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Had a chat with my nephew last week that changed how I see AI training data

My nephew is 22 and works at a small startup in Austin doing data labeling for AI models. I always thought the data these models learn from was mostly scraped from the web or bought in big batches. But he explained they spend hours carefully tagging images and text by hand just to get a few hundred good examples. He said the quality of the data matters way more than the quantity, and one bad label can mess up an entire model's output. That really hit me because I usually focus on the algorithms and not the grunt work behind them. Has anyone else here been surprised by how much manual effort goes into training sets?
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riley_coleman8
Honestly I think people overstate how much "grunt work" actually matters. Most of these data labeling startups are glorified sweatshops where the workers don't even understand what they're tagging. You really think a 22 year old in Austin knows more about proper dataset curation than a web scraper pulling from millions of real world examples? Manual labeling introduces its own biases and errors. Google and OpenAI aren't spending billions on algorithms just to rely on some kid with a mouse clicking boxes for minimum wage.
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umac71
umac718d ago
Some kid with a mouse clicking boxes for minimum wage" sounds like my nephew's summer job, honestly.
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