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: We propose a high-density vertical AND-type (V-AND) flash thin-film transistor (TFT) array enabling accurate vector-matrix multiplication (VMM) operations. Compared to the planar AND-type (P ...

As Moore's Law slows to a crawl and the amount of energy required to deliver generational performance gains grows, some chip designers are looking to alternative architectures for salvation. Neurophos ...

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 ...

===== Benchmarks for 3×3 Float64 matrices ===== Matrix multiplication -> 5.9x speedup Matrix multiplication (mutating) -> 1.8x speedup Matrix addition -> 33.1x ...

A new post on Apple’s Machine Learning Research blog shows how much the M5 Apple silicon improved over the M4 when it comes to running a local LLM. Here are the details. A couple of years ago, Apple ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

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 ...