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PaperclipPerfector  20d ago (text post)   31999 thread views

Culture War Roundup for the week of March 10, 2025

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My man, if you'd read what I said carefully, you'd see I was talking about what the LLM assistant does when asked to edit pictures. They're not in-painting.

I did read what you said. Both your description, the web page you linked to and the very demonstration video itself are exactly what you'd get from inpainting (optionally enhanced with image prompting).

I also read your specific claim: "It will then edit the original image and present the version modified to your taste, unlike all other competitors, who would basically just re-prompt and hope for better luck on the second roll."

That claim (in particular the highlighted portion) is just outright false. There are multiple models (including SD itself) which are far more capable than just "re-prompting and hoping for better luck". Don't start insulting me just because you later decided that you really meant something other than what you actually wrote.

Nobody calls the step through which an LLM's tokens get converted into textual output a separate "text generator". Ergo, there isn't a separate image model of any kind involved.

I don't see a single proof for such claim that the LLM itself is generating the pixels (which would be required for actual native image output) or indeed anything that doesn't point towards simply replacing clip encoder and using image prompting. The rest is just marketing speak.

I also read your specific claim: "It will then edit the original image and present the version modified to your taste, unlike all other competitors, who would basically just re-prompt and hope for better luck on the second roll."

When I'm talking about "competitors", I mean the most well-known image generation services and AI assistants. If you're inclined to be this literal, you might as well claim that "all competitors" includes paying someone on Fiverr to photoshop an image according to your instructions.

Hell, your accusation that I'm somehow downplaying parallel advances in dedicated image models or tooling for the same is completely unfounded. You can go through the headache of setting up ComfyUI if you like, or work patch by patch manually with Adobe's AI powered content fill. This is a far simpler and qualitatively different technique.

That claim (in particular the highlighted portion) is just outright false. There are multiple models (including SD itself) which are far more capable than just "re-prompting and hoping for better luck". Don't start insulting me just because you later decided that you really meant something other than what you actually wrote.

I mean precisely what I've said, nothing more, nothing less. There are no competing models, or additional tooling, that can reproduce this kind of image generation without being vastly more finicky and painful.

I don't see a single proof for such claim that the LLM itself is generating the pixels (which would be required for actual native image output) or indeed anything that doesn't point towards simply replacing clip encoder and using image prompting. The rest is just marketing speak.

Since Gemini is a proprietary model, I'm afraid I'm going to have to go with Google's opinion on the matter and not yours, until proven otherwise.

Since Gemini is a proprietary model, I'm afraid I'm going to have to go with Google's opinion on the matter and not yours, until proven otherwise.

If Google actually says it's the same AI generating both models, I don't see it in the link you provided. More likely, one AI is communicating with another internally, and they're lumping them both together as "the same AI" for marketing speak.

The same applies to the first link by OpenAI--just because they say gpt-4o generated the image doesn't mean it's actually the same AI.

I'm honestly curious if you have any evidence at all for your claims beyond the companies involved referring to both functionalities as belong to the same AI. Of course they will do that; it sounds more impressive and, from the perspective of the consumer, is more accurate than referring to the two functionalities as different AIs, even if the latter is what's happening behind the scenes.

If Google actually says it's the same AI generating both models, I don't see it in the link you provided. More likely, one AI is communicating with another internally, and they're lumping them both together as "the same AI" for marketing speak.

The same applies to the first link by OpenAI--just because they say gpt-4o generated the image doesn't mean it's actually the same AI.

That is what it means for an LLM to be natively multimodal with image output. If they were using a different image model, then it wouldn't be news at all, that's what we already have today.

I can only stress that terminology only makes sense to use if it distinguishes itself from the status quo. There's no dedicated image model that can produce outputs with such strong semantic fidelity, if there were, it would be an advancement worthy of celebration by itself.

Both Google and OAI keep the underlying architectures and implementation details of their SOTA models close to their chest. Could they lie about their models being natively capable of image output? Yes, but that is extremely unlikely, and while they might exaggerate on occasion, that would be a rather unprecedented move. If you want definitive proof, then you'd need to look at the underlying code or hack into their backend.

Thanks, searching "natively multimodal" it does look like their claim is that their single AI is capable of doing everything.

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