
The origin of circuits (2007) - sajid
https://www.damninteresting.com/on-the-origin-of-circuits/
======
andischo
"Five individual logic cells were functionally disconnected from the rest—
with no pathways that would allow them to influence the output— yet when the
researcher disabled any one of them the chip lost its ability to discriminate
the tones. Furthermore, the final program did not work reliably when it was
loaded onto other FPGAs of the same type.

It seems that evolution had not merely selected the best code for the task, it
had also advocated those programs which took advantage of the electromagnetic
quirks of that specific microchip environment. The five separate logic cells
were clearly crucial to the chip’s operation, but they were interacting with
the main circuitry through some unorthodox method— most likely via the subtle
magnetic fields that are created when electrons flow through circuitry, an
effect known as magnetic flux."

This is absolutely incredible. Makes you wonder how much potential the real
world has compared to the simulated environment usually used to test
theoretical solutions.

~~~
nabla9
It's an example of overspecialization and finding weird local minimum trough
loophole in the way the problem is encoded.

Genetic algorithms have the ability to capture the imagination of public and
computer science students because they can find very messy and random
solutions if you run them long enough.

In the general context of search and optimization algorithms they are not
impressive. When you can't use anting better, like Mote Carlo or simulated
annealing, evolutionary algorithms are often the last hope before brute
forcing it. GA can be very impressive when you can restrict the search space
and find good representation for the problem.

~~~
andischo
I get the advantages of generic algorithms. But sometimes overfitting can be
very useful. Imagine wind or water turbines where this method could be used to
increase their efficiency based on the individual hardware.

~~~
slededit
Its also likely the solution it found would not work across the operating
temperature range of the device. To do it properly would take a lot longer and
need a lot more test cases.

------
colllectorof
_> These evolutionary computer systems may almost appear to demonstrate a kind
of sentience as they dispense graceful solutions to complex problems._

Stanislaw Lem wrote about this in Summa Technologiae. He looked at evolution
as an alternative way to acquire knowledge (alternative to intelligence).
Interestingly, this implies there could be other ways too. But the point is,
he postulated that both are examples of the same class of phenomena, which is
a fascinating way to look at it.

(He did write about artificial evolution as well. And simulation. In 1964.
That book aged extremely well and is full of interesting ideas.)

~~~
rebolek
And now I have to read that book again. Thanks!

------
jcims
One of my favorite articles on the Internet.

I remember thinking this was a powerful confluence of genetic algorithms and
reconfigurable computing, two pretty hot topics at the time, and was sure that
real applications of this were on the horizon.

GA's seem to have been generally replaced by various facets of machine
learning (although I'm hard pressed not to see GANs as Darwinian in nature)
and the whole reconfigurable computing thing just seems to have dropped off
the map. I sort of get the former but am curious if anyone on HN knows what
happened to the latter.

Still love the article.

~~~
goodmachine
Me too! Some followup here on why not much happened:

[https://www.reddit.com/r/MachineLearning/comments/2t5ozk/wha...](https://www.reddit.com/r/MachineLearning/comments/2t5ozk/what_ever_happened_with_the_evolutionary/)

Incidentally, GA's (specifically, novelty search/NEAT) are creeping back into
the picture again:

[https://eng.uber.com/deep-neuroevolution/](https://eng.uber.com/deep-
neuroevolution/)

~~~
jcims
Great links! Thank you!

------
zb
For those who are interested, there is a much more thorough technical
treatment of this experiment in Richard Gabriel's article "Design Beyond Human
Abilities":

[http://richardgabriel.org/Files/DesignBeyondHumanAbilitiesSi...](http://richardgabriel.org/Files/DesignBeyondHumanAbilitiesSimp.pdf)

~~~
asadjb
For the interested, this FPGA experiment is discussed from page 21 and beyond.

------
dang
Posted many times, but only one small previous discussion, from 2015:
[https://news.ycombinator.com/item?id=9885558](https://news.ycombinator.com/item?id=9885558)

------
xg15
The subject matter of the article is amazing, but there seems to be some
weirdly out-of-place sexual innuendo in the writing.

Like, what is the purpose of comparing evolutionary algorithms with forced
breeding programs - or mentions of the researcher penetrating virgin fields of
research?

~~~
DamnInteresting
Author of the article (sheepishly) here: In my mind at the time of writing,
the innuendo was an informal experiment of sorts. I wondered whether such
suggestive writing would attract or repel readers; who would applaud and who
would protest; etc. If you read the other articles on the site, you'll see
this one was an outlier, the other articles don't have this tone.

In retrospect I was probably just being juvenile. But then, I always shake my
head when I read my old writings, so I may not be the best to assess.

~~~
jcims
Whoa! Just stealing an opportunity to thank you for writing this, both the
subject matter and your style of presenting it are very compelling to me (in
context that probably says a lot about my own way of thinking lol). I've
shared this with many people over the years as a gentle and sensible
introduction to two very cool topics. Thanks!!!

