Robust, deployable and collaborative machine learning (ML) methods are needed for AI to become truly useful. This ERC-funded research aims to solve a major ML bottleneck and will form a cornerstone of ...

Most ML projects fail to reach production. Five recurring pitfalls drive failures in ML projects: choosing the wrong problem, data quality/labeling issues, the model-to-product gap, offline-online ...

Machine learning, a type of artificial intelligence, has many applications in science, from finding gravitational lenses in the distant universe to predicting virus evolution. Hubble Space Telescope ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Data volumes continue to explode with the global “datasphere” – the total amount of data created, captured, replicated and consumed – growing at more than 20 percent a year to reach approximately 291 ...