Earlier quoted context omitted.
Oh god yes, I've been trying to make a LLM Assisted Magic the Gathering card scanner... its been a hell of a time trying to get it to just OCR card names well....
Why would you use an LLM for OCR?
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ChatGPT Images 2.0
851–860 of 1001 posts
Re: ChatGPT Images 2.0
#852Earlier quoted context omitted.
If "people who made this possible" were getting their fair share, "a millionth of a cent for every billion USD made with it" would be about it for the artists. What makes the dataset valuable isn't that the image 0012992 in it is precious and irreplaceable. It's that the index goes to seven digits. Pre-training is very much a matter of scale - and scraping is merely the easiest way to get data at scale. People who co…
If it was about this why do OpenAI and Anthropic lose their minds when people are training off their output or trying to scrape their systems. I actually don't have an issue with training off the mass of everyones work if the models are open and free to build upon, it's locking them away and then throwing your toys out the pram when people try and do the same thing that bothers me.
Good question. I actually have a technical answer, believe it or not.
Pre-training is: training a model from scratch on cheap data that sets the foundation of a model's capabilities. It produces a base model.
Post-training is: training a base model further, using expensive specialized data, direct human input and elaborate high compute use methods to refine the model's behavior, and imbue it with the capabilities that pre-training alone has failed to teach it. It produces the model that's actually deployed.
When people perform distillation attacks, they take an existing base model and try to post-train it using the outputs of another proprietary model.
They're not aiming to imitate the cheap bulk pre-training data - they're aiming to imitate the expensive in-house post-training steps. Ones that the frontier labs have spent a lot of AI-specialized data, compute, labor and hours of R&D work on.
This is probably not "fair use", because it directly tries to take and replicate a frontier lab's competitive edge, but that wasn't tested in courts. And a lot of the companies caught doing that for their own commercial models are in China. So the path to legal recourse is shaky at best. But what's on the table is restricting access to full chain of thought, and banning the suspected distillation attackers from the inference API. Which is a bit like trying to stop a sieve from leaking - but it may slow the competitors down at least.
Re: ChatGPT Images 2.0
#853So during my Nano Banana Pro experiments I wrote a very fun prompt that tests the ability for these image generation models to follow heuristics, but still requires domain knowledge and/or use of the search tool: Create a 8x8 contiguous grid of the Pokémon whose National Pokédex numbers correspond to the first 64 prime numbers. Include a black border between the subimages. You MUST obey ALL the FOLLOWING rules for th…
How is it that a model can produce what must be near 1:1 images ripped straight out of Pokemon Fire Red (The first ones) for profit and not be infringing copyright.
I know that's the game, but it seems CRAZY to me that they can do this.
Re: ChatGPT Images 2.0
#854Earlier quoted context omitted.
A lot of people here aren't going to like it, but the only reasonable way out I can see is to eventually socialise ownership and control of AI. I don't see an alternative that isn't really bad.
Can you explain some of these alternatives that are so bad?
Bad: let tech (now "AI") companies, built on the collective (often in theory IP-protected) output of humanity, own and mediate an ever increasing proportion of the value created in society. Intellectual rent-seeking, if you will.
Bad: the above but also their power and influence grows so much and governments are so ineffective (or corrupt) against them that the tech companies also become de facto governments and people rely on them to survive. Also they destroy earth even faster with nobody left to stop them. The full fat cyberpunk dystopia.
Bad: the above but with lots more fascism and war. Too many people seem to want this.
Bad: regulate AI to such an extent as to cede all growth and technological leadership to whoever doesn't
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Re: ChatGPT Images 2.0
#855Earlier quoted context omitted.
This is from Gemini - https://lens.usercontent.google.com/banana?agsi=CmdnbG9iYWw6...
Did it correctly follow the instructions? Don't know my pokemon well enough.
Plusul and Minun sit next to each other in the Pokedex, 311 and 312. There's two 307s.
