to give the AI oxytocin. Alex, what do you make of this? >> Yeah, I I I think it’s difficult to to
[00:25:00] buy. seems to be an argument premised on what in the AI alignment research community is called the orthogonality thesis that it’s possible to have intelligent agents of arbitrarily high levels of capability that nonetheless can be directed to pursue any goal in in this case it it seems like Jeff is is basically rearticulating the orthogonality thesis with perhaps a a veneer of digital oxytocin as you said Peter I think I I I think that’s unlikely and probably not that robust a means of in uh alignment for super intelligence. I I think I if if the goal is to have a more uh robust guarantee of intelligence approaches that acknowledge instrumental convergence, instrumental convergence being the idea that no matter what your long-term goal is, you tend to have certain convergent common short-term goals. I I think instrumental convergent type approaches are are more likely to to guarantee or provide robust
[00:26:00] guarantees of friendliness. So, uh, James Miller wrote, I I think an excellent essay called Reasons to Preserve Humanity on Less Wrong that enumerates couple dozen different reasons for why super intelligence should play nicely with humanity out of self-interest, not out of some sort of oxytocin induced surgically added reason. Uh, that that sort of artificial thing. >> All right. Well, >> I want to say one more thing about Jeffrey just really quick. He [clears throat] did a podcast with John Stewart a few weeks ago and laying out and John Stewart kind of said, “I’m a newbie. Take me through deep learning and the uh the the whole framing of neural nets.” And it was an absolutely brilliant episode. If you want to understand a little bit about deep learning, back propagation, etc., he did an amazing job at laying that out. >> All right, I’ll take a look at that. Here’s our next story. Deep fake of Jensen Wong draws more views than the real one. I found this absolutely
[00:27:00] fascinating and I want to share this video and what we’re going to see here is there’s an official Nvidia channel which is showing Jensen’s presentation. It peaked at 12,000 views and then it was a fake live stream that peaked at 95,000 views. Let’s take a look at the fake uh live stream. Cutting edge hardware with decentralized finance. It’s about proving that crypto works reliably globally and for everyone. Couple things to keep in mind. Only use the QR code you see right here on the GTC broadcast. Don’t trust any links floating around online. They’re not us. [laughter] >> I love that the the fake broadcast saying [laughter] don’t trust anything else. >> Uh that’s hilarious. Um [snorts] you know the numbers are pretty staggering. It’s $1.5 billion dollars lost globally for deep fake related fraud um since 2019. uh and only 24.5% according to the numbers here of people
[00:28:01] can actually spot deep fake quality and AI detectors fail up to 50% of the time. So this is going to be a thing. Uh this >> I think uh reality may have just lost the algorithm war. >> Yeah, I think in this case if if you look closely at the video the the lip syncing was poor. I I I think in the short term detecting >> You’re part of the 24% that can notice this. Okay, Alex, you win. >> Definitely notice the the poor lip syncing. Um I [laughter] I I think like in the short term, detecting counterfeit live streams in real time doesn’t seem like a terribly deep technical challenge. In the long term, we’re going to have more solutions like ubiquitous watermarking, perhaps cryptographic guarantees of reality, perhaps. I I don’t think in the long term this is a a deal killer for us drowning in AI generated slop counterfeit live streams. I think this is very tractable. >> Yeah, within the US I agree. I think if you look globally it’s a little more of
[00:29:01] a concern. I there’s a real possibility that um regimes lock themselves in. uh you know control of media content is going to be so easy with AI assistance and then convincing your population of virtually anything gets trivially cheap and easy. So I I would be more concerned about you know in some nation where they’re not as aware of AI watermarking or you know whatever uh they’re they’re seeing things >> our nation isn’t aware of that and Alex you made a point uh you know when we were discussing a year ago that AI generated speech is far more compelling than human speech. All right. Uh let’s move on to the AI wars. This is XAI versus open AI versus Google. We’re just writing off anthropic just like >> Well, no. I mean, they’re in there, but you know, these are our major players today. We’ll we’ll talk a little bit about >> Dario would really object to that. Okay. >> Oh, listen and get [laughter] No, I love Anthropic and I
[00:30:01] want him on the pod for sure. >> All right, but let’s let’s jump in here. So, I’m going to rant on this one. So, XAI launches Graipedia. Um, I had a friend of mine, remember Justine from uh, Singularity University? Uh, Seline. >> Sure. >> Yeah. So, she sends me this this text. She goes, cuz she heard our pod, I was arguing or, you know, lamenting Wikipedia’s inability to correct all the wrong things in my And I actually hired consultants to fix Wikipedia for me because I’d make the changes and they’d be changed back. It’s like, this is ridiculous. So, uh, she says, “Hey, Graipedia is out with your with your Graipedia entry. What do you think about it?” And I look at it and it’s amazing, right? It covers everything in detail, super well referenced. So, Graipedia is being written by Grock. It’s writing, updating, fact-checking it on a real time basis. Um, and uh, uh, they have 900,000 articles compared to Wikipedia’s
[00:31:02] 8 million articles. My particular entry here uh was 8,500 words on Groipedia versus 4,800 on on Wikipedia, but it was so well organized and I just absolutely loved it. Any comments? >> I’ll I’ll throw in a comment. I I want to reason by analogy that there’s a a process that those not steeped perhaps in semiconductor manufacturing may not be familiar with. It’s called zone melting. And it’s a process for purifying not knowledge in this case but purifying semiconductors. And the idea is you take a rod and you pass it through a heater and because there are more ways for impurities to exist in the solid state in the melted state rather than in the solid state the impurities migrate out of the solid into the liquid state and you do this over and over again you get a pure and pure semiconductor. We don’t have a science right now for knowledge purification, but one could imagine somehow near
[00:32:02] future we have a science for it. And we decide there are more ways for correct knowledge to be self-consistent than incorrect knowledge. And I I think we’re starting to see the beginnings of almost a knowledge equivalent of zone melting where you take the raw slop, human slop of the internet. You pass it through multiple passes of AI gen synthesis, creating what aspirationally would be more correct versions of the ground truth. do this over and over again and maybe aspirationally because there are more ways for the truth to be self-consistent than the whatever the starting knowledge was maybe we arrive at some sort of ground truth through this result I don’t know but it would be interesting if that ended >> well that is Elon’s that’s Elon’s objective right basically trying to uh from first principles derive truth I I put a quote down here he says uh uh from Elon says a step towards XAI’s goal of
[00:33:02] understanding the universe which I >> I have two I have two comments. >> Um one is you know Peter you and I have talked for a long time and written in the book that that um staff on demand and a community doing work is essentially a proxy for AI. Yes. >> Right. Driving is a a great example but now we see it actually applied. If you take a Wikipedia article for a human editor to go through and track down all the links and ratify everything it’s just a pain in the ass and it’s not the strength of a human being. Whereas an AI can do this without even blinking. I think that now propagates to a level where Wikipedia with an AI interpretation per Alex’s metaphor, which I think is absolutely fantastic. Um, now gives us the ability to have closer and closer to pure truth. I never quite understood what Elon was talking about when he says maximizing or seeking maximizer. >> Um, but now I’m starting to get a sense of it and it’s absolutely brilliant. It’s fantastic if we can get it there because it can cross reference all the stories and cross check things in a way
[00:34:01] that no human being will take the time to do and it’ll do it much more accurately. >> Well, what Alex described is really really similar to the original Google page rank algorithm where you know just starting from nothing iterating between a reference link and a and a site and assigning credibility back and forth in this self- annealing process a simulated analing process and it worked. I mean they don’t need it anymore because they have so much data flowing in but but when they were just a little startup bootstrapping it worked really well. So >> this is also my comment. This is also my comment. I use page rank as an example when people ask what is AI etc. And I say look at look at page rank. It’s evolving a completely separate type of intelligence for crawling billions of pages making sense of it. That’s very orthogonal the way human intelligence works not replicative. So, I think AI tends to have this totally different type of intelligence of mass crunching data and finding signal from noise in a way that we’re not designed to do at all. >> Well, just uh thank you to Justina Xander for pointing this out to me. I’ll also mention real quick, I checked and
[00:35:02] turns out Wikipedia has a budget of 170 million a year. About 100 million of that is labor uh paying everybody to do this work. Some of it’s voluntary, a lot of it is not. All right, let’s move on. I >> just also just a shout out to Jimmy Wales for creating Wikipedia and managing for all these years. I mean, what an unbelievable gift to humanity. >> I mean, we we’re watching the transition from the encyclopedia of Branonica to Wikipedia to Graipedia. Uh, but it Gracipedia was lowhanging fruit. Any of the AI companies could have taken this on and I think it’s going to become pervasive. I know I’m I’m standing up a new website for diamandis.com and the very first thing I’m putting at the top is my graipedia link right you want to go deep there it is so uh true to AWG’s uh vision this is an important conversation and Alex I actually read this paper so this is a new AGI
[00:36:00] benchmark which gives chat GPT a 57% but I would prefer if you explained it cuz it’s Pretty amazing. And See, this one’s for you, buddy. Finally, we have a definition of what AGI is and how to measure it for the first time ever. This was a paper that was co-authored by Eric Schmidt as well. Uh, and it’s a pretty powerful concept. Alex, would you take us through it? >> Sure. So, there’s an enormous cottage industry of AI researchers trying to define what intelligence even is. I’ve been guilty of that in in past years as well. Uh my bias has always been to look for a universal elegant definition of what intelligence is that isn’t necessarily grounded in human behavior or human psychology. This paper and as Peter you mentioned we know a number of the co-authors on this paper. The the basic idea behind this paper is to do the exact opposite. Instead of trying to look for some human agnostic definition of intelligence so that we can build
[00:37:00] more of it the idea is instead to look at human psychology. So there is a a theory that’s popular in human psychology. It’s called the catel horn carol or CHC theory that decomposes human intelligence into 10 different factors like the ability to reason quantitatively or to do visual processing. So the the idea behind this this paper is to define a benchmark that’s directly inspired by the CHC theory to decompose intelligence of frontier models into 10 different categories with various subtasks associated with each category. And the main upshot of of benchmarking GPT4 and GPT5 auto critically not GPT5 pro according to my reading of the paper. The the main upshot is surprise intelligence is jagged. the frontier models are stronger at some skills, weaker at and other skills that whereas the the archetype uh the archetypical human would perhaps have a more uniform
[00:38:02] distribution of their skills across these 10 categories. But I I would add the important caveat again just based on my reading of the paper, they didn’t actually benchmark the the bleeding edge frontier models like GPT5 Pro. >> For those uh looking at this on YouTube, you’ll see these 10 different categories. These are humanlike skills, uh, knowledge, reading and writing, math, reasoning, working memory, memory storage, memory retrieval, visual, auditory speed, and they’re benchmarking, uh, GPT5 and GPT4 against those. Uh, but it’s a measurable benchmark, right? I mean, the other option is is the pornography definition. We’ll know AGI when we see it. Uh, Dave, what do you want to what do you want to add on this? I I’d love to get Alex’s take because I assume a 10 on each axis on this radar chart is human. So you’re you’re trying to match the outer ring here, but it’s really >> it’s all humans. I mean, no human is going to match 10 on this. Maybe >> quote unquote well educated adult.
