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Prabhat Ram

Principal Architect


AI History / ChatGPT

October 3, 2023 at 7:32:00 PM
Eagle Theater
Prabhat Ram

Science, Technology, Engineering, Math

The term 'Artificial Intelligence' was coined in the 1950s; there have been three distinct waves (1970s, 1990s and 2010s) that have shaped the field of AI, computer science and society most broadly. With the advent of ChatGPT, we believe that we are the inflection point of the application of a much broader suite of powerful applications than ever before.

This talk will briefly touch upon how we got here: what are the key developments in algorithms? what does it take behind the sciences in terms of datasets and computational systems to train AI systems? We will showcase demos from Microsoft and OpenAI, highlighting current applications.

Looking forward, we will speculate about where AI is headed, implications for society at large, and how students can better equip themselves to succeed in an AI-driven world.

Meet the Speaker:

Prabhat Ram is an AI/HPC Architect at Microsoft Azure. In this role, Prabhat works on developing supercomputing systems for enabling Deep Learning workloads. Prior to joining Microsoft, Prabhat led the Data and Analytics Group at NERSC (Berkeley Lab’s supercomputing center), worked as an interdisciplinary computer scientist at Berkeley Lab and a Virtual Reality researcher at Brown University.

Prabhat’s current research interests include Deep Learning, Machine Learning, Applied Statistics and High Performance Computing. He has worked on topics in Big Data and scientific data management; co-editing a book on ‘High Performance Parallel I/O’. Prabhat enjoys being at the interface of domain science (Cosmology, Astronomy, Climate Science, Neuroscience, High Energy Physics) and computer science.

Prabhat received a B.Tech in Computer Science and Engineering from IIT-Delhi, Masters in Computer Science from Brown University, and PhD in Climate Science from UC Berkeley. Prabhat has co-authored over 150 papers and was a part of the team that won the 2018 ACM Gordon Bell Prize for their work on ‘Exascale Deep Learning’.

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