Researchers challenge the "efficiency" theory of the brain, showing that neurons become more coordinated and share more information as learning occurs.

Enterprises expanding AI deployments are hitting an invisible performance wall. The culprit? Static speculators that can't keep up with shifting workloads. Speculators are smaller AI models that work ...

ByteDance’s Doubao Large Model team yesterday introduced UltraMem, a new architecture designed to address the high memory access issues found during inference in Mixture of Experts (MoE) models.

The simplest definition is that training is about learning something, and inference is applying what has been learned to make predictions, generate answers and create original content. However, ...

A technical paper titled “Yes, One-Bit-Flip Matters! Universal DNN Model Inference Depletion with Runtime Code Fault Injection” was presented at the August 2024 USENIX Security Symposium by ...

Historically, we have used the Turing test as the measurement to determine if a system has reached artificial general intelligence. Created by Alan Turing in 1950 and originally called the “Imitation ...

Modern large language models (LLMs) might write beautiful sonnets and elegant code, but they lack even a rudimentary ability to learn from experience. Researchers at Massachusetts Institute of ...