Despite the army of startups that are advancing the capabilities of AI and AI agents, LLMs are still fundamentally limited. This is especially true of their ability to maintain coherence over extended tasks which require them to retain context and information. This limitation, manifesting as context windows, make AI agent’s “less than” what they need to be for more robust applications.
According to researchers at Y Combinator backed Mem0, ideal AI memory should be able to “selectively store important information, consolidate related concepts, and retrieve relevant details when needed—mirroring human cognitive processes.” For conversations between users and AI agents that take place over longer periods of time (say, months), the memory demand will exceed even the most generou
Mem0’s Commitment to AI Agents with Improved Memory
- By Mukundan Sivaraj
- Published on
They say that the OpenMemory MCP Server is just the first step in a “broader effort to make memory portable, private, and interoperable across AI systems.”
