Geospatial Machine Learning at AWS with Kumar Chellapilla - #607

Geospatial Machine Learning at AWS with Kumar Chellapilla - #607

Today we continue our re:Invent 2022 series joined by Kumar Chellapilla, a general manager of ML and AI Services at AWS. We had the opportunity to speak with Kumar after announcing their recent addition of geospatial data to the SageMaker Platform. In our conversation, we explore Kumar’s role as the GM for a diverse array of SageMaker services, what has changed in the geospatial data landscape over the last 10 years, and why Amazon decided now was the right time to invest in geospatial data. We discuss the challenges of accessing and working with this data and the pain points they’re trying to solve. Finally, Kumar walks us through a few customer use cases, describes how this addition will make users more effective than they currently are, and shares his thoughts on the future of this space over the next 2-5 years, including the potential intersection of geospatial data and stable diffusion/generative models. The complete show notes for this episode can be found at twimlai.com/go/607

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Taskonomy: Disentangling Transfer Learning for Perception (CVPR 2018 Best Paper Winner) with Amir Zamir - TWiML Talk #164

Taskonomy: Disentangling Transfer Learning for Perception (CVPR 2018 Best Paper Winner) with Amir Zamir - TWiML Talk #164

In this episode I'm joined by Amir Zamir, Postdoctoral researcher at both Stanford & UC Berkeley, who joins us fresh off of winning the 2018 CVPR Best Paper Award for co-authoring "Taskonomy: Disentan...

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Predicting Metabolic Pathway Dynamics w/ Machine Learning with Zak Costello - TWiML Talk #163

In today’s episode I’m joined by Zak Costello, post-doctoral fellow at the Joint BioEnergy Institute to discuss his recent paper, “A machine learning approach to predict metabolic pathway dynamics fro...

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Machine Learning to Discover Physics and Engineering Principles with Nathan Kutz - TWiML Talk #162

Machine Learning to Discover Physics and Engineering Principles with Nathan Kutz - TWiML Talk #162

In this episode, I’m joined by Nathan Kutz, Professor of applied mathematics, electrical engineering and physics at the University of Washington to discuss his research into the use of machine learnin...

9 Heinä 201843min

Automating Complex Internal Processes w/ AI with Alexander Chukovski - TWiML Talk #161

Automating Complex Internal Processes w/ AI with Alexander Chukovski - TWiML Talk #161

In this episode, I'm joined by Alexander Chukovski, Director of Data Services at Munich, Germany based career platform, Experteer. In our conversation, we explore Alex’s journey to implement machine l...

5 Heinä 201839min

Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk #160

Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk #160

In this episode, I'm joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University to discuss two of her recent papers, “Noisin: Unbiased Regularization for Recurrent...

2 Heinä 201838min

Love Love: AI and ML in Tennis with Stephanie Kovalchik - TWiML Talk #159

Love Love: AI and ML in Tennis with Stephanie Kovalchik - TWiML Talk #159

In the final show in our AI in Sports series, I’m joined by Stephanie Kovalchik, Research Fellow at Victoria University and Senior Sports Scientist at Tennis Australia. In our conversation we discuss...

29 Kesä 201846min

Growth Hacking Sports w/ Machine Learning with Noah Gift - TWiML Talk #158

Growth Hacking Sports w/ Machine Learning with Noah Gift - TWiML Talk #158

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28 Kesä 201850min

Fine-Grained Player Prediction in Sports with Jennifer Hobbs - TWiML Talk #157

Fine-Grained Player Prediction in Sports with Jennifer Hobbs - TWiML Talk #157

In this episode of our AI in Sports series, I'm joined by Jennifer Hobbs, Senior Data Scientist at STATS, a collector and distributor of sports data, to discuss the STATS data pipeline and how they co...

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