Is RL + LLMs enough for AGI? — Sholto Douglas & Trenton Bricken

ℹ️ EPISODE INFO

Released

May 22, 2025

Duration

2h 24m

Channel

Dwarkesh Podcast

Watch on YouTube

▶ Open ↗

📝 EPISODE DESCRIPTION

New episode with my good friends Sholto Douglas & Trenton Bricken. Sholto focuses on scaling RL and Trenton researches mechanistic interpretability, both at Anthropic. We talk through what’s changed in the last year of AI research; the new RL regime and how far it can scale; how to trace a model’s thoughts; and how countries, workers, and students should prepare for AGI. See you next year for v3. Enjoy! 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒

• Transcript: https://www.dwarkesh.com/p/sholto-trenton-2
• Apple Podcasts: https://podcasts.apple.com/us/podcast/dwarkesh-podcast/id1516093381
• Spotify: https://open.spotify.com/episode/3H46XEWBlUeTY1c1mHolqh?si=b645971b1af546fa
• Last year's episode: https://www.youtube.com/watch?v=UTuuTTnjxMQ

𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒

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🎤 SPEAKERS

• Dwarkesh Patel

  host

• Sholto Douglas

  guest

• Narrator

  other

• Trenton Bricken

  guest

🧾 EPISODE SUMMARY

In this episode of Dwarkesh Podcast, featuring Dwarkesh Patel and Sholto Douglas, Is RL + LLMs enough for AGI? — Sholto Douglas & Trenton Bricken explores reinforcement learning plus LLMs race toward agentic white‑collar automation Sholto Douglas and Trenton Bricken argue that RL with verifiable rewards on top of large language models has crossed an important threshold: we now have algorithms that can reach expert-human reliability on difficult, well-specified tasks like competitive programming and math.

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