DSDE: Emerging Technology

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.

The US Department of Energy’s Office of Fossil Energy and Carbon Management awarded a total of $600,000 to four software developers who won a contest to support FECM’s Science-Informed Machine Learning to Accelerate Real-Time Decisions in the Subsurface Initiative.

Data center company Crusoe Energy Systems is sounding out investor interest in a potential debt deal that would help grow the firm’s Bitcoin mining business, according to people with knowledge of the mater.

Although quantum computing, or quantum processing, has still not become a reality in the oil and gas industry, it will prove disruptive according to an executive of a Brazilian player.

The latest iteration of the Top500 list puts the Perlmutter supercomputer at Lawrence Berkeley Laboratory in the spotlight.

The carbon footprint of Bitcoin and other cryptocurrencies has been making headlines recently. This article explains what drives their energy consumption and presents alternative approaches.

Being able to deploy machine-learning applications at the edge is the key to unlocking a multibillion-dollar market. TinyML is the art and science of producing machine-learning models frugal enough to work at the edge, and it's seeing rapid growth.