Father, Hacker (Information Security Professional), Open Source Software Developer, Inventor, and 3D printing enthusiast
This doesn’t make sense when you look at it from the perspective of open source models. They exist and they’re fantastic. They also get better just as quickly as the big AI company services.
IMHO, the open source models will ultimately what pops the big AI bubble.
If only they would actually spend it on things that benefitted the economy instead of:
I firmly believe that a big reason why wealth is consolidating so quickly is because there’s not much for the rich to spend their money on these days. It used to cost a fortune to care for a great big mansion and the surrounding grounds (and you’d have a local economy built on that). These days, it’s not even a rounding error in their monthly income from interest and dividends and you don’t even need to hire very many people.
There used to be actual luxury services the rich needed to pay for if they wanted to appear better off than the riffraff. Now the common man has access to all those luxuries and more.
Once you’ve got a couple private jets and a yacht (that you never spend any time on), what the fuck do you need all that money for‽ Even they don’t know what to do with it!
Larry Ellison—the original tech villain billionaire—bought a huge private island in Hawaii. He’s never there. It just… Sits there. With a small staff and places for his yachts. It’s like he wants to go down in history as one of the biggest, greedy scumbags of all time.
Stick Enthusiasts!
In my experience, the diet soda “best by” date is 100% accurate. My guess is there’s a very tight window of time where aspartame can remain sweet, after which it will degrade into Moxie flavoring (which tastes like… Soda water mixed with dirt).
No, a .safetensors file is not a database. You can’t query a .safetensors file and there’s nothing like ACID compliance (it’s read-only).
Imagine a JSON file that has only keys and values in it where both the keys and the values are floating point numbers. It’s basically gibberish until you go through an inference process and start feeding random numbers through it (over and over again, whittling it all down until you get a result that matches the prompt to a specified degree).
How do the “turbo” models work to get a great result after one step? I have no idea. That’s like black magic to me haha.
Three of the top five are actually just Facebook (Meta)
I want to see a chart that compares AI emissions to global emissions. It would also be great to compare a long chat with an LLM with say, watching a video on Netflix or YouTube.
Lamp cult gets mothballed for the Empire!
Or, with AI image gen, it knows that when some one asks it for an image of a hand holding a pencil, it looks at all the artwork in it’s training database and says, “this collection of pixels is probably what they want”.
This is incorrect. Generative image models don’t contain databases of artwork. If they did, they would be the most amazing fucking compression technology, ever.
As an example model, FLUX.dev is 23.8GB:
https://huggingface.co/black-forest-labs/FLUX.1-dev/tree/main
It’s a general-use model that can generate basically anything you want. It’s not perfect and it’s not the latest & greatest AI image generation model, but it’s a great example because anyone can download it and run it locally on their own PC (and get vastly superior results than ChatGPT’s DALL-E model).
If you examine the data inside the model, you’ll see a bunch of metadata headers and then an enormous array of arrays of floating point values. Stuff like, []. That is what a generative image AI model uses to make images. There’s no database to speak of.
When training an image model, you need to download millions upon millions of public images from the Internet and run them through their paces against an actual database like ImageNET. ImageNET contains lots of metadata about millions of images such as their URL, bounding boxes around parts of the image, and keywords associated with those bounding boxes.
The training is mostly a linear process. So the images never really get loaded into an database, they just get read along with their metadata into a GPU where it performs some Machine Learning stuff to generate some arrays of floating point values. Those values ultimately will end up in the model file.
It’s actually a lot more complicated than that (there’s pretraining steps and classifiers and verification/safety stuff and more) but that’s the gist of it.
I see soooo many people who think image AI generation is literally pulling pixels out of existing images but that’s not how it works at all. It’s not even remotely how it works.
When an image model is being trained, any given image might modify one of those floating point values by like ±0.01. That’s it. That’s all it does when it trains on a specific image.
I often rant about where this process goes wrong and how it can result in images that look way too much like some specific images in training data but that’s a flaw, not a feature. It’s something that every image model has to deal with and will improve over time.
At the heart of every AI image generation is a random number generator. Sometimes you’ll get something similar to an original work. Especially if you generate thousands and thousands of images. That doesn’t mean the model itself was engineered to do that. Also: A lot of that kind of problem happens in the inference step but that’s a really complicated topic…
Note: All of these governments are currently experiencing the biggest flaw in capitalism:
https://en.wikipedia.org/wiki/Baumol_effect
You can expect health and education spending to go up as a percentage… Forever.
Most everything else benefits from economies or scale or consistently has non-trivial gains from automation (anything that improves productivity, really).
I prefer local AI, using open source models🤷
Well, if you’re going to be misled by bullshit, ending up near the Brooklyn Bridge—where nothing at all happened—isn’t so bad.
Obviously, these gullible fools have learned their lesson and won’t be so easily duped in the future.
Hahaha yeah right.
Officer: “I got better!”
There’s going to be some hilarious memes/videos when these get deployed:
I’m ok with rich people getting charged more. But anyone who isn’t making like $1 million/year should get the normal price.
I assume you missed “scrolling” because of all the alcohol?
Shit. I just realized I went straight to the comments!
This will definitely encourage more people to have kids.
Maybe take pictures of them instead?