[00:39:00] >> Okay. >> Yeah. Okay. Well, you know, it’s it’s going to be, you know, the difference between the best human and an average human is a rounding error in the grand scheme of AI. You know, it’s almost identical, actually. uh but you know it’s so asymmetrical and I I don’t understand the memory and storage access axis and the speed access you say the best AI is miles behind humans in speed and I don’t quite get that >> that was the part that struck me also speed seemed off >> so when you when you make a query you know to do something your AI goes off and thinks about it for a while before it comes back with an answer that is speed a human if I ask a question Alex will typically not go away for five minutes and think about it. He’ll give me at least his version of an answer right off the bat. Uh but memory I found incredibly, you know, perplexing because I thought these AIs have incredible memory. Alex, what’s your take on speed and memory? Yeah, based on my read, the
[00:40:01] memory [clears throat] storage access corresponded or the deficiencies thereof corresponded roughly to the fact that off-the-shelf vanilla language models and foundation models have a finite input context window. So if you ask them questions that reference older information, by default, unless there’s some sort of compression or memory compactification or rack type mechanism, they don’t have the ability to remember things that you told them a long time ago. But again, I I want to caveat this benchmark. I love benchmarks in general as I’ve mentioned previously on the pod, but these are off-the-shelf models without any agent bureaucracies on top of them, without prompt optimization, without even access to to bleeding edge reasoning efforts. This is just, if you read the paper, it’s just GPT5 auto. So I’m I’m wary to to to put my finger on certain deficiencies as being in any way indicative or instructive of the limitations of AI. >> Meaning these there are other models
[00:41:00] that would perform much better on these 10 these 10 parameters >> or light modifications of existing models that as with rag retrieval augmented generation make them superb at certain skills. So I I think that where this is useful in my mind is just having yet another benchmark for as a proxy. It’s a start an important start for measuring human capabilities against AI capabilities. But when I see 57%, you know, we’ve talked in in the past on the pod about in in the style of Ray Kerszsw while the moment you’ve passed 10% or maybe even less, you’re you’re basically halfway there in getting 57% on a general human psychological benchmark. That that indicates to me that probably with a little bit of um reinforcement learning, a little bit of bureaucracy, agents, framework, scaffolding, you probably get to 90% today. >> Amazing. Well, by the way everybody, just some uh forward-looking news. Uh Ray Kerszswall is going to be joining us on the pod next month.
[00:42:00] >> Talk about his predictions for 2026. Yeah, it’s going to be it’s going to be a lot of fun. I have my standard responses to this which is I think this is really great for approximating or getting to kind of the frontal cortex and neoortex activities but it doesn’t deal with emotional intelligence or spiritual intelligence or any of the other dimensions of intelligence that we typically attribute to human beings. So, >> but I thought about you, Seem. I thought about you specifically on this one because >> it’s it’s going to be a measurable benchmark that we can at least point at and we’re going to discuss whether we’re going to hit AGI according to OpenAI in late 26, 27 or 30. >> What I’m saying is I disagree with the premise because AGI for me would incorporate these other things. >> Okay. >> So, so if you’re measuring pure IQ test type stuff, fine. This this is a great benchmark and we can kind of I wonder if we’re going to have the first AI spiritual leader who proclaims a religion and lead. >> Oh, I think that’s very doable. You know, I remember once spending time in
[00:43:01] the in the Himalayas with some of these um gurus, right? And I sat with these with the orange robes and the long beards and I came out with the conclusion there’s about 10 or 15 questions like what is the meaning of life type of thing. If you have a pretty good answer for those 10 or 15 questions, you can become a guru. Um and that’s kind of an LLM. Uh that’s your neural network. So, It’s only going to be hard. I think it was very doable. >> By this time next year, there’s going to be an AI based religion that is going to scale at a hyper exponential. It’s going to be amazing. >> All right, big news this week. OpenAI restructures to become a public benefit for-profit corporation and a nonprofit. So, OpenAI will hold uh the OpenAI Foundation uh will hold $130 billion stake, 26% of the new company. And the OpenAI group is now what’s called a PBE, a public benefit corporation. Sele and I did that move with Singularity
[00:44:00] University, converting it from a nonprofit to a for-profit and spinning out a uh >> Exactly. This was a benefit corporation with a nonprofit alongside. >> And so, here’s the ownership point actually. So a BC Corp can do anything a CC corp can do. So you know go public, raise money, be profitable. >> This is a great point that you’re making Dave uh for the viewers from a from a taxation and legal perspective a BC Corp is exactly the same as a CC Corp. It just >> which is every other public company. Yeah. >> The detachment is that on a in a CC corp if the the board is obligated towards financial optimization and can be sued if they’re seen not to be doing that. Whereas in a BC Corp, the board is obligated towards whatever the mandate is of the BC Corp and can be sued for that in theory. >> I I love the I love the percentage ownership here. So, here we go. Microsoft owns 27%, the nonprofit owns 26% and the remaining uh is owned by OpenAI PBC at 47%. And this restructuring is going to allow OpenAI to go out and raise money. But
[00:45:02] here’s the rub. Here’s the rub. Uh Elon’s lawsuit against OpenAI remains active. Uh and he, you know, his bid to try and block the restructuring was denied in court. Uh but the case will proceed to trial uh in the spring of 2026 is what I read about. And the implications are interesting, right? So, number one, the court could order a recision that unwinds the OpenAI for-profit PBC structure uh and restore the nonprofit control. Number two, uh the key deals such as revenue sharing with Microsoft could be voided or renegotiated. And number three, there are potential damage fees and reduced fundraising flexibility for the PBC that could result. So that’s going to be interesting drama in uh uh a year from now. >> Yeah, Alex, you know, if you look at the valuation of the company, the market does not believe any of those problems
[00:46:00] will actually be material >> for sure. >> Um so it seems unlikely, but I think it is, you know, Yan’s got a very valid point in that, you know, that whole time you’re a nonprofit, you’re not paying any tax. And if you’re secretly building a massively profitable, you know, trillion dollar company while avoiding taxes, that’s a terrible precedent. You can’t do that. and and Elon even said it like if if that were legal, everybody would do that and start your company as a charity. Um so I think the courts will have to say, “Yeah, you can’t do that.” Um and the penalty be like a dollar or something just like they did with Microsoft antitrust. You’re like, “Okay, you’re guilty. You’re totally guilty. You’re fined a dollar.” Um so >> $1. Yeah. That was the whole Microsoft, you know, the the whole kill Netscape, destroy the entire Mark Andrees, you’re out of a job. Like what’s the cost? A dollar. >> Wow. The same thing happened, by the way, in the 50s when Good Goodier and GM banded together and bought all the train tracks in LA and ripped them out. Um, and privatized them and just ripped them out. In the court, there was an antitrust and they got find a dollar.
