For Sarthak Dassarma ’26, mathematics isn’t a set of rules to memorize—it’s a story, and the Putnam Competition is just his ...

SALT LAKE CITY, March 26, 2026 /PRNewswire/ -- Intactis Bio Corp, a leader in biohybrid computing, announced a major milestone: in a controlled laboratory setting, living brain cells (neurons) ...

The saying “round pegs do not fit square holes” persists because it captures a deep engineering reality: inefficiency most often arises not from flawed components, but from misalignment between a ...

First look: Light, not silicon, may define the next leap in computing power. That's the bet Austin-based startup Neurophos is making as it challenges the idea that Moore's Law still governs the pace ...

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 ...

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 ...

BUFFALO, N.Y. — Last year, onlookers observed a startling site on China’s Qiantang River: waves forming a grid-like pattern. Dubbed the “matrix tide,” this complex wave pattern was caused by the river ...

Google DeepMind today pulled the curtain back on AlphaEvolve, an artificial-intelligence agent that can invent brand-new computer algorithms — then put them straight to work inside the company's vast ...

We have said it before, and we will say it again right here: If you can make a matrix math engine that runs the PyTorch framework and the Llama large language model, both of which are open source and ...

In a move that directly challenges Nvidia in the lucrative AI training and inference markets, Intel announced its long-anticipated new Intel Gaudi 3 AI accelerator at its Intel Vision event. The new ...

Computer scientists have discovered a new way to multiply large matrices faster by eliminating a previously unknown inefficiency, leading to the largest improvement in matrix multiplication efficiency ...