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at Facebook—both from 2020. The “distance” between each pair of neighbors can be interpreted as a probability.When a question prompt arrives, run graph algorithms to traverse this probabilistic graph, then feed a ranked index of the collected chunks to LLM. Split each document into chunks. Does GraphRAG improve results?
In 2020, we introduced Performers as an approach to make Transformers more computationally efficient, which has implications for many applications beyond robotics. We’re also progressing towards making our learning algorithms more data efficient so that we’re not relying only on scaling data collection.
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