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Comment by _yb2s

> You don't seem to understand how they work

I don't think anyone understands how they work- these type of explanations aren't very complete or accurate. Such explanations/models allow one to reason out what types of things they should be capable of vs incapable of in principle regardless of scale or algorithm tweaks, and those predictions and arguments never match reality and require constant goal post shifting as the models are scaled up.

We understand how we brought them about via setting up an optimization problem in a specific way, that isn't the same at all as knowing how they work.

I tend to think in the totally abstract philosophical sense, independent of the type of model, at the limit of an increasingly capable function approximator trained on an increasingly large and diverse set of real world cause/effect time series data, you eventually develop and increasingly accurate and general predictive model of reality organically within the model. Some model types do have fundamental limits in their ability to scale like this, but we haven't yet found one with these models.

It is more appropriate to objectively test what they can and cannot do, and avoid trying to infer what we expect from how we think they work.

parent _yb2s 1 year ago

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