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At the centre Most future robotics training data will be robots' own autonomous attempts, the way most language-model data is now generated by the model itself. Holds CFChelsea Finn Read this korrent →

• Similar wording Once a robot is good enough, you can teach it with words instead of with demonstrations, and language becomes a training signal for motor skill. Holds SLSergey Levine
• Similar wording AI will not run out of data, because there is already enough real-world data to build the simulators that generate more of it. Holds DHDemis Hassabis
• Similar wording Reinforcement learning cannot be scaled for robots the way it was for language models, because every attempt spends real robot hours instead of data-centre compute. Holds CFChelsea Finn
• Similar wording Robot models will reach ChatGPT-level capability within the next few years, even without a ChatGPT-style moment. Holds CFChelsea Finn
• Similar wording Future AI, say in fifteen years, will not be built on the LLM stack; it will have to move to symbolic learning. Holds FCFrançois Chollet
• Similar wording Large language models will not get to real agency, because a mind has to be embedded in a world through a body. Holds AFAdam Frank
• Similar wording Future language models will be smaller and loop on themselves with a retrieval system, which is what will finally let them cite their sources. Holds GHGeorge Hotz
• Similar wording Training is no longer limited by data but by compute, because most of the data models learn from is now synthetic. Holds JHJensen Huang