ai

TIME
"But the need for humans to label data for AI systems remains, at least for now. 'They’re impressive, but ChatGPT and other generative models are not magic – they rely on massive supply chains of human labor and scraped data, much of which is unattributed and used without consent,' Andrew Strait, an AI ethicist, recently wrote on Twitter. 'These are serious, foundational problems that I do not see OpenAI addressing.'"
Warning: this article is disturbing. Companies shouldn't be able to cause people psychological damage to get funding.
Futurism
"The problem with this description isn't just that it's wrong. It's that the AI is eliding an important reality about many loans: that if you pay them down faster, you end up paying less interest in the future. In other words, it's feeding terrible financial advice directly to people trying to improve their grasp of it."
Our unevenly distributed AI future is terrible already! Update (1/23): And who cares about copyright?
waxy.org
"This academic-to-commercial pipeline abstracts away ownership of data models from their practical applications, a kind of data laundering where vast amounts of information are ingested, manipulated, and frequently relicensed under an open-source license for commercial use."
Andy explains the research to corporate profit pipeline. Seems like there should be a way to handle consent even at this scale. Many CC licenses require attribution—I wonder how these image models handle that.
stablediffusionlitigation.com
"At min­i­mum, Sta­ble Dif­fu­sion’s abil­ity to flood the mar­ket with an essen­tially unlim­ited num­ber of infring­ing images will inflict per­ma­nent dam­age on the mar­ket for art and artists."
Describing image models as sophisticated collage tools takes some of the mystery out of AI and makes it clear work is being used without consent. This essay has a clear description of the diffusion process.
Clive Thompson
"This isn’t just a problem for Stack Overflow. In pretty much every other example where you see ChatGPT screwing up basic facts, it does so with absolute self-assurance. It does not admit a smidgen of doubt about what it’s saying. Whatever question you ask, it’ll merrily Dunning-Kruger its way along, pouring out a stream of text. It is, in other words, bullshitting."
Effortless bullshit. At scale. What could possibly go wrong?
wsj.com
"The statistics contrast starkly with the confidence in AI presented by Facebook’s top executives, including CEO Mark Zuckerberg, who previously said he expected Facebook would use AI to detect “the vast majority of problematic content” by the end of 2019."
If your answer to an extremely difficult problem is "AI will solve it" you are not really interested in solving that problem. Facebook leadership knows this but they say it anyway while human moderators suffer with no resources because AI will solve this problem any minute now.

VQGAN + CLIP + Unreal Engine + Surrealism

I enjoyed Rusty's explanation of the VQGAN + CLIP Unreal Engine trick in Today in Tabs yesterday (subscribers only, sorry). The gist is that people have found a way to improve images created with machine learning by including the phrase "unreal engine" (yes, the Mandalorian-powering video game technology) with their prompt when they ask a GAN to generate an image of that prompt.

Rusty included a link to a colab notebook that could run this particular GAN—VQGAN+CLIP—so I started playing around with it. I know next to nothing about AI or Machine Learning, but I can run code! I tried out the unreal engine trick and the results reminded me of Yves Tanguy paintings.

My next thought was, "why not feed it some lines from surrealist poetry"? (Or their English translations anyway.) So here are a few of those:

VQGAN+CLIP generated image using a surrealist poem phrase, vague castle in a blurry landscape "a meaningless castle rolled along the surface of the earth."
– André Breton, Soluble Fish

VQGAN+CLIP generated image using a surrealist poem phrase, vague night scene with various lights "it is the star struck under my heel in the night."
– Robert Desnos, The Landscape

"The river I have under my tongue"
– Paul Eluard, The River

VQGAN+CLIP generated image using a surrealist poem phrase, a vague flower and vague clock; some fire "where we live the flowers of the clocks catch fire"
– Tristan Tzara, The Great Lament of my Obscurity Three

