To explore all newsletters, click here. By signing, you agree to the terms of service and privacy policy. Self-driving cars, single-pilot commercial planes, robotic soldiers, and widespread gene editing may still be things of the future, but a new research center in San Antonio is working to bring these and other artificial intelligence innovations to life. The University of Texas at San Antonio officially launched its newest research center, the UTSA Matrix AI Consortium, on Thursday morning via a livestream kickoff event. The consortium will bring together experts studying artificial intelligence to expand the use and deployment of AI. "This initiative is a concerted effort to promote AI innovation, something I'm a big fan about these days," UTSA President Taylor Eighmy said.

Join us in the Inaugural AI Summit at UTSA, to discover emerging AI technologies, transdisciplinary use-cases for AI, and how it impacts our society. If interested, please register via the link above.** If your organization is interested in sponsoring our event, please visit: http://www.cvent.com/d/fhqjm4 The University of Texas at San Antonio (UTSA)'s research portfolio has increasingly become more transdisciplinary, with a focus on cybersecurity, brain health,, engineering, biomed education, sustainability, business, public health and policy. These areas of research have been further fueled by focused faculty cluster hires in areas including cloud computing, cybersecurity, brain health, analytics and data science, and most recently, artificial intelligence (AI).

Recently, the posit numerical format has shown promise for DNN data representation and compute with ultra-low precision ([5..8]-bit). However, majority of studies focus only on DNN inference. In this work, we propose DNN training using posits and compare with the floating point training. We evaluate on both MNIST and Fashion MNIST corpuses, where 16-bit posits outperform 16-bit floating point for end-to-end DNN training.