Ya, that’s fair. If this is the case, I might say that the biological neurons don’t have additional useful degrees of freedom for the same number of inputs, and the paper didn’t explicitly test for this either way, although, imo, what they did test is weak Bayesian evidence for biological neurons having more useful degrees of freedom, since if they could be simulated with few artificial neurons, we could pretty much rule out that hypothesis. Maybe this evidence is too weak to update much on, though, especially if you had a prior that simulating biological neurons would be pretty hard even if they had no additional useful degrees of freedom.
Now I think we are on the same page. Nice! I agree that this is weak bayesian evidence for the reason you mention; if the experiment had discovered that one artificial neuron could adequately simulate one biological neuron, that would basically put an upper bound on things for purposes of the bio anchors framework (cutting off approximately the top half of Ajeya’s distribution over required size of artificial neural net). Instead they found that you need thousands. But (I would say) this is only weak evidence because prior to hearing about this experiment I would have predicted that it would be difficult to accurately simulate a neuron, just as it’s difficult to accurately simulate a falling leaf. Pretty much everything that happens in biology is complicated and hard to simulate.
Ya, that’s fair. If this is the case, I might say that the biological neurons don’t have additional useful degrees of freedom for the same number of inputs, and the paper didn’t explicitly test for this either way, although, imo, what they did test is weak Bayesian evidence for biological neurons having more useful degrees of freedom, since if they could be simulated with few artificial neurons, we could pretty much rule out that hypothesis. Maybe this evidence is too weak to update much on, though, especially if you had a prior that simulating biological neurons would be pretty hard even if they had no additional useful degrees of freedom.
Now I think we are on the same page. Nice! I agree that this is weak bayesian evidence for the reason you mention; if the experiment had discovered that one artificial neuron could adequately simulate one biological neuron, that would basically put an upper bound on things for purposes of the bio anchors framework (cutting off approximately the top half of Ajeya’s distribution over required size of artificial neural net). Instead they found that you need thousands. But (I would say) this is only weak evidence because prior to hearing about this experiment I would have predicted that it would be difficult to accurately simulate a neuron, just as it’s difficult to accurately simulate a falling leaf. Pretty much everything that happens in biology is complicated and hard to simulate.