Abstract: Convolutional neural networks (CNNs) are one of the most popular machine learning algorithms. The convolutional layers, which account for the most execution time of CNNs, are implemented ...

Artificial intelligence grows more demanding every year. Modern models learn and operate by pushing huge volumes of data through repeated matrix operations that sit at the heart of every neural ...

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, ...

Researchers from the USA and China have presented a new method for optimizing AI language models. The aim is for large language models (LLMs) to require significantly less memory and computing power ...

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

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 ...