[Cybiote]

I think you're missing the point there. Portia is able to, using just a handful of neurons (~600K), accomplish sophisticated vision tasks, complex planning, online learning and scheduling. Portia and insects in general are much more flexible to changes than our Neural nets. Changing objectives or a slight modification in the rules will often require retraining and a new design but insects can adapt to various lighting, environmental, prey, predator and navigational concerns. From the wiki on portia:

> Laboratory studies show that Portia learns very quickly how to overcome web-building spiders that neither it nor its ancestors would have met in the wild.

We should strive for its kind of energy and hence, computational efficiency in our models. Think for example, what that would mean for prosthetics. I find the overzealous defense of the current state of the art just as frustrating as out of hand dismissals of AI which constantly move goal posts.

[dharma1]

How many connections betweens those 600k neurons? That is one large difference between biological and artificial neural networks (though there are many others).

Current DNN architectures won't be the final solutions, but they do the job much better than anything else we've tried before. That said there is ongoing work in more biologically inspired approaches that might produce better results for the things you mentioned in the future

[Fordrus]

This, this right here is the EXACT situation that causes all the bioinformatics guys to be EXTREMELY NERVOUS using biological analogies like neurons for machine learning topics. They are NOT actually analogous except in the shallowest ways.

First off, there's substantial evidence to suggest that in a biological systems, an activation profile of the neurological system is more analogous to what a Neural Network in machine Learning considers a 'neuron'- that means that when you consider the spider, you're not looking at 600K nodes, you're looking at 600,000 FACTORIAL. As in 600K!, or approx. 2x10^3,200,000.

Second, even THAT number may be substantially too small, because the STRENGTH, as represented by the number of connections a given node in a biological Neural net has to another node, can ALSO variably affect the performance/recall/whatever of the organism. I don't recall what the higheat known number of connections between two nodes is in humans, let alone spiders, but it is not only 2 or 3, it can be many more.

Portia and other insects are operating on an entirely different level, with different hardware, and a different operating system, than your Neural Network ENTIRELY - trying to compare the nodes-to-performance ratio of the spider vs. the DNN is not even wrong, it's like the Twilight Zone of every computer competent neuroscientist on this planet. Utterly and completely meaningless, except maybe in an inspirational sense, to flagellate your statisticians into feeling so inferior that they magically squeeze greater performance out of their networks, not because they cleverly utilized the fundamental differences between biological and silicon computer systems, but rather because they feel so bad about the comparison.

I apologize for my snooty tone- in college I argued with a professor about this, with me asserting that clearly, no one would every REALLY equate biological neurons with machine learning neurons one-to-one, and yet here you are, clearly he was right and I have lost our bet, I shall have to go back and eat a hat. ;)

[Cybiote]

I don't have any disagreement with you--except with your fermi estimate--I've made some of those points before too. In retrospect (and I'd realized it before you posted) I shouldn't have emphasized neuron counts but watts. Ultimately, similar computations are occurring with hugely different energy profiles. That's what we should figure out how to do using software and the right hardware.

[dTal]

>Portia and insects in general

Spiders are not insects!

[Cybiote]

You're right! and I've known this but that distinction didn't come to mind as I was writing the post. It's not really relevant though, as my point was about how adaptable and surprisingly intelligent behaviours even these tiny, tiny creatures with barely more than a milliwatt (I'm guessing) to their name, can produce. And you know, and can be used in a similar way to either set union or intersection in natural language :)