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A Radical New Computer Could Replace Electricity With Light—and Make Processing Unstoppable
A team of researchers developed “parallel optical matrix-matrix multiplication” (POMMM), which could revolutionize tensor processing by enabling a single light source to perform multiple operations ...
More than 900 students at UC San Diego needed catch-up math classes in the fall of 2025 compared to 32 five years earlier.
Here’s what you’ll learn when you read this story: Scientists in China are suggesting a new model of computing that could massively shorten processing time—if it works, that is. To contextualize their ...
For 24 years, Microsoft’s Amanda Silver has been working to help developers — and in the last few years, that’s meant ...
Live Science on MSN
'Proof by intimidation': AI is confidently solving 'impossible' math problems. But can it convince the world's top mathematicians?
AI could soon spew out hundreds of mathematical proofs that look "right" but contain hidden flaws, or proofs so complex we ...
Bitcoin — a type of digital money known as cryptocurrency — is completely decentralized, meaning there are no banks or governments that oversee it. Instead of institutional oversight, they use a ...
How Fast Will A.I. Agents Rip Through the Economy? transcript The thing about covering A.I. over the past few years is it ...
It’s expensive, and it’s not just Mamdani who wants it. Several years ago, the State Legislature passed a law requiring ...
Today's Artificial Intelligence is a super-fast "Guessing Machine." It looks at millions of old examples and makes a "best guess." These guesses are often biased, they can "hallucinate," and they ...
Tech Xplore on MSN
Reasoning: A smarter way for AI to understand text and images
Engineers at the University of California San Diego have developed a new way to train artificial intelligence systems to solve complex problems more reliably, particularly those that require ...
Live Science on MSN
'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images
Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.
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