I find it easy to envision a world, maybe 50 years from now, in which the very concept of "truth in advertising" is viewed as a lost, idyllic fantasy. Something people are nostalgic for, but feel powerless to regain.
From what I hear (fact-check, etc. needed) that's already the case right now with much more consequential transactions, like renting real estate in NYC. Square footages that are blatant lies, etc.
Alternatively, perhaps we'll see models fine-tuned or steer-able towards accuracy that customers can themselves use to get a more honest view on what the product would look like in person.
The funny thing about these tools is that they can go either direction, but it sure seems like there's the potential for it empower individuals and shift the balance. Clothing sales shifting online has given sellers the advantage/ease to deceive without much customers can do other than hope the reviews aren't manipulated (they are) even before AI. Maybe this can turn things around as people start to shop with personal agents.
Here's a recent example: https://www.etsy.com/ca/listing/4509158065/corner-wall-shelf...
Ironically, ChatGPT is decently good at ferreting these out. Like I sent it a screenshot of that listing and it not only helped me find where the original item was for sale, but also pointed out how the dimensioned diagram shows it as being just 49" tall, whereas the "in real life" image looks like it's at least six feet, based on it coming up over the top of the picture frame.
I ended up engaging a local woodworker to make me a piece like it instead. Obviously an order of magnitude difference in price, but it will actually be real solid walnut and finished to match my dining table.
An acquaintance of mine was buying many and not wearing most, as she did not attend that many social occasions. Still, she kept buying.
Eventually, she had to face the actual problem in her life that bothered her. She ended up dealing with it, terribly.
Sure, it’s idealized, but some people benefit from seeing color / neckline / etc on themselves as a visual reference.
Me, I’m a text-learner so I don’t get it at all. But I know people who get value.
But I can't imagine that your conversion wouldn't benefit by showing actual imperfect photos of your products, especially when you run a platform with 1k new listings per month. I'm personally turned off by something that looks like 3D, especially when all the different colour variations look the exact same.
I wish a service existed where I could make something in AI (text, images, whatever), then pass that AI output to an actual human who would use it as a guide to produce an actual product.
In the end the one thing that is completely honest is the portion of the picture that is the item you are re-selling. But somehow to me the entire thing feels disingenuous.
Sort of like how they tried to make gandalf big and the hobbits small in lord of the rings (which wasn't very convincing to me)
Results are mixed, expensive, but it really feels you're few months off the next improvement to really nail it. It's already good enough.
Wonder what Qwen image will provide over nano banana.
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The result was always someone extremely good looking
There’s going to be an entirely new class of mental disorders that will emerge from people being deluded by AI
This is something that can be fixed over time. And if this forces clothing manufacturers to stick more to their advertised "specs" (width/length), then it's a win for us.
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Run this in console to see all the tags:
document.querySelector('meta[name="keywords"]').contenthttps://qianwen-res.oss-accelerate.aliyuncs.com/Qwen-Image/i...
https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen-Image/i...
https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen-Image/i...
https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen-Image/i...
It's a shame they didn't share that prompt - it would make that demo more convincing.
Impressive.
Btw, what is currently the best model to run locally on a 16GB Vram? Is it Z-Image Turbo?
I am seeing third legs and glowing eyes. It's a Microsoft Lens level of quality and that one was pulled.
But: not open-source/open-weights, and no indication that weights/source will be released either.
This may be a myth. Big paper in 2009, but nobody's proved it's real in the 15 years since.
In a 2009 review paper entitled Learning Styles: Concepts and Evidence, researchers investigated the “meshing hypothesis,” which is the idea that students learn better when instruction is provided in a format that matches their learning style. Their conclusion is a hard pill to swallow. “The contrast between the enormous popularity of the learning-styles approach within education and the lack of credible evidence for its utility is, in our opinion, striking and disturbing,” the researchers wrote. “If classfication of students’ learning styles has practical utility, it remains to be demonstrated.”
2009: https://www.psychologicalscience.org/news/releases/learning-...
2022: https://fee.org/articles/learning-styles-don-t-actually-exis...
APA goes so far as to say (2019) believing in learning styles is detrimental:
https://www.apa.org/news/press/releases/2019/05/learning-sty...
What training mechanism or model architecture provides the glue to go from human text to images?
