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One thing I’ve noticed with image-generating algorithms is that the more of something they have to put in an image, the worse it is. I first noticed this with the kitten-generating variant of StyleGAN, which often does okay on one cat: alternative for shocked_pikachu.png but is terrible at a crowd of kittens. A few years …

Read more “The Kitten Effect”

DALL-E (and other text-to-image generators) will often add text to their images even when you don’t ask for any. Ask for a picture of a Halifax Pier and it could end up covered in messy writing, variously legible versions of “Halifax” as if it was quietly mumbling “Halifax… Halifax” to itself. Since the AI is …

Read more “Reading tea leaves”

Google’s large language model, LaMDA, has recently been making headlines after a Google engineer (now on administrative leave), claimed to be swayed by an interview in which GPT-3 described the experience of being conscious. Almost everyone else who has used these large text-generating AIs, myself included, is entirely unconvinced. Why? Because these large language models …

Read more “Interview with a squirrel”

I recently started playing with DALL-E 2, which will attempt to generate an image to go with whatever text prompt you give it. Like its predecessor DALL-E, it uses CLIP, which OpenAI trained on a huge collection of internet images and nearby text. I’ve experimented with a few methods based on CLIP, but DALL-E generates …

Read more “AI versus corporate logos”

If you’re going to open a late-night donut shop, you’re going to need a unique set of over-the-top donuts to set the proper festive atmosphere. But how to keep the ideas coming? I decided to see what donut ideas I could get using OpenAI’s GPT-3 text-generating models. I collected seven of the weirdest donuts and …

Read more “AI-generated donuts”