New KV cache compaction technique cuts LLM memory 50x without accuracy loss

MIT researchers developed Attention Matching, a KV cache compaction technique that compresses LLM memory by 50x in seconds — ...
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 ...
Semiconductor Engineering

Developing ReRAM As Next Generation On-Chip Memory For Machine Learning, Image Processing And Other Advanced CPU Applications

In modern CPU device operation, 80% to 90% of energy consumption and timing delays are caused by the movement of data between the CPU and off-chip memory. To alleviate this performance concern, ...
Semiconductor Engineering

Will In-Memory Processing Work?

The cost associated with moving data in and out of memory is becoming prohibitive, both in terms of performance and power, and it is being made worse by the data locality in algorithms, which limits ...
EDN

Analog memory embedded in neural net processing SoCs

A new breed of system-on-chips (SoCs) serving speech recognition, voice-print recognition, and deep speech noise reduction is starting to employ analog in-memory computing solutions for simultaneously ...
Santa Clara University

Signal Processing and Machine Learning

Signal processing algorithms, architectures, and systems are at the heart of modern technologies that generate, transform, and interpret information across applications as diverse as communications, ...
Hosted on MSN

Psychologists identify a new kind of human memory process

Richard Addante, who has spent more than a decade researching episodic memory—the cognitive process that involves processing and retrieving long-term memory—has identified a new kind of human memory ...