151–160 of 187 posts
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I don't think this analogy holds up.
If someone's copyrighted material was used to train a model, what analogy would you use?
It's surprising how poorly labeled these images are; who is curating this collection? Can't they crowd-source a proper labeling project - I wonder how much better things like Stable Diffusion would be if its training would include correct, complete labels for the images. I'm sure lots of folks would willingly spend a few minutes here and there to aid with the labeling if it means they get to enjoy the model for free.
You're right. I just searched for "milk" and was not expecting the NSFW results...
There is a lot of porn there
On the plus side, i appear to have not (yet) been trained. I can consider myself safe from the AI. For now.
I'm one of the people building this. Hi HN, AMA :)
It's surprising how poorly labeled these images are; who is curating this collection? Can't they crowd-source a proper labeling project - I wonder how much better things like Stable Diffusion would be if its training would include correct, complete labels for the images. I'm sure lots of folks would willingly spend a few minutes here and there to aid with the labeling if it means they get to enjoy the model for free.
I'm very surprised how primitive it is. I put in a few names of uncommon technical objects and some of its images were close and others so far off as to be unrecognizable or totally unrelated/useless.
What it needs is a quick/instant feedback system that allows humans to rate an image against the query word. A rating scale of say 1 to 5 where 1 is an identical match, 2 a close match, 3 marginal, 4 ambiguous, 5 wrong/totally unrelated. If in place then likely thousands would make an effort to optimize the matching.
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labeling 6 billions pictures, even at 10 labels per second would take 20 years, so I guess nobody
Could be done by reCAPTCHA, although might be more difficult to classify the results (whether a user passed the test) compared to their usual challenges.
The ESP game[1] paired two random people looking at the same image while a timer ticked down. The players had to enter labels that described the image, and if both players applied the same label, their score increased, and the label was associated more strongly with that image.
Well-known labels for an image were excluded after a while, so you had to guess less and less obvious labels in order to score as time went by. Once in a while the system would also assign test images with known labels to prevent cheating.
Apparently a lot of people played it because it was fun, so there wasn't even the need to pay them for labeling the dataset...
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This is Laion-5B, you can read more about it here: https://laion.ai/blog/laion-5b/ Imagen and Stable-Diffusion both used subsets of this full 5.8B image set.
Is Imagen actually trained on a subset of Laion-5B and nothing else? I've heard they used huge internal data sets.
> While a subset of our training data was filtered to removed noise and undesirable content, such as pornographic imagery and toxic language, we also utilized LAION-400M dataset which is known to contain a wide range of inappropriate content including pornographic imagery, racist slurs, and harmful social stereotypes.
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The same artists who have been pitching a fit about how the robots are coming for their jobs? Pretty sure they are trying to figure out a way their art can’t be used to train an AI and won’t be willingly participating in making it easier.
I’m skeptical that Al will replace artists. The existence of computer chess and go, though superior in every way, has not killed interest in human competition. I see no reason we couldn’t have the same thing happen with art: people see AI art as a novelty and something worth studying but otherwise preferring human art for its relevance to the human condition.
This is not true of the artist market. While yes, many artists get into it for the fun/satisfaction of producing their own artworks, the reason that they can remain in it long term is that there are other entities in paying for the results of their work. See: game studios, film studios, etc. Before AI, the only way to get the assets for these various projects produced was by paying artists/experts for their work. Now, the production of those building blocks can be automated.