With AlphaTensor, DeepMind Technologies has presented an AI system that is supposed to independently find novel, efficient and provably correct algorithms for complex mathematical tasks. AlphaTensor ...

Abstract: Matrix multiplication is one of the main issues in matrix calculus. The multiplication of small-scale matrices does not cause any difficulties while multiplying of large-scale matrices ...

Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...

ログインして、InfoQのすべての体験をアンロックしましょう！お気に入りの著者やトピックの最新情報を入手し、コンテンツと交流し、限定リソースをダウンロードできます。 MITのComputer Science & Artificial Intelligence Lab(CSAIL)に所属する研究者たちが、AMM ...

Google’s DeepMind has been using applied reinforced learning techniques to the multiplication of mathematical matrices and can do it better than some 50 year-old human-made algorithms. Bored with ...

Abstract: We identify the challenges that are special to parallel sparse matrix-matrix multiplication (PSpGEMM). We show that sparse algorithms are not as scalable as their dense counterparts, because ...

There has been an ever-growing demand for artificial intelligence and fifth-generation communications globally, resulting in very large computing power and memory requirements. The slowing down or ...

We’re just a few years into the AI revolution, but AI systems are already improving decades-old computer science algorithms. Google’s AlphaEvolve AI, its latest coding agent for algorithm discovery, ...

Describe the issue or outstanding question. Thanks for advancing HLSL forward with matrix multiply primitives. I am looking at the proposal with an eye on how it aligns with the WebGPU spec and what I ...