SpaceX's $2T Case, Nvidia's Shock Selloff, America Turns on AI, Trump Pulls AI Order, Bond Crisis?
Episode
102 min
Read time
3 min
Topics
Career Growth, Productivity, Relationships
AI-Generated Summary
Key Takeaways
- ✓Recursive AI Self-Improvement: Anthropic's hiring of Andrej Karpathy to lead pre-training signals a strategic bet that AI-driven model improvement will outpace human-led development. Karpathy's prior work—including auto-research, an open-source training tool that earned 82,000 GitHub stars in days—demonstrates his ability to architect systems where models run five-minute self-improvement experiments autonomously. Combined with Anthropic's existing infrastructure, this approach could compress the timeline to 10x annual model quality gains.
- ✓SpaceX Elon Web Services Revenue: SpaceX's S-1 reveals Anthropic pays $1.25B per month—$15B annually—to rent Colossus compute clusters, effectively adding a second Starlink-scale revenue stream overnight. SpaceX builds data centers in 66–122 days, faster than any competitor. With $20B in 2024 CapEx (60% toward AI compute), and the ability to stamp out gigawatt-scale facilities at declining timelines, SpaceX's AI infrastructure business could quadruple within two years as additional offtake partners emerge.
- ✓AI Sector Cross-Valuation Inefficiency: Gavin Baker identifies a structural mispricing across AI-related equities: memory makers trade at 3–5x PE, Nvidia trades at low-to-mid teens forward earnings, while power, cooling, and optical names are priced for dramatically higher growth. Both sets of valuations cannot simultaneously be correct. Investors should identify which segment's implied growth assumptions are realistic and position accordingly, rather than treating the AI infrastructure trade as a monolithic theme.
- ✓Cursor Composer 2.5 Benchmark Signal: After just three to four weeks of reinforcement learning on Colossus 2 using Cursor's proprietary coding dataset—reportedly larger than all public coding data on the internet—Cursor's Composer 2.5 model became Pareto dominant across all frontier coding benchmarks. This result used the same base model as Composer 2, demonstrating that proprietary training data plus concentrated compute access can leapfrog competitors without a new base model, a replicable playbook for any lab with unique token datasets.
- ✓GPU Useful Life and Financing Implications: The bear thesis that GPU amortization schedules of four to six years overstate AI infrastructure profits has been invalidated. CoreWeave secures asset-backed financing at approximately 6% interest with customers signing six-year contracts and paying in advance. Nvidia's Q1 2025 results, showing CPUs becoming a $20B annual business overnight, confirm that domain-specific architectures are consolidating inside Nvidia rather than fragmenting to ASICs, extending GPU useful life and strengthening the financing case for neo-cloud operators.
What It Covers
Chamath, Jason, Friedberg, and guest Gavin Baker from Atreides Management cover Andrej Karpathy joining Anthropic to lead recursive self-improvement research, SpaceX's $1.75T IPO filing revealing a $15B annual Anthropic compute deal, Nvidia's $81.6B quarter, AI's public relations crisis, rising global bond yields, and the geopolitical implications of the Trump-Xi summit.
Key Questions Answered
- •Recursive AI Self-Improvement: Anthropic's hiring of Andrej Karpathy to lead pre-training signals a strategic bet that AI-driven model improvement will outpace human-led development. Karpathy's prior work—including auto-research, an open-source training tool that earned 82,000 GitHub stars in days—demonstrates his ability to architect systems where models run five-minute self-improvement experiments autonomously. Combined with Anthropic's existing infrastructure, this approach could compress the timeline to 10x annual model quality gains.
- •SpaceX Elon Web Services Revenue: SpaceX's S-1 reveals Anthropic pays $1.25B per month—$15B annually—to rent Colossus compute clusters, effectively adding a second Starlink-scale revenue stream overnight. SpaceX builds data centers in 66–122 days, faster than any competitor. With $20B in 2024 CapEx (60% toward AI compute), and the ability to stamp out gigawatt-scale facilities at declining timelines, SpaceX's AI infrastructure business could quadruple within two years as additional offtake partners emerge.
- •AI Sector Cross-Valuation Inefficiency: Gavin Baker identifies a structural mispricing across AI-related equities: memory makers trade at 3–5x PE, Nvidia trades at low-to-mid teens forward earnings, while power, cooling, and optical names are priced for dramatically higher growth. Both sets of valuations cannot simultaneously be correct. Investors should identify which segment's implied growth assumptions are realistic and position accordingly, rather than treating the AI infrastructure trade as a monolithic theme.
- •Cursor Composer 2.5 Benchmark Signal: After just three to four weeks of reinforcement learning on Colossus 2 using Cursor's proprietary coding dataset—reportedly larger than all public coding data on the internet—Cursor's Composer 2.5 model became Pareto dominant across all frontier coding benchmarks. This result used the same base model as Composer 2, demonstrating that proprietary training data plus concentrated compute access can leapfrog competitors without a new base model, a replicable playbook for any lab with unique token datasets.
