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The Data Foundry for AI with Alexandr Wang from Scale

2024-05-22 · 39 min · episode 65 · 13 entities

episode page audio

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    The Data Foundry for AI with Alexandr Wang from Scale
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  • → hosted by Conviction company
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Entities found in this episode

concepts 6

  • mentioned Science concept
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  • mentioned Business concept
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    Feed category: Business
  • mentioned Entrepreneurship concept
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    Feed category: Entrepreneurship
  • discusses Science concept
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    Feed category: Science
  • discusses Business concept
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    evidence rules-v4
    Feed category: Business
  • discusses Entrepreneurship concept
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    evidence rules-v4
    Feed category: Entrepreneurship

companys 4

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

persons 2

  • mentioned Alexandr Wang from Scale person
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  • mentioned Alexandr Wang person
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    @alexandr_wang

podcasts 1

Episode description as stored
Alexandr Wang was 19 when he realized that gathering data will be crucial as AI becomes more prevalent, so he dropped out of MIT and started Scale AI. This week on No Priors, Alexandr joins Sarah and Elad to discuss how Scale is providing infrastructure and building a robust data foundry that is crucial to the future of AI. While the company started working with autonomous vehicles, they’ve expanded by partnering with research labs and even the U.S. government.   In this episode, they get into the importance of data quality in building trust in AI systems and a possible future where we can build better self-improvement loops, AI in the enterprise, and where human and AI intelligence will work together to produce better outcomes.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alexandr_wang (0:00) Introduction (3:01) Data infrastructure for autonomous vehicles (5:51) Data abundance and organization (12:06)  Data quality and collection (15:34) The role of human expertise (20:18) Building trust in AI systems (23:28) Evaluating AI models (29:59) AI and government contracts (32:21) Multi-modality and scaling challenges