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Show HN: A beetle generator made by machine-learning zoological illustrations

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Re: Show HN: A beetle generator made by machine-learning zoological illustrations

#31
post #5

What a clever idea! By the way, there are over 400,000 naturally occurring species of beetles. Beetles make up 25% of all animal forms according to Wikipedia.

Reminds me of the (possibly apocryphal) Haldane quote, on what nature revealed about the mind of God: "An inordinate fondness for beetles."

https://en.wikipedia.org/wiki/J._B._S._Haldane

Re: Show HN: A beetle generator made by machine-learning zoological illustrations

#32

To the creator: since most (all?) of the beetles are symmetrical, couldn’t you generate left halves and then reflect it to create the right half? This could help you prevent asymmetric generations

The network should just learn that they all have symmetry and only encode the unique information. Once you start hand-coding priors like this, where do you stop? Maybe also constrain the range of colors? Size? Other geometric features? Eventually you're just doing old fashioned programming, not ML. And since generating beetle images isn't really the important goal anyway, why would you use dirty tricks to achieve it?

Re: Show HN: A beetle generator made by machine-learning zoological illustrations

#34
post #8

Earlier quoted context omitted.

-> https://thisrentaldoesnotexist.com All of the dynamic content on each listing is generated via a series of different machine-learned AI models.

"The laundry are converted into a mini central heating for every guest."

Yeah, the listings on this page don't quite make it up to a human level of coherence:

"Thus serve a 24 hour security pournising. Also hype is requested as much as you please empty and have a prestige less um be restriction, day or night."

It's close, though! But maybe not close enough for people to worry -- the last 10% of the security pournising always takes 90% of the development time.

Re: Show HN: A beetle generator made by machine-learning zoological illustrations

#35
post #30

I had the thought of how obfuscating this technology could be to hide information. Imagine this going off and publishing an unlimited number of images with generated descriptions that are indistinguishable from what a human would do. There would be no way to verify what the correct information is if you are someone just casually searching the Internet. (This could also almost apply for any type of information...)

If that was going to be a problem, people would already be generating fake numerical data like material properties, physical constants, statistics, or whatever that's also subtly wrong. You don't need machine learning to do that. This fear of fake information from ML misleading everyone is ridiculous and kind of arrogant. It assumes that the world is full of "other people" who are too stupid to make decisions for the…

I agree that "we must control others" is a bad approach. But I think you're underestimating the problem. Fake news has a body count, and it will only get worse: https://www.wired.com/story/how-whatsapp-fuels-fake-news-and...

At the very least, I think we need to train people in a lot more media literacy. But traditional approaches to that rely on media being scarce and expensive to create, which gave people enough time to carefully vet what they were consuming. As it becomes cheaper to create media than to vet it, we'll have the same problem as spam: it'll be impossible for humans to effectively filter it manually.

I think the real solution is automated vetting tools, so no information is presented without provenance. Basically, any time somebody sees an image or a video, there should be a link that lets you find out about the source, the editing, and who, specifically is vouching for it. And warnings for things that lack that. That still gives the viewer agency, but brings the problem back to human scale.

Re: Show HN: A beetle generator made by machine-learning zoological illustrations

#36
Was this model tested for overfitting? I do not have any sense of whether the beetles that I'm seeing match some source pictures exactly.

I noticed that the transformations seem to be fast through a transition and then seemingly paused. Is this intentional or does this have something to do with the model?

Re: Show HN: A beetle generator made by machine-learning zoological illustrations

#37
post #8

Earlier quoted context omitted.

-> https://thisrentaldoesnotexist.com All of the dynamic content on each listing is generated via a series of different machine-learned AI models.

"The laundry are converted into a mini central heating for every guest."

I've found that creating Markov chains are more human feeling (but maybe a bit overfit) if I use a n[0]-level deep look ahead for my generators.

[0] where n is normally 2 or 3

Re: Show HN: A beetle generator made by machine-learning zoological illustrations

#38
Excellent. I did something similar a few months ago using a dataset of zoological silhouettes, resulting in a menagerie of mammals, bugs, spiders and other mutant wonders.

https://twitter.com/cortesi/status/1153075801891278848

https://twitter.com/cortesi/status/1153088629972934656

Re: Show HN: A beetle generator made by machine-learning zoological illustrations

#39
post #36

Was this model tested for overfitting? I do not have any sense of whether the beetles that I'm seeing match some source pictures exactly. I noticed that the transformations seem to be fast through a transition and then seemingly paused. Is this intentional or does this have something to do with the model?

Is there a good way to test a gan for overfitting?
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