teïlo

Demis Hassabis and Sebastian Mallaby were on stage in SF today and here are the 9 best things they said: 1. "There is a 50% chance that OpenAI goes bankrupt in the next 18mos" -Mallaby 2. "Dario is the best of all the other lab leaders." -Demis 3. On Claude Mythos: "It's not really tenable for a private company to decide who gets access to the frontier of cyber defense tech. What happens when China can do this in 6-12mos?" -Mallaby 4. "Not all countries are pessimistic about AI. I was just in India for the AI Summit Modi had and they're quite optimistic there" -Demis 5. "The most exciting current prospect in AI is our work at Isomorphic Labs. AlphaFold is just one of the many problems we need to solve. We need 6 'AlphaFold' moments to compress the drug delivery timeline from 10yrs to a few months" -Demis 6. "I don't think of p(doom) as probabilities to throw out there. I just know it's non zero. Some people like Marc Andreesen and Yann LeCun think it's 0% and I think that's crazy" -Demis 7. On AGI: "I think of a post-scarcity world where on the bright side we will have an unbelievable amount of science but we will have to think of economic problems of sharing proceeds equitably. We will also have philosophical questions to answer and need great new philosophers" -Demis 8. On career advice: "Immerse yourself in AI tools. Everyone has access to tools 3-6 months behind frontier. Enormous opportunity lies in applying AI to unexplored areas." -Demis 9. On the future: "When I started building this technology, I pictured a future quite different from this. More like CERN researchers where we discuss ideas and help each other out and stress test each other's ideas. It's my job to help how I can to make sure we make more considered, more scientific, more rigorous and more thoughtful decisions and that will also involve social scientists and economists. I'm going to do all I can to try and influence the future in a note thoughtful manner. The decisions we make in the next 5-10 years are going to affect us for 1000s of years. But I remain very optimistic." -Demis

big jump in coding capabilities by Claude 4.7 Opus SWE-Bench Pro 64.3% SWE-Bench Verified 87.6% TerminalBench 69.4% but interestingly, I think they kept CyberGym scores artificially low

Dwarkesh: Why would we want to sell China the materials for a serious cyberweapon? It's like selling them nukes with a casing that says 'made by Boeing' and claiming that's good for the US Jensen: Comparing AI to nukes is lunacy. Enriched uranium is a lousy analogy. It's an illogical analogy. What we have to recognize is that AI is a five-layered cake.

Dwarkesh: Why would we want to sell China the materials for a serious cyberweapon? It's like selling them nukes with a casing that says 'made by Boeing' and claiming that's good for the US Jensen: Comparing AI to nukes is lunacy. Enriched uranium is a lousy analogy. It's an illogical analogy. What we have to recognize is that AI is a five-layered cake.

UK Prime Minister Keir Starmer is set to address the nation this morning, becoming the third leader to do so today, alongside Donald Trump and Australian Prime Minister Anthony Albanese.

Today we're launching ARC-AGI-3 135 Novel Environments (nearly 1K levels) we build by hand It is the only unsaturated agent benchmark in the world Each game is 100% human solvable, AI scores <1% This gap between human and AI performance proves we do not have AGI Agents today need human handholding. Agents that beat V3 will prove they don’t need that level of supervision. Agents that beat V3 will demonstrate: * Continual learning - Each level builds on top of each other. You can’t beat level 3 without carrying forward what you learned in levels 1 and 2. * World modeling - Many of the environments require planning actions many actions ahead. AI will have no choice but to build an internal world model for how the environment works, run simulations “in its head” and proceed with an action In our early testing, we’ve seen a few clear failure modes of AI: * Anticipation of future events - If an environment requires that AI set up a scene, and then carry out a scenario (like in sp80), it starts to break down. * Anchoring on early hypothesis - Early in a game it comes up with a hypothesis (even if wrong) and refuses to update its beliefs later. * Thinking it’s playing another game - AI thinks it’s playing chess, pacman. The training data holds hard! One major problem is there is too much data to carry forward in a single context. Models must learn what to remember and what to forget The agent that beats ARC-AGI-3 will have demonstrated the most authoritative evidence of progress towards general intelligence to date We're excited to get this out and excited to see what you think