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Jeff Beck: evaluation

25 Jan 2026 Machine Learning Street Talk VAEs Are Energy-Based Models? [Dr. Jeff Beck]

“Because you know what's going on, you could say, oh, well, it's it's clearly like executing, you know, this is it's doing planning and counterfactual reasoning.”

— Jeff Beck

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Speaker
Jeff Beck
Attribution
Verified speaker
Claim type
evaluation
Recorded
25 Jan 2026
Publisher
Machine Learning Street Talk

Transcript context

…I think my intuition is if it feels to me that a function, a simple input output mapping can't be an agent. And in a way, is related to what we were talking about with grounding. It seems that when things are physically embedded in the world, then they're more likely to be agents. This functionalist idea that's just a bit of computer code running on a machine, it kind of feels like that can't be an agent. It does. So suppose I coded it up so it was doing all of that planning. It's like gets its inputs to some crazy, like massive Monte Carlo tree search, picks the best policy possible, and then executes it. Now you don't observe any of that. Right? Because you know what's going on, you could say, oh, well, it's it's clearly like executing, you know, this is it's doing planning and counterfactual reasoning. It's going on, like, look, there it is. Because you coded it, so you know it's doing it. But if you're looking at it from the outside, right, it you know, if you don't know what's happening inside, it's going you know, all you have access to is, oh, here's the action that it that it that it did given this long series of inputs. And so it's it's really hard to identify what, you know, something as an agent per se from the outside. You kinda have to know what's going on inside. This, by the way, is why I don't think that, like, you know, can you know, these sort of prediction based approaches to, AI are you know, you could sort of say, well, it it's not really doing anything even remotely agentic unless it's executing and doing planning counterfactual reasoning. So, like, your chess program is is like, oh, clearly, it's doing some planning and counterfactual reasoning because you know it's doing it. But but it but you could like write I could describe the exact same set of behaviors just with the policy function. I think the counterfactual thing is an important feature here because we could take something which was conscious or something which had agency, and we could just take a trace of the actual path which was found. And now we've just got this is reductio ad absurdum. But now we've just got a computational trace. And that thing clearly has now lost whatever agency or consciousness it had. So there's something about considering all of the possibilities.…

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