For the first time, a research team has demonstrated an artificial intelligence semiconductor technology that integrates the ...

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 ...

Tensordyne says logarithmic computing could reduce AI inference costs and power demands, offering an alternative to conventional chip designs.

Abstract: Transformers are at the core of modern AI nowadays. They rely heavily on matrix multiplication and require efficient acceleration due to their substantial memory and computational ...

Abstract: The parallelism and analog computing features of neuromorphic systems bring great challenges in developing a compact model of analog resistive random access memory (RRAM). In this article, ...

Imagine you’re sitting in on a fourth-grade math class, witnessing a multiplication lesson. Instead of splitting the room between fast finishers and students who still need support, the teacher gives ...

A startup hopes to challenge Nvidia, AMD, and Intel with a chip that wrangles probabilities rather than 1s and 0s. The startup’s chips work in a fundamentally different way than chips from Nvidia, AMD ...

Peter Delos, Technical Lead, Bob Broughton, Director of Engineering and Jon Kraft, Senior Staff Field Applications Engineer, all with Analog Devices. With the proliferation of digital phased arrays in ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.

The original version of this story appeared in Quanta Magazine. Moore’s law is already pretty fast. It holds that computer chips pack in twice as many transistors every two years or so, producing ...