New agentic memory framework uses 118K tokens per query. LangMem burns through 3.26M.

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — ...
InfoWorld

How to improve the memory of AI agents

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

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 ...
Forbes

The Limits Of LLMs And Why The Architecture Must Change

LLMs have delivered real gains, but their momentum masks an uncomfortable truth: More data, more chips and bigger context windows don’t fix what these systems lack—persistent memory, grounded ...
Semiconductor Engineering

HW-based Heterogeneous Memory Management for LLM Inferencing (KAIST, Stanford Unversity)

A new technical paper titled “Hardware-based Heterogeneous Memory Management for Large Language Model Inference” was published by researchers at KAIST and Stanford University. “A large language model ...
Semiconductor Engineering

Microarchitecture Tailored to 3D-Stacked Near-Memory Processing LLM Decoding (U. of Edinburgh, Peking U., Cambridge et al.)

A new technical paper, “Rethinking Compute Substrates for 3D-Stacked Near-Memory LLM Decoding: Microarchitecture-Scheduling Co-Design,” was published by researchers at University of Edinburgh, Peking ...
Geeky Gadgets

Why AI Memory Systems Are the Future of Large Language Models

Imagine having a conversation with someone who remembers every detail about your preferences, past discussions, and even the nuances of your personality. It feels natural, seamless, and, most ...