Generalist AI just released GEN-1.5. It might be robotics' GPT-3 moment. What is one-shot learning via in-context prompting? In the case of language models like GPT-3, including a Q&A example in the prompt before the actual question improved performance across a broad suite of language tasks. For example: Prompt: "Q: Who wrote Romeo and Juliet? A: William Shakespeare Q: Who wrote War and Peace?" [model outputs "Leo Tolstoy"] Similar capabilities are now emerging in GEN-1.5, where a short example (a few seconds of demonstration ) alongside language and sensory inputs can solve tasks the model wasn't explicitly trained for. No gradient updates, just in-context examples unlocking new capabilities. The generalization comes from large-scale pretraining on real-world interaction data. It shows up in other adaptive behaviors too: novel tool use, and learning from human demonstrations. For decades, programming a robot took months and an expert. If showing it once is enough, that changes both how fast a robot becomes useful and who can work with one.