Contacts, check-ins, escalation. The dead man's switch is built. Beta soon.

A digital dead man's switch. Store your important files, pick your people. If you stop responding, they get access.

It’s the most transparent estimate yet from one of the big AI companies, and a long-awaited peek behind the curtain for researchers.

Ik zit met een dilemma. En waarschijnlijk jij ook, als je dit leest en consultant bent. Claude (of ChatGPT, of welke AI-assistent je ook gebruikt) is ondertussen een onmisbare collega geworden. Maar hoe ga je daar in godsnaam mee om als je per uur factureert? Laten we eerlijk zijn: AI

DNS Belgium Terms & Conditions: Key Differences v6.2 to v6.3 - Markdown document created with Claude.

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! Read the 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

I’ve noticed something interesting lately. Several people have reached out privately after seeing my comments or articles about AI, content where I express my tech optimism and belief that AI will transform our world similar to how the internet and smartphones did. What surprises me is that many of these conversations, often with professionals I respect from innovative companies, quickly turn to how AI could “eliminate headcount” or replace manual processes. This perspective puzzles me. Are we so focused on protecting our current roles that we’re missing the bigger picture of possibilities? It reminds me of the transition from horse-drawn carriages to automobiles. The farriers, stable owners, and carriage makers who thrived weren’t those who fought to preserve the status quo, they were those who recognized the shifting landscape and adapted. This exact mindset is why we founded Krane Labs. We saw that clinging to traditional old-school hosting infrastructure would leave us optimizing a declining paradigm. Instead, we embraced the public cloud and its transformative potential; not just to do the same things more efficiently, but to enable entirely new possibilities. Are you positioning yourself as the farrier desperately protecting the horseshoe business? Or are you preparing to build the next generation of vehicles? The most exciting opportunities won’t come from doing the same things more efficiently—they’ll emerge from entirely new possibilities we haven’t yet imagined. #TechOptimism #AIFuture #Innovation

Frank on Glass