Forbes contributors publish independent expert analyses and insights. Writes about the future of payments. We live in a world where machines can understand speech, recognize faces, and even generate ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine-learning model might think it is a new data point. In computer science ...

Machine learning interatomic potentials (MLIP) are a topic of very active research, promising to bring the high accuracy of electronic structure methods to large space and long time scales previously ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

Simulating catalytic reactivity under operative conditions poses a significant challenge due to the dynamic nature of the catalysts and the high computational cost of electronic structure calculations ...

Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...

Successful AI adoption depends less on models and technology than on workforce transformation, process redesign and ...

VE3 AI Research publishes a study on synthetic data, magnetic dipole modeling, and unsupervised AI for scalable anomaly ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

The majority (80%) of asset managers now view artificial intelligence (AI) and machine learning (ML) as a key driver of market data delivery and consumption over the next two years, according to new ...