Abstract: Accurate programming of non-volatile memory (NVM) devices in analog in-memory computing (AIMC) cores is critical to achieve high matrix-vector ...

Forgive me for starting with a cliché, a piece of finance jargon that has recently slipped into the tech lexicon, but I’m afraid I must talk about “moats.” Popularized decades ago by Warren Buffett to ...

ETL is a header only library for C++ that provides vector and matrix classes with support for Expression Templates to perform very efficient operations on them. At this time, the library support ...

The LEEMONS project is researching nanostructured silicon that uses low-energy electron multiplication (LEEM) to allow one high-energy photon to generate multiple electrons, reducing energy losses in ...

The growing demand for AI has pushed modern data centers toward unprecedented requirements in computing speed and energy efficiency. Photonic processors, which exploit the massive bandwidth and ...

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Matrix multiplication stands as one of the most computationally intensive operations in modern computing, forming the backbone of everything from 3D graphics to neural networks and scientific ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

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, ...

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 ...

Integer linear programming can help find the answer to a variety of real-world problems. Now researchers have found a much faster way to do it. Inspired by the results of a game-playing neural network ...