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How insects like bumblebees do so much with tiny brains

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Re: How insects like bumblebees do so much with tiny brains

#21

Post by redacted »

midgetjones wrote: post #2

Maybe the real question is 'why can we do so little with our giant brains?'

Read Blindsight by Peter Watts. Apart from being an incredible novel it gets into this question, and it's freely available from the author's site: http://www.rifters.com/real/Blindsight.htm

Trying to avoid spoilers here, so ROT13 - Gur nyvraf rapbhagrerq va gur abiry ner abg pbafpvbhf, naq uhzna pbafpvbhfarff vf cerfragrq nf na ribyhgvbanel fvqr rssrpg / zvfgnxr juvpu erdhverf hf gb jnfgr uhtr nzbhagf bs cbjre guvaxvat nobhg guvaxvat, vafgrnq bs whfg guvaxvat. Bhe phygher, oebnqpnfg vagb fcnpr, nccrnef yvxr n QQBF nggnpx bs vafnar vachgf gb gur aba-pbafpvbhf nyvraf orpnhfr bs ubj zhpu rssbeg vg gnxrf gb cnefr guebhtu vg nyy.

(The neurological phenomena of blindsight is also very very interesting, and suggests that our brains may do more work than is strictly required)

Re: How insects like bumblebees do so much with tiny brains

#22

Post by saosebastiao »

JohnGoGoGo wrote: post #16

"With just a few hundred or thousand neurons, you can easily recognise perhaps a hundred faces". It makes me think we are missing something when creating arificial neural networks which needs much more neurons to achieve only this specific task. Maybe artificial neurons are too simplified models compared to biological ones, maybe our training process could be much more efficient?

Probably a little bit of both, but definitely a huge amount of the former. Simplistic models of human intelligence being the result of neurons ignore huge amounts of human physiology, such as the fact that we have over 400 recognized types of neurons. Marvin Minsky has a lot of criticism of the overly fantastical fantasies of Neural Networks, and this is one of them.

Re: How insects like bumblebees do so much with tiny brains

#24

Post by pc86 »

acqq wrote: post #20
pc86 wrote: post #15

Earlier quoted context omitted.

> it takes k T log 2 joules to erase one bit of information...and our brain uses around 20 Watts of power Yet another time when my Political Science education fails me. What should I take away from this?

> What should I take away from this? Just that you should not omit with "..." the most important part of the statement for you. You haven't studied physics. Then you see the formula and the textual name of it with the most probable entry in Wikipedia and then you throw the most useful bit for you away and ask what the formula without the name means, even though the name would give you an explanation. pc86's quote: >…

I assumed there was some relation between k T log 2 joules and 20 Watts, probably giving some sort of context to how easily or not easily information in our brains could be lost. The theoretical principles behind the amount of energy required to erase one bit, while interesting, doesn't necessary matter for that relationship, does it?

Re: How insects like bumblebees do so much with tiny brains

#25

Post by asgraham »

JohnGoGoGo wrote: post #16

"With just a few hundred or thousand neurons, you can easily recognise perhaps a hundred faces". It makes me think we are missing something when creating arificial neural networks which needs much more neurons to achieve only this specific task. Maybe artificial neurons are too simplified models compared to biological ones, maybe our training process could be much more efficient?

Two points:

First, it's important to keep in mind the difference between artificial "neurons" and real neurons. Real neurons, with their complicated dendritic arbors, are much more complicated than anything you'll see in a typical ANN. So there isn't a one to one correspondence between the "few hundred or thousand" neurons in a bee and the number of units in an ANN. Now is there a one to thousand correspondence? I don't know. There's probably research on it, but I'm unfamiliar. Certainly for some neurons even a thousand unit ANN would seem inadequate (look at the arborization of a Purkinge cell, for example).

