For R&D leaders evaluating AI investments, I’d offer one piece of advice: Before spending more on models, look hard at your ...

Training AI world models on data about physical environments could improve their real-world capabilities in technologies such ...

Model-based systems engineering (MBSE) has been around for a while, but it continues to gain ground in engineering projects ...

By putting the weights of a highly capable, 33B-parameter agentic model in the hands of researchers and startups, Poolside is ...

LAS VEGAS— Users of the Pentagon’s enterprise-wide generative-AI platform now have access to Google Cloud’s latest and most ...

Physics-trained AI models are accelerating engineering simulations by replacing or supplementing traditional solvers, enabling rapid design iteration in industries like automotive and aerospace. These ...

AI models trained on physical principles are starting to replace or complement traditional simulations in sectors such as automotive, aerospace, and semiconductors. These large physics models can ...