I am not confused. Because herein these forums, I predicted everything that was going to happen years ago.

And the "insane inefficiency" of deep learning is fully to be expected from how it works. As well, there are provably no—literally no—emergent properties in these models. The choice of metric was a convenient, sloppy, and embarrassing fault of the field. It should be discredited; the field should be embarrassed; expectations on messaging should have changed; and it did not.

Why? Because the industry is full of charlatans, and this is a highly profitable enterprise telling people that this would lead to AGI.

Multiply two floating point numbers without a tool call. Still can't, because it's a curve fit.

So, in summary, nothing you just said is relevant. There are no emergent capabilities, simply 1) search, + 2) the original set of learned feature vectors from throwing tons of data at this.

Current LLMs can absolutely multiply floats without a tool call. In fact, that's a much more rote symbol-manipulation task than doing original math research.

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"I am not confused. Because herein these forums, I predicted everything that was going to happen years ago."

I mean, lol.