Anchoring self-improvement loops with real external signals prevents AI model collapse
Mostafa Dehghani · AI is Already Building AI — Google DeepMind’s Mostafa Dehghani · Apr 2, 2026 · at 14:14
Mostafa Dehghani, research scientist at Google DeepMind, addresses whether training AI on its own synthetic data leads to model collapse during self-improvement loops.
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“Model collapse mainly happens when you have a loop that is Completely closed. Right. And if you don't have any outside signal and just the model, for example, talking to itself or operating in a very like a restricted environment there's a good chance that your model can access, but if you have a strong verifier or some sort of a, like a real reward signal that anchor this kind of like signals that is coming from like AI generated data, for example, it can be quite powerful.”
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