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Google’s $10 Million Bid for Spirit Airlines’ Data Reveals AI’s Next Frontier
Until now, the biggest jumps from this type of training have come from coding models, mostly because code has a useful property: it either works or it doesn’t, meaning that the reward signal is immediate, so improvement can happen in a fast loop. (It’s also helpful that there was plenty of coding data already out there on the internet, meaning models were good coders to begin with.)
But AI companies’ long-term goal is to automate large swathes of the economy. That’s where Spirit’s data likely comes in.
What makes the data useful
RL environments are only as good as the data that populates them, says Heiner of Surge AI. Companies like Surge and Mercor often hire human workers who are tasked with populating these environments with realistic data, either from scratch or in partnership with AI tools. “But even that is a little bit removed from literally having actual data that was used in the real world,” Heiner says. “That’s where deals like Spirit come in.”
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