Re: ChatGPT Images 2.0
#856So during my Nano Banana Pro experiments I wrote a very fun prompt that tests the ability for these image generation models to follow heuristics, but still requires domain knowledge and/or use of the search tool: Create a 8x8 contiguous grid of the Pokémon whose National Pokédex numbers correspond to the first 64 prime numbers. Include a black border between the subimages. You MUST obey ALL the FOLLOWING rules for th…
Neither of them drew them in an 8-bit style either. It's way too many colors.
They made the same mistake a lot of people do, 8-bit meaning Retro style. But they're from the 16bit(?) GBA games.
Re: ChatGPT Images 2.0
#857Earlier quoted context omitted.
If I see art and get inspired by it, then paint my own thing and make millions do I owe my inspiration money?
If you end up creating something sufficiently similar, yes in fact you do. Or rather, you have done a copyright infringement and retroactive payment may be one of the remedies. This also applies to AI, just worse because: A) AI is not a human brain, and pretending that the process of human authorship is the same as AI is either a massive misunderstanding of the mechanics and architecture of these systems, or plain di…
But open models are only about 8 months behind closed models. So even aggressive copyright-enforcement would only create an 8 month delay.
This is essentially a LimeWire problem. And OpenAI is essentially Spotify.
Even with revenue sharing, 99% of artists will get nothing (just like streaming), and revenue will be much lower than before (just like streaming compared to record era).
Only IP giants like Disney would see any real income.
Re: ChatGPT Images 2.0
#858So during my Nano Banana Pro experiments I wrote a very fun prompt that tests the ability for these image generation models to follow heuristics, but still requires domain knowledge and/or use of the search tool: Create a 8x8 contiguous grid of the Pokémon whose National Pokédex numbers correspond to the first 64 prime numbers. Include a black border between the subimages. You MUST obey ALL the FOLLOWING rules for th…
I do not think this is a good prompt or useful benchmark, but nonetheless, it seems to work better for me: https://chatgpt.com/share/69e88a94-ded8-8395-b5dc-abceb2f44d...
Huh, that is indeed better. If ChatGPT Images 2.0/gpt-2-image is more nondeterministic than usual, than that is in itself a useful data point.
Re: ChatGPT Images 2.0
#859Earlier quoted context omitted.
A lot of people here aren't going to like it, but the only reasonable way out I can see is to eventually socialise ownership and control of AI. I don't see an alternative that isn't really bad.
Yes. And it can be done in less "communist" ways; have countries' governments invest serious capital (even if they have to raise debt - they do anyway) in income producing assets related to AI, like large stakes in AI labs, building data centres etc.
Yes, doesn't need to be "communist" or even fully socialist.
I think governments should invest in their economies - mostly by investing in research, education, infrastructure, health and wellbeing of citizens, etc. but also putting capital into the later stages of expansion would make sense.
I certainly don't think people should not be able to start or own or profit from companies. But I do see a reason to limit their scale and/or make them more publicly owned beyond an certain scale.
I quite like the idea that "public" markets should become truly public, e.g. by some ratcheting percentage of public companies becoming owned by society at large over time (there would be several ways this could be done). This somewhat happens with the largest companies via index funds but only for those big enough to be in the indices and the distribution in unequal.
Maybe there are other/better ways, but it's pretty clear to me that big companies have a lot of negative impacts that aren't properly accounted for and so they are a very significant way in which a few people get richer at the expense of everyone else.
Re: ChatGPT Images 2.0
#860Earlier quoted context omitted.
Prompts like this feel like it's using the wrong abstraction. The "obvious" thing to do with something like this would be to generate some code that generates the image and then run that code. Inspired by this, I tried something much simpler. I asked it to draw 12 concentric circles. With three tries it always drew 10 instead. https://chatgpt.com/share/69e87d08-5a14-83eb-9a3b-3a8eb14692...
I think prompts like this are where agentic workflows come in to play. If you asked it to do generate the first 64 prime numbers, AI tools could do that. If you asked it to draw a charcoal image of Pokemon 13, it could do that. If you asked it to add a white Menlo 13 on a black background to the top left corner of that image, it could do that. If you asked it to do that 63 more times, it could do those things, and if…
That's what makes it a fair evaluation of its limits