Jessy Lin

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

Dan Biderman, Jessy Lin, Sonya Huang, Shaun Maguire

Ngram addresses the scalability and cognitive limitations of current retrieval-augmented generation by training custom, continually learning models directly within workspace environments. This approach utilizes adapter fine-tuning to internalize organizational knowledge into model weights, reducing inference token consumption by a factor of 100 while enabling true intuition rather than static fact retrieval. By shifting the focus from pre-training generic AI to perpetual, private adaptation, the platform aims to create personalized neural interfaces that evolve alongside a team's data.