[00:47:02] >> Okay, >> I’d like to point out maybe quickly two two possible societal goods here. One is that this results in one of the world’s largest nonprofits being created that now has the backing of a Frontier Lab. and the the stated goal of the the new OpenAI nonprofit, one of their first goals is to spend $25 billion using AI to solve disease. And I I think that’s that’s a tremendous societal good. We’ve spoken here in the past about how AI has the potential to to solve disease and biology in the next 5 years. I think this is another arrow in the quiver of making that happen. Second, societal good. One of the things I I worry about is what happens if a private frontier lab develops incredible super intelligence and decouples from the human economy. I I think putting open AAI on a trajectory where it can reasonably be expected to go public sometime in the next 2 to 3 years. I I think an IPO by OpenAI and other frontier labs and and putting the equity
[00:48:00] in in the hands of retail investors and index funds is is almost certainly a net societal good because it keeps the economic interests of large chunks of humanity aligned with these frontier labs and vice versa. Well, correlary to all that too, Alex, I think that, you know, everyone’s like, “Hey, Brendan Foody Mccor, he’s a billionaire at age 23.” He spent immense amount of time inside OpenAI’s building. And we saw this on there in the lobby last time we were there. If if you think what’s my life mission, am I starting a company? Am I, you know, changing the world? Am I solving all disease? Regardless of what your life mission is, think about the impact of $25 billion of charitable money just to solve disease. What What about the other hundred billion dollars? where’s that going to go? So, if you’re involved in this in any way and you don’t have a strategy for how you interact with open AI, how am I in that building? How am I relevant? How am I going to be when they start turning to commercialization and goods through the AI engine? How do I interconnect with that? You know, I ask all these entrepreneurs, what’s your open AI
[00:49:01] strategy? And a lot of them have no answer. >> But you [laughter] think about the scale just of what Alex just said. you know, >> yeah, this will be this will be this is the largest nonprofit in terms of capital base and it will be even bigger. It’ll reach a half a trillion dollars. And Dave, you remember you and I met with I’m not going to say who it is cuz I don’t think it’s been officially released. The individual who is a co-founder there that will likely run this OpenAI Foundation. We’re talking about potentially spinning up some X- prizes uh as a means. He was very knowledgeable about these ideas of incentive competitions to sort of leverage capital 10x and we just learned this year that the numbers from X-P prize is we leverage every dollar in the purse by 60fold. So imagine if um you know uh a hundred hundred billion becomes $6 trillion of leverage. What a what a fun time ahead. >> Yeah. Well, think about the scale too. which is exactly a great point that you
[00:50:01] know a normal big big X-P prize is $und00 million prize you know and you here you’re talking about $130 billion which you know if the stock goes up post IPO could be $260 billion so all they have to do is you know sell some shares and fund $und00 million prize could do that every day of the of the week >> I dream about >> I dream about having 101 $1 billion prizes for the 10 biggest problems it would steer where students spend their time we’re we’re founding partners focus on building companies. I mean it would be sort of a a flame to the entrepreneurial moths out there. >> Can I can I take the other side of this just for a second? >> Sure. Sure. virtue signaling, greenwashing. They’re putting all this money over there and then going full speed towards the IPO and hoping that the uh the good that they can do will will kind of balance the crazy path to greed. >> Do not notice the man behind the screen.
[00:51:00] And speaking about greenwashing, here’s here’s our next story with Sam Alman on turned green here. a a little bit of uh Shrek in his in his DNA. And the title here is OpenAI plans a $1 trillion IPO and to spend a trillion dollars a year in AI infrastructure. I love this. You know, we’ve said this before, a trillion dollars here, a trillion dollars there. Uh it’s becoming a word far too popular these days. I mean, the speed is incredible. So, open >> use your word, Peter. It’s incredible. >> It is incredible. You also got to hand it you got to hand it to Sam for the unbelievable sheer gumption for just going for it. >> Yes. >> Wow. No. Amazing. >> Just incredible. >> Well, hey, let me let me put some Let me put some numbers behind that. So So here he is. I’m going to spend a trillion dollars a year. I do a trillion dollar IPO and then I’m going to spend a trillion dollars a year on data centers. Your actual revenue today, dude, is 13 billion. Now you’re saying you’re going to get to hundred billion. But the equivalent would be is if you have a household with $100,000 of income and
[00:52:02] your husband or wife comes home and says, “Honey, we should spend 10 million a year on [laughter] houses and stuff.” That’s the equivalent metric. Okay. So, just to put it in context, that’s that’s the gumption like you said behind this claim. But hey, he’s done everything he said so far, so it’s plausible. >> Yeah. So, there >> I’ll try I’ll try that with Lily and see how far I get. [laughter] Well, you did that when you mortgaged your house to buy Bitcoin, which in retrospect turned out to be a good idea. >> We didn’t put all of it in, unfortunately. But still, >> you still mortgage it again. [laughter] Alex, >> I think it’s actually like a a pretty tiny number. The global GDP is is upwards of a 100red trillion. So, just saying we’re we’re going to spend, you know, 1% of of global GDP on AI infrastructure. >> Yeah. But one guy, Alex, [laughter] he’s one company. >> One company, right? So, so, so if you have like five frontier labs each doing that, that that’s still like 5% of global GDP. I I think this is a drop in
[00:53:00] the bucket and that’s before AI starts to radically grow the global economy. That this feels on the low end to me. And we saw this last time compared to the railroads or uh telecom infrastructure, the AI build is still as a percentage of the US GDP on the low side. But here are the numbers. Uh, OpenAI is working on the largest IPO in history. uh with targets uh to do this in 26 27. Um and the other point made here is that they’re planning to build one gigawatt capacity per week at 20 billion per gigawatt. Uh there are 52 weeks in the year. That’s a trillion dollars a year, which is uh pretty extraordinary. Um >> just to give people a context, a gigawatt is enough to power the whole of Dallas Fort Worth. It’s a truckload of energy. >> Mhm. [clears throat] Um, in incredible. There we go again. Sorry. [laughter] Okay. Time freak.
