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

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 * WorkOS ensures that AI companies like OpenAI and Anthropic don't have to spend engineering time building enterprise features like access controls or SSO. It’s not that they don't need these features; it's just that WorkOS gives them battle-tested APIs that they can use for auth, provisioning, and more. Start building today at https://workos.com. * Scale is building the infrastructure for safer, smarter AI. Scale’s Data Foundry gives major AI labs access to high-quality data to fuel post-training, while their public leaderboards help assess model capabilities. They also just released Scale Evaluation, a new tool that diagnoses model limitations. If you’re an AI researcher or engineer, learn how Scale can help you push the frontier at https://scale.com/dwarkesh. * Lighthouse is THE fastest immigration solution for the technology industry. They specialize in expert visas like the O-1A and EB-1A, and they’ve already helped companies like Cursor, Notion, and Replit navigate U.S. immigration. Explore which visa is right for you at https://lighthousehq.com/ref/Dwarkesh. To sponsor a future episode, visit https://dwarkesh.com/advertise. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 00:00:00 – How far can RL scale? 00:16:27 – Is continual learning a key bottleneck? 00:31:59 – Model self-awareness 00:50:32 – Taste and slop 01:00:51 – How soon to fully autonomous agents? 01:15:17 – Neuralese 01:18:55 – Inference compute will bottleneck AGI 01:23:01 – DeepSeek algorithmic improvements 01:37:42 – Why are LLMs ‘baby AGI’ but not AlphaZero? 01:45:38 – Mech interp 01:56:15 – How countries should prepare for AGI 02:10:26 – Automating white collar work 02:15:35 – Advice for students