Automation in Labeling

Shayan discusses the growing accessibility of data labeling work, which has led to an oversupply of labor and declining wages. He emphasizes the need for automation to alleviate the burden of undesirable jobs, like content moderation, and advocates for a more efficient process where a single expert can leverage software to streamline labeling tasks. This shift aims to create sustainable workflows while reducing reliance on manual labor.

In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
635: The Perils of Manually Labeling Data for Machine Learning Models — with Shayan Mohanty
Related Questions
- Is less labeled data needed for training machine learning models according to the episode The Fallacy of "Ground Truth" with Shayan Mohanty - #576 and the clip Active Learning Insights?

Automation in Labeling

In this clip

From this podcast

Super Data Science: ML & AI Podcast with Jon Krohn

635: The Perils of Manually Labeling Data for Machine Learning Models — with Shayan Mohanty

Related Questions

Is less labeled data needed for training machine learning models according to the episode The Fallacy of "Ground Truth" with Shayan Mohanty - #576 and the clip Active Learning Insights?