High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

The UC Berkeley crew has now shown the value of AI-based optimization work by having OpenEvolve work out a more efficient ...

Researchers from the Institute for Artificial Intelligence at Peking University, led by Sun Zhong, have developed a ...

According to the researchers, the approach uses what they call a “fingerprint matrix,” which is a mathematical description of the way each object uniquely scatters waves such as light or ultrasound.

Chinese researchers develop high-precision scalable analog matrix computing chip based on resistive memory, realizing for the ...

Researchers in India have developed an algorithm for quadrant swapping in PV arrays, enabling the creation of new quadrants ...