Mario Klingemann💧💦
@quasimondo
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Artist, Neurographer, Automancer, Purveyor of Systems, Data Dumpster Diver, Information Recycler
Joined April 2007
Peter sees the computer. "But the machine only.creates what humans.have taught it to,".says Peter. "So do you,".says Mummy.
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Saw a pretty moiré effect in the Manchester airport smoking area and tried to replicate it in a shader. #CreativeCommute
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Some real time face play, checking if the models have learned something new.
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Turn your face into an oil painting in real-time*. * ᵃᵖᵖˡᶦᶜᵃⁿᵗˢ ᵐᵘˢᵗ ᵇᵉ ʷʰᶦᵗᵉ ᵐᵃˡᵉ ᵃⁿᵈ ᵒᵛᵉʳ ⁴⁰ ʸ��ᵃʳˢ ᵒˡᵈ
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I didn't know who Harry Styles was until today when I learned that he's the guy who blocked off the entire St. Abbs harbour and prevented us to enjoy our fresh crab rolls. 😫🚧🕺🦀🥖.
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Current progress on mapping music to facial expression vectors. #StyleGAN2 #realtime. Song: "Triggernometry" by Kraftamt, 2014
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With my similar scene finder I can quickly find interesting training material to fine tune my Old Masters face model and it adapts pretty fast.
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Another attempt at a longer piece. An imaginary Jerome K. Jerome writes about Twitter. All I seeded was the title, the author's name and the first "It", the rest is done by #gpt3. Here is the full-length version as a PDF:.
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Somebody should have told me in 1984 that this was generative art. But they called it "Games with Computer Graphics".
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I started collecting some direction vectors in #StyleGAN2 that try to change only a certain property of a generated face. But it's hard to get clean ones. Here's head rotation:
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So spectral normalization is a mixed bag. Overall it seems to make everything more consistent and there are no blatant artifacts anymore. But it couldn't fully heal the one that had settled in the top-left corner.
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Here's what happens if you badly train a neural network to predict the next frame in a video and give it a still image to start with:
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This might be one the creepiest clips that I have made so far. Yes Sir, that's my baby. #FaceFeedback
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I am proud that I had the chance to work with #MassiveAttack creating neural visuals for their new #Mezzanine anniversary tour which started yesterday. (I ripped that video from in_cmmn on instagram).
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Wrote me a little "hacked terminal" screensaver for my 10€ computer. The nice extra is that it shows the content of real random files on that machine and occasionally sprinkles in current news.
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Another pretty sketchy clip of the Old Masters model in action.
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Some pose-to-pose puppeteering with #StyleGAN2. Just the head so far, but obviously expression mapping is the actual target.
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"Generative Computergraphik" from 1969 by Georg Nees arrived in my mailbox today. Here's some pioneering generative art written in ALGOL.
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I do not really care much for "pretty" generative art. I want something that has an interesting concept, is algorithmically challenging and ideally so complex that I cannot reverse engineer its mechanism right away. Unfortunately I don't see a lot of that these days.
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Generating faces from a sketch. I trained a pix2pix net on 1500 #bldigital faces. Left input, right output.
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Now that I have my local version of #BigGAN running, exploring the wilderness and weirdness of its latent space will become a bit faster and comfortable.
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If you just woke up to and wonder what happened to the hic et nunc website and its "discontinued" twitter account here's some info what is going on as far as I know:.
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Inverse #BigGAN search for a previously generated image across the entire 1128-dimensional latent space starting from a random vector.
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Hey #gpt3, the sentence: "A giraffe in a forest with trees in the background" is correct but boring. Make it sound more interesting.
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Finding movie scenes by example. After recording a scene with my camera the machine analyzes it and returns the visually most similar ones.
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Here is my nasty visage run through a chain of two GANs, the first one "normalizes" it, the second one re-imagines the lost details.
