Computing power has increased exponentially over the past few decades. We now have cameras on smartphones with incredible computational photography, voice assistants that respond near instantaneously, ...

In real applications of Reinforcement Learning (RL), such as robotics, low latency, energy-efficient and high-throughput inference is very desired. The use of sparsity and pruning for optimizing ...

In 1943, a pair of neuroscientists were trying to describe how the human nervous system works when they accidentally laid the foundation for artificial intelligence. In their mathematical framework ...

Transformer in artificial intelligence has become the core technology behind most modern AI systems. Since the breakthrough 2017 research paper “Attention Is All You Need” by scientists at Google, the ...

Mark Zuckerberg has reorganized his company’s ambitions around a hypothetical future that is suddenly the talk of Silicon Valley. By Cade Metz Reporting from San Francisco On Thursday, Meta unveiled a ...

Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this ...

Designing materials that steer light is a slow kind of trial and error. Each candidate structure must be tested in computer ...