Meta-learning wanted a good initialization — language models turned out to be it
brianryhuang · x · 2026-10-29
Hamed Mahdavi observes that meta-learning researchers tried to define a loss and algorithm producing an initialization that trains well across diverse tasks — and language is precisely how the real world encodes domains, tasks, facts and problem-solving techniques. He notes it took only a few years to go from the meta-learning optimization framing to realizing a language model could achieve that goal.
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