Don't you need to have millions of really descriptively labelled images?
Slightly longer answer for older text to image models you teach them how to encode images and text into the same latent space. Then you simply do a conversion, take a text input, put it into latent space and then extract the image that latent space represents.
As for the image model, wow...
Kinda wild to think they haven't fixed it yet. On mobile you cannot zoom in to view their images.
Maybe the site is vibe coded and nobody at Qwen actually knows how to fix it..
Another astonishing UX fail was (still is) on Xiaomi's page[1] - where they try, and successfully fail, to showcase a video editor implemented by their model.
They embed a screen capture hosted on a Chinese hosting site BiliBili, too bad the video is 360p pixel soup.
To be able to change the resolution you are required to:
- know to use desktop view in the browser to make the resolution button show
- know Chinese to understand which button is "resolution" and that you need to login to switch resolution
- have and account with the video hoster or be willing to register
I was curious, but not that curious...
[1] https://mimo.xiaomi.com/mimo-v2-5-pro#AFull-FeaturedVideoEdi...
I see lots of useful tools made related to translation and code generation, but image generation seems to be primarily used to deceive, harass, or embelish to the point of questioning what the point of a photo is anymore anyway?
But I understand the jaded perspective. I guess the idea of ‘deepfakes’ didn’t give AI image gen a great reputational start.
And yet the Korean text is not accurate... [1]
[1] E.g. "드레스 컬렉션 dress collection" has vowels ㅔ mixed with ㅐ, "초웜한" should be "초월한 exceeding", "신키한" should be "실키한 silky", "디자언되다" should be "디자인되다 have been designed", "로얼" should be "로열 royal", and so on.
Image token pricing has been fairly steady while text token prices fall, yet image model release discussion seems to be more focused on how beautiful the women the model generates are versus any sort of substantive discussion.
going to a fancy restaurant coz of 'you can take good pics' - dead - a.i can recreate that cheaper.
which means for a certain demographic - dating apps are dead too - since those were largely based on swiping photos.
the premium of in-person / small intimate events has gone up. likewise meeting in person, or doing things with a person live.
this also means imperfection has gone up in value (imperfection is a human quality).
I hope these stakeholders have good enough layers.
Try asking it for a plot of Polish GDP growth over the past 20 years. It's slop.
> Especially text rendering
That's true though. I still got some completely fried letters in headings.
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we live in a world where the norm is to use filters on pictures of your own face to lie about how you look, imagine thinking than people actually care about truthness
I think they actually care about "truthness" when it comes to how others will perceive them. You might filter your face for an online photo.
However, you're not going to want to look at yourself through your selfie camera with a filter that hides your imperfections when you're checking to see if something is stuck in your teeth on a date, don't you think?
There's nuance. People will fudge the truth to be perceived better, but don't want to be lied to when gathering data about how to be perceived better.
No, but you definitely use it in all the pictures you put on dating apps
I wonder what kind of capabilities those might be?
There hasn't been "truth in advertising" for many, many years. The only thing that has changed recently is that you don't even have to hide most of the lies.
It's infuriating the amount of effort people will expend to claim that what was achieved in the past is literally impossible to do now. It's pervasive, especially from allegedly-smart people like software engineers.
The myth of impossibility remains, because we can't imagine what it means to forever occupy those places, even when others rise past them.
I find it easy now!
Regardless, I'd rather see real clothing on a real person when it comes to my purchasing decisions. I buy a lot of vintage clothes online and I've noticed a dramatic uptick in AI images of models wearing the clothes. I've never once bought from those sellers because it feels disingenuous. Sometimes they have fake runways which is actual false advertising because it makes the item appear more expensive than it really is. I've also noticed that the AI models' body types are always thin even if the item is a L or XL. Needless to say, the AI isn't showing me what an XL looks like on a small model; it's showing what a small model would look like if the item fit perfectly.
[1] https://www.primermagazine.com/wp-content/uploads/2011/02/St...
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And at this level it's barely any different than an architectural render, more for "how could this look" rather than "how will this look"
If marketing had to be honest, an entirely different set of products would likely be the most popular. I don’t think that’s a good thing by any means, just that the problem hasn’t really changed much beyond more focused targeting, which has always been a goal of marketing anyway.
