Latest Interviews
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Clear all filters- Jane Street16 min
Dwarkesh Goes Inside Jane Street's Latest AI Data Center
Dwarkesh, Ron Minsky, Daniel Pontecorvo, Mark Mirchandani
Jane Street transformed a Texas data center into a high-density liquid-cooled facility housing 4,032 GPUs to execute large language model training and custom trading architectures. The retrofit replaces legacy air-cooling with an 18°C fluid distribution system that manages 140 kW per cabinet while utilizing proprietary software to dynamically redistribute power and prevent breaker trips during peak loads. Engineering safeguards now focus on mitigating new liquid-cooling risks like biological growth and leaks, enabling sub-100-nanosecond latency required for modern algorithmic trading compared to the millisecond scales of its historical "Hive" cluster.
- Dwarkesh Patel17 min
Why I don’t think AGI is right around the corner
A July 2025 analysis challenges industry forecasts by arguing that current large language models cannot replace white-collar workers due to a fundamental lack of continual learning and context accumulation. While dismissing the immediate arrival of autonomous computer agents, the speaker projects that end-to-end tax filing capabilities will emerge by 2028 and human-level on-the-job learning will arrive around 2032, contingent on shifting from data scaling to algorithmic breakthroughs. The presentation frames these timelines as probabilistic bets, warning that post-2030 progress will rely on overcoming physical constraints to enable a gradual intelligence explosion rather than an immediate singularity.