Why I Was Wrong About AI Companies Pumping the Brakes: It Wasn’t About Data
A short while ago, I published a piece arguing that the sudden, performative hesitation by frontier AI companies wasn’t driven by altruistic safety concerns, but by a cold, physical reality: the data wall.
I laid out the math. The public internet had been scraped dry. Citing projections from research groups like Epoch AI on the limits of LLM scaling, human-generated text was on track for exhaustion. The web was drowning in recursive synthetic slop, and model collapse was threatening the brute-force scaling paradigm. I argued that the labs were hitting the brakes because their engines were simply starving for clean fuel.
I was right about the physics. But I was fundamentally wrong about the strategy.
I gave these executives too much credit for engineering humility.
The labs aren’t tapping the brakes because they fear their models will collapse on bad data, nor because they fear AGI will break out...
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