PEAK:AIO Solves Long-Running AI Memory Bottleneck for LLM Inference and Model Innovation with Unified Token Memory Feature ...

In 1982 physicist John Hopfield translated this theoretical neuroscience concept into the artificial intelligence realm, with the formulation of the Hopfield network. In doing so, not only did he ...

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

Elon Musk's AI company, xAI, has added a 'memory' feature to its Grok chatbot, bringing it closer to party with ChatGPT and Google's Gemini.

Microsoft researchers have developed — and released — a hyper-efficient AI model that can run on CPUs, including Apple's M2.

Optimizing the mind: Brown researchers develop neural model to understand working memory Researchers said the model could help scientists address symptoms of neurodegenerative diseases and other ...

Learn about the architecture and optimization of AI memory systems in LLMs, driving smarter, more efficient AI interactions and applications.

A paper from October 2024 explored the concept of AI self-evolution through long-term memory, showing that models and agents actually improve the more they remember.

The "tip and tail" release model represents a significant step forward, offering revolutionary changes that are ambitious but not without challenges.

According to Meta, memory layers may be the the answer to LLM hallucinations as they don't require huge compute resources at inference time.

"The model's 3D geometry allows us to study communication between brain areas, and most interestingly, to recreate experiments combining complex laboratory methods such as optogenetics with ...