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Using ML to Improve Labeling Quality on Scale Rapid

Scale Rapid helps ML teams iterate quickly with an on-demand, end-to-end, labeling solution with rapid turnaround times. In this tech talk, we discuss the challenges to build quality infrastructure for crowd management, then discuss the role machine learning can play in:

  • Achieving high quality even with subjective tasks
  • Flagging potential problems with evaluation tasks
  • Suggesting improvements for project health

We'll discuss where ML can accelerate and scale human insights, the challenges of creating generalizable quality mechanisms, and the trade-offs that must be considered between accuracy and generalizability for such ML solutions.

Speakers
Kiko Ilagan
Kiko Ilagan
ML Lead, Rapid @ Scale AI
Bryan Chen
Bryan Chen
Lead Engineer, Rapid @ Scale AI
Zhichun Li
Zhichun Li
Head of Rapid @ Scale AI
Kiko Ilagan
Kiko Ilagan
ML Lead, Rapid @ Scale AI
Bryan Chen
Bryan Chen
Lead Engineer, Rapid @ Scale AI
Zhichun Li
Zhichun Li
Head of Rapid @ Scale AI
Agenda
7:00 PM
8:00 PM
Presentation

Using ML to Improve Labeling Quality on Scale Rapid

Scale Rapid helps ML teams iterate more quickly with an on-demand, end-to-end, labeling solution. In this tech talk, we discuss the challenges to build quality infrastructure for crowd management, then discuss the role machine learning can play in improving labeling quality and managing distributed workforces.

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Kiko Ilagan
Bryan Chen
Zhichun Li
Event has finished
April 06, 7:00 PM, GMT
Online
Hosted by
AI Exchange
AI Exchange
Event has finished
April 06, 7:00 PM, GMT
Online
Hosted by
AI Exchange
AI Exchange
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