Data-centric AI using
global crowd labeling

Date: January 27th, 2022
Time: 10:00 AM Pacific Time
In this webinar, we will initially review the fundamentals of Model-Centric AI vs. Data-Centric AI. We shall then showcase how the tasq.ai platform supports data-centric AI using adaptive sampling of the labeling from global crowds, automatic enrichment of the crowd itself, exploring the quality and consistency guarantees, and more.
 

Speakers

Speaker Img

Vadym Boikov

Head of AI
tasq.ai

Speaker Img

Prof. Shai Dekel

Visiting Associate Professor, School of Mathematical Sciences, University of Tel Aviv. General Partner, TLVSeed.

In this webinar, we will initially review the fundamentals of Model-Centric AI vs. Data-Centric AI. We shall then showcase how the tasq.ai platform supports data-centric AI using adaptive sampling of the labeling from global crowds, automatic enrichment of the crowd itself, exploring the quality and consistency guarantees, and more.

In this webinar you will learn:

  • Some fundamental model-centric AI concepts and understand their limitations
  • What data-centric AI is, and its key benefits
  • Algorithms used in data-centric AI platforms to ensure quality

Schedule:

  • 10:00 AM - 10:20 AM Model-centric AI versus data-centric AI, Prof. Shai Dekel
  • 10:20 AM - 10:50 AM Data-centric AI using the tasq.ai platform, Vadym Boikov
  • 10:50 AM -11:00 AM Q&A session
 

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Data-centric AI using global crowd labeling

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