The database of 200 million protein-structure predictions now includes homodimers, adding new biological relevance.
Microsoft used Nvidia's GTC conference this week to roll out a series of enterprise AI announcements spanning agent infrastructure, real-time voice interactions and next-generation GPU deployments.
Nvidia used GTC 2026 to unveil new physical AI models, simulation tools, and robotics partnerships aimed at factories, healthcare, and logistics.
Physical AI demands real-world orientation: agents need spatial grounding, sensors, and context beyond language.
The 13% succeeding with AI platforms share one move: unifying their data on an extensible Postgres® foundation.
Abstract: Early availability of estimated values of critical Power-Performance-Area [PPA] parameters which are known only after end of EDA tool run, can be of immense value in accelerating design ...
Tight oil reservoirs, such as the Chang 8 formation in the Dadonggou area of the Ordos Basin, commonly encounter severe challenges including strong heterogeneity, and low recovery factors under ...
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AI weather models show promise for hurricane forecasts, but new study finds key physical limitations
Artificial intelligence is rapidly transforming weather prediction, enabling forecasts that once required hours of supercomputing time to run in just minutes. But as AI tools play an expanding role in ...
Abstract: Because of the complex and multifactorial nature of gear degradation, purely data-driven prediction models are often limited by their closed box characteristics, resulting in low reliability ...
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