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Elasticity Institute's @cherylwoooo explains the 3 questions AI labs need to answer to know whether recursive self-improvement has actually begun: "The first thing for labs to measure is a very diverse and unsaturated set of benchmarks. And I hope they can put out more data on their internal models, as well as checkpoints." "The next question is whether the capability comes from training compute or from algorithmic improvements. If it's from training compute, we probably feel more relaxed. If…
[1/5] The 8 most valuable data points labs should share to help measure RSI: First, RSI would likely accelerate growth in AI capabilities. Thus, companies should report performance on diverse benchmarks for the latest internally deployed models.