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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?

A team of interdisciplinary researchers has discovered a new technique to store information in DNA – in this case "The Wizard of Oz," translated into Esperanto – with unprecedented accuracy and efficiency. The technique harnesses the information-storage capacity of intertwined strands of DNA to encode and retrieve information in a way that is both durable and compact. The technique is described in a paper in this week's Proceedings of the National Academy of Sciences.

Earl Potts, a University of Texas at Austin Computer Science and African and African Diaspora Studies student, has been featured in several local media outlets after he created the app "Keep Austin Black" to provide Austinites with an extensive directory of local Black-owned businesses. 

The datasets used by many software applications can be represented as graphs, defined by sets of vertices and edges. These graphs are rich with useful information, and can be used to determine patterns and relationships among the stored data. This process of discovering relevant patterns from graphs is called Graph Pattern Mining. A team of Texas Computer Science (TXCS) researchers advised by Dr. Keshav Pingali has done groundbreaking work to make these programs more efficient and accessible. Their work was recently accepted to Very Large Databases (VLDB) 2020, one of the premier conferences in computer science.

In response to high demand for professionals with scientific and technical training to understand and work with massive amounts of data, The University of Texas at Austin is set to launch a new online master's degree program in data science. Pending final approval by UT System and the Texas Higher Education Coordinating Board, the new program will be a collaboration between the Department of Computer Science, ranked among the top 10 programs in the country by U.S. News and World Report; the Department of Statistics and Data Sciences, one of the university's newest and fastest-growing departments; and online learning company edX.

Texas Computer Science graduate students Garrett Bingham and William Macke, under the advisement of professor Risto Miikkulainen, are contributing to the improvement of AI with their research. Their paper, entitled "Evolutionary Optimization of Deep Learning Activation Functions" was accepted into the 2020 Genetic and Evolutionary Computation Conference. The work concerns the evolutionary optimization of activation functions as a potential means of improving neural networks, which may ultimately lead to the creation of smarter and more accurate AI.

Each year, the College of Natural Sciences bestows its highest honors for graduating seniors on a select group of students. These students, known as Dean's Honored Graduates demonstrate excellence across multiple domains, achieving not only academically but in scientific research, independent intellectual pursuits, leadership, service, entrepreneurship and community building. Below are biographies of the 30 outstanding students selected by a committee of College of Natural Sciences faculty for this distinction in 2020.

Students at UT Austin already had plenty on their plates. When COVID-19 hit, the usual return from spring break and settling back into campus life turned instead into a mass migration—students scattering to shelter in place wherever they call home, in many cases moving back in with their families. Some became ill or began caring for sick family members. Classes moved online. Jobs ended. Everything was topsy turvy (it still is). But that hasn't stopped College of Natural Sciences undergraduates in public health, neuroscience and computer science from finding ways to help out their communities and fellow classmates.

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.

Artificial intelligence is becoming more and more a part of our daily lives. But will AI have mostly positive or negative impacts on society?