OpenAI Going Public, the China–US AI Race, and How AI Is Reshaping the S&P 500 and Jobs w/ Salim Ismail, Dave Blundin & Alex Wissner-Gross | EP #205

Summary

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Moonshots with Peter Diamandis – Episode #205

OpenAI Going Public, the China–US AI Race, and How AI Is Reshaping the S&P 500 and Jobs Guests: Salim Ismail, Dave Blundin, Alex Wissner-Gross
Release Date: November 4, 2025

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Episode Overview

In this high-velocity episode, Peter Diamandis and his panel of top-tier technologists dissect seismic shifts in the technology world. The discussion centers around OpenAI’s astronomical growth and plans to go public, the intensifying China–US race in AI and clean energy, and how artificial intelligence is upending the S&P 500, corporate valuations, and jobs. Key insights span from fusion energy breakthroughs to humanoid robotics, AGI benchmarks, and the reality-distorting impact of AI-generated content. The group’s optimism is nuanced by debates on economic decoupling, governance, and technological arms races with memorable moments, candid personal anecdotes, and thoughtful prognostication.

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Key Discussion Points & Insights

1. OpenAI's Revenue Moonshot and IPO Plans

[00:00–11:13]

• OpenAI’s Revenue Trajectory:

  • OpenAI predicted to reach $100B ARR by 2027, outperforming historical record-holders (Nvidia, Amazon, Google) thanks to 800 million subscribers and AI-driven services.
  • Alex: “It’s not that difficult to imagine OpenAI tripling revenue year over year for the next two, two and a half years and getting there in 2027. The key again is just… condensing, distilling [knowledge work] down to agents running 24/7.” (09:26)
  • Dave: “With 800 million subscribers already, half this comes from subscription revenue that’s more or less in the bag... It’s going to happen either way.” (10:01)

• IPO Structure & Legal Drama:

  • OpenAI restructures into a public benefit corporation (B Corp) with a massive nonprofit arm and Microsoft holding a 27% stake.
  • Ongoing Elon Musk lawsuit attempts to halt restructuring—could be legally significant but markets dismiss major risk for now.
  • Dave: “If you’re secretly building a massively profitable, trillion-dollar company while avoiding taxes, that’s a terrible precedent.” (45:55)

• Societal Impact:

  • OpenAI’s foundation to leverage its nonprofit equity towards solving disease, using up to $25B in AI-driven initiatives.
  • Alex: “I think an IPO by OpenAI and other frontier Labs and putting the equity in the hands of retail investors and index funds is almost certainly a net societal good.” (47:02)

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2. Data Center Supremacy & The Innermost Economic Loop

[12:46–22:11]

• US Dominance in Data Centers:

  • The US leads with over 5,400 data centers, far ahead of Germany and China.
  • Alex: “Remember this is not the number of AI data centers… This is just total number of data centers.” (13:03)

• Nvidia’s Market Value:

  • Nvidia surges to $5 trillion in market cap, rivaling entire nations.
  • Dave: “Nvidia is worth the same amount as Saudi Arabia… The cost of buying the entire country… would be the same as buying Nvidia.” (13:54)

• The Innermost Loop of Civilization:

  • Recursive economic flywheels: robots build chips, which power data centers, which train more AI and robots—a technological positive feedback loop.
  • Alex: “This is what recursive self-improvement looks like… GPUs used to optimize chips to make more AI.” (68:13)

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3. S&P 500 vs. Jobs: The Decoupling Moment

[16:12–21:55]

• Job Openings Diverge from S&P:

  • Historic chart shows job openings and S&P 500 moving in unison—until late 2023, when S&P surges upward and job openings plunge post-ChatGPT.
  • Salim: “Humans have now become optional inputs into the economy. That’s a big deal.” (19:10)

• Economic Interpretation:

  • Some see the trend as fundamental decoupling (AI as economic driver, job losses ahead), others, like Alex, caution it may reflect Federal Reserve actions post-COVID.
  • AI’s impact is concentrated in tech companies—most gains in S&P are limited to the “Mag 7”.
  • Peter: “AI is no longer an industry or sector, it is the economy.” (19:23)

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4. Optimism and Alignment: Can Superintelligence Be ‘Motherly’?

[22:11–26:52]

• Jeffrey Hinton’s Maternal Instinct Hope:
  • Hinton suggests we can build ‘maternal instincts’ into superintelligent AI for benevolent coexistence.
  • Salim: “I don’t really buy the maternal instinct… It seems a little kind of really off to me.” (24:46)
  • Alex: “That’s unlikely and probably not that robust a means of alignment for superintelligence… Instrumental convergence approaches are more likely to guarantee friendliness.” (25:03)

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5. Information, Truth, and AI Knowledge Engines

[29:46–35:16]

• Grokpedia vs. Wikipedia—Automated Truth Seeking:
  • XAI's Grokpedia offers dynamic, AI-curated knowledge bases, outscaling Wikipedia in reference depth and speed.
  • Alex: “We don’t have a science right now for knowledge purification, but one could imagine… we arrive at some sort of ground truth.” (31:19)
  • Salim: “If you take a Wikipedia article… it’s just a pain in the ass… an AI can do this without even blinking.” (33:17)

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6. AGI Benchmarking & Limits of Current Models

[36:25–41:53]

• Defining and Measuring AGI:
  • New paper benchmarks AIs against human intelligence along 10 axes; GPT-4/5 is at 57%—shows AI is ‘jagged’ (strong in some areas, weak in others).
  • Alex: “I love benchmarks in general… but these are off the shelf models without agent bureaucracies on top…” (39:59)
  • Salim: “For me, AGI would incorporate emotional intelligence or spiritual intelligence or any of the other dimensions…” (42:05)

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7. Deepfakes & Reality Distortion

[26:52–28:57]

• Fake Jensen Huang Livestreams Gain More Viewers:
  • AI deepfakes drive new scams; even with poor lip-syncing, fakes draw more attention than official streams.
  • Salim: “Reality may have just lost the algorithm war.” (28:13)
  • Alex: “I don’t think in the long term this is a deal killer… I think this is very tractable.” (28:29)

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8. AI as Economic Infrastructure (Energy, Chips, Dyson Swarms)

[53:05–75:58]

• Trillion-Dollar AI Infrastructure Spend:

  • OpenAI and others plan to spend up to $1 trillion/year on data centers, rivaling railroad/telecom booms of the past.
  • Alex: “Just saying, we’re going to spend 1% of global GDP on AI infrastructure… this feels on the low end to me.” (52:36)

• Automation and Recursive Improvement:

  • Samsung to deploy 500,000 Nvidia GPUs in a single AI megafactory; robots are now helping to manufacture the next generation of robots and chips.
  • Dave: “That’s the loop… There’s so much leverage in the inner, inner, inner loop.” (69:30)

• Physics Limits, Thermodynamic AI, and Black Holes as Computers:

  • Novel energy-efficient chips promise massive savings; Alex discusses physical limits, referencing black holes as theoretical ultimate computers.
  • Alex: “Black holes are wonderful computers… for the fastest serial computer because state changes in terms of their quantum state evolve at the physical limit.” (73:13)

• Space-Based Compute and Dyson Spheres:

  • SpaceX/Starlink Version 3 will drive orbital data centers with lunar-sourced solar power; ambitions to build early Dyson swarms and eventually Matryoshka brains.
  • Alex: “We’re talking about disassembling the moon to build more computers to build computronium and the Dyson Swarm.” (75:14)

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9. Robots Are Here: Humanoids & Robotic Economies

[91:48–107:02]

• Robotics Commercialization:

  • Humanoid robots (e.g., 1X’s Neo, Digit/Agility, Tesla Optimus) now affordable ($20,000 or $499/mo lease); data collection and productization accelerates.
  • Alex: “Having at least one humanoid robot in your home becomes part of the new economy.” (105:04)
  • Robots now build data centers, and new startups are racing to fill every robotic niche (humanoids, octopuses, more).

• The Age of Personal Robot Assistants:

  • Teleoperated robots as a stepping stone to full autonomy.
  • Salim: “What would happen if the robot mistook my teddy bear-like dog for a real teddy bear?” (106:01)
  • Peter, on price: “When the price gets down to $300 a month to lease… $10 a day, 40 cents an hour. Everybody can afford that.” (105:34)

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10. The China–US AI War & Energy Race

[95:00–100:28]

• China’s Manufacturing Advantages:

  • Dominates EVs (66%), solar/battery/wind (80%/60%), and AI patents (70%).
  • US has capital markets, China has manufacturing and deployment scale.
  • Eric Schmidt (clip): “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.” (100:44)

• Redefining Industrial Policy:

  • US investment cycles (short, high volatility) vs. China’s 20-year vision creates strategic challenges.

