Using Generative AI to Enable Robots to Reason and Act with ReMEmbR
SMRTR summary
ReMEmbR combines vision-language models and retrieval-augmented generation to enable robots to reason and act based on long-term visual memories. The system efficiently builds semantic memory using video captioning and vector databases, then uses an LLM agent to query and reason over that memory to answer questions and guide robot actions.
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