Scientists at Carnegie Mellon Train AI to Predict the Mass of a Galaxy

Hubble Nets a Subtle Swarm. This Hubble image shows NGC 4789A, a dwarf irregular galaxy in the constellation of Coma Berenices. Original from NASA. Digitally enhanced by rawpixel.

Researchers at Carnegie Mellon University (CMU) used resources, including Bridges-2, supplied by the Pittsburgh Supercomputing Center (PSC) and allocated through ACCESS to train artificial intelligence to predict the mass of the Coma Cluster of galaxies. By feeding the AI all the known information about the Coma Cluster and teaching it to predict mass, CMU scientists could get a new kind of prediction, this time from a machine with deep-learning capabilities…

The post Scientists at Carnegie Mellon Train AI to Predict the Mass of a Galaxy appeared first on HPCwire.

More Related Posts

Teleoperation: indirect control methods for autonomous vehicles

Remote assistance methods such as “path choice” allows the remote operator to...

This AI Model Never Stops Learning | WIRED

Scientists at Massachusetts Institute of Technology have devised a way for large...

Chicago’s Bet on Quantum for Riches and Renewal

There’s a race around the world to build the next Silicon Valley,...

Home

Highly Niched Headhunters Specialized in Physical AI/Robotics, High-Performance Computing, Unmanned/Autonomous Systems, Defense Technology and Energy.

Specializations

We recruit across complex engineering markets where understanding the technology is critical to finding the right talent.

How We Work

Overview of how PACE partners with teams: Our process, what clients get, and why PACE is different.

About Us

PACE’s story, values, and culture define how we operate and who we are.

News & Insights

Stay up to date on industry trends.

Contact

All the information needed for anyone interested in contacting us.