It’s hard to convince someone who isn’t interested to buy something which is why tech ads sell on tech channels and car ads sell on car channels. Now you get to star in your very own clothes ads…for yourself…targeting you…
I suspect companies drool for that prospect because you are selling it to yourself with only some nice gentle nudging. That is the grail of marketing; that you don’t even realize you are in the midst of being marketed to.
who made qwen stefani's dress
spiderman into the spider verse did qwen meet Peter
qwen stacey porn
do blake shelton and qwen stafani have children togetherIf you look at past snapshots at archive.org, you notice that the meta keywords are growing like an append-only list, which means it's probably part of some messed up seo pipeline. The other clue is that it's stuffing the meta keywords which apparently only Yandex uses as a search signal[0].
The list has 3882 entries. A lot of them are clustered and look like auto-complete results. But a bunch of them look like hyper-specific, misspelled search results (e.g. "145 gwen rd cheshire ct"). Google's webmaster tools doesn't provide distinct queries like that, but yandex's does[1].
My best guess of what's happening is that Qwen is monitoring it's search queries in Yandex, dumping that list into a serp service that scrapes yandex's autocomplete suggestions, and then taking that list and dumping it into their meta keywords.
It explains the urls in the list (ppls using search engines like address bars), the seeming fixation around certain topics (which usually starts with a misspelling), and the random one-off queries.
0: https://yandex.com/support/webmaster/en/controlling-robot/me...
1: https://yandex.com/support/webmaster/en/service/popular-quer...
Yes it does
Anyways your theory is wrong because they don't rank for things like "ChatGPT login". It's just a keyword list from auto complete data not their own ranking data
(i.e. the porn references)
ben 10 four arms porn qwen
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It apparently adds common search terms that contain words like "qwen". This evidently includes possibly mistyped searches for "gwen" or "ben" in a NSFW context.
Maybe someone knows more about how such SEO tools work, and where they pull the data from.
Am i gregnant?
That said it's possible search engines in China or other countries might use it, but it's very easy to game so it doesn't really make sense
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So not at all then as Apple Pie is a traditional English desert. :P
It also seems to have an obsession with this celebrity, based on how many times ctrl-f for "stefani" turns up a result.
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[whynotboth.gif]
Do you want to know more?
[ ] Yes [x] no
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erm... what?
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[1] https://www.globaltimes.cn/page/202102/1215710.shtml
[2] https://xcancel.com/thouse_opinions/status/13616465112479539...
source: work at a photograph start, even training on raw images things get tinted, it is an uphill battle
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Any suggestions for the best open, non-opinionated model?
Edit: just to test myself I asked Nano Banana 2 to generate “an undergraduate infographic poster about how atoms work” - and the result was something right out of a middle-school science textbook and very Bohr…
There's definitely more dogfooding that needs to be done. And id argue that if your purpose is truly to learn or to teach, the process of describing that image will do wonders for retention.
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There are ML models that do the reverse and output image to text, which assist quite a lot.
The better the text represents the unique thing in the photo, the better the model understands what that text means.
For example, Google's Imagen 3 usually looked a lot less fake than the newer Imagen 4, but the latter still scored higher on most benchmarks because it made fewer mistakes and had better prompt following capabilities.
A similar thing happened with Dalle-E 2 and Dell-E 3: The new model was better but also more fake looking.
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When I want to emphasize something, I tend to repeat it
Ironically they have extremely limited influence on how the larger world moves: normal people won't meaningfully change their habits around eating good food or meeting up with each other just because AI can generate a picture of either.
It included the table verbatim and even managed to hallucinate a reasonable heading for it, but then the graph doesn't even manage to align the data points with the time axis, leading to an unfortunate collision in the middle.
I guess you should use a traditional graphing library for your presentation slides for now.
They can't.
(See kids, it is possible to fight memes/racism with memes! And well... yeah, this really is racist.)
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This is pathologically outside scope. I don't think I have ever seen somebody threaten somebody else on hn before. The 'don't make me do it to you' abuser trope is next level.
Apart from that, I made no judgement about porn in general, just about porn tags in Chinese backed AI websites.
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If you're wanting to learn then you won't have the expertise to craft a prompt that has the correct details or to spot when the model makes a mistake in its output.
If you're in a teaching position then you won't have anything to learn.