Comment by proc0 | Hacker News Reader

Comment by proc0 | Hacker News Reader

Another article basically saying something along the lines of "there is no current technology that comes close to producing AGI, therefore let's dismiss all these technologies". Of course we don't know what we don't know, until we do, and then it's not as mysterious.

It's not hard to see that the reason NN are becoming the prime candidate for AGI, is because of their inspired architecture based on biological neurons. We are the only known AGI, therefore something similar to the brain will be producing an AGI. NN at least mimic the massively parallel property of biological neurons. And if we're optimistic, the fact that NN is mimicking how vision works in our brain, might mean that we are at some point in the continuum of the evolution of brains, and it's a matter of time until we discover the other ways brains evolved intelligence.

What keeps me optimistic is evolution. At some point brains were stupid, and then they definitely evolved AGI. The question is how did this happen and whether or not there is a shortcut, like inventing the wheel for transportation instead of arms and legs.

To paraphrase a comment from another thread:

Artificial neural networks have basically nothing to do with actual biological neurons. First, neuroscientists do not have even a decent understanding of biological neurons: you cannot say that neural networks mimic neurons when we don't understand biological neurons. Of the bajillion things we do know neurons do, neural networks do on the order of 1% of those things. On the flip side, neural networks do a ton of things that biological neurons do not (like backpropagation(!)* ).

* In fairness, Hinton hypothesizes the brain has a way of doing backprop, but what he talks about only barely resembles actual backprop.

Right, no debate there. They're inspired by biological neurons. But it's still a step in the right direction. The facts are we have billions of neurons and there's some form of information processing going on. Perhaps we could continue the trend, and model NN to include other brain cell features like whatever the glyal cells do for example.

A link to anything Dr Hinton has written about the brain doing backprop would be appreciated, if you've got one.

You can have a look at the second half of this video https://www.youtube.com/watch?v=IcOMKXAw5VA for a recent account. He has been suggesting this for almost a decade, but I don't know that there is any article (yet).

I've heard people suggest a comparison between birds wings and planes. We don't understand everything about bird wings. They're incredibly complex and messy biological structures. However, we do know enough about the general principles of aerodynamics to build aircraft. Perhaps a similar dynamic is at work here. We don't understand brains, but perhaps neural networks are able to capture the same principles of information processing.

Yes, plane wings are built on fundamental physical principles. We do not know the fundamental physical principles of intelligence.

Building an NN and hoping its brain-like structure will start to think is like building a flapping machine and hoping its bird-like structure will start to fly.

> Building an NN and hoping its brain-like structure will start to think is like building a flapping machine and hoping its bird-like structure will start to fly.

But... you're replying in a comment thread that has explicitly stated that "NNs" don't at all qualify as "brain-like".

Which was my response to someone implying we should make them more brain-like. So the comment was quite relevant.

Edsger Dijkstra famously made such a comparison [1]:

"The Fathers of the field had been pretty confusing: John von Neumann speculated about computers and the human brain in analogies sufficiently wild to be worthy of a medieval thinker and Alan M. Turing thought about criteria to settle the question of whether Machines Can Think, a question of which we now know that it is about as relevant as the question of whether Submarines Can Swim."

[1] E. W. Dijkstra, EWD898: The threats to computing science

It would be great to be able to replicate neurons and neural signals exactly. Direct interfacing between artificial neural networks and biological ones would be very interesting

http://www.theguardian.com/technology/2016/jan/20/us-militar...

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