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

Multiverse’s flagship product is a platform called CompactifAI that reduces the amount of infrastructure needed to run AI models. According to the company, the software can halve training times and ...

Quantum physics may sound abstract, but Ph.D. candidates Kirsten Kanneworff and David Dechant show that quantum research can also be very concrete. Together, they are investigating how quantum ...

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

A mathematical equivalent of a microscope with variable resolution has shed light on why some atoms are exceptionally stable, a riddle that has persisted in nuclear physics for decades ...

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

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.

Historian Philip Decker, mathematician Victor Geadah, computer scientist Sayash Kapoor, and literary scholar Eliana Rozinov are this year’s Porter Ogden Jacobus Fellows.

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 ...

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