Point two: Absolutely modern ANNs are missing something fundamental. I would wager obscenely large amounts of money that they are missing more than one fundamental idea, and I doubt I could find another neuroscientist who'd take that wager. What are ANNs missing? Obviously I don't know or I would have published it already. But I'll guarantee you the first step is recurrence. Hell, intelligent recurrence might be the only thing missing and I'd lose my bet. But recurrence is hard. And anyway, back in point one, even the simple facial recognition in a bee using only a thousand neurons would take a few hundred thousand to a few tens of millions of modularly-recurrently connected "neurons." Not exactly a laptop simulation.

Re: How insects like bumblebees do so much with tiny brains

#26

Post by [deleted] »

JohnGoGoGo wrote: post #16

"With just a few hundred or thousand neurons, you can easily recognise perhaps a hundred faces". It makes me think we are missing something when creating arificial neural networks which needs much more neurons to achieve only this specific task. Maybe artificial neurons are too simplified models compared to biological ones, maybe our training process could be much more efficient?

[deleted]

Re: How insects like bumblebees do so much with tiny brains

#27

Post by [deleted] »

JohnGoGoGo wrote: post #16

"With just a few hundred or thousand neurons, you can easily recognise perhaps a hundred faces". It makes me think we are missing something when creating arificial neural networks which needs much more neurons to achieve only this specific task. Maybe artificial neurons are too simplified models compared to biological ones, maybe our training process could be much more efficient?

[deleted]

Re: How insects like bumblebees do so much with tiny brains

#28

Post by Xophmeister »

pizza wrote: post #3
midgetjones wrote: post #2

Maybe the real question is 'why can we do so little with our giant brains?'

Maybe something along the lines of "our brains would overheat" - there's a small temperature window in which proteins won't denature, it takes k T log 2 joules to erase one bit of information (Landauer's principle), and our brain uses around 20 Watts of power. Maybe tin foil hats make good heatsinks.. Interestingly enough there is some evidence that the Gibbs free energy of ketone metabolism is more thermodynamically…

Doesn't that imply that people who live in hotter climates have...how can I put this politely?...a disadvantage when it comes to the stability of their brains? I would assume that the brain has a certain amount of redundancy, but has this ever been researched: How hot can it get before people start getting noticeably "stupider"?

Re: How insects like bumblebees do so much with tiny brains

#29

Post by chongli »

JohnGoGoGo wrote: post #16

"With just a few hundred or thousand neurons, you can easily recognise perhaps a hundred faces". It makes me think we are missing something when creating arificial neural networks which needs much more neurons to achieve only this specific task. Maybe artificial neurons are too simplified models compared to biological ones, maybe our training process could be much more efficient?

If I had to guess: neural networks have to operate on pixel data whereas real neurons don't. Brains and eyes have evolved in tandem. Perhaps what makes them so efficient is that the eyes handle some of the processing as a consequence of their physical shape and characteristics.

Look at the eyes of bees. Very different from our own (and from the cameras we build) and perhaps very specialized to the limited set of tasks that bees carry out?

Re: How insects like bumblebees do so much with tiny brains

#30

Post by joshmarlow »

Highly relevant is the Portia genus of spiders ([0], [1]) and apparently other related jumping spiders ([2]).

One of my favorite excerpts from [1]:

> Harland says Portia’s eyesight is the place to start. Jumping spiders already have excellent vision and Portia’s is ten times as good, making it sharper than most mammals. However being so small, there is a trade-off in that Portia can only focus its eyes on a tiny spot. It has to build up a picture of the world by scanning almost pixel by pixel across the visual scene. Whatever Portia ends up seeing, the information is accumulated slowly, as if peering through a keyhole, over many minutes. So there might be something a little like visual experience, but nothing like a full and “all at once” experience of a visual field.

[0] - https://en.wikipedia.org/wiki/Portia_(spider) [1] - http://www.dichotomistic.com/mind_readings_spider%20minds.ht... [2] - http://news.nationalgeographic.com/2016/01/160121-jumping-sp...

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