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> The risk is that we've developed a formalism and ecosystem that works on entirely different principles [...] It's a possibility, but I sometime have the feel
by bnegreve 7y ago
> The risk is that we've developed a formalism and ecosystem that works on entirely different principles [...]
It's a possibility, but I sometime have the feeling that people dismiss the idea that such a simple model of the brain could be enough to explain complex behaviors because they want to believe there is more to the brain.
I'm sure real neurons are very complex and difficult to model, but I also believe that the real challenge is to explain how neurons interact with each other, not how they behave individually.
- AstralStorm 7y agoAnd why do you believe the current non-intelligent ML is sufficient? As it is, ML is running away rather fast from the integrator model by introducing explicit gating and nonlinearities in the neurons. Yet it is still a toy compared to a nematode.
- bnegreve 7y agoYou're right, I doubt that the current models are enough to capture the complexity of the brain. But models based on incredibly simple neurons can already produce quite complex behaviors. They show how many simple computing units interacting with each others can lead to things like vision. And I do believe that this is a fundamental principle. Maybe we should explore that idea and scale this model up, instead of rejecting it as "too simple" and hoping that the complexity of the brain will be fully explained by the discovery of some quantum effect in neurons. > As it is, ML is running away rather fast from the integrator model by introducing explicit gating and nonlinearities in the neurons. I think the idea of a non-linear activation function has always been around. But for the rest I agree.