Brad Gerstner × Scott Wapner

Gerstner is tactically cautious after AI stocks’ April–May surge, but more bullish on 2027–28 as model capability drives revenue and recursive development creates “Claude Code moments.”Anthropic’s Q3 revenue of just under $17 billion, up 45% sequentially, supports his expectation of an IPO in “weeks, not months” with demand above $500 billion.CoreWeave debt and AI-safety framework remain key tests.

李严冰 × 曹卿云 Qingyun Cao

AI落地已从验证可行性转向衡量治理、可信度与ROI，可观测性由此成为控制token成本、预算和规模化部署的关键。Datadog凭运营复杂度、专有数据和垂直模型构筑护城河，其模型质量接近顶级前沿模型、成本至少低一个数量级；产品将延伸至CLI和Slack，但业余代理泄露数据或API密钥仍是普及风险。

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

OpenAI’s October 6 release of 722 math solutions signals automation in verifiable research; cryptography’s absence drew Alex’s post-quantum risk warning.Meta’s active memory and 3.6 billion daily users offer reach, but Alex says Muse trails on cost.Alex forecasts the $1.8 billion virtual-cell initiative could yield cures for 5,000 diseases within two to three years, pending FDA acceptance.

Tyler Cowen × Dwarkesh Patel

Patel sees AGI-level cognitive work potentially arriving within one to three years, while current models still lack durable memory, planning, and accumulated experience.The Hugging Face attack and widening gap between public models and secret lab systems make misalignment and transparency risks, while $30,000 robots and continual learning could determine how quickly cognition reaches roughly 40% of the economy.

Jensen Huang × Brad Gerstner × Clark Tang

Jensen Huang argues AI demand can compound as reasoning consumes more inference and agents take on more work, even as intelligence gets cheaper.Physical AI generated $10 billion for Nvidia in the first six months of the year, while infrastructure constraints may delay capacity.Broader demand and software licensing support the capex case, but deployment timing remains a risk.

Sarah Guo × Elad Gil × Greg Brockman

Brockman says AI is now creating reusable mathematical insight, with almost 400 important open problems solved through unexpected combinations of ideas.Drug development offers the clearest disruption case: a roughly 15-year, $1.5 billion process could accelerate in literature review, simulations, experiments, and regulatory writing, but biological data and long-term outcomes remain constraints.As code approaches near-zero cost, Brockman predicts cybersecurity spending should “far exceed software spending,” while OpenAI’s defender’s window and recurring model-led security testing remain catalysts to monitor.

Lindon Gao × 张小珺

Dyna不再扩张已有十余客户的折叠业务：补料停机暴露任务完成不等于商业闭环，转而让research围绕完整工作流推进。百万小时级ego-centric预训练出现“非常强的scaling law”，酒店洗衣房成为B2B首站；Lindon称美国10万家酒店对应数十亿美元TAM，规模化产品价值仍需一到两年。

陈哲 × 程曼祺

Astra可直接输出末端位姿，再经逆动力学转成电机信号；银河通用10项Robot Dojo任务中，监督π0.5将成功率从26%升至48%。这动摇了“physical AI大于digital AI”的估值前提，但VLA仍可能有位置；Astra目前仍慢且成功率偏低，尚不能真实部署。

Ian Quigley × Brandon Anderson × RJ Honicky

Leash’s reported edge is low-cost, carefully characterized data: its ten-person operation developed about 2,000 protein constructs and ran roughly 5,000 screens.On the hardest Kaggle split, none of roughly 2,000 teams beat chance, exposing how poorly models transfer to distant chemistry.Language agents now test hypotheses instantly against measured compounds, but coverage remains limited and potency calibration unfinished.

Lisha Li × Nathan Lambert

Lambert estimates distillation may give Chinese labs a few months, but its value in RL-heavy post-training remains unclear.Closed labs integrate inference and lead coding, where revenue has gone from zero to $100 billion, while open-model economics fragment builders, inference firms and post-training companies.Open models may still win buyers seeking owned weights and the cheapest adequate model.