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[00:55:00] demo and start building with Blitzy today. [music] >> Okay, let’s go. Let’s visit our friends at Quad. Uh, and I love this article, Alex, that you found, uh, Claude shows signs of introspection, a model that is partially self-aware. Claude 4.1, take it away. >> Really interesting paper. You you’ll recall that historically the best suggestion that was floating around the AI research community for diagnosing self-awareness was maybe you train a model on the internet excluding any notion or any mention of self-awareness and see whether the model is then able to articulate something about self-awareness. This I I I think that original proposal was probably somewhat impractical. This is a far more practical diagnostic for self-awareness. And the idea is basically take the internal hidden activations of a model and graft on an external thought. Sort
[00:56:01] of inceptting an externally imposed thought onto a model and detecting whether a model is is able to recognize that it’s having external thoughts intrude upon its its internal activations. And >> isn’t that called psychosis? [laughter] I >> I think that might be slightly different. I think this is closer to some sort of maybe telepathic forcing. >> You’re you’re you’re taking an external activation vector and forcing it upon the internal hidden activations of the model and then checking whether the model realizes that it’s being externally influenced. And pretty remarkably, some of their stronger models, the uh Opus 4 4.1, were about 20% of the time able to articulate not only that they were being externally influenced through this sort of vector activation injection, but were also able to reasonably well articulate precisely the nature of the external thought that was being forced into their internal streams. So the question is what does
[00:57:01] self-aware mean? uh it understands it’s an AI model. It understands what Alex >> the the proposal in this paper is that self-awareness means that the model is able to think about its own thought. >> It’s able to understand what its own inner thoughts if you will its own inner inner uh activations are and able to reason based on that. Well, just a high level point for the neural net geeks out there too, like this research can only be done if you have access to the internal weights and activations of the neural net. So, it’s done inside anthropic. Now that meta is not going open source, uh it’s you have to actually use a Chinese model to do this kind of research or you’re screwed. Which is really very sad because I think you know before I switched to computer science at MIT, I was cognitive psychology. And I think that experimenting with the parameters and activations of a neural net will tell you far far more about how a human brain works than than the normal stick a you know little probe into a rat. Uh and so
[00:58:02] it’s an incredible research playground and these these ideas of what’s the definition of self-awareness and can I inject a thought you know so what you do is you say here’s the neural net thinking about a very specific topic I’ll grab the actual activations from part of the neural net and then while it’s thinking about something else I’ll inject those and see if it it somehow is complimentary and then of course the result is the neural net is like where did that thought come from so that’s the introspection and self-awareness but you can only do that if you can splice thoughts which is an incredibly powerful cool tool Cool. And as soon as you go API only and you start because on that radar chart we saw earlier, you know, you’re operating outside the neural net and trying to define AGI from outside the neural net, but you’re so much powerful more powerful to operate inside the neural net. But we we may be in danger of losing that as a as a tool. Hopefully the Chinese models will keep coming out and Alex is warning me against using them too much. But >> Selene, final word from you. This reminds me of Hod Lipson who’s a professor at Colombia and he builds self assembling robots and evolutionary
[00:59:00] robots that have a feedback loop to improve themselves. And he actually tried out his approach to self-awareness which was ask the AI what it would look like in 5 years. Uh and then by the feedback loop of constantly forcing itself to go oh well who am I that that I might look like something in 5 years. He thought that would generate self-awareness. He thought that’s what happened in Facebook a few years ago when they shut it down. And that question, by the way, is blocked in all the major models, but somebody will do that to Deepseek, and you’ll get to that same point. Uh, and I remember Dan Barry talking about the frog. We may have talked about this on the podcast before. He’s watched a ton of free floating animals in labs at NASA, and his opinion of self-awareness was frog. And we’re like, frog? He goes, well, a mosquito is an automaton. Doesn’t really know it’s a mosquito. A dog definitely has self-awareness, knows it’s a dog. For him, the boundary condition was a complexity of about a frog, where in his opinion, a frog kind of goes, “Oh, I’m a frog. Above that, more, below that, less.” >> Okay, let’s let’s move to our friends at
[01:00:00] Alphabet. Uh, an incredible quarter for them. They topped hundred billion dollars in quarterly revenue for the first time ever. Uh, Google Cloud grew at 34%. So, just good on on on Alphabet and Google, they’re rocking it. Um and a couple of other elements that Google and Alphabet have announced uh a new marketing tool which I love called uh uh Pomaly and this is Google’s AI marketing tool. Let’s take a look at this video and then uh we can discuss it because I think this is you know again Google provides all of these incredibly useful enduser tools uh that make them so so powerful as a company. So Pomaly will understand your business DNA [music] and prompt your own campaigns
[01:01:01] or get suggestions. >> All right. Bottom line. >> Yeah. Bottom line, this is an AI tool >> from Yes. Go. Yeah. from deep mind that help small businesses create onbrand marketing campaigns. So uh Pomaly will analyze your business website uh learn the tone, the color, the style to create ads that match that brand and generate readyto use posts that can be edited in the tool. So they’re basically helping their customers who are advertisers do better advertising. I think super smart. Any comments on this, Dave? Well, you know, uh, you know, before before Google had AdSense, you know, they they thought they were going to hire 10,000 salespeople and be kind of like los and nobody remembers all this, but there was a very very smart original employee there, an Iranian guy who said, “Hey, why don’t we create an auction marketplace and people can just come and bid on Google and we’ll we’ll open it up
[01:02:01] to the economy. We’ll make we’ll democratize it. We’ll make every entrepreneur in the world able to thrive along with Google.” And it worked incredibly well and that created the Google we see today. They’re going to do that again with all these >> Gil Alba created that engine, right? Uh and uh yeah in incredible. >> Yeah, incredible. So, hey, you just just drinking >> as they roll these capabilities. >> I just want to point out the >> I just want to point out the latent trading ability of people in the Middle East is off the charts and when you apply that to kind of deep internet paradigms, um that’s kind of incredible. What this struck me as was another example of Peter in our book uh exponential organizations we have the concept of interfaces right and Google AdSense succeeded because you automated the supply side and the demand side of the ad business and this is now pushing the boundaries of that further and further into the creative process >> just to comment Peter on on this as well I I think the the elephant in the room here is that the the visual ads that are being generated are not being generated
[01:03:01] pixel by pixel I’ve spoken on the pod in the past about how in the future user interfaces I I think are just going to be every pixel is purely generative. In this case, it’s almost charmingly retro in the sense that it’s not pixel by pixel generated. It’s vector graphics. It’s images and photos clipped from the original underlying website. And I I think the elephant in the room that it’s not purely generative means that it’s going to be ultra low compute cost to generate. And that that is suggestive that we may live in a very near-term future where display ads on the internet are generated on demand because it’s relatively computensive at the moment to generate a custom image pixel by pixel for an ad, but it’s relatively lightweight. >> I love I love that especially as agents are cruising all of my tabs on my search engines and listening to my conversations. They know exactly what I want in that moment and can generate an ad to influence me until such time that I just give my AI permission to do all the buying in which case it’s game over
[01:04:01] for advertising. >> Charmingly retro in all of this. >> Hold on, Peter. Peter, you’ve hit on something unbelievably huge here. This on all of this is assuming a human consumer, right? >> Yeah. >> And very quickly we’re going to go through that. >> Yeah. I remember having this conversation with, you know, we were advising Proctor and Gamble and we did a workshop with them and they’re like, “Spend a huge amount of R&D on what color should the Pampers box be to attract somebody’s eye at what level.” I’m like, “Well, my wife has a an Amazon subscription to diapers and doesn’t care what the box says anymore.” And they’re like, “Huh?” And it’s just the dissonance between the old way and the way that you’re talking about once we have our own AI interfacing, it changes everything. I think that also has to be taken account. So maybe this is just a short-term thing. Jarvis will just equivalence take over. >> Jarvis will buy everything I need cuz it knows when I’m running out and it knows what the best quality is and it doesn’t really care what the ads say. All right, let’s move on in the Google verse here.
[01:05:01] So, uh, we’re seeing Google AI Studio introduce Vibe Coding. So, Vibe Coding is now available on Google Studio. No coding or API needed. Uh, Dave, do you want to take this one or Alex? Well, it looks a lot like uh Replet and Lovable, so we’ll [clears throat] see how that shakes out. This is the big guys stepping on the toes of the little guys. >> Yeah, I I I used it. It was a fantastic experience and and and I think somewhat differentiated from the vibe coding the in browser vibe coding experiences from OpenAI or Anthropic. For one, it creates multiple files. If you ask it to create an app, it’s not just sort of fixated on a a single self-contained file. So it can create multiple files of code which is very important for certain sorts of apps. So I I ran it of course through my my favorite eval for vibe coding which is create a visually stunning cyberpunk firsterson shooter and it created a visually stunning dashboard uh sort of an intro lobby dashboard for for the FPS
[01:06:02] but I had to prompt it to create the rest of the game but it was what what it did create was visually stunning and I I think it’s a promising first step. I am curious what the interaction with uh with Replet and lovable will be. We spent uh a few days with Amjad Msad, the CEO of Replet and I’ve been playing with Replet on my phone and computer sort of vibe coding different apps uh which is fun. One of the things I had a long conversation with Jack Hittery while we were in in Riad and one of the things that Jack said which I love is every morning instead of becoming a consumer become a creator. Right? So, you know, usually I get up and I’m reading all of Alex’s texts, [laughter] all the breakthroughs that he found last night, and I’m just constantly, you know, as all of us are, consuming hundreds of articles over the course of uh of the week, maybe, maybe 20 or 30 per day. And and Jack was, “No, no, no. Every morning I’m going to vibe code something. Every