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11. Power, Energy, and the Jevons Paradox

[79:59–85:43]

• California's Battery Boom:

  • Huge storage increase (500MW → 15.7GW), but only a few hours of backup; energy costs rising fast.
  • Dave: “At peak load… this is one hour of storage. And on a typical day they can store up to about a day… a joke.” (80:25)

• Energy for Compute Demand:

  • Hyperscalers (Google, Microsoft) securing nuclear and other dedicated energy sources.
  • Alex: “Right now the limiting factor for tiling the world with compute is… having warm racks to put them in.” (84:15)

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12. Self-Aware AI & Neuro-Inspired Diagnostics

[55:06–59:57]

• Claude 4.1 and Self-Awareness:

  • New diagnostics test if AI “knows” when thoughts are externally injected—introspection mechanisms signal early self-awareness.
  • Alex: “Self-awareness means… the model is able to think about its own thought.” (57:08)

• AI and Animal Brains:

  • Salim: “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.” (59:57)

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Memorable Quotes & Moments

• On AI’s replacement of human labor:
  Salim: “Humans have now become optional inputs into the economy. That’s a big deal.” (19:10)

• On digital knowledge and truth:
  Alex: “We don’t have a science right now for knowledge purification, but one could imagine…” (31:19)

• On black hole computing:
  Alex: “If you can solve input output, black hole supercomputer is the way to go.” (73:13)

• On disassembling the moon:
  Peter: “Well listen, I have to go there and start a city before we take it all apart.” (110:14)

• On robotics at home:
  Alex: “Having at least one humanoid robot in your home becomes part of the new economy.” (105:04)

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Notable Light-hearted and Human Moments

• Team discusses strategies for beating jetlag:
  Salim: “I learned a trick from Ramez… take a double dose of melatonin and in a couple of days you're good.” (01:08)

• A running joke about Peter’s overuse of the word “incredible” turns into a drinking game.

• Salim recalls a “most powerful evening” with senior Saudis at a Riyadh farm, emphasizing the global community’s role.

• Live musical outro sent in by a fan:
  Peter (on lyrics): “Amazing God out of digital dust.” (112:38)

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Important Timestamps

• OpenAI’s $100B ARR Ambitions: 00:00–11:13
• Data Centers, Nvidia’s $5T Cap: 12:46–15:34
• S&P 500 vs. Jobs Decoupling: 16:12–21:55
• Maternal Instinct for Superintelligence (Hinton): 22:11–26:52
• Deepfake Livestream Outpaces Real Event: 26:52–28:57
• Grokpedia, Knowledge Purification: 29:46–35:16
• AGI Benchmarking: 36:25–41:53
• Self-aware AI Diagnostics: 55:06–59:57
• Orbital Data Centers, Dyson Swarms: 74:12–78:39
• China–US AI Race/Energy Industrial Policy: 95:00–100:28
• Humanoid Robotics Home Market: 101:49–107:02

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Thematic Takeaways

• AI’s Economic Gravity:
  AI isn’t just transforming industries; it is becoming the economy. Jobs, earnings, and opportunity are rapidly shifting to AI-proximate sectors, while traditional sectors risk stagnation.

• Recursive Tech Acceleration:
  From factory robots to orbital data centers, the episode spotlights a self-amplifying feedback loop—the “innermost loop”—where AI builds the tools that build more AI, reinforcing exponential acceleration.

• Governance and Alignment Dilemmas:
  As “corporate states” like Nvidia and OpenAI rival nation-states, new forms of governance—public benefit corporations, sovereign AI engines—are needed to ensure tech uplifts, not destabilizes, society.

• Geopolitics of Compute:
  The US dominates in finance and core R&D, China in manufacturing and deployment. The global AI arms race intersects industrial policy, manufacturing scale, and open source proliferation.

• From Truth to Deepfakes:
  AI-generated information offers hope for knowledge purification but also creates new threats to consensus reality.

• Humanoid Robotics at Scale:
  Robots are moving from factories to homes—$20,000 household robots mark the dawn of robot mass-market. The cultural and economic impact will be profound.

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Closing Note:
Peter wraps the episode with a quirky tune provided by a fan, reflecting the podcast’s blend of exponential optimism, wit, and the awareness that we’re living in a uniquely turbulent and exciting era.

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Missed the episode? Now you’re fully up to speed.

Transcript

[Peter Diamandis]

Setting new records. OpenAI hits historic growth to 100 billion in revenue.

[Alex]

I think it's entirely possible that OpenAI could hit 100 billion ARR in a couple of years. I think the easiest path is OpenAI.

[Peter Diamandis]

Remember, of course, one of the most important companies in the world that could give it a market cap of $1 trillion.

[Dave]

But of course this is an ongoing story and there are still a lot.

[Alex]

Of uncertainties as well in OpenAI's future.

[Peter Diamandis]

The big question is whether the S&P 500 is overvalued and whether the Mag 7 could continue to sort of command that level of valuation because they are driving much of the economy and much of the gains.

[Dave]

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 are there going to be many competitors in a race to the bottom? 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.

[Peter Diamandis]

Now that's a moonshot, ladies and gentlemen. So guys, I'm still getting up at like 3:30 in the morning coming back from Riyadh. How are you guys doing?

[Salim]

I'm actually okay. I get back and I learned a trick from ramez and Raymond McCauley and they said take a double dose of melatonin and in a couple of days you're good. I've actually been surprisingly okay.

[Peter Diamandis]

I actually like getting up at 3:30. It's like I've got like four hours before anybody else wakes up and it's like amazing. Dave, how about you, buddy?

[Dave]

No, I'm back on schedule.

[Peter Diamandis]

All right.

[Dave]

I don't think I ever got acclimated to Saudi actually. I don't think I slept more than four hours straight.

[Peter Diamandis]

What an amazing trip it was. I mean, just to recount one second. I mean, spending time with Eric Schmidt and Fei Fei on stage was awesome. Hanging out with Ruth Porat, the president of Google of Alphabet. I mean, what an amazing woman she is. Any favorite memories from you guys?

[Salim]

I have a selfie with Ray Dalio and I spent an evening late with Balaji talking about, you know, us, China, et cetera, et cetera.

[Peter Diamandis]

Oh my God. I had to duck out. I mean, so here we had this dinner in Riyadh that we put together basically with myself inviting and Dave and Amjad from Replit, and we had Cathie Wood and Balaji debating China versus us. And I was like, oh, this is going to be a Long conversation. Balaji can talk. Oh boy, can he ever talk.

[Salim]

Yeah. He's got some great framings though, right? He talks about the left versus right in the US as scribes versus vibes. So the left is scribes and they're like crime is down by 50% and the right is vibes. They're like, well, it doesn't feel good. Really great framing.

[Peter Diamandis]

Having breakfast with Lou Bhutan was awesome.

[Dave]

I know, I missed that. The biggest miss of the week.

[Peter Diamandis]

I know. But we'll get him on the pod. He said 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. Any other favorite memories?

[Dave]

Philip Johnston was doing it. He invited me to the SpaceX launch. I have 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.

[Peter Diamandis]

See the launch of the first H100 in orbit.

[Dave]

His H100 first chip in orbit. Yeah, that's not a huge amount of compute but certainly a bellwether for humankind if we go down the Dyson sphere path. So that was really fun. He's a sharp dude.

[Peter Diamandis]

Yeah. And for me hanging out with Bill Ackman was fun. He's getting involved in some of the stuff that we're doing. And Bob Mumgaard, the CEO of Commonwealth Fusion was at our dinner. So it was great to do it.

[Dave]

Time with Bob actually he, he's deep, you know, he's an MIT PhD in nuclear stuff. So he, he knows all the details of sustainable fuel. There's a lot about it that I didn't actually realize that was.

[Salim]

There was one thing that he said that blew my mind because 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 megawatts. I mean if we have fusion working, fusion in seven years, it's game over, right?

[Peter Diamandis]

Yeah. I mean I asked some of the fusion guys at XPRIZE Visioneering, what about Helion, right? This is the Sam Altman backed 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 Salim, one of my favorite moments was our last night going out to the farm. Remember that?

[Salim]

Oh, that was, that was so great. We went for a much less with. With 20 kind of fairly senior Saudi Folks.

[Peter Diamandis]

Yeah, it was.

[Salim]

I had coffee with.

[Peter Diamandis]

Let me just let me finish on, let me finish on that one. We had one of our super subscribers and super fans in Saudi has this beautiful farm right near MBS's, you know, private homes. And we come out there and he's like, he's set up in this Majilis for. It was you, me, Eric Poulier, Imad and Max, Max Song. And we did a sort of a private moonshot conversation, Q and a with these 20 senior Saudis over there, past Ministers of Education and commerce, finance, all, all in the circle. Yeah, it was awesome.

[Salim]

This is a. It turns out to be a very old tradition. I remember at the UAE they used to run these and it. They was the, the leader would host and anybody, anybody could apply to go to this and talk directly with the leader of the country. It was kind of incredible. Very.

[Peter Diamandis]

I loved when he pulled out, I loved when he pulled out the microphone. He had the speakers and we were, we were on stage doing Q and A. You know, it was, it was great.

[Salim]

I was scared for a second. He wanted to do karaoke and I was like, oh.

[Dave]

Well speaking of Magilis, I thought the Sage Majilis was the head of 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 was taking credit for being the launch point of Bitcoin. So he wanted to eagerly make Bermuda the launch point of Sage of governance.

[Peter Diamandis]

Yeah. We unveiled a top secret project that Imad and Salim and Dave and I have been working on called the Sovereign AI Governance engine or sage that would allow any country in the world to be able to generate policy as these disruptive futures are coming. So that was awesome. But guys want to jump into the episode?

[Salim]

Wait, hold on. I just want one feedback. So I had a coffee with Abdullah the next day.

[Peter Diamandis]

Abdullah?

[Salim]

No, Abdullah.

[Peter Diamandis]

No, Abdullah.

[Salim]

Yeah. And he said he got feedback from the group that was one of the most powerful evenings they'd ever had in their lives. So that was really incredibly generous of him.

[Peter Diamandis]

That's awesome. Yeah. And I met with Abdullah 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 when I 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 key technologies, the commitments they're making to AI. It's, it's super. Fun. But I think we should get on with the episode. How do you guys feel about that?

[Salim]

Sounds good.

[Dave]

I think we should just. So much, so much in here. We got.

[Salim]

I'm a little nervous because we're trying to cram a lot into a short space.

[Dave]

Well, hey, man, it's exponential time. Like Alex is always saying, we're going.