The other day I linked to Nick Cave saying that AI lacks the nerve to create great music. How about visual art? Seeing machines struggle to make what humans make is interesting, but I don't think the results are inspired. Again, I have no idea how to tune these tools to get more interesting results and maybe further tuning or more attempts would create better images. Right now I think we haven't progressed beyond Hayao Miyazaki's thoughts on art by artificial intelligence. (spoiler alert: "I strongly feel that this is an insult to life itself.")
spectator.co.uk
"A sense of awe is almost exclusively predicated on our limitations as human beings. It is entirely to do with our audacity as humans to reach beyond our potential."
AI lacks nerve is a fantastic way to put it. [via om]

Tom Swarfties

"I trained a neural network to write Tom Swifties," Tom said artificially. But seriously, after "success" with Oregon Placenames I wanted to try something more complex. The short, repeating format of Tom Swifties seemed like something it could tackle. I found a good compilation and set to work training. (Start with the compilation if you haven't seen Tom Swifties before. You'll get the idea after a handful.)

I have a feeling I need to look into the whole GPU thing for processing because I've been training the AI nonstop on AWS for a few days now and while it has come a long way, it's still not speaking English. But the Swifty form is there and I think it has some interesting things to share. Here are a few:
  • "Allye! Peen!" said Tom guiltorively.
  • "I had a modight", said Tom inderitively.
  • "I've not beat'd will we I sfong that take ban hisse", said Tom bardingly.
  • "Let's go! wrong wo", said Tom posthalicteitingly.
  • "Looks oke run shats", Tom repocked.
  • "I more for owlanimors!" said Tom jauntly.
  • "I haven to reperent", said Tom barch-oned.
  • "I'm going to have sow manartioutive", said Tom pridely.
  • "I like that a get a tround of chairs?" asked Tom consically.
  • "You're faloamintica", Tom canied consentingly.
  • "I don't play due the stragumed glan to the botheric", said Tom rasmitally.
  • "It's tere takes my pief?" asked Tom centatically.
I notice that it's putting asked with the questions. I wonder if the adverb will eventually match the subject in the quote. I'll keep training, but it seems to get slower as it gets more complex. "I wonder if I could tap into more processing power," pb said cloudily.

Fake Oregon Placenames

Dan Hon recently trained an A.I. to generate British placenames. I followed his recipe and did the same for Oregon placenames.

I found a list of real Oregon placenames at the US Board on Geographic Names. I did a round of A.I. training with the raw data and found the output too noisy. So I did a little data massaging and gave it another shot, this time with cleaner results.

I set the whole thing up on a free AWS instance with the torch-rnn docker image. It was a snap. A slow snap. It would be faster with more processing power.

Without further setup, plan your next camping trip and imagine the vistas you'll see in such artificially imagined Oregon places as:
  • Thkewood Meadows
  • Cookstop Lake
  • Thedrel Springs Cemetery
  • Water Reservoir
  • Rogah Butte
  • Newar Creek
  • Willaning Creek
  • Dazian
  • Booper Summit
  • Pister Creek Ranch Spring
  • Josspor Ridge
  • Bickmass Log Pond
  • Trout Bucktuby
  • Monnnit Hellant Plant Creek
  • Pitter Cip Number One
  • Seven Creek
  • Giam Creek
  • Hemil M Creek
  • Hug Waterhole
  • Dukapin Meadows
  • Bensbush Creek
  • Malow Creek
  • Lattle Lake Recreation Meadows
  • Mule Park
  • Road Ranch
  • Bruck Creek
  • Gregley Park Recreation Site
  • Forent Well
  • Kench Bed Reservoir
  • Indian Slide
  • Sinkhawk Trail
  • Tondyle Canyon
  • Spilling Pond
  • Syn Reservoir
  • Pieson Reservoir
  • Thirn Mountain
  • Fence and Swalich
  • Lower Spring Cemetery
  • Bolard Creek
  • Coney Butte Park
  • Skihino Peak
  • Laix Spring
  • Clenmill Creek
  • Oshers Forest
  • Fork Slow Spring
This is a random linear sampling from potentially infinite output. It might be funnier to go through with an editorial eye and find the most amusing, but it's getting late and I have a trip to Fence and Swalich to plan.
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