Quantum physics may sound abstract, but Ph.D. candidates Kirsten Kanneworff and David Dechant show that quantum research can ...

Multifidelity optimization can inform decision-making during process development and reduce the number of experiments ...

Let’s look at how RL agents are trained to deal with ambiguity, and it may provide a blueprint of leadership lessons to ...

Multiverse Computing SL, a startup with technology that reduces the hardware footprint of artificial intelligence models, is reportedly raising new capital. Sources told Bloomberg today the Spanish ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

Quantum physics may sound abstract, but PhD candidates Kirsten Kanneworff and David Dechant show that quantum research can ...

A Russian mathematician has developed a new method for analyzing a class of equations that underpin models in physics and economics and are considered "eternal" as they have challenged researchers for ...

Although bioreactor scale-up often involves matching key engineering parameters, a biology-first approach should dictate the process.

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...