AI Weirdness: the strange side of machine learning

Tag: clip

Total 14 Posts
A screenshot of the AI Weirdness 2021 Advent Calendar, with one of the doors highlighted

An AI advent calendar

When I was a kid I looked forward to opening advent calendar doors in December, although the pictures behind the doors were pretty forgettable. A bell. A snowflake. If you were lucky, a squirrel. So I thought I'd see if I can generate something a bit more interesting, with the
A vivid green and red landscape with wobbly jelly-like bushes.

Playing with Pixels

Here's "Ice Cream Planet Swirl", as generated by Pixray. Full prompt: Ice Cream Planet Swirl #8bit #pixelart. Colors are chocolate, minty green, and cream.Pixray uses CLIP, which OpenAI trained on a bunch of internet photos and associated text. CLIP acts as a judge, telling Pixray how much its images
How to haunt and unhaunt a house

How to haunt and unhaunt a house

What do you get if you instruct an AI to turn a house into the most haunted house in the world? What if you ask it for the LEAST haunted house? How does an AI know what "haunted" looks like, anyways? I did some experiments with CLIP+VQGAN (link and
Several lumps of olden cake covered with generous dollops of creamy frosting.

Neural networks vs the Bake-off technical challenge

There's this baking competition I really like, and one of the elements in every show is what they call the Technical Challenge. In the Technical Challenge, Great British Bakeoff contestants have to bake something they may never have seen before, based solely on a brief description and a very sparse
AI is based on math so it is correct

AI is based on math so it is correct

Since OpenAI released CLIP, trained on internet pictures and their nearby text, people have been using it to generate images. In all these methods - CLIP+Dall-E, CLIP+BigGAN, CLIP+FFT, CLIP+VQGAN, CLIP+diffusion - you come up with a text prompt, some algorithm presents its images to CLIP,
It looks like a log of rice that's been rolled lightly in rainbow sequins.

In search of a unicorn cake

I've generated a lot of terrible unicorn cakes by this point. Last time I experimented with generating cakes, using CLIP's internet training to guide a couple of image generating methods. Around the time I posted my experiments, RiversHaveWings, who developed one of the most popular methods, came out with a
Generating images from an internet grab bag

Generating images from an internet grab bag

Still amazed by this: Here's CLIP+VQGAN (trained on internet photos and their accompanying text), prompted two different ways: "A car driving down a desert road in monument valley" A car driving down a desert road in monument valley"A car driving down a desert road in monument valley | dramatic
The art of asking nicely

The art of asking nicely

There are upsides to working with a neural net that trained on a huge collection of internet images and text. One is that, instead of ominous grey geometric blobs when it doesn't understand your prompt (there is a free interactive demo of AttnGAN here and it is a lot of
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