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Geospatial Machine Learning at AWS with Kumar Chellapilla - #607

2022-12-22 · 37 min · episode 607 · 14 entities

Asserted relationships

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    Geospatial Machine Learning at AWS with Kumar Chellapilla - #607
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    Feed author/publisher: Sam Charrington
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  • → hosted by TWIML company
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    Feed author/publisher: TWIML

Entities found in this episode

companys 5

  • mentioned TWIML company
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    Feed author/publisher: TWIML
  • mentioned Technology company
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    evidence rules-v4
    Feed category: Technology
  • discusses Technology company
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    evidence rules-v4
    Feed category: Technology
  • hosted by TWIML company
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    Feed author/publisher: TWIML
  • mentioned AWS company
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    AWS

concepts 5

  • mentioned Science concept
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    Feed category: Science
  • mentioned Tech News concept
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    Feed category: Tech News
  • discusses Science concept
    0.40
    evidence rules-v4
    Feed category: Science
  • discusses News concept
    0.40
    evidence rules-v4
    Feed category: News
  • discusses Tech News concept
    0.40
    evidence rules-v4
    Feed category: Tech News

persons 3

  • mentioned Kumar Chellapilla person
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    evidence rules-v4
    Geospatial Machine Learning at AWS with Kumar Chellapilla - #607
  • mentioned Sam Charrington person
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    evidence rules-v4
    Feed author/publisher: Sam Charrington
  • hosted by Sam Charrington person
    0.55
    evidence rules-v4
    Feed author/publisher: Sam Charrington

podcasts 1

Episode description as stored
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