Abstract: Reprogrammable optical meshes comprise a subject of heightened interest for the execution of linear transformations, having a significant impact in numerous applications that extend from the ...
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 ...
A linear algebra program for the TI-84 Plus CE graphing calculator. Matrix automates the mechanical parts of linear algebra, such as computing determinants, row reductions, inverses, Cramer's rule, ...
Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...
At the core of Transformers, a set of input activations is multiplied by a learned weight matrix to produce a new set of output activations. When the weight matrix is updated during training, the ...
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 ...
This project is a 24-core, 32-thread GPU designed for the Spartan-7 FPGA (xcs50-csga324-1). It is optimized for integer matrix multiplication and sprite copying to a frame buffer. The GPU employs a ...
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 ...
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