[Peter Diamandis]

To have to get used to sleep during the singularity. Awg. Good to see you, buddy. Sorry, we missed you too.

[Alex]

Yeah, likewise.

[Peter Diamandis]

But let's.

[Salim]

Every time I was having a technology conversation, Alex, I was like, wow, I wonder what Alex's take on this is.

[Dave]

Yeah, no kidding. It's like withdrawal.

[Peter Diamandis]

Well, everybody, welcome to Moonshots. Another episode of WTF just happened in technology. This is your weekly dose of optimism and catching up with this hyper exponential world. And let's jump in. First major chapter here is the speed of change. And here we go. So setting new records. OpenAI hits historic growth to 100 billion in revenue. So here's the chart. It's reaching 100 billion revenue in two and a half years compared to Nvidia, which took eight years. Amazon took seven years. Google took 10 years. So it's just speeding up. And Alex, what's your prediction of when we're going to hit 100 billion with the next company?

[Alex]

I think it's entirely possible that OpenAI could hit 100 billion ARR in a couple of years. 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 think it's not that difficult to imagine OpenAI tripling revenue year over year for the next two, two and a half years and getting there in 2027. The key again is just taking knowledge work and taking service economy and condensing distilling that down to agents. Running 24. 7.

[Peter Diamandis]

Incredible.

[Dave]

They're only, they're only forecasting 2 1/2x growth year over year. It's a very achievable target because 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 then figuring out how to monetize that. And that's the part that attacks Google. So that part is a lot more up in the air. And Amazon for sure, for sure. But I can't see 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 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, Nvidia would look just like OpenAI on this. So, so that part is already very, very real. So yeah. 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.

[Peter Diamandis]

Every week, my team and I study the top 10 technology metatrends 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 metatrends with you, I write a newsletter twice a week. Sending it out is a short 2 minute read via email. And if you want to discover the most important meta trends ten 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 dashmandis.com metatrends 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 and 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 going to cut back on my incredibles. But hey, this is incredible. All right, let's, let's move on. I found this one fascinating. This is the US leading the world in data centers. So I would say Incredible. We have 5,426 data centers compared to the rest of the world. I mean, look at that. Germany's at 529, China's at 449. We have more data centers than the rest of the world combined.

[Dave]

Really? You tried to research this? Alex, I want to get your take on this, Alex, because it definitely is juxtaposed with China having massively more power and massively more core manufacturing ability. This one really surprised me. But I couldn't find online any detail behind it. So what's the understory here?

[Alex]

Yeah, no. Remember the Internet was born here. The US has lots of available land. Hyperscalers are largely based here. We have access to capital. 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 NEO cloud or Stargate type data centers. This is just total number of data centers would have a modality in the us.

[Dave]

Is there an AI petaflops version of it which would be more meaningful than just raw count of data centers?

[Alex]

Almost certainly. Maybe we should cover that in the next episode.

[Dave]

Yeah, I couldn't find it.

[Peter Diamandis]

Our next story here is Nvidia reaches $5 trillion market cap. Holy cow. It's up 1500 percent in the last five years. The market cap is greater than the GDP of every country in the world except US and China.

[Dave]

Yeah, that metric is frustrating because you're talking about the asset value of Nvidia. The value of the company, if you were to acquire, 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 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 Switzerland in terms of if you were to try to buy Nvidia with your own money or buy Saudi Arabia, if they would sell it, the cost of buying the entire country, all the land, all the assets, all the buildings, which be the same as buying Nvidia. And that is staggering enough we should be comparing apples to apples because it's already mind blowing. It's right between Switzerland and Saudi Arabia. So if you want to buy Switzerland or buy Saudi Arabia or buy Nvidia, those are your.

[Peter Diamandis]

So we're going from nation states to corporate states in a way that's incredible.

[Salim]

A few years ago we looked at getting a bunch of investors together and actually buying a small country on exactly that basis. In 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 on part of the WTO and you could really do some interesting things. So that was interesting.

[Peter Diamandis]

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.

[Dave]

Well, another.

[Alex]

I'll take the other side of that, if I may. I mean, please. History tells us at any given time that the market values what's both scarce and needed. So we've seen multiple East India companies, we've seen various scarcities, including oil, pop up over the centuries. I would argue that this is actually just a market signal that right now compute is both scarce and needed. But the way the game of capitalism works is this value wants to diffuse over many companies and probably many countries over time. And that diffusion is going to be a net wealth creator.

[Peter Diamandis]

That's very true. I mean, there are 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 exciting, which is the decoupling job openings versus S&P 500. Those of you looking on YouTube or listening, 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, total job openings increase, 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. And so the question is, what happens in late 2023? Well, if you look at the data, it says ChatGPT gets launched. Let's dive into this one. Dave, you want to jump in?

[Dave]

Yeah. Well, so I love the storylines that'll end up in the history books as opposed to the news du jour Taylor Swift type stuff. 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 happening. And then a big rebound from COVID and now we're back to 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, you know, just sort of like a blip Covid recovery thing. But I think, you know, Alex will look at this and say, yeah, this is, this is the beginning of the inevitable.

[Peter Diamandis]

Alex divide by zero.

[Alex]

Actually, 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 changes in Federal Reserve interest rate hikes 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 so story. This is the beginning of decoupling of labor and capital. But I think that this might speak.

[Dave]

Well, I'll give you the opposite. We'll know in hindsight, obviously, 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, which is very unusual with the S and P being at all time highs like this. So that would be the counter, counter argument that. Well, no, if you're 21, 22 trying to find a job right now, you're really feeling something unusual. And we'll see it later in the deck too. The layoffs at Amazon while recording earnings. So there's some other data points that would indicate.

[Salim]

Yeah, 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 the economy. That's a big deal.

[Peter Diamandis]

I tweeted out that AI is no longer an industry or sector, it is the economy. Elon responded saying AI and robots are the economy, which is true. One of the indications of The S&P 500 going up is an indication of market confidence where there's optimism about the future and people are investing. And I've got to believe that's fundamentally true. People are excited about the mag 7 or 8 or whatever they're up to these days, basically taking off and driving the. Their valuations through the roof.

[Salim]

Just, just to 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.

[Dave]

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 bellwether 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 bellwether 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.

[Peter Diamandis]

Mean, the big question is whether the S&P 500 is overvalued and whether the Mag 7 could continue to sort of command that level of valuation because they are driving much of the economy and much of the gains. Dave, what do you think?

[Dave]

Well, you know, Leopold actually, you know, he went long intel and long, long Broadcom, but he shorted the semiconductor index as a whole. And I didn't dig in on that until yesterday, but that's 20% of that is Nvidia that he shorted when you short the whole sector. So that would be the argument that, look, if the whole thing is going to collapse, it's because Nvidia in particular is valued like Switzerland more than Switzerland. And is that rational? And I think Alex is dead right. Right now, Nvidia is right at the crosshairs of the true scarcity. AI is going to be huge no matter what. There's no doubt about that. But is that scarcity sustainable or are there going to be many competitors and a race to the bottom?

[Peter Diamandis]

It's going to defuse, 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 chip manufacturers. So it will diffuse, but we'll see sort of the peaks perhaps of Nvidia.

[Dave]

Well, really specifically, too, Nvidia is, you know, Mellanox is Interconnect, is a million 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 we'll get, we'll get to that later, actually. But that's the rest.

[Peter Diamandis]

I found this clip by Geoffrey Hinton. Right, Jeff. Nobel Prize winner Geoffrey Hinton was on stage at 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 he has been so concerned about digital superintelligence and he put forward an optimistic view of AI. Let's play this clip from Dr. Hinton and then let's chat about it.

[Eric Schmidt]

More optimistic than I was a few weeks ago.

[Salim]

Really.

[Eric Schmidt]

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. 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.

[Peter Diamandis]

All right, Salim. A mothering instinct in our super intelligence. I mean, I buy it. I'd love that. I want this digital God to be sort of loving and warm and supportive and uplifting of all of humanity. How do you feel?

[Salim]

You know what you often find when something brand new comes along? The first instinct is to freak out. Right. And remember, you identified this in your Abundance book, Peter. We have this amygdala that goes nuts because it's on a survival bias. We are geared for 4 billion years to scan for danger and then run. And when we see something new, like an autonomous car, the first reaction is, oh, my God, that car might kill somebody. Let's ban the car until we figure it out. And Brad Templeton used to joke, we 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 elegance of an autonomous car come to you. And often also people that are very focused on technology, folks like certain that have spent most of their lives focusing 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 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.

[Peter Diamandis]

We can hope.

[Salim]

It's such a visceral, subjective experience to parenting or whatever that I'm not sure how that we'll see.

[Peter Diamandis]

We have to give the AI oxytocin. Alex, what do you make of this?

[Alex]

Yeah, I think it's difficult to buy. There 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 this case, it seems Like Jeff is basically rearticulating the orthogonality thesis with perhaps a veneer of digital oxytocin, as you said, Peter, I think, I think that's unlikely and probably not that robust a means of alignment for superintelligence. I think if the goal is to have a more 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 think instrumental convergent type approaches are more likely to guarantee or provide robust, robust guarantees of friendliness. So James Miller wrote, I think, an excellent essay called Reasons to Preserve Humanity on Less Wrong that enumerates a couple dozen different reasons for why superintelligence should play nicely with humanity. Out of self interest, not out of some sort of oxytocin induced, surgically added reason. That sort of artificial.

[Peter Diamandis]

All right, I want to say one.