[01:07:00] morning I’m going to create something.” And I think that creator uh mindset is so critically important for us to be be using. So a conversation with your AI and creating something every day uh would be super fun. >> All right. What are you creating? >> I was creating a an app on my phone last night to remind me to take my pill packs cuz I have five pill packs a day and so it will now text me uh uh in certain windows and remind me did you take your pill pack? and then I can dismiss it if it didn’t. So, it’s, you know, sort of an agent adjunct uh to my health. Okay. Uh moving on, let’s go on to the chips and data center wars. A lot going on here. Uh you know, again, a trillion here, a trillion there. First story is Samsung is building a facility with 500,000 Nvidia GPUs automating chip manufacturing. This is an AI megaactory that’ll combine Nvidia’s Omniverse with Samsung’s chipmaking for up to 20 times
[01:08:01] faster performance. Uh, Blackwell chips have generated $500 billion in business so far. Uh, again, uh, a nice chunk of change. Alex, what do you make of this one? >> This is what recursive self-improvement looks like, Peter. This is GPUs, AI being used to optimize chips to make more AI. And I there are so many applications ranging from computational lithography to fab optimization for this. I I think when I’ve spoken in past of the innermost loop of civilization looking like some linear combination of chips, robots, data centers, power sources, all of these this is what the the innermost loop of civilization spinning faster and faster looks like. >> This is the economy, right? That innermost loop is the economy going forward. certainly the future of the economy. >> Yeah, you know, I I I did some reference checking here. So 500,000 Nvidia GPUs that will draw somewhere between uh you know a quarter to point4 gawatt of
[01:09:03] energy. There’s no single site in China or the west that compares. So the Chinese top centers are topping out at 10,000 to 35,000 GPUs and in the US clusters like Azure and Meta are ranging from 30,000 [clears throat] to 55,000 and this is 500,000. Wow. >> Does this mean the machines are now basically uh manufacturing their own evolution? Is that basically where we’re going? >> Absolutely. >> Yeah, that’s the right way to think about it for sure. And and also you know the the fabs AI fabs themselves have always been automated. They’re they’re all roboticized on day one, but it’s the periphery around that turning it into a data center or or feeding the front end of the of the fab that huge amount of investment opportunity there to to close the inner loop. I think Alex really should write a book if books still exist um with that [laughter] title. Uh but it’s such a brilliant insight. But there’s so much leverage in the inner
[01:10:00] inner inner loop. And if you focus on okay, where are the bottlenecks on the innermost inner loop and you’re going to find that it’s the chip getting out of the fab and into a data center and actually doing something useful. That’s where most of the bottlenecks are now. Huge robotation and energy. Yeah. And then that’s the feeding on the front end of it. >> Yep. >> All right. Uh here is a a fun conversation and article. Extropic creates thermodynamic AI chips combating industry’s energy crisis. This comes from a friend of ours, Gil Verdon, who’s been on my stage at the Abundant Summit. He’s been on our podcast here, and he’s talking about a breakthrough in hardware, uh, a technology called thermodynamic sampling units, TSUs, that are using 10,000 times less energy than GPUbased systems, uh, using probabilistic bits. Alex, so what does that all mean? >> Well, so I read Gil’s paper and I’m a a huge fan in general of trying to get closer and closer to the physical limits
[01:11:00] of computing. Seth Lloyd famously 20 plus years ago discovered slash reported that the ultimate physical computer would probably at least for for serial computing look like a black hole. Black hole as as the ultimate supercomputer. So I’m I’m a big fan of of approaching the physical limits of of computing. In this case though, my worry is there’s such a sort of a sorted history of probabilistic computing approaches being attempted and failing to keep up with Moors law and algorithmic improvements. This is my worry. I I I want to believe I I want something like this to succeed, but I’m not super optimistic that uh that this isn’t just going to get steamrolled by algorithmic advances and advances in good old-fashioned CMOS digital logic. It it it looks too much like uh analog computing, probabilistic computing. And remember 10,000 times e even generously 10,000 times energy improvement at at the rate that models
[01:12:00] and algorithms are advancing and the rate that good old-fashioned digital CMOS is is improving that that may only be a few years of of headroom which a new architecture would need anyway to get off the ground. But can’t we view it from the energy perspective? Because reducing the energy requirements on Earth by 10,000fold seems staggeringly uh beneficial. >> In principle, yes. But in practice, the workloads that that the economy demands have to be able to run on on these computers in order for you to realize this hypothetical energy advantage. I I think the uh for for better or for worse, the the burden of proof is on Extropic and and Gil to demonstrate that his hardware can host workloads that are as commercially valuable as say B and video workloads. >> I saw Elon and and Gil going back and forth on uh on X uh and Elon saying, “So, do you have something I should be looking at?” And Gil say, “Yes, let me show you.” So, we’ll see if uh if the Musk verse gets behind this technology.
[01:13:02] >> I have a quick com. Yeah. Alex, can you go back to the black hole being the ultimate super [laughter] can you cuz you lost me right there and I’m my head’s like stuck now. Could you just go over that just for a second? >> Black holes are wonderful computers. uh they’d be a little bit difficult on the input output side especially the output >> a little [laughter] >> but but I in principle so so you can uh and Seth and others have refined this notion you can define a generalized notion of computation and then in in pure physics so it it deals with uh terms of how quickly can internal state changes happen inside a physical system and turns out black holes are absolutely the physical limit based on the physics that we have today for the fast as a serial computer because state changes uh in terms of their quantum state evolve at the physical limit. Uh so programming them maybe a little bit challenging. Maybe you’d have to fire in like an X-ray laser, gammaray laser, and maybe you have to parse the Hawking radiation.
[01:14:00] But if you can solve input output, black hole supercomputer is the way to go. >> I can see the title of this episode this week is black hole supercomputer is the ultimate. >> Black hole supercomputer on your desktop. [laughter] >> Okay, let’s move on. This is a fun article. So Elon Musk on data centers in orbit. SpaceX will be doing this. So here we see in the image here uh V3 of Starlink. So Starlink version 3 will be coming out. It will be delivering 10,000 times or 10,000 10x more capacity uh 1 terab per second and enabling large scale off-world processing. And I love this quote uh that you shared with me last night, Alex. I added it. 100 terowatts per year uh is possible from a lunarbased producing solarp powered AI satellite locally and accelerating them to escape velocity with mass driver. So basically turning lunar material into uh into compute and then uh accelerating
[01:15:00] them off the moon with a mass driver again the work of Gerard K. O’Neal and into Earth orbit. Uh so this is the beginning uh of a lot of things Alex we’ve been talking about Dyson swarm >> let’s talk about what we’re we’re talking about we’re talking about disassembling the moon to build more computers to to build computium and the Dyson swarm and and what’s more remarkable I mean just in in the past few episodes of the pod I I’ve been beating the drum for how you know mark your calendar now we’re at the very beginning of the construction of the Dyson swarm maybe I was overly pessimistic maybe we’re actually going to see multiple competing Dyson swarms and SpaceX is going to launch one. You’ll see other companies, maybe other Frontier Labs launch competing Dyson swarms. At this point, in the style of worrying about overpopulation on Mars, I’m I’m starting to wonder whether I should be instead banging the drum for ensuring good interoperability between all of the Dyson swarms. Let’s take a moment. uh Freeman Dyson, brilliant
[01:16:01] individual, who said, “At some point, you’re going to disassemble all the planets in the solar system and create a a sphere around the sun that captures all of its energy.” And that’s going to be the hallmark of an advanced civilization, that’s called a Dyson sphere. If it’s not one sphere, but a bunch of different uh satellites and computes, that can be viewed as a Dyson swarm. But the real fun concept is a matrioska brain. So Alex over to you. >> Yeah. So the these are three overlapping concepts. So Dyson sphere, Dyson swarm, matroka brain. Dyson sphere was this notion of having basically and and there was a even a Star Trek Next Generation episode that did this. uh a a solid sphere at roughly Earth radius from from the sun that lots of people perhaps could live on the interior of uh and and enjoy nice environments and things. Probably not practical from a material science perspective. The the stresses
[01:17:01] would be enormous. That’s Dyson sphere. Dyson Swarm says, “Let’s rather than having this be a solid enclosure that’s rigid, let’s instead have this be lots of orbiting lots of orbiting satellites that are nonetheless collecting the energy from the sun.” Mroska brain says let’s take multiple Dyson spheres at different radi from the sun and have the innermost spheres consume the light the the solar insulation at at certain frequencies and then radiate waste heat outward to to the outer more outermost spheres which then will consume progressively more and more infrared shifted radiation and use that to power their compute. So these these three concepts Dyson sphere, Dyson swarm and metroka brain and also Jupiter brain is another popular depiction. These are all interrelated concepts. Uh I I think if if we go the trajectory of taking apart our solar system, whether we brand it as
[01:18:01] one or the other, they’re they’re pretty similar. >> And maybe a black hole >> maybe a black hole is a matroka brain circling a star and we can’t see the light. You know, I I I wonder about this. Like, if this is the fate of intelligent civilizations, I would expect to see more infrared shifted solar systems elsewhere in the galaxy. To my knowledge, we haven’t observed this. That that makes me suspicious that even though I bang the drum for for Dyson swarms, maybe there’s something out there lurking in our technological future that will cause us to not actually need to take apart our solar system. >> Two points. one uh for those of you interested uh Metroska brain comes from the Metrosca dolls which are the nested Russian dolls. So you can imagine nested spheres around the sun each one absorbing energy utilizing energy and then radiating waste heat that becomes the input for the next sphere that it radiates to and the next sphere and so
