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Luckily we can train the AIs to give us answers optimized to sound plausible to humans.

I think Minsky got those two stages the wrong way around.

Complex plans over long time horizons would need to be done over some nontrivial world model.

When Jan Leike (OAI's head of alignment) appeared on the AXRP podcast, the host asked how they plan on aligning the automated alignment researcher. Jan didn't appear to understand the question (which had been the first to occur to me). That doesn't inspire confidence.

Just listened to this.

It's sounds like Harnad is stating outright that there's nothing an LLM could do that would make him believe it's capable of understanding.

At that point, when someone is so fixed in their worldview that no amount of empirical evidence could move them, there really isn't any point in having a dialogue.

It's just unfortunate that, being a prominent academic, he'll instill these views into plenty of young people.

Is it the case the one kind of SSL is more effective for a particular modality, than another? E.g., is masked modeling better for text-based learning, and noise-based learning more suited for vision?

It’s occurred to me that training a future, powerful AI on your brainwave patterns might be the best way for it to build a model of you and your preferences. It seems that it’s incredibly hard, if not impossible, to communicate all your preferences and values in words or code, not least because most of these are unknown to you on a conscious level.

Of course, there might be some extreme negatives to the AI having an internal model of you, but I can’t see a way around if we’re to achieve “do what I want, not what I literally asked for”.

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