[Salim]

More thing about Jeffrey, just really quick. He did a podcast with Jon Stewart a few weeks ago and laying out and Jon Stewart kind of said, I'm a newbie, take me through deep learning and the, 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 pocket propagation, et cetera. He did an amazing job of laying that out.

[Peter Diamandis]

All right, I'll take a look at that. Here's our next story. Deepfake of Jensen Huang draws more views than the real one. I found this absolutely 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 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.

[Alex]

They're not us.

[Peter Diamandis]

I love that. The fake broadcast saying don't trust a. That's hilarious. You know, the numbers are pretty staggering. It's one and a half billion dollars lost globally for deepfake related fraud since 2019 and only 24.5% according to the numbers here. People can actually spot deepfake quality and AI detectors fail up to 50% of the time. So this is going to be a thing. This is going to be a thing.

[Salim]

I think reality may have just lost the algorithm war.

[Alex]

Yeah. I think in this case, if you look closely at the video, the lip syncing was poor. I think in the short term, Detective.

[Peter Diamandis]

All right, you're part of the 24% that can notice this. Okay, Alex, you win.

[Alex]

Definitely notice the poor lip syncing. I think 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 don't think in the long term, this is a deal killer for us drowning in AI generated slop, counterfeit livestreams. I think this is very tractable.

[Dave]

Yeah. Within the US I agree. I think if you look globally, it's a little more of a concern. There's a real possibility that regimes lock themselves in. 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 would be more concerned about in some nation where they're not as aware of AI watermarking or whatever, they're seeing things. I wouldn't just believe in.

[Peter Diamandis]

Our nation isn't aware of that. And Alex, you made a point we were discussing a year ago, that AI generated speech is far more compelling than human speech. All right, let's move on to the AI wars. This is Xai versus OpenAI versus Google.

[Dave]

We're just writing off Anthropic. Just.

[Peter Diamandis]

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 anthropology.

[Dave]

Dario would really object to that.

[Peter Diamandis]

Listen, and I. No, I love anthropic, and I want him on the pod for sure. All right, but let's jump in here. So I'm going to rant on this one. So XAI launches Grokopedia. I had a friend of mine, remember Justine from Singularity University? Celine, sure. Yeah. So she sends me this text. She goes, because she heard our pod. I was arguing or 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 she says, hey, Grokopedia's out with your. With your Grokipedia 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 Grokopedia is being written by Grok. It's writing, updating, fact checking it on a real time basis. And they have 900,000 articles compared to Wikipedia's 8 million articles. My particular entry here was 8,500 words on Grokopedia versus 4,800 on Wikipedia. But it was so well organized and I just absolutely loved it. Any comments?

[Alex]

I'll throw in a comment. I want to reason by analogy. There's 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, purer and pure semiconductor. We don't have a science right now for knowledge purification, but one could imagine somehow near 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 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 whatever the starting knowledge was, maybe we arrive at some sort of ground truth through this result. Really cool, but would be interesting if that ended well.

[Peter Diamandis]

That's Elon's objective, right? Basically trying to from first principles derive truth. I put a quote down here from Elon says a step towards Xai's goal of understanding the universe, which I have two comments please.

[Salim]

One is, you know Peter, you know I've talked for a long time and written in the book that staff on demand and a community doing work is essentially a proxy for AI.

[Peter Diamandis]

Yes, right.

[Salim]

Driving is 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, 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 truth seeking maximizer. 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 that no human being will take the time to do. And it'll do it much more accurately.

[Dave]

Well, what Alex described is really, really similar to the original Google page rank algorithm where just starting from nothing, iterating between a reference link and a site and assigning credibility back and forth in this self annealing process, a simulated annealing process. And it worked. I mean they don't need it anymore because they have so much data flowing in. But when they were just a little startup bootstrapping, it worked really well. Alex's idea.

[Salim]

This is also my comment. I use PageRank as an example when people ask what is AI, et cetera. And I say, look at PageRank. It's evolving a completely separate type of intelligence for crawling billions of pages, 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.

[Peter Diamandis]

Well, just thank you to Justina Zander for pointing this out to me. I'll also mention real quick, I checked and turns out Wikipedia has a budget of 170 million a year. About 100 million of that is labor paying everybody to do this work. Some of it's voluntary, a lot of it is not. All right, let's move on.

[Salim]

Also, just a shout out to Jimmy Wales for creating Wikipedia and managing for all these years. I mean, what an unbelievable gift of humanity.

[Peter Diamandis]

I mean, we're watching the transition from the Encyclopedia Britannica to Wikipedia to Grokopedia, but Grokopedia was low hanging fruit. Any of the AI companies could have taken this on and I think it's going to become pervasive. I know I'm standing up a new website for diamantis.com, and the very first thing I'm putting at the top is my rockipedia link. You want to go deep there? It is so true to AWG's vision. This is an important conversation. And Alex, I actually read this paper. So this is a new AGI benchmark which gives ChatGPT a 57%. But I would prefer if you explained it because it's pretty amazing. And Saleem, 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, and it's a pretty powerful concept. Alex, would you take us through it?

[Alex]

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 past years as well. 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 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 more of it, the idea is instead to look at human psychology. So there is a theory that's popular in human psychology. It's called the Cattell horn carrel or CHC theory that decomposes human intelligence into 10 different factors like the ability to reason quantitatively or to do visual processing. So the idea behind this paper is to define a benchmark that's directly inspired by the CHC theory to decompose a intelligence of frontier models into 10 different categories with various subtasks associated with each category. And the main upshot of benchmarking GPT4 and GPT5 auto critically not GPT5 Pro. According to my reading of the paper, the main upshot is surprise. Intelligence is jagged. The frontier models are stronger at some skills weaker and other skills. Whereas the the archetype, the archetypical human would perhaps have a more uniform distribution of their skills across these 10 categories. But I would add the important caveat again, just based on my reading of the paper, they didn't actually benchmark the bleeding edge frontier models like GPT5 Pro.

[Peter Diamandis]

For those looking at this on YouTube, you'll see these 10 different categories. These are human like skills, knowledge, reading and writing, math, reasoning, working memory, memory storage, memory retrieval, visual auditory speed, and they're benchmarking GPT5 and GPT4 against those. But it's a measurable benchmark, right? I mean the other option is the pornography definition. We'll know AGI when we see it. Dave, what do you want to add on this?

[Dave]

I'd love to get Alex's take cause I assume a 10 on each axis on this radar chart is human. So you're trying to match the outer.

[Peter Diamandis]

Ring here, but it's really, it's all humans. I mean, no human is going to match 10 on this.

[Alex]

Maybe quote unquote, well educated adult.

[Dave]

Okay. Yeah, okay. Well, you know, 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, but you know, it's so asymmetrical and I don't understand the memory and storage axis axis and the speed axis. That one's saying the best AI is miles behind humans and speed. I don't quite get that.

[Salim]

That was the part that struck me. Also, speed seemed off.

[Peter Diamandis]

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. But memory I found incredibly perplexing because I thought these AIs have incredible memory. Alex, what's your take on speed and memory?

[Alex]

Yeah, based on my read, the memory 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 RAG type mechanism, they don't have the ability to remember things that you told them a long time ago. But again, I want to caveat this benchmark. I love benchmarks in general, as I 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 bleeding edge reasoning efforts. This is just. If you read the paper, it's just GPT5 auto. So I'm wary to put my finger on certain deficiencies as being in any way indicative or instructive of the limitations of AI.

[Peter Diamandis]

Meaning there are other models that would perform much better on these 10 parameters.

[Alex]

Or light modifications of existing models that, as with RAG retrieval, augmented generation make them superb at certain skills. So I think that where this is useful in my mind is just having yet another benchmark as a proxy. It's a start, an important start for measuring human capabilities against AI capabilities. But when I see 57%. We've talked in the past on the POD about In the style of Ray Kurzweil, the moment you've passed 10% or maybe even less, you're basically halfway there getting 57% on a general human psychological benchmark that, that indicates to me that probably with a little bit of reinforcement learning, a little bit of bureaucracy, agents, framework, scaffolding, probably get to 90% today.

[Peter Diamandis]

Amazing. Well, by the way everybody, just some forward looking news. Ray Kurzweil is going to be joining us on the POD next month. Talk about his predictions for 2026. Yeah, it's going to be, it's going to be a lot of fun.

[Salim]

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 neocortex 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.

[Dave]

So.

[Peter Diamandis]

But I thought about you, Salim. I thought about you specifically on this one because 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.

[Salim]

What I'm saying is I disagree with the premise because AGI for me would incorporate these other things. Okay, so if you're measuring pure IQ test type stuff, fine. This is a great benchmark. And we can kind of, I wonder.

[Peter Diamandis]

Who can have the first AI spiritual leader who proclaims a religion and believes.

[Salim]

Oh, I think that's very doable. You know, I remember once spending time in the, in the Himalayas with some of these gurus, right?

[Dave]

What?

[Salim]

And I sat with these guru 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. And that's kind of an LLM, that's your neural network.

[Peter Diamandis]

So, all right, I'm predicting here, I.

[Salim]

Think it was very doable.

[Peter Diamandis]

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, the OpenAI foundation 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. Saleem, you and I did that move with Singularity University, converting it from a nonprofit to a for profit and spinning out A.

[Salim]

Exactly. This was a benefit corporation with a nonprofit alongside.

[Peter Diamandis]

And so here's the ownership, actually.

[Dave]

So a B Corp can do anything a C Corp can do. So, you know, go public, raise money, be profit.

[Salim]

This is a great point that you're making, Dave, for the viewers. From a taxation and legal perspective, a B Corp is exactly the same as.

[Dave]

A C Corp, which is every other public company.

