NVIDIA AI Day at University of Texas at Austin
from Wednesday, April 4, 2018 1:00PM to Wednesday, April 4, 2018 9:00PM
Ticket Information
Event Details
Join us for NVIDIA AI Day at UT Austin! Stop by and meet our University Recruiting team in the Engineering Education and Research Center (EERC) from 1PM-4PM. Pick up some cool swag and enter a raffle to win an NVIDIA Shield! In the evening, we will be hosting Technical Talks in EERC 1.518. Dr. Jeff Layton and Dr. Branislav Kisacanin from NVIDIA will be speaking on Accelerating AI with GPUs and Autonomous Driving. After the talks we will raffle off a Nintendo Switch. Food and drinks will be provided. When: Wednesday, April 4, 2018 Where: Engineering Education and Research Center (EERC) Who it's for: All University of Texas at Austin undergraduates, graduate students, postdocs, researchers, and professors Schedule of Events: 1:00PM - 4:00PM NVIDIA in the Lobby Location: EERC Lobby Pick up swag and enter the raffle! 7:00PM - 9:00PM Tech Talks Location: EERC 1.518 Dr. Jeff Layton, NVIDIA Senior Solutions Architect Dr. Branislav Kisacanin, NVIDIA Senior Architect Technical Talk Speakers and Details: Dr. Jeff Layton, NVIDIA Senior Solutions Architect Session Topic: Accelerating AI with GPU’s Data scientists in both industry and academia have been using GPUs for AI and machine learning to make groundbreaking improvements across a variety of applications including image classification, video analytics, speech recognition and natural language processing. In particular, Deep Learning – the use of sophisticated, multi-level “deep” neural networks to create systems that can perform feature detection from massive amounts of unlabeled training data – is an area that has been seeing significant investment and research. Although AI has been around for decades, two relatively recent trends have sparked widespread use of Deep Learning within AI: the availability of massive amounts of training data, and powerful and efficient parallel computing provided by GPU computing. Early adopters of GPU accelerators for machine learning include many of the largest web and social media companies, along with top tier research institutions in data science and machine learning. With thousands of computational cores and 10-100x application throughput compared to CPUs alone, GPUs have become the processor of choice for processing big data for data scientists. Dr. Branislav Kisacanin, NVIDIA Senior Architect and Master Builder Branislav Kisacanin is a computer scientist with Nvidia, where he works with chip architects towards future processors dedicated to autonomous vehicles. The first such chip, Xavier, offers its 30 TFLOPS / 30 Watts silicon brain to developers of self-driving cars. Branislav has been active in computer vision community with three computer vision books and six special issues of major vision journals. In his spare time, Branislav teaches competitive math and physics through the AwesomeMath Academy and Summer Programs and loves to travel with his family. Session Topic: AI and Visual Computing - Autonomous Driving We are approaching a new revolution in transportation fueled in large measure by advances in AI and visual computing - autonomous driving. The societal impact will be huge: self-driving cars will facilitate a drastic reduction in the number of fatalities and injuries due to car crashes, improve utilization of transportation resources, and open up new mobility options for many people. With this talk we hope to shed some light on impact that AI and visual computing have on what is likely to be the greatest revolution in transportation since the invention of internal combustion engine.
University of Texas at Austin
Engineering Education and Research Center Austin TX USType: Eventbrite