this post was submitted on 15 Apr 2024
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Showerthoughts
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A "Showerthought" is a simple term used to describe the thoughts that pop into your head while you're doing everyday things like taking a shower, driving, or just daydreaming. The most popular seem to be lighthearted clever little truths, hidden in daily life.
Here are some examples to inspire your own showerthoughts:
- Both “200” and “160” are 2 minutes in microwave math
- When you’re a kid, you don’t realize you’re also watching your mom and dad grow up.
- More dreams have been destroyed by alarm clocks than anything else
Rules
- All posts must be showerthoughts
- The entire showerthought must be in the title
- No politics
- If your topic is in a grey area, please phrase it to emphasize the fascinating aspects, not the dramatic aspects. You can do this by avoiding overly politicized terms such as "capitalism" and "communism". If you must make comparisons, you can say something is different without saying something is better/worse.
- A good place for politics is c/politicaldiscussion
- Posts must be original/unique
- Adhere to Lemmy's Code of Conduct and the TOS
If you made it this far, showerthoughts is accepting new mods. This community is generally tame so its not a lot of work, but having a few more mods would help reports get addressed a little sooner.
Whats it like to be a mod? Reports just show up as messages in your Lemmy inbox, and if a different mod has already addressed the report, the message goes away and you never worry about it.
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Im fascinated with the history of image AI as just some algorithms to help clean up noisy photos. Eventually they advanced enough that you just feed it complete noise, tell it what its an image of, and it just "gets rid of the noise"
Wait is that how image generation works? Denoising a random noise seed?
Yes! It's called "stable diffusion", and it's how you get a unique image everytime.
Yeah thats the mechanism its generating with, and why every generation is different in some way. Theres a lot more cool components to the whole process and history tho. Tying language models into image recognition models, and then the image generation algorithm has an arms race with the image recognition, where the image generation is learning by trying to deceive image recognition, and image recognition is trying to distinguish between generated images and real images its also being fed.