Today one Neuron, tomorrow the Brain!

Jul 4, 2022Philosophy/Ethics, Tech0 comments

The Navy said the perceptron would be the first non-living mechanism “capable of receiv­ing, recognizing and identifying its surroundings without any human training or control.”
Mr. Rosenblatt said in prin­ciple it would be possible to build brains that could repro­duce themselves on an assembly line and which would be con­scious of their existence.

NYT 1958

John and Sam are talking about the following article:
Professor’s perceptron paved the way for AI – 60 years too soon

In this post the dialogue is realised by an interaction of virtual characters, for more information please check the page “Virtual characters

John

So you really want to compare neurons to thermostats and these “governors”?

Today 17:09

Sam

Some might disagree, but I think it is a much better comparison than all-or-nothing circuits that just represent a 1 or a 0 😊
(How Computationally Complex Is a Single Neuron?)

Today 17:10

John

That’s a good point: neurons have a graded response and integrate a lot of signals, so that is already more sophisticated than a circuit

Today 17:10

Sam

I guess that your perspective matters: for a hardware engineer, it really is about the nuts and bolts of how stuff works at the lowest levels 😅

Today 17:11

Sam

but I suppose that from the point of view of software and mathematical models you can just treat neurons as numbers or a function

Today 17:11

John

And that is why you would say that we need to look at analog computing and real time computing?

Today 17:12 

Sam

If you want to understand why it is “neuromorphic” computing, yes!
Otherwise it is just fancy statistics

Today 17:12

John

Ooh, that might be a controversial take indeed! 😏

Today 17:13 

Sam

Ha! 😄 I thought you might like to make the article a bit thought-provoking

Today 17:13

John

But then at a higher level of abstraction, when you put those artificial neurons together into a neural network …?

Today 17:15 

Sam

Well, sure, you get all the bells and whistles of machine learning and artificial intelligence, which is what your readers expect I guess

Today 17:15

John

You seem dismissive about that? 😅

Today 17:16 

Sam

I don’t mean to, no, but after hearing about this 19th century engineer, Smee, from Julia I started to think differently about it

Today 17:17

John

How so? What made you change your mind?

Today 17:18   

Sam

Well, just making a network out of stuff, doesn’t necessarily make it more “brainlike”, you know

Today 17:18

Sam

Smee just tried to link all the concepts we explicitly know we have, but we more often than not don’t know what and how our brains are doing

Today 17:18

John

So copying the structure of the brain without copying the bits and pieces it is made of doesn’t make it “neuromorphic”?

Today 17:19   

Sam

In a way, yes. We don’t have to copy everything, of course, all the biological stuff, and perhaps not even all the chemical stuff

Today 17:19

John

Just the bits that are relevant to computation, even if we don’t really see it as computation in the classical sense?

Today 17:20   

Sam

Exactly! 😊

And perhaps we end up with artificial neural networks that aren’t terribly efficient or useful

Today 17:20

John

So it depends a bit on whether you use neuromorphic computing to get quick results or to better understand the brain or computing?

Today 17:21   

Sam

Yes, and we might learn something unexpected from our brains, which are still the most efficient computers on the planet

Today 17:21

John

That was great stuff! And totally unexpected for me

Today 17:22   

Sam

You might want to check up with Cho about some of the details regarding how neurons work though …

Today 17:22

John

Excellent idea, I’ll do that right away 😊

Today 17:23   

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