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A 0.12% parameter add-on gives AI agents the working memory RAG can't
AI agents forget. Every time a coding assistant loses track of a debugging thread, or a data analysis agent re-ingests the same context it already processed, the team pays in latency, token costs, and [...]
DeepSeek’s conditional memory fixes silent LLM waste: GPU cycles lost to static lookups
When an enterprise LLM retrieves a product name, technical specification, or standard contract clause, it's using expensive GPU computation designed for complex reasoning — just to access stati [...]
MeMo's memory model lets teams upgrade their LLM without retraining it — and performance jumps 26%
Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits.MeMo, a [...]
Google PM open-sources Always On Memory Agent, ditching vector databases for LLM-driven persistent memory
Google senior AI product manager Shubham Saboo has turned one of the thorniest problems in agent design into an open-source engineering exercise: persistent memory.This week, he published an open-sour [...]
MIT's MeMo lets teams swap in a better LLM without retraining — and performance jumps 26%
Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits.MeMo, a [...]
