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GPT Image 1.5

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Re: GPT Image 1.5

#181

Post by gs17 »

Nition wrote: post #172
gs17 wrote: post #104

Earlier quoted context omitted.

> however im not sure if these are true uv maps I can tell you with 100% certainty they are not. For example, Crash doesn't have a backside for his torso. You could definitely make a model that uses these as textures, but you'd really have to force it and a lot of it would be stretched or look weird. If you want to go this approach, it would make a lot more sense to make a model, unwrap it, and use the wireframe UV m…

That's a remake model in a modern game. The original Crash was even simpler than that one. Most of Crash in the first game was not textured; just vertex colours. Only the fur on his back and his shoelaces were textures at all.

"Original" as in the original of the one they used in their tweet.

Re: GPT Image 1.5

#182

Post by encroach »

This outperforms Gemini 3 pro image (nano banana pro) on Text-to-Image Arena and Image Edit Arena. I'm surprised they didn't mention this leaderboard in the blog post.

I like this benchmark because its based upon user votes, so overfitting is not as easy (after all, if users prefer your result, you've won).

https://lmarena.ai/leaderboard/text-to-image

https://lmarena.ai/leaderboard/image-edit

Re: GPT Image 1.5

#183

Post by nycdatasci »

encroach wrote: post #182

This outperforms Gemini 3 pro image (nano banana pro) on Text-to-Image Arena and Image Edit Arena. I'm surprised they didn't mention this leaderboard in the blog post. I like this benchmark because its based upon user votes, so overfitting is not as easy (after all, if users prefer your result, you've won). https://lmarena.ai/leaderboard/text-to-image https://lmarena.ai/leaderboard/image-edit

The arena concept doesn’t work for image models due to watermarks.

Re: GPT Image 1.5

#184

Post by wahnfrieden »

cheema33 wrote: post #129
wahnfrieden wrote: post #54

Earlier quoted context omitted.

They've published anticipated price increases over coming years. Prices will rise dramatically and steadily to meet revenue targets.

AI doesn’t have much of a moat. People can and will easily switch providers.

Sure but there are only a couple leading providers worth considering for coding at least, and there will be consolidation once investment pulls back. They may find a way to collude on raising prices.

Where switching will be easier is with casual chat users plus API consumers that are already using substandard models for cost efficiency. But there will also always be a market for state of art quality.

Re: GPT Image 1.5

#185

Post by encroach »

nycdatasci wrote: post #183
encroach wrote: post #182

This outperforms Gemini 3 pro image (nano banana pro) on Text-to-Image Arena and Image Edit Arena. I'm surprised they didn't mention this leaderboard in the blog post. I like this benchmark because its based upon user votes, so overfitting is not as easy (after all, if users prefer your result, you've won). https://lmarena.ai/leaderboard/text-to-image https://lmarena.ai/leaderboard/image-edit

The arena concept doesn’t work for image models due to watermarks.

There are no watermarks in the arena.

Re: GPT Image 1.5

#186

Post by GaryBluto »

God OpenAI are so far behind. Their own example shows that trying to only change specific parts of the image doesn't work without affecting the background.

Re: GPT Image 1.5

#187

Post by famahar »

ares623 wrote: post #98

My copium is that analog photography makes a come back as a way to recover some level of trust and authenticity.

I was reading a trend report on art and it seems like collage, squiggly hand drawn text, and lots of intentional imperfections are becoming popular. I'm not sure how hard it is for AI to recreate those, but it is nice to see people trying to do more of what AI struggles with.

Re: GPT Image 1.5

#188

Post by ewoodrich »

laurent123456 wrote: post #128
KaiserPro wrote: post #59

Is there a watermarking, or some other way for normal people to tell if its fake?

There are ways to tell if an image is real, if it's been signed cryptographically by the camera for example, but increasingly it probably won't be possible to tell if something is fake. Even if there's some kind of hidden watermark embedded in the pixels, you can process it with img2img in another tool and get rid of the watermark. Exif data, etc is irrelevant, you can get rid of it easily or fake it.

Sure, you can always remove it, but an average person posting AI images on Facebook or whatever probably won't bother. I was skeptical of Google's SynthID when I first heard about it but I've been seeing it used to identify suspected AI images on Reddit recently (the example I saw today was cropped and lightly edited with a filter but still got flagged correctly) and it's cool to have a hard data point when present. It won't help with bad/manipulative actors but a decent mitigation for the low effort slop scenario since it can survive the kind of basic editing a regular person knows how to do on their phone and typical compression when uploading/serving.

Re: GPT Image 1.5

#189

Post by somenameforme »

pierrec wrote: post #142
vunderba wrote: post #102

Okay results are in for GenAI Showdown with the new gpt-image 1.5 model for the editing portions of the site! https://genai-showdown.specr.net/image-editing Conclusions - OpenAI has always had some of the strongest prompt understanding alongside the weakest image fidelity. This update goes some way towards addressing this weakness. - It's leagues better at making localized edits without altering the entire image's ae…

This showdown benchmark was and still is great, but an enormous grain of salt should be added to any model that was released after the showdown benchmark itself. Maybe everyone has a different dose of skepticism. Personally I'm not even looking at results for models that were released after the benchmark, for all this tells us, they might as well be one-trick ponies that only do well in the benchmark. It might be too…

You don't need skepticism, because even if you're acting in 100% good faith and building a new model, what's the first thing you're going to do? You're going to go look up as many benchmarks as you can find and see how it does on them. It gives you some easy feedback relative to your peers. The fact that your own model may end up being put up against these exact tests is just icing.

So I don't think there's even a question of whether or not newer models are going to be maximizing for benchmarks - they 100% are. The skepticism would be in how it's done. If something's not being run locally, then there's an endless array of ways to cheat - like dynamically loading certain LoRAs in response to certain queries, with some LoRAs trained precisely to maximize benchmark performance. Basically taking a page out of the car company playbook in response to emissions testing.

But I think maximizing the general model itself to perform well on benchmarks isn't really unethical or cheating at all. All you're really doing there is 'outsourcing' part of your quality control tests. But it simultaneously greatly devalues any benchmark, because that benchmark is now the goal.

Re: GPT Image 1.5

#190

Post by arnz-arnz »

zkmon wrote: post #70

AI-generated images would remove all the trust and admire for human talent in art, similar to how text-generation would remove trust and admire for human talent in writing. Same case for coding. So, let's simulate that future. Since no one trusts your talent in coding, art or writing, you wouldn't care to do any of these. But the economy is built on the products and services which get their value based how much of hu…

all I can hope for is that a new industry or reliable ecosystem of vetters of real human talent will emerge. Are you really as good a writer as you claim to be? Show us the badge. That or AI firms have to be forced to 'watermark' all their creative outputs, and anyone misleading the public/audience should be punishable by law.
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