The results include a comparison between two different basis functions for temporal selectivity and how these generate different predictions for the dynamics of neural populations. The conclusions are ...

Here’s a quick library to write your GPU-based operators and execute them in your Nvidia, AMD, Intel or whatever, along with my new VisualDML tool to design your operators visually. This is a follow ...

When a videogame wants to show a scene, it sends the GPU a list of objects described using triangles (most 3D models are broken down into triangles). The GPU then runs a sequence called a rendering ...

This mini PC is small and ridiculously powerful.

FuriosaAI Inc., a Seoul-based developer of artificial intelligence chips, is reportedly in talks to raise a new round of funding. Sources told Bloomberg today that the startup is seeking $300 million ...

What’s the difference between a GPU and a TPU? It’s a wonkish question, to be sure, but one that has a lot of interesting applications to the AI arms race, where companies are trying to be the go-to ...

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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 ...

CublasOps is a PyTorch extension library that provides high-performance linear layers for half-precision (FP16) matrix multiplications using NVIDIA's cuBLAS and cuBLASLt libraries. It offers fast and ...

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 ...