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> but both birds and planes relying on the laws of aerodynamics Complexity of biological systems is so mind-blowing that we likely don't even have computationa
by bitL 8y ago
> but both birds and planes relying on the laws of aerodynamics
Complexity of biological systems is so mind-blowing that we likely don't even have computational capacity to simulate one of those processes in veracious detail. In addition, we can't even comprehend primitive, 1000-layer deep neural networks, not mentioning significantly more complex neurons (that are performing some local, protein-based computations alongside electric spikes we measure). We should be happy that Deep Learning surprisingly somewhat works, obliterating "classical" ML and make use of it to the full extent of its capabilities. Romantic idea that we can construct AGI with it should be retired.
- rdlecler1 8y agoThis is lazy thinking. You could say the same thing about planetary motion but the ellipse equation does a pretty good job giving us a null hypothesis to build up from. If you’re a materialist then you’re going to believe that all of the minute biological details are relevant. If you’re a functionalist you can work at a more abstract level. From the 12 years of research I did in this space (both CS and Bio) I can tell you for certain that we can learn a lot more from a functionalist approach. And the reason we “can’t understand” 1000 layer deep neural networks is again because we don’t have a good theory of these types of computational systems. For instance I can tell you that most of the interactions w_ijk are completely spurious and if you cull the network you actually end up with a circuit that you can understand in the same way any EE undergrad can identify a 3 bit adder from the circuit topology.