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If AI data recognition can be automated, AI data that avoids recognition can be automated. It has nothing to do with imagination. It's simple reality.
by kdheiwns 7mo ago
If AI data recognition can be automated, AI data that avoids recognition can be automated. It has nothing to do with imagination. It's simple reality.
- eru 7mo agoYou still lack imagination! Assume it's exactly the arm's race you suggest. So OpenAI develops a new AI-content detection today, and tomorrow someone brings out something that defeats it. In a month OpenAI brings out another new technique that is unbeaten for only a day. Rinse and repeat. Is that what you had in mind? In any case, OpenAI knows exactly what it crawled when. So if it has a technique that only got beaten at timestamp X, then everything they crawled up to is good to use.
- kdheiwns 7mo agoThat solves nothing because that's already what it's doing. The problem of training is adding new data beyond what's currently validated and into the future. And it'll get harder to validate it.
- eru 7mo agoHuh? With the approach outlined above you can continuously keep adding new validated data. > And it'll get harder to validate it. Sure, and that's true in general: advances become harder, because we pick the low hanging fruit first anyway. Nothing new about that. The arms race I described is also only one approach. Model trainers will also want to investigate economising on training data, making their approaches more robust to model collapse, multi-modal training, and a million other strategies and tricks that I can't think of in thirty seconds.