- •GPU Useful Life and Financing Implications: The bear thesis that GPU amortization schedules of four to six years overstate AI infrastructure profits has been invalidated. CoreWeave secures asset-backed financing at approximately 6% interest with customers signing six-year contracts and paying in advance. Nvidia's Q1 2025 results, showing CPUs becoming a $20B annual business overnight, confirm that domain-specific architectures are consolidating inside Nvidia rather than fragmenting to ASICs, extending GPU useful life and strengthening the financing case for neo-cloud operators.
- •AI Public Perception and Messaging Failures: Tech CEO communications are accelerating anti-AI sentiment. Cloudflare's CEO publicly labeled laid-off employees "measurers" while reporting record revenue, and Meta simultaneously announced 8,000 layoffs while installing recording software on all employee computers to train models. Both actions confirm the public's fear that AI adoption means workers train their replacements. The actionable counter-strategy: redirect media narratives toward verified end-user outcomes—specific drug discoveries, crime reduction data, productivity gains—rather than model capability announcements.
- •Global Bond Market Stress Indicators: Japan's 30-year yield hit a record 5.1%, UK yields reached their highest since the 2008 financial crisis, Germany's highest since 2011, and Polymarket prices a 99% probability that May US CPI prints at 4.2% or higher, with professional forecasters projecting CPI reaching 6% in Q2. The Federal Reserve rate-cut narrative has reversed toward potential hikes. Gavin Baker argues America remains relatively insulated due to energy self-sufficiency, natural gas-based electricity generation, and dominant AI and public market positions versus all other major economies.
Notable Moment
Gavin Baker described a hedge fund manager whose daughter was born with a rare neurological condition causing severely reduced neural firing. Using LLMs to research existing approved drugs, the father identified a treatment that raised her neural activity from 30–40% to 80–90%. Baker added the father now believes AI-assisted drug tailoring could produce a complete cure within months.
Episode Transcript
Alright, everybody. Welcome back to the number one podcast in the world. It's the All In podcast, episode two seventy four. Saks is out today, but we're very lucky to have Gavin Baker from Atreides Management joining us. The spicy takes must flow. Welcome back to the program, bestie Gavin. Thanks for having me. Always love it. It's been a huge week in tech. We can start with the SpaceX and OpenAI IPOs. We've got Andrej Karpathy joining Anthropic, NVIDIA crushing it. So many different places to go, but I think we'll start with Andrej Karpathy joining Anthropic. Karpathy is only 39 years old. He's already a legend in the tech industry if you don't know him. I believe he's also coming to Liquidity. Hechema? He's gonna keynote on Monday morning. Oh, fantastic. I'll talk to you on Tuesday, Tuesday, Tuesday, day two. I think he's still here. Okay. As is Gavin. Gavin will be there. Founding member of Gavin anchoring day two as well. Excellent. Yeah. This is Gavin's second appearance. Alright. Look at those two bookmarks, Andre Karpathy and Gavin Baker. Oh, yeah. Liquidity pulls in the stars. Obviously, Andre was a founding member of OpenAI. He led the self driving team. Also, hold on. Gavin is gonna help us judge the best ideas section as well. I don't know if you know that, Gavin, but you're a judge. You're gonna be a judge. I'm up for anything, man. I'm easy. Yes. Kurpathi also coined the term vibe coding. He recently built auto research. I think we talked about that here a bit. That's an open source training tool. It helps AI models improve themselves by running five minute experiments. That got over 82,000 stars in GitHub. He did that, like, as a weekend experiment, and all these civilians started building their own, recursive LLMs. Really inspiring. And the Andrej Karpathy skills is a tool based on his set of principles for Claude Code, and somebody just released that. And so that's just pretty crazy when you think about it. He's gonna be in charge of a new pre training team at Anthropic. The focus obviously being recursive self improvement. In other words, they're going to have Claude improve itself, and they've already talked a little bit about AI, improving AI over at Anthropic. Shmock, what's your take on this? Is this, super important in 2026? Obviously, Karpathy is super well respected. He's obviously, you know, one of the true talents in the space, but, hey, we're in a we're in a different inning than we were, say, ten years ago when he was at Tesla or five years ago when he co founded OpenAI. You know what's interesting? If you go back to, like, Google, the culture of Google, which they got right was the singular technical talents there. They were singled out and they were called Google Fellows. I don't know if you guys remember this, like, Ahmed Singlet, Sridhar Ramaswamy, Jeff Dean. These guys are …
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Books, tools, and gear mentioned in this episode
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Tools
by Polymarket
“Polymarket prices a 99% probability that May US CPI prints at 4.2% or higher, with professional forecasters projecting CPI reaching 6% in Q2.”
by Cursor
“After just three to four weeks of reinforcement learning on Colossus 2 using Cursor's proprietary coding dataset—reportedly larger than all public coding data on the internet—Cursor's Composer 2.5 model became Pareto dominant across all frontier coding benchmarks.”
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