Artificial Intelligence

Artificial intelligence and machine learning are among the trendiest technologies in the world right now, and The University of Texas at Austin is rapidly becoming a leader in advancing these concepts as they come to impact more aspects of our daily lives. UT’s AI/ML chops leveled up even further this year when Zhangyang “Atlas” Wang joined the Cockrell School after three years as an assistant professor at Texas A&M University. Wang’s research has garnered recognition from such luminaries in the field as Amazon and IBM.

Modern communications technology, regardless of use, relies on a similar formula: devices send signals and information through data centers, towers and satellites en route to their final destination. The effectiveness of the communication relies on how well that information travels, and there are a variety of factors that can slow down that journey – geography, weather and more.

The National Science Foundation has selected The University of Texas at Austin to lead the NSF AI Institute for Foundations of Machine Learning, bolstering the university’s existing strengths in this emerging field. Machine learning is the technology that drives AI systems, enabling them to acquire knowledge and make predictions in complex environments. This technology has the potential to transform everything from transportation to entertainment to health care.

After graduating from UT Austin in 2010 with a master’s degree in electrical and computer engineering, Sowmiya Narayanan went on to co-found Lily AI — an AI-based software designed to enhance users’ online shopping experiences — and she now serves as its chief technology officer.

Bringing together experts in areas ranging from robotics to space, the Cockrell School of Engineering will host the U.S. Army’s annual Mad Scientist Conference on April 24-25 in the school’s Engineering Education and Research Center. The two-day event explored the individual and convergent impacts of technological innovations on the future of military operations, from present day through 2050.

Where Longhorns once played basketball, robots now play soccer.

Wang, a pioneer in the integration of data, has begun analyzing driving behavior by interconnecting three different data sources — a driving simulator; a standalone engine, or powertrain; and a fully equipped autonomous vehicle prototype designed by UT researchers.

Thanks to Luis Sentis and the amazing work happening in his Human Centered Robotics Laboratory, the same type of balance and “natural” control that humans use may soon be experienced by robots.

Tom Truskett and his team believe there is a better way to bring products to market sooner, and it starts with machine learning.

The smart cities movement has gained momentum, pushed forward by political leaders, scientists, engineers and residents of cities themselves.