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Artificial Intelligence

Mission Accomplished

Anna Hiss Gym Ribbon Cutting

11/05/2020 - UT Austin is committed to working with the U.S. military to identify and prioritize research that can quickly be adapted to help protect and defend the nation’s interest.

UT Scientists Use AI to Find Tourist Movement Patterns in Cuzco, Peru

10/28/2020 - We live in an increasingly digital era. Research shows that the average American checks their phone about 58 times daily, and spends an average of 4.5 hours a day on their phone. Without a doubt the amount of time the modern-day person spends on their phones has changed many aspects of how our society functions. For example, in the past decade we have seen a dramatic shift in forms of advertising.

Artificial Intelligence Revs Up Evolution’s Clock (Audio)

Hyenas mobbing a lion

10/14/2020 - Evolutionary biologists never have enough time. Some of the most mysterious behaviors in the animal kingdom—like parenting—evolved over thousands of years, if not longer. Human lifespans are just too short to sit and observe such complex behaviors evolve. But computer scientists are beginning to offer clues by using artificial intelligence to simulate the life and death of thousands of generations of animals in a matter of hours or days. It's called computational evolution.

Mobile Robotics Lab Reaches Milestone in Campus-Scale Autonomous Navigation

The UT Campus-Jackal (left) and the UT Campus-Husky (right)

10/06/2020 - A group of Texas Computer Science (TXCS) researchers from the Autonomous Mobile Robotics Laboratory (AMRL) comprising Joydeep Biswas, Sadegh Rabiee, Jarrett Holtz, Kavan Sikand, Max Svetlik, and John Bachman (UMass Amherst) have reached an incredible milestone in their research: deploying an autonomous robot that autonomously navigates on the campus-scale, resilient to everyday changes and varying conditions.

UT Austin Selected as Home of National AI Institute Focused on Machine Learning

Image from Philipp Krähenbühl's Object Detection Research

08/26/2020 - The National Science Foundation has selected The University of Texas at Austin to lead 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.

Investigating How to Make Robots Better Team Members

surgical team in operating room monitoring patient stats

07/17/2020 - Imagine that you are a robot in a hospital: composed of bolts and bits, running on code, and surrounded by humans. It’s your first day on the job, and your task is to help your new human teammates—the hospital’s employees—do their job more effectively and efficiently. Mainly, you’re fetching things. You’ve never met the employees before, and don’t know how they handle their tasks. How do you know when to ask for instructions? At what point does asking too many questions become disruptive?

New Partnership Aims to Demystify Artificial Intelligence “Black Boxes”

03/25/2020 - The promise of artificial intelligence to solve problems in drug design, discover how babies learn language, and make progress in many other areas has been stymied by the inability of humans to understand what's going on inside AI systems. Researchers at six universities, including The University of Texas at Austin, are launching a partnership aimed at turning these AI "black boxes" into human-interpretable computer code, allowing them to solve hitherto unsolvable problems.

Texas CS Alumnus Joins the Race to Build Self-Driving Trucks

01/23/2020 - The race to build the best autonomous cargo vehicle is heating up, indicating big developments for the $700 billion U.S. trucking market. With the rise of e-commerce comes the accompanying need for more efficiently delivered goods, a demand that the transportation industry is not currently equipped to cope with. Self-driving trucks could solve this problem by simultaneously decreasing the cost and increasing the safety of freight transport.