Relationship between High Performance Computing and Artificial Intelligence
Monday, April 16
2:00 – 3:00 p.m.
Level 0 lecture hall between bldg. 2 and 3
High performance computing applications have typically been used to calculate predictions for example, of the weather, oil and gas field, financial derivative behavior or how mechanical structures respond to loads. Their approach has traditionally been deductive. For instance, one may start with the Black-Scholes or Navier Stokes equations, run compute-intensive calculations on input initial conditions and then make the needed predictions in finance or fluid dynamics respectively. However, the advent of artificial intelligence resulting from the reemergence of machine learning fueled by decades of accumulated records, we are starting to employ a data-intensive inductive approach.
Hosted by Dr. Jysoo Lee (Contact: 054 038 3167)
About the speaker:
Dr. Eng Lim Goh is the VP and CTO, HPC and AI, at Hewlett Packard Enterprise. His current research interest is in the progression from data-intensive computing to analytics, inductive machine learning, deductive reasoning and artificial specific to general intelligence. In collaboration with NASA he is currently principal investigator of a year-long experiment aboard the International Space Station – this project won both the 2017 HPCwire Top Supercomputing Achievement and Hyperion Research Innovation Awards. In 2005, InfoWorld named Dr. Goh one of the 25 Most Influential CTOs in the world. He was included twice in the HPCwire list of “People to Watch”. In 2007, he was named “Champions 2.0” of the industry by BioIT World magazine, and received the HPC Community Recognition Award from HPCwire. Dr. Goh did his postgraduate work at Cambridge University, UK. He has been granted six U.S. patents with three pending.