Memory and Continual Learning: Engram's Dan Biderman and Jessy Lin

Dan Biderman and Jessy Lin of Engram introduce their "always training" paradigm, focusing on baking a team's knowledge directly into a model's weights to achieve true memory and continual learning. This contrarian approach, which they call a "RAG killer" for specific use cases, promises up to 100x token savings and superior performance by internalizing context rather than relying on ever-larger context windows or external retrieval, envisioning a future where everyone has their own continually learning, personalized AI model.