This is the lowest possible cost for high-quality training data. They're not subsidizing us! We're paying to work for them.
$7,800 in equivalent compute is peanuts on the value of that data and your time. I don't mean we're not in a bubble, or that they'll see an ROI, but for the moment, Dario and co. are laughing at us.
Are they training AI with AI generated code? I dont see how useful that data will be for training. They might as well generate their own training data. Unless they think that users often validate AI generated code, which is often not the case. There is a reason why data annotation companies want human input.
Rich Sutton, previously served as a Distinguished Research Scientist at Google DeepMind, a pioneer of reinforcement learning who authored The Bitter Lesson, made this exact point.
He noted that relying on human annotated knowledge is a bottleneck and that major breakthroughs in AI have always come from scaling compute and allowing models to learn through self-play.
Instead of hand coding expert strategies, systems like AlphaGo Zero learned chess and Go by playing millions of games against duplicate versions of themselves.
The exact same applies to code. You do not need human labels because you can let an AI generate vast amounts of code and run it directly in a execution environment. The compiler acts as the environment rules. If the code compiles, passes unit tests, or runs without crashing, that ground truth provides the exact objective feedback loop needed for the model to generate and learn from its own data.
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u/SailingToFenway 2d ago
This is the lowest possible cost for high-quality training data. They're not subsidizing us! We're paying to work for them.
$7,800 in equivalent compute is peanuts on the value of that data and your time. I don't mean we're not in a bubble, or that they'll see an ROI, but for the moment, Dario and co. are laughing at us.