AMD and Intel have now published a full technical specification for ACE — AI Compute Extensions — the most significant overhaul to x86 AI compute in the architecture's history, co-authored by eight ...

Purdue University’s Artificial Intelligence Microcredentials offer quick and convenient online courses that cover the fundamentals of artificial intelligence and its applications. Every course ...

From cellular neural networks to human–machine interfaces, the applications of memristors continue to grow. The search for new energy-efficient electronic hardware for machine learning and artificial ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...

The tiling algorithm for matrix multiplication is a technique that illustrates how to leverage the memory hierarchy to speed up memory-bound operations. At a high level the idea is simple: move blocks ...

Computer scientists at UC Berkeley say that AI models show promise as a way to discover and optimize algorithms. In a preprint paper titled "Barbarians at the Gate: How AI is Upending Systems Research ...

About a year ago, an AI startup known as Recogni announced a patented number system for AI math, known as Pareto. Pareto is a logarithmic system, meaning that it stores numbers using their logarithmic ...

nvmath-python brings the power of the NVIDIA math libraries to the Python ecosystem. The package aims to provide intuitive pythonic APIs giving users full access to all features offered by NVIDIA's ...

Abstract: Numerical libraries derive performance from highly specialized code – known as kernels/microkernels – written by experts. Reliance on a small group of experts poses challenges to the ...

As transformer models grow in size and complexity, they face significant challenges in terms of computational efficiency and memory usage, particularly when dealing with long sequences. Flash ...

A handy open source tool for packaging up LLMs into single universal chatbot executables that are easy to distribute and run has apparently had a 30 to 500 percent CPU performance boost on x86 and Arm ...