Adam Marblestone: evaluation

Transcript context

…Right. So there’s a bunch of cellular stuff happening in the brain that is not just about neuron-to-neuron synaptic connections. How much of that is functionally doing more work than the synapses themselves are doing versus it’s just a bunch of kludge that you have to do in order to make the synaptic thing work. So with a digital mind, you can nudge the synapse, sorry the parameter, extremely easily. But with a cell to modulate a synapse according to the gradient signal, it just takes all this crazy machinery. So is it actually doing more than it takes extremely little code to do? I don’t know, but I’m not a believer in the radical, “Oh, actually memory is not synapses mostly, or learning is mostly genetic changes” or something like that. I think it would just make a lot of sense, I think you put it really well for it to be more like the second thing you said. Let’s say you want to do weight normalization across all the weights coming out of your neuron or into your neuron. Well, you probably have to somehow tell the nucleus of the cell about this and then have that send everything back out to the synapses or something. So there’s going to be a lot of cellular changes. Or let’s say that you just had a lot of plasticity and you’re part of this memory. Now that’s got consolidated into the cortex or whatever. Now we want to reuse you as a new one that can learn again. There’s going to be a ton of cellular changes, so there’s going to be tons of stuff happening in the cell. But algorithmically, it’s not really adding something beyond these algorithms. It’s just implementing something that in a digital computer is very easy for us to go and just find the weights and change them. In a cell, it just literally has to do all this with molecular machines itself without any central controller. It’s kind of incredible. There are some things that cells do, I think, that seem more convincing. One of the things the cerebellum has to do is predict over time. What is the time delay? Let’s say that I see a flash and then some number of milliseconds later, I’m going to get a puff of air in my eyelid or something. The cerebellum can be very good at predicting what’s the timing between the flash and the air puff, so that now your eye will just close automatically. The cerebellum is involved in that type of reflex, learned reflex. There are some cells in the cerebellum where it seems like the cell body is playing a role in storing that time constant, changing that time constant of delay, versus that all being somehow done with like, “I’m going to make a longer ring of synapses to make that delay longer.” No, the cell body will just store that time delay for you. So there are some examples, but I’m not a believer out of the box in essentially this theory that what’s happening is changes in connections between neurons and that that’s the main algorithmic thing that’s going on. I think there’s very good reason to still believe that it’s that rather than some crazy cellular stuff. Going back to this whole perspective of how our intelligence is not just this omnidirectional inference thing that builds a world model, but really this system that teaches us what to pay attention to what the important salient factors are to learn from, et cetera. I want to see if there’s some intuition we can drive from this about what different kinds of intelligences might be like. So it seems like AGI or superhuman intelligence should still have this ability to learn a world model that’s quite general, but then it might be incentivized to pay attention to different things that are relevant for the modern post-singularity environment. How different should we expect different intelligences to be?…

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