World Model · podcast knowledge graph

Machine Learning as a Software Engineering Enterprise with Charles Isbell - #441

2020-12-23 · 46 min · episode 441 · 13 entities

episode page audio

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    Machine Learning as a Software Engineering Enterprise with Charles Isbell - #441
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  • → hosted by TWIML company
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    Feed author/publisher: TWIML

Entities found in this episode

concepts 5

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

companys 4

  • mentioned TWIML company
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    Feed author/publisher: TWIML
  • mentioned Technology company
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    Feed category: Technology
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    Feed category: Technology
  • hosted by TWIML company
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    Feed author/publisher: TWIML

persons 3

  • mentioned Charles Isbell person
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    Machine Learning as a Software Engineering Enterprise with Charles Isbell - #441
  • mentioned Sam Charrington person
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    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
As we continue our NeurIPS 2020 series, we’re joined by friend-of-the-show Charles Isbell, Dean, John P. Imlay, Jr. Chair, and professor at the Georgia Tech College of Computing. This year Charles gave an Invited Talk at this year’s conference, You Can’t Escape Hyperparameters and Latent Variables: Machine Learning as a Software Engineering Enterprise. In our conversation, we explore the success of the Georgia Tech Online Masters program in CS, which now has over 11k students enrolled, and the importance of making the education accessible to as many people as possible. We spend quite a bit speaking about the impact machine learning is beginning to have on the world, and how we should move from thinking of ourselves as compiler hackers, and begin to see the possibilities and opportunities that have been ignored. We also touch on the fallout from Timnit Gebru being “resignated” and the importance of having diverse voices and different perspectives “in the room,” and what the future holds for machine learning as a discipline. The complete show notes for this episode can be found at twimlai.com/go/441.