memt-1.0

Explore how memt-1.0 bakes memory into AI computation for massive storage savings

Building long-horizon agents that don't drown in context windows? That's the promise of memt-1.0, which bakes memory directly into AI computation rather than stacking prompts or bolting on external RAG. The engineering tradeoffs here are genuinely fascinating. By internalizing procedural experience into model weights via gated deltanet-2 and a mixture-of-storage layer, they achieve a 66x storage reduction at 128k context. For teams wrestling with kv cache bottlenecks, this architecture-level approach feels like a genuine path forward.