[01:19:01] forth. Second point is we’ve got to get Elon back on the pod here to talk about this. I think it would be a a lot of fun. All right, let’s talk about energy and robotics. Our final topic for today. Um, this is a big deal. So, California invests big in battery energy storage and leaves blackouts behind. So, it used to be pretty awful, and I remember this, we had rolling blackouts in California. But the state has done something amazing which they’ve increased battery storage by 3,000% going from 500 megawatts in 2020 to 15.7 gawatts this year and the battery store solar from uh for evening demand replacing underperforming gas plants uh and uh you know I’m glad to see this is happening and uh See thoughts? >> I think this is awesome. I mean, what a
[01:20:01] testament to uh 15 gawatt is an incredible number of >> no idea this was happening. >> No, it’s not. Stay away from the word incredible. >> Yeah, [laughter] >> it’s a stupid trivial round. >> Stoning. How about stoning? >> This is We’re going to get our subscribers drunk. Um, so interestingly, >> store gigawatts. Batteries store gigawatt hours. >> Yes, gig hours. >> Read the story underneath this. It’s only got 3 hours at that power level. This is a joke. >> This is just like >> this is like all of Alex and and my interactions with government trying to do things that sound important >> that are these stupid little edge rounding cases. This at at peak load for California this is one hour of storage and on a typical day they can store up to about a day of an average. >> All right. But but let’s take a look at the numbers. Right. So blackouts have been have been cut from by 90% from 15 a year to two a year. Uh which is which is great. And here’s the here’s the
[01:21:02] problem. We’re going to see the CPI of electricity just skyrocketing. Right? So the price for electricity was 22.5 cents per kilowatt hour in 2020. Uh it’s increased now to 32.4 cents per kilowatt hour. 44% increase. And if we continue to make, you know, the demands that we have on on data centers, uh, there’s going to be a problem, the proverbial, you know, shit’s going to hit the fan sometime soon. Well, I agree with that. But I mean, California has has done everything humanly possible to self-destruct at the government level despite having the greatest tailwinds, like the most incredible state, massive state, all the innovation in the world, every advantage in the world, and the government claiming to do something good by piling up a bunch of batteries. It’s like what? You’re down to two blackouts a year. I mean, seriously, [laughter] that’s our our expectation of what we do. At least the 13% tax rate. >> At least they’re down a lot. It’s
[01:22:00] ridiculous. There’s something there. I >> I’ll point out also just for for California specifically, if if folks are familiar with the infamous so-called duck curve of California, where the demand for electricity peaks in the the evening like right after sunset uh and also in the morning. There is a mismatch between California, which is rich in in insulation in in solar energy on the one hand, and the need for early evening power. I I think even just a few hours of battery storage can help to smooth out the duck curve and and that’s transformative for California in a way that we here perhaps in in New England don’t have quite the same problem in our energy story. Google to buy power from next era uh nuclear plant being revived. So Google signs a 25-year deal with Next Era to buy power from a revived Dwayne Arnold nuclear plant in Iowa. It’s reopening in 2029 to provide 615 megawws roundthe-clock carbon-f free. It’s a 1.6 billion dollar project. And it’s
[01:23:01] interesting that we’ve got uh these again these hyperscaler companies that are buying energy. They’re basically it used to be that this was something the government did. You know, the government provided a distribution network for power and you would buy it off the grid. uh that is no longer the case. Companies need to provide their own energy. So going all in on on fision plants, uh SMRs, soon fusion plants, hopefully solar plants. Uh Salem, you want to jump in? >> And ooh look, it’ll create 400 jobs. [laughter] >> Such negativity. This is huge. Like this is this is great. Yeah, this is an important bridge I I think to the near future. >> I think what what this shows is that we’re basically uh dissociating the energy sources from the grid and and now we can have energy wherever it is happening in Plunka data center next to
[01:24:00] it and then leverage it. So the marginal energy usage around the world will totally explode. >> I can’t wait for geothermal to really kick in here, right? There’s so many places in a way. >> But wait, Alex, you’re putting it way more emphasis than I would have thought. Tell us why. Well, I I think bridges are important. We we right now the limiting factor for tiling the world with compute is as as uh a number of executives have recently pointed out, we have the GPUs. The the problem is having warm racks to to put them in as as Satia Nadella said in the past few days. >> I saw that Microsoft has thou you know what hundreds of thousands of GPUs they can’t turn on because they don’t have the energy for it. >> Yeah. Mhm. [clears throat] >> So I I I think like having bridges like reactivating uh otherwise disused nuclear plants. I think this is an incredibly important bridge to the future until we get SMRs and fusion and and maybe solar and and uh maybe new forms of net gas. Totally totally right. And I you know they what Chase Lockm
[01:25:00] Miller is doing also the same bridge kind of structure where you start with or you know regular fuels use natural gas or whatever but it it’s steam turbine generation right into the grid right into the data center you can reuse all that when you move it to small nuclear you move it to SMR >> and then a fusion comes online in 2030 2032 maybe >> you replace the boiler >> you replace the boiler it’s just like by far the most efficient way to get to the ultimate end state the Dyson swarm or whatever, but but between here and there, that’s the right stepping stone. It’s much harder to do with solar because solar doesn’t feed into a generator. It feeds into a battery pack. And so, you’re not reusing any of that when you move it to fusion in 2032. >> I wonder I love this. >> I wonder what takes four years, right? This is four years away. What takes four years to get an existing nuclear plant up and going? Are they retrofitting it? Are they updating it? or is this all paperwork? >> It’s very it’s all of the above, Peter,
[01:26:00] because we’re advising um Fermy America on this stuff. They’re planning to do six gawatts of gas turbine and six g of nuclear. Um it is very very complicated to spin up a nuclear power plant. >> You can that is the the the Alex loop inner loop of the inner loop of the inner loop. Like focus on that like Peter, why is it four years? Could we make it three years? >> You could build a starship and go to Mars in four years. I don’t understand why you can’t get a nuclear plant up and going in four years time. >> To their credit, they they’ve had an AI generate an S11 in record amount of time and got it out the door. So that it’s starting to happen. It’s just that the this is why that Sage project is so important, Peter, to rewrite policy as we need it. M I listen when the Trump administration finally says we’re going to accelerate this tenfold that’s when they’ll get they’ll get serious about energy production. >> All right, these are some fun articles coming out. Uh we’re about to see the robo taxi wars coming online. So Nvidia
[01:27:02] is planning a robo taxi project to challenge Whimo and Tesla. So here are the numbers. Uh Nvidia is launching a $3 billion robo taxi project in the self-driving car race. Uh this is a partnership between Nvidia, Uber, and Stalantis. For those of you who don’t know Stalantis, they are behind brands like Chrysler, Jeep, uh Pujo, and Fiat. One of the largest uh automakers in terms of um not the brand, but building the parts. And it will use an end-to-end AI system called Cosmos that Nvidia has built uh to handle driving simulation. Interesting. They want 100,000 robo taxis launched by 2027. Uh it’s coming. All right. I you know we saw god 100 years ago there was a 10-year period where we went from you know 99% horse and buggy and 1% cars.
[01:28:01] flipped it all over to 99% cars and 1% horse and buggies. And the question is, is that this decade between all these players and all the capital going in? Thoughts, gentlemen? >> I made a prediction uh 10 years ago that um that uh all uh driving would be automated. My son, who’s now 14, would never get a driver’s license. So, we got two years to satisfy that. >> Yeah, mine my boys, too. So, here here’s some of the numbers. Uh Tesla Cyber Cabs right now they have 200 vehicles operating I think in Austin and their plan is to scale up to 10,000 this coming year. Can’t wait for them to be in Santa Monica where I live. Whimo has 700 vehicles and by the way I see them all the time as I’m driving around. I I must see 20 25 of those a day. So 700 vehicles is is a pretty small number. So they must have concentrations here in LA and up in San Francisco. And uh there’s
[01:29:00] 500,000 miles between collisions with Whimo. It is the safest player out there. And Nvidia uh is partnering now to go live with this. >> I love that 3 billion is a stoning amount of money. And and yet for Nvidia, it’s like a drop in the bucket given the market. [laughter] >> It is a drop in the bucket. >> Like they don’t even notice it’s like a little side project. >> But this is their this is where they’re this is where their GPUs are going next. They’re going into humanoid robots and autonomous cars, right? It’s it’s automating the entire world around us. >> That’s right. I’ve spoken in past about how this innermost loop is not going to remain contained inside data centers for very long. I think as I’ve noted in past, the compute is literally going to walk out the door of the data centers. In this case, it’s going to drive out the door. But I I think for many people, these driverless cars I I have one uh and many people I know surprisingly haven’t even driven in one or haven’t had the experience of driving in one. For many people, this is going to be their first encounter with a
[01:30:01] generalist robot. It’s going to be either seeing or driving in or or owning a driverless car. And it’s not going to stop there. I I think the same stack that that we’re seeing Nvidia with with their autonomous vehicles pushing, it’s going to generalize to humanoid robots on the the time scale of 1 to 3 years. So, this is again the beginning of the expanded innermost loop of civilization that we’re seeing. >> On the flip side, here’s the article from Uber’s perspective. And just to remind folks, Dra, who’s the CEO of Uber, will be on stage with us uh at the Abundance Summit in March. Uh it’s going to be my best ever. We have only 30 seats left for the Abundance Summit. It’s selling out faster than any time ever in history. Uh if you’re interested in grabbing one of those 30 seats, you can apply at uh abundance360.com. But uh this is not a commercial. The program will fill, but it’s going to be incredible. Can’t wait. We’re going to be talking with Dra about not only autonomous vehicles, but flying cars and
[01:31:03] uh and Uber is going in so many new directions, just driving revenue. So, their goal is 100,000 Nvidia based robo taxis beginning in 2027. And this puts them in direct competition with Whimo and Tesla. Today, uh in a number of cities, you can order up a Whimo on your Uber app, uh which is which is fantastic. Any final thoughts on this story? >> I think this is too slow for my tastes because there’s like such a huge demand for this. Uh even Whimo only has I think 2,000 is what I looked up. Um there’s 800 in the Bay Area, 500 in LA. We need like tens of thousands of these things. The good news is each Whimo car replaces dozens of cars that are sitting around 94% of the time empty. >> Yeah, most definitely. All right. Uh our next story here, I love this one. Foxcon to deploy humanoid robots at its Houston AI server plant. So, uh, check this out.
