Today one Neuron, tomorrow the Brain!

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

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?)

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

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 😅

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

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

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

Ooh, that might be a controversial take indeed! 😏

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

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

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

You seem dismissive about that? 😅

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

How so? What made you change your mind?

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

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

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

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

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

Exactly! 😊

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

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

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

That was great stuff! And totally unexpected for me

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

Excellent idea, I’ll do that right away 😊