Jordan Nanos × Doug O'Laughlin × Max Kan × Joey Brookhart

“Pacing” would slow Anthropic’s capability progress without halting training or compute purchases, potentially weakening its strongest internal model.Near-term scarcity and safety workloads keep compute demand elevated, while semiconductor signals increasingly depend on frontier-lab ARR and capacity premiums.Bank hacks, data leaks, or AI-assisted biological attacks could accelerate regulation.

Jensen Huang × President Trump

Jensen Huang cites failed forecasts on radiology, AI-generated code and entry-level jobs to challenge doomsday narratives, while arguing that AI incidents so far call for root-cause engineering and independent evaluation rather than sweeping regulation.With 80% of AI-native companies receiving $400 billion in recent venture funding using open models, NVIDIA is building infrastructure bottlenecks as Jensen predicts China will reach advanced lithography by 2030, leaving commercialization, lab controls and data-center execution to monitor.

Raymond × 马克汤

英伟达联合 BlackRock、Brookfield、Goldman 和 KKR，以类 REITs 方式融资数据中心，担保仍不确定。需求若被证伪，价格可能腰斩；A100 价格、交易量和 CDS 可作指标，DeepSeek V4 的十分钟切换也将检验 AI 公司的真实经济性。

Astra’s roughly 3x productivity on the same compute makes Jevin’s paradox tangible: lower AI costs could drive far greater usage, not weaker infrastructure demand.Its tenacious A-to-Z autonomy still takes shortcuts, leaving human engineers essential and preserving incentives to scale compute, memory, and energy.Amazon, Unity’s $18B entry, and trillion-dollar IPO filings frame catalysts; AI-driven margin gains in earnings calls are the efficiency signal to monitor.

Harry Stebbings × Cliff Weitzman

Speechify’s owned-GPU strategy compares $35,000–50,000 annual H100 rental with roughly $30,000 to buy, potentially lowering compute costs.NVIDIA’s deal with Blackstone, BlackRock, Apollo and Goldman Sachs could create a liquid secondary market and price floor through buybacks up to 25% of GPU value.Weitzman calls missing B2B his biggest strategic mistake; Simba 3.2 costs $10 per million characters versus ElevenLabs’ $100, but execution against an “unstoppable” rival remains unresolved.

Tony Kim × Molly O'Shea

AI has shifted value toward chips and hardware, with Kim estimating $30T+ there versus roughly $10T across software/services/internet.Base compute has jumped 10,000×, while the rebuild may require a trillion dollars this year and ten trillion over five years.Token factories may compress SaaS margins; memory and foundation-lab IPOs are watchpoints as Kim says his thesis may change.

Rene Haas × Elad Gil × Sarah Guo

Arm moved from IP licensing into physical silicon with the Arm AGI CPU after Meta sought a general-purpose agentic CPU no one else could provide.AI reaches 80% to 90% of engineers, while Arm’s documentation and test benches may make proprietary IP more trainable; supply may remain constrained for 3 to 5 years, with data-center construction a possible next bottleneck.

David George × Gavin Baker

AI demand accelerated through July and August, with usage concentrated among possibly sub-10 million heavy users and no leader identifying a worsening quantitative metric.Nebius suggests nine-to-ten-month paybacks on $50B-per-gigawatt builds, supported by 50-60% customer prepayments; undersupply through ’28 could lift token prices, while shifting capacity to training could cut lab revenue from $480B to $120B.

Bryan × Myron × Jordan Nanos

OpenAI’s first Jalapeño results decisively beat GB300 and exceeded Vera Rubin’s July output-token performance per utility megawatt, though HBM4 versus HBM3 makes Blackwell comparisons imperfect.At roughly 50–100 tokens per second, Jalapeño delivers about twice GB300’s tokens per megawatt and may also win on TCO, while a reported three-to-five-times production uplift remains unverified and scaling to millions of chips is the key risk.

Peter Diamandis × Salim Ismail × Dave Blundin × Dr. Alexander Wissner-Gross

Nvidia’s $96.2B quarter grew 106% year-over-year with $108B guidance and 80% to 85% gross-margin revenues, while OpenAI’s Broadcom-developed Jalapeño targets inference at 1.5–1.9× more work per watt.Inference may be leaving NVIDIA as CUDA’s moat shifts toward training interconnects, but TSMC concentration and Alex Wissner-Gross’s circular-financing concern remain key risks alongside a possible OpenAI cloud.