MIT’s new ‘recursive’ framework lets LLMs process 10 million tokens without context rot

While standard models suffer from context rot as data grows, MIT’s new Recursive Language Model (RLM) framework treats ...
Science Daily

AI's memory-forming mechanism found to be strikingly similar to that of the brain

An interdisciplinary team consisting of researchers has revealed a striking similarity between the memory processing of artificial intelligence (AI) models and the hippocampus of the human brain. This ...

DeepSeek’s conditional memory fixes silent LLM waste: GPU cycles lost to static lookups

Through systematic experiments DeepSeek found the optimal balance between computation and memory with 75% of sparse model ...
EurekAlert!

Elucidating the double duty of sleep in memory processing

Distinguished Professor Kaoru Inokuchi and Specially Appointed Assistant Professor Khaled Ghandour explain the rationale, goals, and main findings of this research, which focuses on the importance of ...
Geeky Gadgets

AI Memory Hacks: Boosting AI Model Performance with Context

In the fast-paced world of artificial intelligence, memory is crucial to how AI models interact with users. Imagine talking to a friend who forgets the middle of your conversation—it would be ...
SDxCentral

AI inference crisis: Google engineers on why network latency and memory trump compute

Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
EurekAlert!

AI's memory-forming mechanism found to be strikingly similar to that of the brain

(a) Diagram illustrating the ion channel activity in post-synaptic neurons. AMPA receptors are involved in the activation of post-synaptic neurons, while NMDA receptors are blocked by magnesium ions ...