[01:32:00] Foxcon to expand AI server production in Texas to half a million square feet, uh, producing GB300s and Blackwell series AI servers. Uh, it’s got a partnership uh, with uh, Digit, which is Agility Robotics. Uh we’re going to have the CEO of Digit on our or the the CEO of Agility Robotics on our stage this year. See, uh we’ll have >> at this stage. Abundance needs to be like 8 days long. Peter, >> well, it’s it’s tough. I mean, I’m trying to make sure that we have enough time for all of the uh the community members to like meet each other, hang out, have conversations, and have it fun. But yeah, it’s 4 and 1/2 days, but we’ll have four currently four robot companies there. I’m trying to get a fifth one from China. We’ll see if we can get the the new version of uh uh of one of the top Chinese robots there as well. But so check this out. These humanoid robots are going to be driven by Nvidia’s Isaac Gurut Nen model. Um
[01:33:03] uh you know this is this is the innermost loop, isn’t it, Alex? >> It is. This is robots operating factories that make servers that go in data centers that power the robots. That’s the loop. >> Yeah, I won’t say incredible. Not going to say it. Not going to say it. But wow. >> I will I will say there aren’t nearly enough companies working on all the different form factors and and yeah, like there’s room for a thousand more startups doing different variants of this >> for all the mechies out there that are wondering what they should do. [clears throat] >> I also think this is a >> pre build a robot company that has an eight armed octopus type robot and beat everybody else. I I also think this is a preview of how we get, you know, you were talking earlier, Peter, about uh Sam’s forecast of a gigabte per week. I I think this is a plausible technical trajectory for how we get there. We’re we’re going to have robots building the fabs and the the factories producing the servers and the data centers. It’s going
[01:34:01] to be one massive flywheel. >> All right, our next story in energy is Blue Energy and Caruso partnered to develop an advanced nuclearpowered AI data data center. But I think the more interesting story here is that they plan to stand it up with uh with natural gas plants uh and then convert it to nuclear about 3 years after that. Right? So don’t wait for nuclear. Get it operating with what you can right now and then retrofit nuclear when you can. So, the wait time for a new gas turbine uh engine today for the gas turbine stuff is about four and a half years. >> It’s crazy. >> It’s It’s insane. Like we advise Semen’s Energy and it’s they’re like sold out forever and it’s incredible. Everybody’s trying to go to dump heaps and and get spare parts for gas turbines out of their garbage dumps. It’s like really really in the recycling plants. It’s really crazy right now. >> Wow. I want to talk a little about the
[01:35:01] China US battle uh and hit a couple of different points here. So uh here are some numbers and and they’re important to note you know that China is dominating production in a few different areas. 66% of electric vehicles are being built in China. 80% of solar panels and batteries are in China. 60% of wind turbines. Those are staggering numbers. uh add to that that on the innovation metrics metrics 70% of all global AI patents are coming out of China and 75% of clean energy filings are coming out of China. Uh you know this was part of the debate that uh on our on our evening in Riad uh that we hosted this dinner and and Kathy and Bology were going back and forth on on topics like this. Uh Dave or Sem, you want to weigh in? you know, we really ought to have a just a focused session with Antonio Gracias and Chase Lock
[01:36:00] Miller on on how to how to deal with this in the US because our whole investment cycle isn’t geared up for this type of investing and China is. You know, it’s just very manufacturing heavy and you know, hey, we need more power, we need more melters, we need more whatever. Um, we don’t really do that well in the US venture economy, but that’s all getting rethought right now. And Antonio and Chase are the guys right in the middle of it. So, we should just get them on the pod and brainstorm our way through. How are we going to how are we going to restructure because, you know, these are these are very expensive projects. They’re not venture projects. Uh they they seem to work every time. The playbook is right on that prior slide. It’s not a mystery. Uh you have to be involved with the government. You can’t just, you know, you need zoning, you need a location, you need per permits and all that. So, it’s it’s just a new format for American innovation, but it’s it’s going to last for, you know, 10, 20, 30 years. So, you might as well get ahead of it. I mean, imagine if Elon weren’t doing what he what he does right now. You know, these numbers would be far worse. So, uh, this >> there’s I want to make a comment here.
[01:37:00] There’s something this is the one of the flaws of our democracy where in four-year high metabolism election cycles, nobody’s thinking 20 years down the line, right? And China may be authoritarian, but they can look out 20 years and say, “We need that much energy, that much water, and do things to make that happen.” I think I actually I actually had a hack for this. I if I I kind of did some brainstorming. Somebody asked me at a conference, “What would you do?” And I said, “Every four presidential terms, I would appoint a government, give them 10% of GDP, and say, “Your only job is to fix all the stuff that’s long 20-year range projects, and then you’re out. One term only, full authoritarian, go.” which is essentially [laughter] some of what Trump is doing in this case. >> So you just want to rewrite the constitution. Okay. Um >> it’s a great thought though because you know flying back from Saudi Arabia and just looking down and you know there’s nothing out in the desert for hundreds and hundreds of miles and then you get to Europe and it’s just the most blessed
[01:38:00] Mediterranean green field. Like everything should be perfect in Europe but the government dysfunction is preventing them from any kind of involvement in what’s going on right now. So, it’s a good case study like you can mess it up in a real hurry and so if we don’t have but we’re not geared up to compete with China right now on this particular front and it does need to get rethought but if you don’t rethink it yeah things can go really bad don’t take it for granted so guys on our one of our next WTF episodes I want to bring some of the data that we found at FI9 right the future investment initiative uh event that we were just at uh some of the data is staggering about how the rest of the world looks at this and I want to share that on an episode because it’s really important because it’s going to drive the near-term future. All right, this particular chart comes uh from uh a tweet that Bology put out and he labeled it it’s happening. the AI flipping is here. >> And so this is a look at who’s making
[01:39:01] the open- source models. And what we saw this summer was open- source models were being dominated by China uh versus the US and most definitely not Europe. Uh and I think what’s most important here is that as governments start adopting different AI systems, their ability to get access to free uh open uh models uh versus paying for the models from the uh hyperscalers in the US. It’s kind of a land grab going on. I don’t have much more to say. >> You know, you know where this is really really going to collide. I was talking to Brian Elliot over at Blitzy about exactly this topic. you know with Meta doing open source we had a huge open source option in the US and then Meta fell off the grid you know and the last models were terlama 4 I guess was terrible and now they’re trying to rebuild it but they’re rebuilding it closed source so the US doesn’t really have an open source option but then when you look at the uh there’s a bunch of projects for the military that you know
[01:40:00] the blitzy will ultimately end up working on that need to be airgapped and there’s you got to use an open source model in an airgapped environment you can’t just go to the open AI you know API with super proprietary government data. Uh so but you know right now my only choice is uh is Kimmy Kimmy 2 running on Grock with a Q chips and the Grock cloud which I I think is a phenomenally good option but it’s it’s all Chinese code and God knows what’s what’s inside there. So >> so we spent a bunch of time with Eric Schmidt. I want to play uh a short video of Eric from the FI9 event we were at last week talking about US versus China just to sort of provide the US perspective. >> Who’s winning this >> race? At the moment, the United States without question. Um the US has a deep financial market that allows you to raise literally a trillion dollars on a thesis and an idea which is incredible. You have this massive buildout going on
[01:41:00] and you have a real potential of solving hard problems. >> Tell me how close China is to overtaking us. >> It’s not as close as I thought. I went to visit. China does not have the depth of the capital markets. They do have lots of energy, which we don’t. They have lots of energy, but they don’t have the depth of the capital markets, and they don’t have the chips. The capital markets, they haven’t figured out a way to make all that money the way the US does. and the chips, they haven’t been able to make the chips that the United States and others won’t give them. That keeps them behind by a good chunk. China is however focusing on exploiting AI in every aspect of its business much better than the United States. So I think the US will win on the intelligence race, but China is likely to win on the deployment race and that’s a problem for America and Europe. >> All right, I want to jump into robots as our last topic here. So, 1X, we’ve had a great pod with uh Bern Borick, the CEO of 1X. Look it up if you haven’t seen