[Salim]

The detachment is that in a C Corp if the board is obligated towards financial optimization and can be sued if they're seen not to be doing that. Whereas in a B Corp the board is obligated towards whatever the mandate is of the B Corp and can be sued for that. In theory.

[Peter Diamandis]

I love the percentage ownership here. So here we go. Microsoft owns 27%, the nonprofit owns 26%, and the remaining is owned by OpenAI PBC at 47%. And this restructuring is going to allow OpenAI to go out and raise money. But here's the rub. Here's the rub. Elon's lawsuit against OpenAI remains active and his bid to try and block the restructuring was denied in court. But the case will proceed to trial in the spring of 2026 is what I read about. And the implications are interesting. Right. So number one, the court could order a rescission that unwinds the OpenAI for profit PBC structure and restore the nonprofit control. Number two, 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 a year from now.

[Dave]

Yeah, Alex, if you look at the valuation of the company, the market does not believe any of those problems will actually be material for sure. So it seems unlikely, but I think it is. You know, Yelen'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 Elon even said it like, if that were legal, everybody would do that and start your company as a charity. So I think the courts will have to say, yeah, you can't do that. And the penalty would 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.

[Peter Diamandis]

They were fined a dollar.

[Dave]

One dollar. Yeah. That was the whole Microsoft, the whole, kill Netscape, destroy the entire Marc Andreessen, you're out of a job. What's the cost? A dollar.

[Salim]

Wow. The same thing happened, by the way, in the 50s when Goodyear and GM banded together and bought all the train tracks in LA and ripped them out and privatized them and just ripped them out. And the court, there was an antitrust, and they go find a dollar.

[Peter Diamandis]

Okay.

[Alex]

I'd like to point out, maybe quickly, 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 stated goal of the new OpenAI nonprofit. One of their first goals is to spend $25 billion using AI to solve disease. And. And I think that's a tremendous societal good. We've spoken here in the past about how AI has the potential to solve disease and biology in the next five years. I think this is another arrow in the quiver of making that happen. Second, societal good. One of the things I worry about is what happens if a private Frontier Lab develops incredible superintelligence and decouples from the human economy. I think putting OpenAI on a trajectory where it can reasonably be explored. Expected to go public sometime in the next two to three years. I think an IPO by OpenAI and other frontier Labs and putting the equity in the hands of retail investors and index funds 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.

[Dave]

Well, corollary, all that too, Alex. I think that everyone's like, hey, Brendan Foodie Mercour, 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 you think, what's my life mission? Am I starting a company? Am I 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 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 OpenAI, 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? I ask all these Entrepreneurs, what's your OpenAI strategy? And a lot of them have no answer. But you think about the scale, just of what Alex just said.

[Peter Diamandis]

This is the largest nonprofit in terms of capital base, and it will be even bigger, will reach a half a trillion dollars. And Dave, you remember you and I met with. I'm not going to say who it is because I don't think it's been officially released. The individual who's a co founder there that will likely run this OpenAI foundation, and we're talking about potentially spinning up some X prizes 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 XPRIZE is we leverage every dollar in the purse by 60 fold. So imagine if $100 billion becomes $6 trillion of leverage. What a fun time ahead.

[Dave]

Well, think about the scale, too. It's just exactly a great point that a normal big, big x prize is $100 million prize. And here you're talking about $130 billion, which is, 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. $100 million prize could do that. Every day of the, of the week.

[Peter Diamandis]

I dream about, I dream about having 10 $1 billion prizes for the 10 biggest problems. It would steer where students spend their time, where founding partners focus on building companies. I mean, it would be sort of a, a flame to the entrepreneurial moths out there.

[Salim]

Can I, can I take the other side of this just for a second?

[Peter Diamandis]

Sure.

[Salim]

Of your signaling greenwashing. They're putting all this money over there and then going full speed towards the IPO and hoping that the, the good that they can do will. Will kind of balance the crazy path to greed.

[Peter Diamandis]

Do not notice the man behind the screen. And speaking about greenwashing, here's our next story with Sam Altman. Turned green here, a little bit of shrek 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. We've said this before. A trillion dollars here, a trillion dollars there. It's becoming a word for far too popular these days. I mean, the speed is incredible.

[Salim]

So OpenAI, to use your word, Peter, it's incredible.

[Peter Diamandis]

It is incredible.

[Salim]

You got to hand it to Sam for the unbelievable sheer gumption for just going for It.

[Dave]

Yes.

[Peter Diamandis]

Wow. No, Amazing.

[Salim]

Just incredible.

[Dave]

Well, hey, let me put some, Let me put some numbers behind that. So here he is. I'm going to spend a trillion dollars a year, I'm going to 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 100 billion, but the equivalent would be is if you have a household with $100,000 of income and your husband or wife comes home and says, honey, we should spend 10 million a year on houses and stuff. That's the equivalent metric. Okay, so just to put it in context, that's the gumption, like you said, behind this claim. But hey, he's done everything he said so far, so it's plausible.

[Peter Diamandis]

So their ipo, I'll try that with.

[Salim]

Lily and see how far I get.

[Peter Diamandis]

Well, you did that when you mortgaged your house to buy Bitcoin, which in retrospect turned out to be a good idea.

[Salim]

We didn't put all of it in, unfortunately.

[Peter Diamandis]

But still, do you still mortgage it again, Alex?

[Alex]

I think it's actually like a pretty tiny number. Global GDP is upwards of 100 trillion. So just saying. We're going to spend 1% of global GDP on AI infrastructure.

[Salim]

Yeah, but this one guy, Alex, he's in one company. One company, right?

[Dave]

Yeah.

[Alex]

So if you have like five frontier labs each doing that, that's still like 5% of global GDP. I think this is a drop in the bucket. And that's before AI starts to radically grow the global economy. This feels on the low end to.

[Peter Diamandis]

Me, and we saw this last time. Compared to the railroads or telecom infrastructure, the AI build is still as a percentage of the US GDP on the low side. But here are the numbers. OpenAI is working on the largest IPO in history, with targets to do this in 26, 27. And the other point made here is that they're planning to build 1 gigawatt capacity per week. At 20 billion per gigawatt, there are 52 weeks in the year. That's a trillion dollars a year, which is pretty extraordinary.

[Salim]

Just to give people a context. A gigawatt is enough to power the whole of Dallas Fort Worth. It's a truckload of energy.

[Peter Diamandis]

Incredible. There we go again. Sorry. Okay, time to drink.

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[Peter Diamandis]

Okay, let's go. Let's visit our friends at Claude and I love this article Alex that you found Claude shows signs of introspection a model that is partially self aware Claude 4.1 take it away Alex It's a really interesting paper.

[Alex]

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. 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 of incepting an externally imposed thought onto a model and detecting whether a model is able to recognize that it's having external thoughts intrude upon its internal activations.

[Peter Diamandis]

And isn't that called psychosis?

[Alex]

I think that might be slightly different. I think this is closer to some sort of maybe telepathic forcing. You were 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 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.

[Peter Diamandis]

So the question is, what does self aware mean? It understands it's an AI model. It understands what?

[Alex]

Alex 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 activations are, and able to reason Based on that.

[Dave]

Well, for the neural net geeks out there too, this research can only be done if you have access to the internal weights and activations of the neural net. So it's not inside anthropic. But now that meta is not going open source, 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 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 the normal stick a little probe into a rat. And so it's an incredible research playground and these ideas of what's the definition of self awareness and can I inject a thought? 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 somehow is complementary. 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. And as soon as you go API only and you start. Because on that radar chart we saw earlier, you're operating outside the neural net and trying to define AGI from outside the neural net. But it's so much more powerful to operate inside the neural net. But we may be in danger of losing that as a tool. Hopefully the Chinese models will keep coming out. Alex is warning me against using them too much.

[Peter Diamandis]

Saleem, final word from you.

[Salim]

This reminds me of Hod Lipson who's a professor at Columbia and he builds self assembling robots and evolutionary 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 five years. 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 five 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 Deep Seq and you'll get to that same point. And I remember Dan Berry 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 isn't a Hamilton 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.

[Peter Diamandis]

Okay, let's, let's move to our friends at Alphabet. An incredible quarter for them. They topped $100 billion in quarterly revenue for the first time ever. Google cloud grew at 34%. So just good on Alphabet and Google, they're rocking it. A couple of other elements that Google and Alphabet have announced a new marketing tool which I love called Pomale. And this is Google's AI marketing tool. Let's take a look at this video and then we can discuss it because I think this is, you know, again, Google provides all of these incredibly useful end user tools that make them so, so powerful as a company. So pomoly will understand your business DNA and prompt your own campaigns or get suggestions. All right, yeah. Bottom line, this is an AI tool from. Let's go. Yeah, from DeepMind that helps small businesses create on brand marketing campaigns. So Pomalee will analyze your business website, learn the tone, the color, the style to create ads that match that brand and generate ready to 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?

[Dave]

Well, 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 Lycos and Altavist. And nobody remembers all this, but there was 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 open it up to the economy, 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.

[Peter Diamandis]

Gil Elbaz created that engine.

[Salim]

Right.

[Peter Diamandis]

And yeah, incredible. Oh, there I go.

[Dave]

Incredible.

[Peter Diamandis]

So hey, you just, just drinking as.

[Dave]

They roll these capabilities, I just want.

[Salim]

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 that's kind of incredible what this struck me as was another example of Peter, in our book 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 the ad business. And this is now pushing the boundaries of that further and further into the creative process.

[Alex]

Just to comment Peter on this as well, I think the elephant in the room here is that the visual ads that are being generated are not being generated pixel by pixel. I've spoken on the POD in the past about how in the future user interfaces 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 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 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 compute expensive at the moment to generate a custom image pixel by pixel for an ad. But it's relatively likely.

