How to use, analyze, and interpret the AI-powered data Quality Control runs offered by Hasty.ai

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In the modern world, data quality is just as (if not more) important as data quantity. Still, the conventional Quality Control process for annotations is expensive, slow, and time-consuming. So, we in Hasty addressed the problem and developed an AI-powered Quality Control feature - AI Consensus Scoring. With its help, you can streamline your Quality Control process and spare some time, money, and nerves. Want to know more? Watch the video and see how exactly we can help.

Links:

Chapters:

0:00 Intro
0:56 How to schedule an AI Consensus Scoring run?
2:31 How to work with the AI CS runs' results?
4:45 How to review AI CS suggestions in the annotation environment?
5:42 The real power of AI Consensus Scoring
7:08 Give us a try!