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 ...
Hackaday

TurboQuant: Reducing LLM Memory Usage With Vector Quantization

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...
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 ...
InfoWorld

AI memory is really a database problem

If we want to avoid making AI agents a huge new attack surface, we’ve got to treat agent memory the way we treat databases: with firewalls, audits, and access privileges. The pace at which large ...
XDA Developers on MSN

I tested my local LLM across 4 different tools, and only one actually unleashed its potential

Utility plus convenience wins ...
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 ...
XDA Developers on MSN

I ran my local LLM for hours and watched it get dumber in real time

The AI was smarter than the person setting it up ...
SDxCentral

DeepSeek looks to offload simple LLM tasks to save billions of parameters

A little over a year after it upended the tech industry, DeepSeek is back with another apparent breakthrough: a means to stop current large language models (LLMs) from wasting computational depth on ...