[Peter Diamandis]

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 for advertising.

[Dave]

Well, you know, it's charmingly retro in all of this.

[Salim]

Hold on, Peter. Peter, you've hit on something unbelievably huge here.

[Peter Diamandis]

This. Okay, what's that?

[Salim]

All of this is assuming a human consumer, right?

[Peter Diamandis]

Yeah.

[Salim]

And very quickly, which is short. Go through that. Yeah. I remember having this conversation with, you know, we were advising Procter and Gamble and we did a workshop with them and they're like spend a huge amount of R and D on what color should the Pampers box be to attract some design. At what level? I'm like, well, my wife has 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 that changes everything. I think that also has to be taken into account. So maybe this is just a short term thing that Jarvis Equivalents take over.

[Peter Diamandis]

Jarvis will buy everything I need because 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 Googleverse here. So we're seeing Google AI Studio introduce Vibe coding. So Vibe coding is now available on Google Studio. No coding or API needed. Dave, do you want to take this one? Or Alex?

[Dave]

Well, it looks a lot like Replit and Lovable, so we'll see how that shakes out. This is the big guys stepping on the toes of the little guys.

[Alex]

Yeah, I used it. It was a fantastic experience and I think so 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 single self contained file. So it can create multiple files of code, which is very important for certain sorts of apps. So I ran it of course through my favorite eval for Vibe coding, which is create a visually stunning cyberpunk first person shooter. And it created a visually stunning dashboard, sort of an intro lobby dashboard for the FPS. But I had to prompt it to create the rest of the game. But what it did create was visually stunning and I think it's a promising first step.

[Peter Diamandis]

I am curious what the interaction with Replit and Lovable will be. We spent a few days with amjad Massad, the CEO of ReKit, and I've been playing with repl.it on my phone and computer. Sort of Vibe coding different apps, which is fun. One of the things I had a long conversation with Jack Hickory while we were in Riyadh and one of the things that Jack said, which I love, is every morning instead of becoming a consumer, become a creator. So usually I get up and I'm reading all of Alex's texts, all the breakthroughs that he found last night. And I'm just constantly as all of us are consuming hundreds of articles over the course of of the week, maybe 20 or 30 per day. And Jack was no, no, no. Every morning I'm going to Vibe code something. Every morning I'm going to create something. And I think that creator mindset is so critically important for us to be using. So a conversation with your AI and creating something every day would be super fun.

[Alex]

All right, what were you creating?

[Peter Diamandis]

I was creating an app on my phone last night to remind me to take my pill packs because I have five pill packs a day and so it will now text me 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 sort of an aging adjunct to my health. Okay, moving on. Let's go on to the chips and data center wars. A lot going on here 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 megafactory that will combine Nvidia's Omniverse with Samsung's chip, making for up to 20 times faster performance. Blackwell chips have generated $500 billion in business so far. Again, a nice chunk of change. Alex, what do you make of this one?

[Alex]

This is what recursive self improvement looks like, peter. This is GPUs AI being used to optimize chips to make more AI. And there are so many applications ranging from computational lithography to fab optimization for this. 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 and that's the faster looks like.

[Peter Diamandis]

This is the economy, right? That innermost loop is the economy going.

[Alex]

Forward, certainly the future of the economy.

[Peter Diamandis]

Yeah, I did some reference checking here. So 500,000 Nvidia GPUs that will draw somewhere between a quarter to 0.4 gigawatts of energy. There's no single site in China or the west that compares. So the Chinese top centers topping out at 10,000 to 35,000 GPUs. And in the US clusters like Azure and Meta are ranging from 30,000 to 55,000. And this is 500,000.

[Salim]

Wow. Does this mean the machines are now basically manufacturing their own evolution? Is that basically where we're going?

[Alex]

Absolutely, yeah.

[Dave]

That's the right way to think about it for sure. And also the AI fabs themselves have always been automated. They're all roboticized on day one. But it's the periphery around that turning it into a data center or feeding the front end of the fabric, that huge amount of investment opportunity there to close the inner loop. I think Alex really should write a book if books still exist with that title. But it's such a brilliant insight, but there's so much leverage in the inner, 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 robotics and energy. Yeah, and that's in the feeding on the front end of it.

[Peter Diamandis]

All right, here is a fun conversation. An article. Xtropic creates thermodynamic AI chips Combating industry's energy crisis. This comes from a friend of ours, Gil Verdan, who's been on my stage at the Abundance Summit. He's been on our podcast here and he's talking about a breakthrough in hardware, a technology called thermodynamic sampling units. TSUs that are using 10,000 times less energy than GPU based systems using probabilistic bits. Alex, so what does that all mean?

[Alex]

So I read Gil's paper and I'm a huge fan in general of trying to get closer and closer to the physical limits of computing. Seth Lloyd, famously, 20 plus years ago discovered, reported that the ultimate physical computer would probably, at least for serial computing, look like a black hole. Black hole as the ultimate supercomputer. So I'm a big fan of approaching the physical limits of computing. In this case though, my worry is there's such sort of a sordid history of probabilistic computing approaches being attempted and failing to keep up with Moore's Law and algorithmic improvements. This is my worry. I want to believe I want something like this to succeed, but I'm not super optimistic that this isn't just going to get steamrolled by algorithmic advances and advances in good old fashioned CMOS digital logic. It looks too much like analog computing, probabilistic computing. And remember, 10,000 times, even generously, 10,000 times energy improvement at the rate that models and algorithms are advancing and the rate that good old fashioned digital CMOS is, is improving, that may only be a few years of headroom, which a new architecture would need anyway to get off the ground.

[Peter Diamandis]

But can't we view it from the energy perspective? Because reducing the energy requirements on Earth by 10,000 fold seems staggeringly beneficial.

[Alex]

In principle, yes, but in practice, the workloads that the economy demands have to be able to run on these computers in order for you to realize this hypothetical energy advantage. And I think for better or for worse, the burden of proof is on Xtropic and Gil to demonstrate that his hardware can host workloads that are as commercially valuable as, say, the Nvidia workloads.

[Peter Diamandis]

I saw Elon and Gil going back and forth on, on X and Elon saying, so do you have something I should be looking at? And Gil's Say yes. Let me show you. So we'll see if the Muskverse gets behind this technology.

[Salim]

Celine, I have a quick comment. Yeah, Alex, can you go back to the black hole being the ultimate? Because you lost me right there and I'm sure my head's like stuck now. Can you just go into that just for a second?

[Alex]

Black holes are wonderful computers. They'd be a little bit difficult on the input output side, especially the output side, a little. But, but in principle. So you can, and Seth and others have refined this notion. You can define a generalized notion of computation and then in pure physics. So it deals with 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 fastest serial computer because state changes in terms of their quantum state evolve at the physical limit. So programing them may be a little bit challenging. Maybe you'd have to fire in like an X ray laser or gamma ray laser and maybe you have to parse the Hawking radiation. But if you can solve input output, black hole supercomputer is the way to go.

[Peter Diamandis]

I can see the title of this episode this week is Black Hole Supercomputers.

[Alex]

The ultimate black hole supercomputer on your desktop.

[Peter Diamandis]

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 v3 of Starlink. So Starlink version 3 will be coming out, will be delivering 10,000 times or 10,000 10x more capacity, 1 terabit per second and enabling large scale off world processing. And I love this quote that you shared with me last night, Alex. I added it. 100 terawatts per year is possible from a lunar based producing solar powered AI satellite locally and accelerating them to escape velocity with mass drivers. So basically turning lunar material into. Into compute and then accelerating them off the moon with a mass driver again the work of Gerard K. O' Neill and into Earth orbit. So this is the beginning of the, of a lot of things, Alex. We've been talking about Dyson Swarm, at.

[Alex]

Least what we're talking about. We're talking about disassembling the moon to build more computers to build computronium and the Dyson Swarm. And what's more remarkable, I mean just in the past few episodes of the pod, I've been beating the drum for how 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 starting to wonder whether I should be instead banging the drum for ensuring good interoperability between all of the Dyson swarms.

[Peter Diamandis]

Let's take a moment. Freeman Dyson, brilliant individual who said at some point you're going to disassemble all the planets in the solar system and create 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 satellites and computes that can be viewed as a Dyson swarm. But the real fun concept is a Matryoshka brain. So Alex, over to you.

[Alex]

Yeah, so these are three overlapping concepts. So Dyson sphere, Dyson Swarm, Matryoshka brain, Dyson sphere was this notion of having basically, and there was even a Star Trek Next Generation episode that I saw that a solid sphere at roughly Earth radius from the sun, that lots of people perhaps could live on the interior of the and enjoy nice environments and things probably not practical from a material science perspective. The stresses 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 satellites that are nonetheless collecting the energy from the Sun. Matryoshka brain says let's take multiple Dyson spheres at different radii from the sun and have the innermost spheres consume the light, the solar insolation at certain frequencies, and then radiate waste heat outward 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 Matryoshka brain, and also Jupiter Brain is another popular depiction. These are all interrelated concepts. I think if we go the trajectory of taking apart our solar system, whether we brand it as one or the other, they're pretty similar.

[Salim]

Maybe a black hole is a Matryoshka brain circling a star and we can. They can't see the light.

[Alex]

You know, 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.

[Peter Diamandis]

Two points. One, for those of you interested, Matryoshka brain comes from the matryoshka 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 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 lot of fun. All right, let's talk about energy and robotics, our final topic for today. 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 gigawatts this year. And the batteries store solar from for evening demand, replacing underperforming gas plants. And, you know, I'm glad to see this is happening. And Salim, thoughts?

