By allowing models to actively update their weights during inference, Test-Time Training (TTT) creates a "compressed memory" ...

Recently, the team led by Guoqi Li and Bo Xu from the Institute of Automation, Chinese Academy of Sciences, published a ...

Artificial intelligence has been bottlenecked less by raw compute than by how quickly models can move data in and out of memory. A new generation of memory-centric designs is starting to change that, ...

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 ...

During sleep, the human brain sorts through different memories, consolidating important ones while discarding those that don’t matter. What if AI could do the same? Bilt, a company that offers local ...

Working memory is what allows humans to juggle different pieces of information in short-term scenarios, like making a mental grocery list and then going shopping or remembering and then dialing a ...

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 ...

While Large Language Models (LLMs) like GPT-3 and GPT-4 have quickly become synonymous with AI, LLM mass deployments in both training and inference applications have, to date, been predominately cloud ...

Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of acquiring new skills or adjusting behaviors in response to positive outcomes ...