Engram aims to bake memory into AI model weights, challenging RAG

Engram, a startup featured on Sequoia's podcast, proposes training company-specific knowledge directly into model weights rather than relying on retrieval-augmented generation (RAG). The approach uses lightweight adapters like LoRA to enable continual learning without catastrophic forgetting. Founders argue this reduces inference costs and enables abstract associations that RAG struggles with.