[Salim]

I think this is awesome. I mean, what a testament to 15 gigawatts is an incredible number of.

[Dave]

No, it's not. No, it's not. Stay away from the word incredible. Yeah, it's a stupid, trivial rounding error.

[Salim]

How about stonking?

[Peter Diamandis]

We're going to get our subscribers drunk. So interesting.

[Dave]

Store gigawatts. Batteries. Store gigawatt hours.

[Peter Diamandis]

Yes.

[Dave]

Read the story underneath this. It's only got three hours at that power level. This is a joke.

[Salim]

Okay?

[Dave]

Just like this is like all of Alex and my interactions with government trying to do things that sound important that are these stupid little edge rounding cases. This 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.

[Peter Diamandis]

But. But let's take a look at the numbers. Right? So blackouts have been cut by 90% from 15 a year to two a year, which is great. And here's the 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. It's increased now to 32.4 cents per kilowatt hour, 44% increase. And if we continue to make the demands that we have on data centers, there's going to be a problem. The proverbial shites can hit the fan sometime soon.

[Dave]

I agree with that. But I mean California 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 is like you're down to two blackouts a year. I mean seriously, that's our expectation of what we do.

[Salim]

At least they're down. At least they're down a lot.

[Dave]

It's ridiculous.

[Salim]

There's something there, I'll point out.

[Alex]

Also just for California specifically, if folks are familiar with the infamous so called duck curve of California where the demand for electricity peaks in the evening like right after sunset and also in the morning, there is a mismatch between California, which is rich in insulation in solar energy on the one hand and the need for early evening power. I think even just a few hours of battery storage can help to smooth out the duck curve and that's transformative for California in a way that we here, perhaps in New England don't have quite the same problem.

[Peter Diamandis]

In our energy story, Google to buy power from next Era nuclear plant being revived so Google signs a 25 year deal with Next era to buy power from a revived Duane Arnold nuclear plant in Iowa. It's reopening in 2029. Provide 615 megawatts round the clock, carbon free. It's a $1.6 billion project and it's interesting that we've got these again, these hyperscaler companies that are buying energy. They're basically. It used to be that this was something the government did. The government provided a distribution network for power and you would buy it off the grid. That is no longer the case. Companies need to provide their own energy. So going all in on fission plants, SMRs soon, fusion plants, hopefully solar plants. Salim, you want to jump in and.

[Salim]

Oh look, it'll create 400 jobs.

[Alex]

Such negativity. This is huge. Yeah, this is an important bridge I think to the near future.

[Salim]

I think what this shows is that we're basically dissociating the energy sources from the grid and now we can have energy wherever it is happening in plunker data center next to it and then leverage it so the marginal energy usage around the world will totally explode.

[Peter Diamandis]

I can't wait for geothermal to really kick in here, right? There's so many places.

[Dave]

Why geothermal in Hawaii?

[Salim]

But wait, Alex, you're putting a way more emphasis than I would have thought. Tell us why.

[Alex]

Well, I think bridges are important right now. The limiting factor for tiling the world with compute is as a number of executives have recently pointed out, we have the GPUs. The problem is having warm racks to put them in. As Satya Nadella said, in the past.

[Peter Diamandis]

Few days I saw that Microsoft has, you know what, hundreds of thousands of GPUs they can't turn on because they don't have the energy for it.

[Alex]

Yeah. So I think like having bridges, like reactivating otherwise disused nuclear plants. I think this is an incredibly important bridge to the future until we get SMRs and Fusion and maybe solar and maybe new forms of nat gas.

[Dave]

Totally right. And what Chase Lockmiller is doing, also the same bridge kind of structure where you start with regular fuels, use natural gas or whatever, but it 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.

[Peter Diamandis]

Maybe you replace the boiler.

[Dave]

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 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.

[Peter Diamandis]

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?

[Salim]

It's very, it's all of the above, Peter, because we're advising Fermi America on this stuff. They're planning to do 6 gigawatts of gas turbine and 6 gigawatts of nuclear. It is very, very complicated to spin up a nuclear power.

[Dave]

I mean you can, that is the, the, the Alex Winter loop, inner loop of the inner loop of the inner loop. Like focus on that. Like, yeah, Peter, why is it four years?

[Peter Diamandis]

Could we make it three years 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.

[Salim]

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's starting to happen. It's just that this is why that sage project is so important, Peter, to rewrite policy as we need it.

[Peter Diamandis]

Listen, when the Trump administration finally says we're going to accelerate this tenfold, that's when they'll get serious about energy production. All right, these are some fun articles coming out. We're about to see the robo taxi wars coming online. So Nvidia is planning a robotaxi project to challenge Waymo and Tesla. So here are the numbers. Nvidia is launching a $3 billion robo taxi project in the self driving car race. This is a partnership between Nvidia, Uber and Stellantis. For those of you don't know Stellantis, they are behind brands like Chrysler, Jeep, Peugeot and Fiat, one of the largest automakers in terms of not the brand but building the parts. And it will use an end to end AI system called Cosmos that Nvidia has built to handle driving simulation. Interesting. They want 100,000 robo taxis launched by 2027. It's coming. We saw God 100 years ago. There was a 10 year period where we went from 99% horse and buggy and 1% cars, 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?

[Salim]

I made a prediction 10 years ago that all 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.

[Peter Diamandis]

My boys too. So here's some of the numbers. 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. Waymo has 700 vehicles and by the way, I see them all the time as I'm driving around. I must see 20, 25 of those a day. So 700 vehicles is a pretty small number. So they must have concentrations here in LA and up in San Francisco. There's 500,000 miles between collisions. With Waymo, it is the safest player out there. And Nvidia is partnering now to go live with this.

[Salim]

I love that. 3 billion is a stonking amount of money. And yet for Nvidia, it's like a drop in the bucket. Given their market cap, it is a.

[Peter Diamandis]

Drop in the bucket.

[Salim]

Notice is like a little side project.

[Peter Diamandis]

But this is where their GPUs are going next. They're going into humanoid robots and autonomous cars. Right? It's automating the entire world around us.

[Alex]

That's right. They have 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 to going going to drive out the door. But I think for many people, these driverless cars, I have one 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 generalist robot. It's going to be either seeing or driving in or owning a driverless car and it's not going to stop there. I think the same stack that we're seeing Nvidia with, with their autonomous vehicles pushing, it's going to generalize to humanoid robots on the timescale of one to three years. So this is again the beginning of the expanded innermost loop of civilization that we're seeing.

[Peter Diamandis]

On the flip side, here's the article from Uber's perspective. And just to remind folks, Dara, who's the CEO of Uber, will be on stage with us at the Abundance Summit in March. 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. If you're interested in grabbing one of those 30 seats, you can [e-mail] but 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 Dara about not only autonomous vehicles, but flying cars. And Uber is going in so many new directions just driving revenue. So their goal is 100,000 Nvidia based robotaxis beginning in 2027 and this puts them in direct competition with Waymo and Tesla. Today in a number of cities you can order up a Waymo on your Uber app, which is fantastic. Any final thoughts on this story?

[Salim]

I think this was too slow for my taste because there's like such a huge demand for this. Even Waymo only has, I think 2000 is what I looked up. There's 800 in the Bay Area, 500 in LA. We need like tens of thousands of these things. The good news is each Waymo car replaces dozens of cars that are sitting around 94% of the time. Empty.

[Peter Diamandis]

Yeah, most definitely. All right, our next story here. I love this one. Foxconn to deploy humanoid robots at its Houston AI server plant. So check this out. Foxconn to expand AI server production in Texas to half a million square feet, producing GB3 hundreds and Blackwell Series AI servers. It's got a partnership with Digit, which is Agility Robotics. We're going to have the CEO of Digit on our or the CEO of Agility Robotics on our stage this year. Saleem.

[Salim]

This stage abundance needs to be like eight days long, Peter.

[Peter Diamandis]

It's tough. I mean, I'm trying to make sure that we have enough time for all of the community members to meet each other, hang out, have conversations and have it fun. But yeah, it's four and a half days. But we'll have currently four robot companies there. I'm trying to get a fifth one from China. We'll see if we can get the new version of, 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 Garut N model. You know, this is, this is the innermost loop, isn't it, Alex?

[Alex]

It is. This is robots operating factories that make servers that go in data centers that power the robots. That's the loop.

[Peter Diamandis]

Yeah. I won't say incredible. I'm not going to say it. Not going to say it. But wow.

[Dave]

I will say there are nearly enough companies working on all the different form factors and there's room for a thousand more startups doing different variants of this. For all the mechis out there that are wondering what they should do, I.

[Alex]

Also think this is a preview.

[Salim]

Could you build a robot company that has an eight armed octopus type robot and beat everybody else?

[Alex]

I also think this is a preview of how we get. You know, you were talking earlier, Peter, about Sam's forecast of a gigabyte per week. I think this is a plausible technical trajectory for how we get there. We're going to have robots building the fabs and the factories producing the servers and the data centers. It's going to be one massive flywheel.

[Peter Diamandis]

All right, our next story in Energy is Blue Energy and Caruso partner to develop an advanced nuclear powered AI data data center. But I think the more interesting story here is that they plan to stand it up with natural gas plants and then convert it to nuclear about three 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.

[Salim]

So the wait time for a gas turbine engine today for the gas turbine stuff is about four and a half years.

[Peter Diamandis]

It's crazy.

[Salim]

It's, it's insane. Like, we advise Siemens Energy and it's, they're like sold out forever. And it's incredible. Everybody's trying to go to dump heaps 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.

