
The Alien Style of Deep Learning Generative Design - iwh
https://medium.com/intuitionmachine/the-alien-look-of-deep-learning-generative-design-5c5f871f7d10
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pierrebai
One wonders at the unexpected brittleness. Take that bike stem: they describe
the automated design process as inputting the forces you wish to withstand and
let the algorithm optimize. That implies that the final form has no validation
for any other forces. The bike stem might be weak to a diagonal force.

I also see that the structural design presented are mostly variation around
the simple known trick of triangulation. I'm not sure the extra optimisation
is worth the more complex form: extra manifacturing complexity and problematic
adaptibility to other parts you need for a completed product. Look at that car
body: can you imagine the body work to make it into a real car?

~~~
RangerScience
These design techniques pretty much require 3d printing for fabrication.

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tfgg
It's not obvious that these designs have anything to do with deep learning; it
doesn't appear to be mentioned in any of the linked articles.

~~~
nickpsecurity
I was seriously wondering about the metal one. Let's go link by link.

1\. 3D Makeover Link for metal CAD work says nothing about generative
techniques. It's about additive manufacturing" letting them do designs like in
the photo.

2\. The antenna link says it was a generative design by automated search and
simulation. Describes Dreamcatcher system that does this with cloud computing.
Gives example of roll cage that looks kind of like the bike stem.

3\. Bike stem link uses Dreamcatcher to do a bike stem. The video below shows
visually the optimization/design process in a way that reminds me of T-1000's
liquid metal in Terminator 2.

[https://vimeo.com/144713382](https://vimeo.com/144713382)

4\. Engine block link says they did a load-bearing, engine block in
Dreamcatcher. No other info.

5\. Meta models link just takes back to the page you're viewing. Cute waste of
my time...

6\. Intuition link doesn't tell me about any of these things. Instead, it's
some kind of analytics product for enterprises. Sounds like a mini-SAS with
Watson's analysis or Q&A.

So, there were some relevant links that were mostly Dreamcatcher demos. Ended
with an irrelevant one that might interest enterprise analysts. This article's
citations are definitely unreliable. It's mostly interesting artwork.

~~~
chas
With the exception of the antennas designed with genetic algorithms[0], the
"alien" aesthetic in all of these examples looks like the output of
topological optimization tools. For example:
[https://www.youtube.com/watch?v=igRFFMSfwSQ](https://www.youtube.com/watch?v=igRFFMSfwSQ)

They emphasize that Dreamcatcher uses a "top-down" style of design, so maybe
they are using deep learning for NLP to parse requirements and then feeding
those requirements into normal topological optimization tools?

[0] [https://ti.arc.nasa.gov/m/pub-
archive/1244h/1244%20(Hornby)....](https://ti.arc.nasa.gov/m/pub-
archive/1244h/1244%20\(Hornby\).pdf) (pictures from their post on page 5)

~~~
mattkrause
I would amazed if NLP that good existed.

Instead, I suspect top-down means something like "the part must span this
bounding box, weigh no more than X grams, and survive the following forces..."

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daysforbeef
Man some of those examples taken from application of genetic algorithms, and
iterative algos that are definitely not deep learning ... not everycomputer
optimized design success is an AI success and not every AI success is a deep
learning success

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nerdponx
Why couldn't generative optimization be considered AI? Iteration leading to
invention is a common pattern in human intelligence.

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dogma1138
If it's just mutation then no.

~~~
crestedtazo
This user rarely contributes to discussions and frequently gives short,
useless answers like this.

Can I ask HN why this account hasn't been banned yet? I thought the behavior
this user is demonstrating directly violates HN guidelines?

~~~
grzm
If you have concerns about a member, you can email the mods directly via the
Contact link in the footer. This is more effective than commenting on it.

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chriswarbo
It's certainly cool that our computers and manufacturing capabilities are now
able to pull off such optimisation, but this has been going on for a while;
compare the box-like car bodies of the 80s to the curved aerodynamics of
today.

Also, I'd guess this "alien style" has a lot to do with the user's choice of
algorithm and representation. An alternative approach, e.g. building up by
connecting tubes like scaffolding, or lego-like blocks, then I'd imagine the
results may have a very different "style".

~~~
jerf
"Also, I'd guess this "alien style" has a lot to do with the user's choice of
algorithm and representation."

I'd find that very likely. In the machine learning world the term "bias" means
something more like "what the set of hypotheses the learning system can have
is" rather than the human English definition, and my question would be, do the
biases of the learning processes even encompass "fractal" solutions? They
probably don't, because you would encode what is even manufacturable in the
first place directly into the biases of the system, because otherwise the
learning system is very likely to pop out an optimal solution that is not
manufacturable at all. Nobody wants to manufacture a fractalline lattice,
whereas given how Nature _grows_ them they come up very naturally.

On that note, another thing you have to watch out for with these solutions is
that you didn't miss an issue in your optimization. I'm looking at the first
picture in the article, at the middle solution. It has a very fine mesh at the
very top. I hope that either that mesh isn't all that important, or that we
are effectively-100% sure this part is never going to corrode or experience
other manufacturing defects (excessively large metal crystals perhaps) that
could cause such a fine tracery of metal to be not work the way the model is
expecting. (Unless there is some on the inside, the third piece doesn't seem
to have that problem, it looks a lot more robust.) Of course there are places
where we can indeed be confident that corrosion is not an issue, and the parts
could be tested; I'm not saying that this particular instance is guaranteed to
be flawed, just using this as an example of the possible issues with this
style of design.

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programnature
Wolfram was there in 2002. Pretty cool examples though.

~~~
chriswarbo
If you mean that Wolfram advocates programmatic generation of structures, then
that's true; the approach is very different though. These appear to come from
a continuous optimisation process, i.e. starting with a "bad" design and
iteratively tweaking it. In contrast, Wolfram tends to focus on discrete
systems (e.g. cellular automata) and perform the search interactively, like a
form of superoptimisation rather than numerical optimisation.

The examples I'd cite are from the 1990s, e.g. evolved antennas (
[https://en.wikipedia.org/wiki/Evolved_antenna](https://en.wikipedia.org/wiki/Evolved_antenna)
) and integrated circuits (
[https://en.wikipedia.org/wiki/Evolvable_hardware](https://en.wikipedia.org/wiki/Evolvable_hardware)
)

