The cloud-based agentic AI platform aims to help human researchers overcome resource constraints and complex data challenges ...
Researchers at the Department of Energy's Pacific Northwest National Laboratory use a slew of autonomous robots to design and ...
Quantitative experiments are essential for investigating, uncovering, and confirming our understanding of complex systems, necessitating the use of effective and robust experimental designs. Despite ...
Design of experiments (DOE) is an established method to allocate resources for efficient parameter space exploration. Model based active learning (AL) data sampling strategies have shown potential for ...
A research team at Google co-led by Michael Brenner, Catalyst Professor of Applied Mathematics and Physics at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and Google ...
This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. AI is moving beyond assisting scientists and taking an active role in discovery, with ...
Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.
AI life science benchmark LifeSciBench, published June 17 by OpenAI with 173 PhD scientists, shows frontier models clear only ...
Gabriel Gomes believes the future of chemistry is as much about flasks and fume hoods as it is about code. A chemical engineer at Carnegie Mellon University, Gomes works at the intersection of ...