[01:42:01] it. Dave and I went and visited his factory. Let’s take a look. They have a release of their Neo Gamma. And here’s their promotion. >> My name is Burch and today we’re launching Neo, our humanoid for the home. Ain’t no sunshine when she’s [music] gone. >> Neo is a humanoid companion designed to transform your life at home. It combines AI and advanced hardware to help with daily chores and bring intelligence into your everyday life. [music] >> And this housein’t no home. >> As someone [music] who lives with Neo every day, there is no experience quite as much. All right. So, here are their commercials. Uh, they just went out. You can put a $200 deposit down on a Neo Gamma robot. And they announced their pricing. $20,000 to buy it in their early access. And I love this. Or $4.99
[01:43:00] per month. Uh, and you can buy it in three skin tones. I find that fascinating. [laughter] Uh, but check this out. on the right hand side. Uh I was walking to my workout gym uh which is just outside my my studio and uh there was this giant sticker on the ground. Uh so this is incredible marketing. I have to hand it to them. They’re doing in, you know, really uh a super job on direct to consumer marketing on this. >> Yeah, I pre-ordered mine. Can’t wait to to have the experience. I I do think it’s interesting that in in many of the scenarios for for the Neo, at least in the early days, the according to the uh according to 1X, they’re going to be TA operated. And that may that may turn some people off. Having someone tell a remote into their home doesn’t bother me at all. I’m very very excited to try this out. >> I I think uh I got my order in when I was there at their facility. I’m hoping. No, they’re going to be so Burnt will be at the Abundance Summit and he’s going
[01:44:00] to be bringing a number of the Neogamama robots. I’m just going to put one in my car and drive away at the end of the summit. So, >> that’s I’m getting mine in March. >> Peter, when we were out there, he was saying 140k price point. I I can’t fathom how he’s coming in at 20K. Look, looking film back in the factory, but there’s so much going on inside this robot. I cannot believe that they can get it out the door at 20K. Yeah, if I were running this company, I’d be subsidizing. I mean, this is a data collection play to get a huge VA trade in. Yeah. >> Yeah. >> Skating to where the puck is going to be. So, you know, Elon said Optimus is going to be at this 20 uh,000 not price point, but cost of goods uh in when they get to a millions of robots being built and eventually robots being building robots. Again, the innermost loop over here. And this is this is competition against the prices out of China, the prices from uh Elon and from Brett
[01:45:00] Adcock. So you’ve got to be competitive >> and it’s training people to expect price points that resemble if you’re purchasing it outright a cheap car and if you’re you’re leasing it like it’s like leasing a car that this will be for you know the I’ve mentioned in in past the the American dream you know so-called of having a house in the suburbs a car and now a humanoid robot doesn’t necessarily generalize that well to the rest of the world but I I think having at least one humanoid robot in in your in your home becomes part of of the the new economy. >> And when the price gets down to $300 a month to lease, right? Again, I’ve made these numbers. I say them every time. $10 a day, 40 cents an hour. Everybody can afford that because your robot now becomes part of your earning potential. Your robot can go and do stuff for other people or for you. Right? As Elon has said, this is all about creating the world of abundance. I
[01:46:00] love this story. >> I’ve got a I’ve got a couple of quick thoughts. >> Uh, one is I have a a dog that literally looks like a teddy bear and I’m wondering what would happen if the robot mistook the twos. That would be one and I know all the models out there. Um, uh, at least in this case with all the visuals and so on, it’s not a kickboxing robot, which I thought was not great marketing thing to say from the last couple episodes. Unit >> I’m excited to see what happens here. Unitry has definitely taken a different approach and and I have to say that Optimus has still got a hard metal exterior. Uh Neo Gamma from 1X came out with this soft, cuddly, you know, uh warm sweaterlike look. >> Very important. >> And then uh and then Figure copied it. Um there the latest release of Figure 3 has the same look. So, uh, anyway, I guess borrow from the best. Uh, this is this is a story, Alex, that you shared,
[01:47:00] uh, Torino. How do you pronounce it? >> I think tool. >> Toriel. It’s an autonomous drone that ends mosquitoes. And I love this. Can you imagine you’re you’re a tech entrepreneur and you’re someplace with a lot of mosquitoes and you’re just being bothered. You go, how do we end these mosquitoes? And then your answer is intelligence drones. So here in this video uh we see this this uh uh this drone that is very lightweight and it is autonomously flying around. It’s spotting the mosquitoes and it’s zapping them with uh an electric grid that the mosquito [clears throat] is flown through. It recharges and patrols 24/7 from its base station. uses ultrasonic sonar to detect the mosquitoes, you know, the beating of its wings and a kinetic interception to eliminate them. This is like smart rocks in space or smart dust in space. >> We’re going to get nanobots. I I I think that will enable us to regulate
[01:48:00] ecosystems. And I I I think in the process, it’s probably going to raise a number of bioethical questions. Peter, you and I and and Dave have talked offline about near-term futures where uh for bioethical reasons or maybe even dare I say effective altruistic reasons where repairing butterfly wings on the one hand, but on the other hand we have drones to uh to to obliterate mosquito populations. It it’s going to be a very interesting future. >> It will and it is an interesting right now being in the present. It’s a super exciting time. Uh, I’m gonna end this pod uh with a thanks to uh Ruken, one of our subscribers and one of our fans uh who sent us over uh a musical piece called Don’t Look Up, The Singularity is Near. Uh and I’m going to play it as our outro music. But before we do that, gentlemen, uh any closing thoughts?
[01:49:03] Awesome episode. I learned so much today. This was amazing. >> Yeah. >> Yeah. There’s no doubt the pace the pace of stories is really accelerating. You got to anticipate it’ll 2x every month or two. So >> I mean I wake up in the morning >> interesting keeping up. >> I wake up in the morning at now 3:30 and I’m like what happened while I was asleep? You know it’s like >> well discussing a flying mosquito killing drone was not part of my thinking for what I would be talking about today. So that’s just Oh, we’re we’re trying. >> What about What about putting a What about putting a black hole supercomput on every desktop in every home? >> That’s also not part of it. >> Yay. Or Motraoska brains. Uh, you know, and taking apart the moon >> to get us a Dyson breathing. >> And butt brea that butt breathing was our article last year, our last episode, our our new episode, our new closing article. I think we should do that. I wish I have an unusual science closing
[01:50:01] uh piece or unusual tech. And I I’ll take the uh mosquito killing drone as our one for this week. >> All right. >> Or ending the moon. The the moon had it coming. [laughter] >> Well, listen. I have to go there and start a city before we take it all apart. That’s one of my goals, >> you know. Anyway, gentlemen, I love you much. And uh everybody uh if you’re a audio or video creator and you have an ending outro music piece you want to share with us, you can share it with us on the pod. We read all the comments. Uh and they are incredible comments. Uh and thank you all for subscribing. Uh please share this with your friends, your family. One of the best parts of being in Riad, Dave and Salem, was all of our fans there. I kept on everybody kept on coming up. I mean, this is a conference of like 5,000 people, sort of a World Economic Forum in the desert, and everybody’s I love your podcast. So, Alex, you were sorely missed. Uh, and a
[01:51:02] lot of fans >> going, “Where’s Alex? Is he joining this episode you’re doing?” >> Yeah. >> Got got to invite me next time. >> Okay. Well, we’ll do we’ll do FI in March in Miami altogether and uh try and line up a live podcast from FI Miami. All right. Here is our outro music. Uh, enjoy this everybody and have a beautiful exponential day and don’t sleep through the singularity. It’s the most exciting time ever to be alive. [music] Someone’s frying [music] data with a hint of smoke. The fridge is floating like a cosmic joke. My toaster [music] in love with a crypto bro and entropy hums on the radio. The satellites [music] gossip but who
[01:52:00] even cares? My cat just posted it all nightmares. Don’t look up the [music] singularity near. It’s bary [music] loud and clear. We built a god from electric dust. How it prays to us out of habit [music] or trust. Don’t look up. The code’s gone divine. [music] Heaven’s a glitch in the command line. >> All right. >> Oh, the lyrics are amazing. >> Amazing. A god out of digital dust. >> Yeah. >> All right, guys. >> Awesome. >> Have an awesome day. Every week, my team and I study the top 10 technology meta trends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI, and quantum computing to transport, energy, longevity, and more. There’s no fluff, only the most important stuff that matters that impacts our lives, our companies, and our careers. If you want
[01:53:01] me to share these meta trends with you, I write a newsletter twice a week, sending it out as a short two-minute read via email. And if you want to discover the most important metat trends 10 years before anyone else, this report’s for you. Readers include founders and CEOs from the world’s most disruptive companies and entrepreneurs building the world’s most disruptive tech. It’s not for you if you don’t want to be informed about what’s coming, why it matters, and how you can benefit from it. To subscribe for free, go to dmmandis.com/metrends to gain access to the trends 10 years before anyone else. All right, now back to this episode. >> [music]