Daniel Kokotajlo

Kevin Roose × Casey Newton × Sayash Kapoor × Daniel Kokotajlo × George Ekas × Dwarkesh Patel

Daniel Kokotajlo assigns a 50% chance to AI conducting its own AI R&D by late 2028, with coding automation shifting bottlenecks toward research judgment and management.Sayash Kapoor argues that coding’s objective feedback does not generalize to law or other real-world domains, leaving reliability, sample efficiency and continuous learning as the key constraints to monitor.

Gary Marcus × Daniel Kokotajlo × Dan Hendrycks

Fully automating AI research is the pivotal red line, shifting progress from human speed to machine speed and making even a short lead potentially decisive.Containment proposals target explosive recursion, expert virology or offensive-cyber agents, and model-weight security, but labs’ “if we don’t do it, someone else will” incentives leave coordination unresolved as forecasts diverge from end-2028 to beyond ten years.

Daniel Kokotajlo

Tariff whiplash exposed Apple’s concentration risk, with roughly 90% of iPhones made in China, while Nintendo and TikTok showed how uncertainty can freeze launches and transactions.AI 2027 assigns a 50% chance to autonomous, superhuman coding agents by the end of 2027, while Llama 4’s arena-versus-downloadable-model gap highlights an industry-wide evaluation crisis.

Scott Alexander × Daniel Kokotajlo × Dwarkesh Patel

AI 2027 models a coding-led intelligence explosion reaching AGI in 2027 and potentially superintelligence in 2028, with research progress accelerating from roughly 5x to hundreds or 1000x.The pivotal mid-2027 signal is inconclusive misalignment evidence that could trigger a rollback or a race toward deceptively aligned systems, while robot manufacturing, China, and government transparency determine how quickly capability becomes power.