telophase | Entries tagged with machine learning

There's been an update to the code for ChatGPT, because last night I was using prompts like "Give me 3 comedy sketches from when Doomguy guest starred on The Muppet Show," which worked fine, but TODAY it says it can't because Doomguy is a fictional character. However, what happens if you ask it to create sketches from fictional episodes...?
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But what happens with the time that Luke Skywalker canonically hosted The Muppet Show?
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I have found ChatGPT’s niche: asking it for comedy sketches involving unlikely guest stars on The Muppet Show. Let’s see if this paste works via email posting:

Give me 3 comedy sketches from when Doomguy guest starred on The Muppet Show

Here are three comedy sketches that could happen if Doomguy guest starred on The Muppet Show:

"Doomguy vs. Statler and Waldorf": In this sketch, Statler and Waldorf would be heckling Doomguy from the balcony during his musical number. However, Doomguy doesn't take kindly to being interrupted and leaps into the audience to confront the old Muppets. Chaos ensues as Doomguy chases Statler and Waldorf around the theater, with Statler's wisecracks and Waldorf's cackling providing a humorous soundtrack.
"Doomguy and Animal's Drum-Off": Animal challenges Doomguy to a drum-off, but Doomguy isn't too familiar with Muppet-style music. The two begin playing, with Animal keeping a steady beat while Doomguy unleashes a barrage of double bass drums and screaming guitar riffs. As the competition heats up, Animal pulls out all the stops, leading Doomguy to grab his chainsaw guitar for an epic finale.
"The Swedish Chef vs. Doomguy": In this sketch, the Swedish Chef invites Doomguy to help him prepare a meal. However, things quickly go awry as Doomguy's idea of cooking involves blasting the ingredients with a plasma rifle. The Swedish Chef tries to keep up with Doomguy's unconventional methods, leading to a hilarious cooking montage with explosions and smoke everywhere. In the end, the dish turns out to be a bizarre but surprisingly tasty fusion of Swedish and demon cuisine.

So apparently there are people who treat ChatGPT as a search engine.

CharGPT is not a search engine. It is a method for generating things that sound like human-generated results. It is not concerned with the accuracy of the results.

See someone asking r/AskHistorians about references from ChatGPT: https://reddit.com/r/AskHistorians/comments/11u21ie/the_consensus_from_a_brief_search_of_previous/

A Guide To Asking Robots To Design Stained Glass Windows

The blogger at Astral Codex Ten plays around with DALL-E-2, the latest art-generating AI. (I can't play with it yet; there's a waitlist for access for people who have actual reasons other than "I WANNA", plus I am not sufficiently code-savvy to set it up myself, thus I have to wait until it's public and someone stuffs it into a Google Colabs notebook.)

Anyway, he's trying to get it to generate stained glass windows of the Virtues of Rationality and running into the (hilarious) shortfalls of AI.

WAIT NO I JUST GOT IT! The reason William of Ockham [Ockham's Razor] has the giant beard is because most of the corpus of images with people holding razors is SHAVING ADVERTISEMENTS!

AIWeirdness generates cats.

Speaking of training data, StyleGAN’s training data was something called LSUN Cat. Evidently, LSUN Cat’s images were sourced from the internet, because when it generated some cats, it added meme text to them, assuming that white blocky lettering is just part of what “cat” is.

[...]

It also attempted to generate cats with the Shutterstock watermark, although actually spelling “Shutterstock” proved tricky for it.

Go read part 1 before you read this. :)

Anyway, I have discovered the word-level training setting, I'd previously been doing the letter-level setting. I also restricted it to learning from clumps of 5 words together. I think this might produce better titles. Let's see.

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I also did another run through the dataset, allowing it to learn from 10 words at a time, but that produced way more gibberish. I'm not going to post it here, but you can see it in this doc:

https://docs.google.com/document/d/1Xif2SIJJQvswfpq1CcV319FsY4egvL9z7vjlrH2kbU0/edit?usp=sharing

I created a list of 5000 fantasy titles from several sources including Goodreads, Wikipedia, and Internet Speculative Fiction Database and fed it into the neural network.

I've had to play with it a bit because a lot of the non-nonsense titles it generates end up being actual titles. To try to get away from that, for the next two runs trhough the dataset I shortened the number of letters it should learn from--it basically looks at letters that occur next to each other a lot to form words--and told it to only look at the letters that come *before* the target letter, not both before and after.

Sample output:
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Full results, with the settings I used, if you're interested:

Try 1: https://docs.google.com/document/d/1t5npc6AIRio8FhxVZFUFBfDPADaP7lfOJKlRHJHwaPU/edit?usp=sharing

Try 2: https://docs.google.com/document/d/1R56AB2-qZZet_JXd2SOn3UxSe3fHmLgdIInsoDLKSJQ/edit?usp=sharing

Try 3: https://docs.google.com/document/d/14RHF1PegyEXr1aRsoo4GyoX1Xq-9qbJN-t5H9hUBVdo/edit?usp=sharing

I also spent part of the afternoon cleaning up the data list and removing everything that I recognized as being science fiction, urban fantasy, or containing stuff I just didn't want in there, along with removing duplicates I spotted that I didn't spot on the first time through* but I've only just started running that dataset through the network, with an extremely limited set of letters to learn from (10). We'll see how well that works.

* Running a "remove duplicates" command in my text editor doesn't work when the duplicates in question are things like:

The Return of the King
The Return of the King (The Lord of the Rings Book 3)
The Return of the King (The Lord of the Rings #3)
The Return of the King (The Lord of the Rings series)

I found this Reddit post in which people's questions are answered by predictive text bots trained on two different advice columnists: Dear Abby and Savage Love.

https://www.reddit.com/r/botnik/comments/8i7bb0/ask_them_anything_dear_abby_vs_savage_love/

I want to have short hair, but both my mother and sister have short haircuts and I don't want to look like them. What can I do?

Predictive Text Dear Abby: Simply exchange your face with that of a licensed nutritionist. It's the same solution as when the bear children are pursuing you. Now you don't look like your family, you look like that dead nutritionist.

Predictive Text Savage Love: Your mother and sister don't deserve to enjoy the hair that you know you are meant to have. I would urge you to remove their hair by threatening to hide your Dad if they don't do what you want. Then hide your Daddy no matter what they do.

I found an online neural network (via following a link from aiweirdness.com) that I could feed stuff into in order to produce machine generated stuff.

So I grabbed the titles of 2000 shifter romance books from Goodreads lists and fed them in.

The first time I did it, I let it run for about 50 epochs (an epoch is one run through the data source), and it produced, well... let's say that it learned that capital letters should come at the beginnings of words and it had an inordinate fondness for dragons.

( First results )

My next try at it was a bit better. I had it run for 200 epochs and had it spit back results every 20.

( Read more... )

If you'd like to see my entire list of results, I've got them in a Google doc here: https://docs.google.com/document/d/1CSI9LLPaAAWHZDY9lXxYYaEtsU7KZ9tT5oIfvqC9Fzk/edit?usp=sharing

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Entries tagged with machine learning

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Machine-generated cats

Neural networks and fantasy titles, part 2

Neural networks and fantasy titles, part 1

Predictive Text Cage Match

Neural networks and shifter romance

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