MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...

Researchers create a photochromic fluorescent system that performs optical neural computing and visual output in one step, cutting power use and complexity. (Nanowerk News) The rapid growth of ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

Element-wise multiplication in Python is a fundamental operation, especially when working with numerical data using libraries like NumPy. Understanding how to perform this efficiently is crucial for ...

Abstract: Structured sparsity has been proposed as an efficient way to prune the complexity of Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. Accelerating ...

A new technical paper titled “Leveraging ASIC AI Chips for Homomorphic Encryption” was published by researchers at Georgia Tech, MIT, Google and Cornell University. “Cloud-based services are making ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.

Artificial intelligence (AI) processing rests on the use of vectorised data. In other words, AI turns real-world information into data that can be used to gain insight, searched for and manipulated.