DSDE: Emerging Technology

During transfer learning, the knowledge gained and rapid progress made from a source task is used to improve the learning and development to a new target task.

Integrating physics and machine learning combines the best of the two worlds, resulting in higher accuracy, better scalability, and cost efficiency.

A supervised machine-learning algorithm is developed to classify drilling parameters that increase rate of penetration and bit endurance for use in unconventional fields in Australia.

The register aims to help the maritime industry embrace technology advances in artificial intelligence.

The sheer expanse of the deep sea and the technological challenges of working in an extreme environment make these depths difficult to access and study. Scientists know more about the surface of the moon than the deep seafloor. The Monterey Bay Aquarium Research Institute is leveraging advancements in robotic technologies to address this disparity.

The most promising AI approach you’ve never heard of doesn’t need to go big.

This article examines how clusters with different properties are produced by different clustering algorithms. In particular, it provides an overview of three clustering methods: k-Means clustering, hierarchical clustering, and DBSCAN.

The authors develop a data-driven approach, enabled by machine learning, to find an optimal operating envelope for gas-lift wells.

Privacy concerns about AI systems are growing. So researchers are testing whether they can remove sensitive data without retraining the system from scratch.

Energy giant General Electric will be using one of the world's most powerful supercomputers, IBM's Summit, to run two new research projects that could boost the production of cleaner power.