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I really hate when people post idealogical nonsense like this when looking at cross-displinary work. It almost feels like a religious level of arrogance to make
by __loam 3y ago
I really hate when people post idealogical nonsense like this when looking at cross-displinary work. It almost feels like a religious level of arrogance to make these comparisons.
There are some interpretability problems with modern machine learning models but we have perfect information about how they work. You can observe their state directly and the math backing them is very well understood. Contrast that with the brain where observability is extremely limited and how it works on the tissue scale still isn't that well understood.
The similarities are surface level and, imo, a distraction to making serious progress in both fields. Talking about how these things mimic the brain is more marketing than science.
- FrustratedMonky 3y ago1. Where was there any reference to any 'ideology'? 2. Cross Silo ("disciplinary") work is often misunderstood, rebelled against. 3. "Perfect Information" isn't understanding. "Observing State" isn't understanding. See the dozens of articles on AlphaGo. 4. Yes, there is still a lot to learn about the brain. That doesn't mean we don't already know a lot. There are neurons right? There are electrical potentials right? It exists in the physical universe right? It can be modeled right? So when do the models scale up enough to match reality? You can't say 'Never'.
- __loam 3y agoThe ideology of your views exists whether you're aware of it or not. Your points 3 and 4 are contradictory. You simultaneously assert that AI models that we have a direct view of are these mysterious and unknown things while making the opposite point about the brain, an object that stresses the limits of computation.
- FrustratedMonky 3y agoPoint 3 and 4 are not contradictory. I'm just not being clear. And I am not being 'mysterious'. For the brain, let's suppose we can have as 'perfect information' about 'state', as we can have about a computer neural net. Then 1 Either they would be equally 'mysterious', we would still not know how they 'subjectively' feel when making decisions. Where is the 'experience' coming from. Like with humans, where do 'thoughts' arise from before you think about what to think about (going back to Schopenhauer). Like with AlphaGo, can you really find the point when it 'decided' on Move 37, or is it a process with pre-curser neural "firing's" same as a human has. OR 2 In both, we have perfect information of state, and further, do determine some correlates between a 'state' and a 'feeling' or 'process' and actions. Let's suppose as you imply we 'understand' everything about what is happening in AI. What I am say, this will eventually happen for humans, that we'll understand the brain. There wont be any mystery left. Since for both we would have perfect information about state, and we can figure out how the processing is happening, and we 'understand' both -> THEN we would have to accept that AI is also as conscious as a human. --- I'm just saying the Silicon-Carbon argument. Either we prove or understand that Humans and AI are both Conscious. or Neither are Conscious. Once we completely explain away human thought, we'll find we are 'clockwork' machines also. But, yes, in future, and any rudimentary comparisons right now are probably a leap. Just I don't think it is as far a leap as you are implying. Neural nets were literally modeled on brains, why can't we make comparisons.
- __loam 3y ago> Neural nets were literally modeled on brains, why can't we make comparisons. They're quite a shitty model that comes from a 1950's understanding of neuroscience.
- FrustratedMonky 3y agoThink in AI and Neuroscience, there has been some progress since 1950.