One of the first steps toward becoming a scientist is discovering the difference between speed and velocity. To nonscientists, it’s usually a meaningless distinction. Fast is fast, slow is slow. But ...

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The ...

Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...

(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...

SHENZHEN, China, Jan. 16, 2026 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, proposed an innovative hardware acceleration ...

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 ...

I had great fun writing neural network software in the 90s, and I have been anxious to try creating some using TensorFlow. Google’s machine intelligence framework is the new hotness right now. And ...