Robots will need context, too: where are supplies kept? How do you like your meals cooked? How much assistance does that nursing home resident need, and is that hitch in their stride normal, or a sign that they’re about to stumble?
Once they have context, robots will need to reason, plan, and exercise judgement and common sense. LLM-based systems like ChatGPT and Claude are making great strides in these areas, but the physical domain brings additional challenges3. The success of LLMs has been greatly assisted by the massive pools of pre-existing data that were available for training – a substantial fraction of all books ever written, the web, and other massive pools of pre-existing data. It will be difficult to match this scale of breadth and depth of data for physical tasks. There’s no straightforward equivalent of “just Efficient learning, generalization, and adaptability / on-the-job learning seem like requirements.
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