I mean. Fundamentally they are just autoregressive next token predictors. Fundamently fou can simplify to f(x) -> x+y where x is input tokens, y is the next tok

I mean. Fundamentally they are just autoregressive next token predictors. Fundamently fou can simplify to f(x) -> x+y where x is input tokens, y is the next token and f() is the model function. Yes the model function is complex but still.