zlacker

As important and impressive a result as this is, I am reminded of the cornerstone problem of neuroscience, which goes something like this: if we knew next to nothing about processors but could attach electrodes to the die, would we be able to figure out how processors execute programs and what those programs do, in detail, just from the measurements alone? And now scale that up several orders of magnitude and introduce sensitivity to timing of arrival for signals, and you got the brain. Likewise ok, you have petabytes of data now, but will we ever get closer to understanding, for example, how cognition works? It was a bit of a shock for me when I found out (while taking an introductory comp neuroscience course) that we simply do not have tractable math to model more than a handful neurons in time domain. And they do actually operate in time domain - timings are important for Hebbian learning, and there’s no global “clock” - all that the brain does is a continuous process.

>>ein0p+(OP)
Particle physics works in a similar way, but instead of attaching electrodes, you shoot at them with guns and then analyze trajectories of the fragments.

>>ein0p+(OP)
>> The sample was immersed in preservatives and stained with heavy metals to make the cells easier to see.

Try experimenting with immersing your brain in preservatives and staining with heavy metals to see how would you be able to write the comment similar to the above.

No wonder that monkey methods continue to unveil monkey cognition.

>>golerg+11
The cheap monkey headset works in a similar way: monkeys just essentially continue to analyze trajectories of medieval cannon balls in the LHC and to count potatoes in the form of bytes.

>>spacet+a6
> Try… immersing your brain in preservatives and staining with heavy metals

I think we all do every day

>>dudein+57
Try using the protocols and doses from the original article.

>>ein0p+(OP)
Right. The arguments for the study of A.I. were that you will not discover the principles of flight by looking at a birds feather under an electron microscope.

It’s fascinating, but we aren’t going to understand intelligence this way. Emergent phenomenon are part of complexity theory, and we don’t have any maths for it. Our ignorance in this space is large.

When I was young, I remember a common refrain being “will a brain ever be able to understand itself?”. Perhaps not, but the drive towards understanding is still a worthy goal in my opinion. We need to make some breakthroughs in the study of complexity theory.

>>ein0p+(OP)
The reverse-engineering issue was popularized by this article, https://www.cell.com/cancer-cell/fulltext/S1535-6108%2802%29...

On the second point, the failure of Openworm to model the very well-mapped-out C. elegans (~0.3k neurons) says a lot.

>>lll-o-+wa
> but we aren’t going to understand intelligence this way

The same argument holds for "AI" too. We don't understand a damn thing about neural networks.

There's more - we don't care to understand them as long as it's irrelevant to exploiting them.

>>hotiwu+Vg
> The same argument holds for "AI" too. We don't understand a damn thing about neural networks.

Yes, which is why the current explosion in practical application isn’t very interesting.

> we don't care to understand them as long as it's irrelevant to exploiting them.

For some definition of “we”, I’m sure that’s true. We don’t need to understand things to make practical use of them. Giant Cathedrals were built without science and mathematics. Still, once we do have the science and mathematics, generally exponential advancement results.

>>lll-o-+wa
I love that analogy with birds!

Yes we figured out how to build aircraft.

But it can not be compared to a bird flying. Neither in terms of efficiency or elegance.

>>hotiwu+Jg
I just read that article and enjoyed it. Thanks for sharing! I don’t think the author was arguing biological processes can’t be reverse engineered, but rather that the tools and approaches typically used by biology researchers may not be as effective as tools and approaches used by engineers.