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I've created an experimental GAN architecture I call #RecuResGAN or "Recursive-Residual GAN" and I am pretty astonished that:.- it works at all.- how well it works across a pretty wide range of scales. - it is just 15% the size of a comparable #pix2pixHD model
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This CGAN neural network I trained overnight has its own ideas what "Enhance!" means. Left: input, right: output
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The autobahn is open. The pioneer silently weeps and reminisces how there used to be jungle here just 3 years ago.
Neural Filters is a major breakthrough in AI-powered creativity and the beginning of a complete reimagination of filters and image manipulation inside @Photoshop 🤩: #AdobeMAX
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I have spent too much time in front of my Uncanny Mirror - it has learned my glasses, my shirt and my mobile phone. @mediacityseoul
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This is a fully generated clip, made from the random interpolation, transformation and scaling of the original Françoise Hardy face markers.
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Now would be a great time to try out Universal Basic Income for a year.
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We made our first million at @hicetnunc2000.
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Another round of fine-tuning, starting from a state where the artifacts had not shown yet. This model uses batch norm in the deep residual layers, instance norm in the surrounding ones and spectral norm in the discriminator.
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This might show it a bit better. Left is input, right is output. My latest progress in neural enhancement using a modified #pix2pix architecture which tries to achieve better details. The training data right now is female faces only.
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No, "Famous artist finding a new way to make more money in an already booming market" is not a game changer. "Artists from all backgrounds creating a thriving decentralized ecosystem and community from scratch on the blockchain without having any funding" is one. @hicetnunc2000.
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Josh Mobley @joshmobleymusic just sent me a new song called "A Walk in the Park" and I had my algorithm give it the #BigGAN treatment. Since it can create an infinite amount of versions it's hard to pick one, but I really like what it does at 1:08.
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It's no secret that Art Basel Miami is all about NFTs this year. Make sure to check in at the @tezos booth and get your surreal self-portrait NFT minted by my installation:.@TheArtNewspaper
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Ungrateful lazy bastards. Just a few years ago you could be happy if there was any code accompanying a paper.
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This actually does stand out amongst the current avalanche of "I trained a GAN on everything and the kitchen sink". Nice one!.
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I wish this glitch version of my work were intentional, but it's an actual glitch.
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Oh, this is working better than I had hoped for. A different type of #BigGAN evolutionary search. #neurography #neurealism
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After a few hours of figuring out how to translate bezier curves into robot moves that don't wiggle, stutter or run into singularities I finally managed to have it sketch a #CLIP generated "Mona Lisa".
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Sketch for a new work - "Three Latent Body Problem"
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Some #genart history:. Algorithm 133 by Peter G. Behrenz from 1962 might be the first documented random number generator used in generative art. It can be found in Georg Nees' book "Generative Computergraphik"
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This model tries to learn fluid dynamics by watching a video and then generating it via next-frame prediction. #pix2pixHD #feedbackloop #GAN
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I had to try my own method for this problem. Not sure if you can call it an improvement, but by simply starting the gradient descent from different random locations in latent space you can already get more variation in the results.
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Here's how they are made: The input is a 32-dimensional human pose vector as visualized in the upper corner, the output is what you see.
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So many variables in just drawing a straight line with ink + brush (+ robot). 🤯
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WARNING: Unfortunately somebody has figured out a new nasty copyminting scam on @hicetnunc2000 which is very deceptive since it shows the real artists as the creator, but they did not actually mint it. Do not buy from this wallet: tz1ch5WHJDZbbFR8R98cDkriVMwFP6RN9it2.
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Ah, the cat is out of the bag. 😊.
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Cloning and installing #ChatGPT inside of itself and then running the experimental concious_chat.py script. 😂
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My new model makes it really hard to decide what to throw away, when the worst results I get look like this. #aiart #neurography
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Q: "Where do the little faces come from?".A: "Well, when two not very well trained GANs meet and enter a feedback loop it just happens"
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If all you have is an automatically generated uv map everything looks op-artable.
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