Data science and machine learning technologies have long been important for data analytics tasks and predictive analytical software. But with the wave of artificial intelligence and generative AI ...

The list below is comprised of enterprise-level tools that include any level of AI capability which have been vetted and approved by CU Boulder. Campus users are encouraged to utilize these tools as ...

Traditional algorithms power complicated computational tools like machine learning. A new approach, called algorithms with predictions, uses the power of machine learning to improve algorithms.

Talk to any industry insider, and they’ll tell you that the landscape of software testing is undergoing a paradigm shift that’s rendering many existing practices inadequate. The pace of software ...

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...

The computational biologist Anne Carpenter creates software that brings the power of machine learning to researchers seeking answers in mountains of cell images. You can’t judge a book by its cover, ...

Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development.

A group of researchers are launching an open-source database of chemical synthesis procedures that they think will benefit artificial intelligence algorithms for reaction prediction, synthesis ...