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Al then φ(x) min x2 f ~ GP(m(x), k(x, x) w s.t. yi(wTxi +b)≥1-ξi A B f(x)↑ X X 5i≥0 . C k(x,x)= 2 |lwll (φ(x)φ(x)) E x D $x1 y = f (x) +c ε ∼ N (0,λ2 designed kernel methods proved generalization fit graphical models built gaussian processes feature maps and SVMs bounds bayes nets + message passing uncertainty came for free statistical learning theory Al now Tokens ↑ More data Transformer Scale Block Everything + More GPUs Transformer Block ↑ GPU just scaled scaled them it worked state of the art transformers up again somehow just keep scaling make it bigger more data more GPUs emergent abilities?

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