Am I missing something? The AI video examples on this just look like non-temporally stable image gen frames with the wobbly/morphy look. I don't think the comparison is there to what Luma shipped.
The problem for me is that they took our design, styles, fonts, colors, gradients, and name for a very similar product and shipped it with quite an impressive team that is well-funded by A16z.
Their product is much slicker than what we are doing with Pollinations, of course. We are a few people working on it in our spare time.
It would have just been nice to get a kind of mention or have someone reach out. I'm all for getting inspired and copying.
The current state of the Pollinations site is very different. The Luma Labs page looks like what Pollinations had on its site about nine months ago when the Dream Machine was a more significant focus of ours.
I could get into the weeds and show side-by-side screenshots but it seems like the wrong direction to invest time. The person who did our design didn't think it was very funny.
In my opinion Gen AI startups should be extremely careful in crediting because the whole copyright thing is already such a hot potato with artists and designers.
If it's any consolation, the Luma website is so laggy and poorly-designed that I don't think I could recommend their service simply as a matter of principle. The Pollinations site is much more static and doesn't have any distracting or finicky on-scroll effects, which at least makes it enjoyable to read.
We're giving free access to a model that other people trained on other people's data. The code for all improvements or tweaks is accessible in public repositories. From a copyright perspective, I think one can make a fair use argument.
Nevertheless, it would be great to credit artists and designers whose work was used for training. Practically, it's not easy because I think one would have to credit humanity.
Every image in the training data influenced the model's output to a certain degree, so one would have to credit every person who uploaded an image to a public place.
One could argue that a model should not be trained on public data in the first place because we can't fairly credit all individuals who contributed to it.
