Memory and Continual Learning: Engram's Dan Biderman and Jessy Lin
Engram, a new lab from Dan Biderman and Jessy Lin, treats memory and continual learning as baking new context directly into model weights.
“We don't see the world through the lens of pre-training or post-training. Our models are always training.”
Engram co-founders Dan Biderman and Jessy Lin argue the real bottleneck for useful AI is not raw intelligence but absorbing new and evolving context directly into model weights, rather than relying on context windows or external memory databases. They frame memory and continual learning as two sides of the same problem and pitch applying frontier-lab training pipelines to every domain. This signals a research direction betting against context-engineering as the endgame for personalization and adaptation.