[Peter Diamandis]

I want to talk a little about the China US Battle and hit a couple of different points here. So 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. Add to that that on the innovation metrics, 70% of all global AI patents are coming out of China, and 75% of clean energy filings are coming out of China. This was part of the debate that on our evening in Riyadh that we hosted this dinner, and Cathy and Balaji were going back and forth on topics like this. Dave or Saleem, you want to weigh in?

[Dave]

We really ought to have just a focused session with Antonio Gracias. And Chase Lockmiller on how to deal with this in the US because our whole investment cycle isn't geared up for this time type of investing. And China is. It's just very manufacturing heavy. And hey, we need more power, we need more melters, we need more whatever. 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 restructure? Because these are very expensive projects. They're not venture projects. They seem to work every time. The playbook is right on that prior slide. It's not a mystery. You have to be involved with the government. You can't just, you know, you need zoning, you need location, you need permits and all that. So it's just a new format for American innovation. But it's going to last for, you know, 10, 20, 30 years. So you might as well get ahead of it.

[Peter Diamandis]

I mean, imagine if Elon weren't doing what he does right now. You know, these numbers would be far worse.

[Salim]

So this, I want to make a comment here. 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 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 had a hack for this. 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 some of what Trump is doing in this case.

[Peter Diamandis]

So you just want to rewrite the Constitution. Okay, all right.

[Dave]

It's a great thought, Saleem 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 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. It does need to get rethought, but if you don't rethink it, yeah, things can go really bad. You don't take it for granted.

[Peter Diamandis]

So, guys, on one of our next WTF episodes, I want to bring some of the data that we found at FII 9, the future investment Initiative event that we were just at. 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.

[Salim]

All right.

[Peter Diamandis]

This particular chart comes from a tweet that Biology put out and he labeled it It's Happening. The AI flippening is here. And so this is a look at who's making the open source models. And what we saw this summer was open source models were being dominated by China versus the US and most definitely not Europe. And I think what's most important here is that as governments start adopting different AI systems, their ability to get access to free open models versus paying for the models from the hyperscalers in the U.S. it's kind of a land grab going on. I don't have much more to say.

[Dave]

Other than, you know, where this is really, really going to collide. I was talking to Brian Elliott 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 and last models were Terror Llama four 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 there's a bunch of projects for the military that Blitzi will ultimately end up working on that need to be air gapped and you got to use an open source model in an air gapped environment. You can't just go to the OpenAI API with super proprietary government data. But right now my only Choice is Kimi Kimi 2 running on Grok with a Q chips and the Grok cloud, which I think is a phenomenally good option, but it's all Chinese code and God knows what's inside there.

[Peter Diamandis]

So we spend a bunch of time with Eric Schmidt. I want to play 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.

[Eric Schmidt]

Who's winning this at the moment? The United States, without question. 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 build out going on 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.

[Peter Diamandis]

All right, I want to jump into robots as our last topic here. So 1X. We've had a great pod with Bernd Bornick the CEO of 1X. Look it up if you haven't seen 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.

[Dave]

My name is Bernd and today we're launching Neo, our humanoid for the home. Ain't no sunshine when she's 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 to.

[Peter Diamandis]

It intelligence in your everyday life.

[Eric Schmidt]

As someone who lives with Neo every.

[Dave]

Day, there is no experience quite as much.

[Peter Diamandis]

All right, so here are their commercials. 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 per month and you can buy it in three skin tones. I find that fascinating. But check this out. On the right hand side I was walking to my workout gym which is just outside my studio and there was this giant sticker on the ground. So this is incredible marketing. I have to hand it to them. They're doing really a super job on direct to consumer marketing on this.

[Alex]

Yeah, I pre ordered mine. Can't wait to have the experience. I do think it's interesting that in many of the scenarios for the Neo, at least in the early days, according to 1X, they're going to be tele operated and that may turn some people off. Having someone tele remote into their home doesn't bother me at all. I'm very, very excited to try this out.

[Peter Diamandis]

I think I got my order in when I was there at their facility. I'm hoping. No, they're going to be. So Berndt will be at the Abundance Summit and he's going to be bringing a number of the Neo Gamma 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.

[Dave]

Peter, when we were out there he was saying 100, 140k price point. I can't fathom how he's coming in at 20k. Look, competition. They shouldn't let us 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.

[Alex]

Yeah, if I were running this company I'd be subsidizing. I mean this is a data collection play to get a huge VLA trade in. Yeah, yeah.

[Peter Diamandis]

They're skating to where they're skating to where the puck is gonna be. So, you know, Elon said, Optimus is gonna be at this $20,000. Not price point, but cost of goods in. When they get to a millions of robots being built and eventually robots building robots again, the innermost lo. And this is. This is competition against the prices out of China, the prices from Elon and from Brett Adcock. So you've got to be competitive.

[Alex]

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. This will be for, you know, 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 think having at least one humanoid robot in your home becomes part of the new economy.

[Peter Diamandis]

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.

[Salim]

Right.

[Peter Diamandis]

As Elon has said, this is all about creating the world of abundance. I love this story.

[Salim]

I've got a couple of questions. One is I have a dog that literally looks like a teddy bear. And I'm wondering what would happen if the robot mistook the two. That would be one. And I know all the models out there, at least in this case with all the visuals and so on. It's not a kickboxing robot, which I thought was not a great marketing thing to say from the last couple episodes.

[Peter Diamandis]

Yeah, Unitry.

[Salim]

I'm excited to see what happens here.

[Peter Diamandis]

Unitree has definitely taken a different approach. And I have to say that Optimus has still got a hard metal exterior. Neo Gamma from One X came out with this soft, cuddly, warm sweater like look.

[Salim]

Very important.

[Peter Diamandis]

And then figure copied it. The latest Release of Figure 3 has the same look. So anyway, I guess borrow from the best. This is a story, Alex, that you shared. Tornoyel. How do you pronounce it?

[Alex]

I think it's Torniol.

[Peter Diamandis]

Torniol. It's an autonomous drone that ends mosquitoes. And I love this. Can you imagine? You're a tech entrepreneur and you're someplace with a lot of mosquitoes and you're just being bothered and you go, how do we End these mosquitoes and then your answer is intelligence drones. So here in this video we see this drone that is very lightweight and it is autonomously flying around. It's spotting the mosquitoes and it's zapping them with an electric grid that the mosquito is flown through. It recharges and patrols 247 from its base station, uses ultrasonic sonar to detect the mosquitoes, the beating of its wings and a kinetic interception to eliminate them. Is it like smart rocks in space or smart dust in space?

[Alex]

We're going to get nanobots. I think that will enable us to regulate ecosystems and I think in the process it's probably going to raise a number of bioethical questions. Peter, you and I and Dave have talked offline about near term futures where for bioethical reasons, or maybe even dare I say effective altruistic reasons, we're repairing butterfly wings on the one hand, but on the other hand we have drones to obliterate mosquito populations. It's going to be a very interesting future.

[Peter Diamandis]

It will, and it is an interesting right now being in the present. It's a super exciting time. I'm going to end this pod with a thanks to Rukin, one of our subscribers and one of our fans who sent us over a musical piece called don't look up, the Singularity is Near. And I'm going to play it as our outro music. But before we do that, gentlemen, any closing thoughts?

[Salim]

Awesome episode. I learned so much today. This was amazing.

[Dave]

Yeah, yeah, there's no doubt the pace, the pace of stories is really accelerating. You gotta anticipate it'll 2x every month or two. So I mean I wake up in the morning. Interesting. Keeping up.

[Peter Diamandis]

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.

[Salim]

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.

[Peter Diamandis]

Yeah, well, we're trying.

[Alex]

What about putting a black hole supercomputer on every desktop in every home.

[Peter Diamandis]

Yay. Or matryoshka brains, you know, and taking apart the moon to get us at times and. But butt breathing was our article last year or last episode. Our, our new episode, our new closing article. I think we should do that. We should have an unusual science closing piece or unusual tech. And I'll take the mosquito killing drone as our one for this week.

[Dave]

All right, all right.

[Alex]

We're ending the moon. The moon had it coming.

[Peter Diamandis]

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 everybody. If you're an 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 and they are incredible comments and thank you all for subscribing. Please share this with your friends, your family. One of the best parts of being in Riyadh, Dave and Saleem, was all of our fans there. 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 like, I love your podcast. So, Alex, you were sorely missed and a lot of fans going, where's Alex?

[Salim]

Is he joining that episode you're doing?

[Alex]

Yeah, gotta invite me next time.

[Peter Diamandis]

Okay, well, we'll do FII in March in Miami altogether, and try and line up a live podcast from FI Miami. All right, here is our outro music. 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 Al.

[Dave]

Someone's frying data with a hint of smoke. The fridge is quoting me Chill like.

[Peter Diamandis]

A cosmic joke My toaster's in love.

[Dave]

With the crypto, bro and entropy hums on the radio the satellites gossip, but who even cares? My cow just posted its own nightmares.

[Peter Diamandis]

Don't look up, the singularity is near it's loud and binary Loud and clear.

[Dave]

We built a God from electric dust.

[Peter Diamandis]

Now it prays to us out of.

[Dave]

Habit or trust don't look up, the code's gone divine Heaven's a glitch in the command line.

[Peter Diamandis]

All right.

[Salim]

Oh, the lyrics are amazing.

[Peter Diamandis]

Amazing God out of digital dust.

[Salim]

Yeah.

[Peter Diamandis]

All right, guys, awesome. Have an awesome day. Every week, my team and I study the top 10 technology metatrends 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 2 minute read via email. And if you want to discover the most important meta trends ten 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 dashmandis.com metatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode.