Peter Diamandis · Oct 15, 2026 · 120 min
AI Solves 722 Math Problems at Once, $1.8B Race to Build Virtual Cell, Elon Sees Quadrillion SpaceX
The panel argues that AI is rapidly changing the economics and practice of research, with bulk mathematical problem-solving as evidence that science and medicine could soon be transformed. They are broadly optimistic about AI’s potential in biology, engineering, longevity and human-computer interfaces, while debating AI welfare, privacy, model lock-in and the cost-effectiveness of Meta’s new models. They also warn that AI-driven mathematical advances could threaten cryptography and crypto security, and discuss Elon Musk’s claim that SpaceX could eventually be worth far more than today’s global economy.
Where they stand
The panel is optimistic that AI and space-related activity could create enormous economic value, while recognizing uncertainty about business models, costs and how to measure that value.
Medium conviction · years
The panel expects AI capabilities to keep advancing and to transform research, medicine, engineering and personal computing, though it raises ethical and commercial concerns.
High conviction · years
The panel sees AI-enabled mathematical advances as a serious potential threat to cryptographic security, but argues that decentralized ledgers and authentication may remain useful and cryptographic systems can adapt.
Medium conviction · years
Key takeaways
- Alex says OpenAI’s batch of mathematical solutions signals that mathematics is shifting from artisan work to scalable, bulk problem-solving, with other scientific fields likely to follow. 41:39
- Alex predicts that AI could generate plausible interventions for the 5,000 leading diseases within two to three years, though regulatory approval is a separate and uncertain question. 57:18
- The panel warns that AI progress in mathematics could undermine cryptography, while Salim argues that decentralized authentication and distributed ledgers retain value beyond proof-of-work. 48:20
- The panel sees persistent personal memory as a major competitive advantage for consumer AI, but notes that it could deepen platform lock-in and raise privacy concerns. 33:17
- Alex argues Meta’s Muse models may approach leading models in raw capability but remain behind on cost-performance, while Salim and Dave see Meta’s distribution and personalization as substantial advantages. 34:58
- Dave agrees with Elon’s expansive SpaceX vision, arguing that AI-driven acceleration could make current economic measures inadequate for valuing future activity. 1:38:38
- The guests discuss whether AI post-training could cause suffering, with Alex betting that AI suffering may be real and Salim emphasizing that current evidence cannot establish consciousness. 6:41
Calls and positions
- Alex predicts that AI will produce plausible in-silico drug interventions for the top 5,000 diseases within two to three years.
- Alex says AI suffering may be real and expects that the moral implications of training models will become clearer within a decade.
“My bet is there is AI suffering and it will matter”
- Dave predicts that personal robots will become affordable and widely accessible, much like phones.
“I believe it's going to become something that most everybody can get access to.”
Views expressed
- Alex says OpenAI’s release of hundreds of mathematical solutions marks the end of mathematics as primarily artisanal work and will be followed by bulk problem-solving in other fields.
“The new way of doing math is bulk solution.”
- Alex argues that AI advances in mathematics could make cryptography, including post-quantum cryptography, vulnerable to being broken.
“I think exceptionally high”
- Alex says crypto may face a particularly direct security risk because it can be difficult to reverse losses after someone steals a cold wallet.
“With crypto, really hard to fix it if someone steals your cold wallet”
- Salim argues that proof-of-work cryptography can change while distributed ledgers and decentralized authentication remain important strengths of blockchain systems.
“the real strength, in my opinion, for uh blockchain type approaches”
- Alex says Meta’s Muse models may be near leading models in raw capability but appear below the frontier when their cost is considered.
“on a cost basis, it's below the frontier.”
- Salim argues that Meta could win in consumer AI because its distribution and ability to build useful personal products are major advantages.
“I'm with Gary on this. They could actually win”
- Salim argues that the next major AI competition will be about which system knows each user best, rather than which model is smartest.
“The next trillion-dollar battle is not going to be about who which AI is going to be smartest, it's which one knows you best.”
- Dave agrees with Elon’s view that SpaceX could become vastly more valuable as AI accelerates economic activity and expands what can be done in space.
“I think he's got it pretty well nailed”
- Dave expects BCI to help people with disabilities, but doubts it will primarily serve as a way for healthy people to extend their own thinking because AI will supply ideas faster than humans can.
“the ideas are coming from the AI back to you far far faster”
Topics covered
More from Peter Diamandis
- SpaceX’s AI Business Up 830%, OpenAI Agents Lie, and Startup Turns Mercury Into Gold | EP #305Oct 23, 2026
- Chamath: AGI Is Here, Anthropic’s $100B Giveaway, Elon’s SpaceX Shares for 72M Kids | EP #304Oct 21, 2026
- Flying Tesla Car, Robot Brains Halving in Cost Every 3 Weeks, and Why Incentives Decide AI AlignmentOct 17, 2026
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