{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"My AI Opinions","description":"I recently had a minor spat over someone misinterpreting my AI beliefs (see section marked \u201cUpdate\u201d at the bottom here), so I thought I would list them in one place, so I can refer people when they ask. Timelines1 Define AGI as AI intelligent enough to do 90% of knowledge work jobs. I think there\u2019s a 25% chance of AGI by 20272, a 50% chance by 2034, and a 75% chance by 2045. Basic argument: In a certain sense, AI is already \u201csmart\u201d enough for this (eg it can answer quantum physics problems, which require higher IQ than most knowledge work). Its remaining limitations are that it\u2019s confused, unagentic, lacks situational awareness, and tends to hallucinate. The METR time horizon graph, and several other related benchmarks\/experiments\/intuition pumps, suggest it\u2019s improving on time horizons at an (exponential) rate that lets it cross human-level performance sometime around the early end of the schedule above, and subjectively it feels like harder-to-measure constructs like situational awareness are improving about as fast. Arguments for earlier: recursive self-improvement causes a speedup compared to the trend. This is one of the biggest blank spots in my model: I don\u2019t know how fast RSI will progress, and I don\u2019t think anyone else does either. There\u2019s some function mapping a combination of AI talent and compute to progress, and we don\u2019t know how it behaves in the domain when there\u2019s far more talent than compute available. It could fizzle out completely for lack of compute, or it could go vertical. The AI Futures Project has done some of the best work trying to model this, but even they have low confidence. ","author_name":"Astral Codex Ten Podcast","author_url":"http:\/\/sscpodcast.libsyn.com\/website","html":"