Retrieval-augmented generation enhances the performance of AI agents by expanding their recall. It can do this in three ...

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — using step-by-step reasoning.

The research project promises more efficient long-term recall by organizing knowledge around abstractions and cue-based ...

Perplexity's Brain is a self-improving memory layer that tracks what the AI agent Computer did, what worked, and what failed.

Forbes contributors publish independent expert analyses and insights. I am an MIT Senior Fellow & Lecturer, 5x-founder & VC investing in AI In the big conversation that companies and people are having ...

Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.

I finally stopped babying my MacBook.

The organizations treating AI as a stack, rather than a single model integration, are building durable competitive advantages ...

My Proxmox node now powers my entire smart home without touching a single cloud service ...