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Manish Gupta

Director

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Dr. Manish Gupta is the Director of research at Google, leading teams across India, Australia, and the US. Previously, Manish has led VideoKen, a video technology startup, and the research centers for Xerox and IBM in India. As a Senior Manager at the IBM T.J. Watson Research Center in Yorktown Heights, New York, Manish led the team developing system software for the Blue Gene/L supercomputer. IBM was awarded a National Medal of Technology and Innovation for Blue Gene by the then US President Barack Obama in 2009. Manish holds a Ph.D. in Computer Science from the University of Illinois at Urbana Champaign. He has co-authored about 75 papers, with more than 8,000 citations in Google Scholar, and has been granted 19 US patents. While at IBM, Manish received two Outstanding Technical Achievement Awards, an Outstanding Innovation Award, and a Lou Gerstner Team Award for Client Excellence. Manish is a Fellow of ACM and the Indian National Academy of Engineering and a recipient of a Distinguished Alumnus Award from IIT Delhi. He has been working with and leading the research community in India for roughly two decades.

We begin by presenting the recent advances in the area of artificial intelligence and the high-level ideas underlying the progressively narrower domains of machine learning, deep learning, and foundation models, which have emerged over time as dominant paradigms for artificial intelligence. We describe the tremendous progress of these models on problems ranging from understanding, prediction, and creativity on the one hand and challenges likes, open technical, safety, fairnes and transparency on the other hand.

These challenges are further amplified as we seek to advance Inclusive AI to tackle problems for billions of human beings in the context of countries like India. We present our work on multilingual models to democratize information access in a diverse set of Indian languages, on healthcare in environments where we lack data in digital form, to begin with, and on analysis of satellite imagery to help transform agriculture and improve the lives of farmers. Through these examples, we hope to convey the excitement of the potential of AI to make a difference to the world, and also a fascinating set of open problems to tackle. 

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Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More

Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More
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