MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

Abstract: We propose an efficient quantum subroutine for matrix multiplication that computes a state vector encoding the entries of the product of two matrices in superposition. The subroutine ...

llama.cpp runs incredibly fast on Apple silicon, I ran a build with pure CPU, and it is closer to the memory bandwidth e.g. 28 tokens/s on an M3 Pro. llama3.java seems to be rather slow on Apple ...

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 ...

PyTorch introduced TK-GEMM, an optimized Triton FP8 GEMM kernel, to address the challenge of accelerating FP8 inference for large language models (LLMs) like Llama3 using Triton Kernels. Standard ...

One way to grasp how fully our relationship to computers changed over the 1990s is to look at the cyberthrillers Hollywood made during that time. Mass surveillance, identity theft, the hacking of the ...

A matrix is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. They are a crucial part of linear algebra and have various applications in fields like engineering, ...