With better response to details and text, DALL-E 3 hopes to make prompt engineering obsolete.

On Wednesday, OpenAI announced DALL-E 3, the latest version of its AI image synthesis model that features full integration with ChatGPT. DALL-E 3 renders images by closely following complex descriptions and handling in-image text generation (such as labels and signs), which challenged earlier models. Currently in research preview, it will be available to ChatGPT Plus and Enterprise customers in early October.

Like its predecessor, DALLE-3 is a text-to-image generator that creates novel images based on written descriptions called prompts. Although OpenAI released no technical details about DALL-E 3, the AI model at the heart of previous versions of DALL-E was trained on millions of images created by human artists and photographers, some of them licensed from stock websites like Shutterstock. It’s likely DALL-E 3 follows this same formula, but with new training techniques and more computational training time.

Judging by the samples provided by OpenAI on its promotional blog, DALL-E 3 appears to be a radically more capable image synthesis model than anything else available in terms of following prompts. While OpenAI’s examples have been cherry-picked for their effectiveness, they appear to follow the prompt instructions faithfully and convincingly render objects with minimal deformations. Compared to DALL-E 2, OpenAI says that DALL-E 3 refines small details like hands more effectively, creating engaging images by default with “no hacks or prompt engineering required.”

  • lloram239@feddit.deEnglish
    1·
    1 year ago

    And you quickly realize that when you generate things from similar prompts over and over the model gives you the same results but slightly adjusted.

    That’s quite true, however it’s worth keeping in mind that this is largely not due to a limit in the model itself, but a limit how that model interfaces with the human. Text just isn’t very good to get specific results, especially not when it lacks the incremental refinement that you can do in ChatGPT with follow up prompts.

    On the other side if I take StableDiffusion with ControlNet, instead of just a text prompt, I can generate far more specific results, as I can feed other images and sketches into the generation.

    but I think once the new toy factor wears off people will realize they aren’t as good as they seem.

    Quite the opposite, there is a ton of hidden potential still left to uncover. We have barely even started to train them on video or 3D data, integration of image models with newer language models is also a work in progress and integration into old-school image manipulation tools has just began as well.

    Worth keeping in mind that Dalle-1 isn’t even three years old. We are basically still in the Atari2600 days of image generation.

    Meanwhile Dalle-3 comes along and can produce this level of quality with a complete generic prompt: “A fan-art of Guardians of the Galaxy Vol. 3” on the first try.

    I think the next “revolution” in art is going to be having human art as a selling point

    The big problem for artists is that AI art drives the value of art down to zero. It’ll be hard to convince anybody to pay hundred of dollars for something when AI can produce something similar in 30sec for free. Worse yet, AI can take any existing image and remix it. The whole idea of a singular static images feels quite restrictive once you played around with AI art for a while, as everything is just a few clicks away from being something different.

    I think the idea of AI art as just generators for stock images doesn’t capture the magnitude of the changes that are coming. We are straight up heading into Holodeck territory where you tell the computer what you want and you get it. The AI generators won’t be a tool for the artists, but go right to the users. There won’t be an static image that comes out the other end, the AI will be the medium of media consumption. Just like people today can flip through TikTok, future people will flip through a AI generated stream of content custom made for them.

    Wanna play some 2D game with snow and ice? Tell the computer, a couple seconds waiting, and boom here it is. First try. Want lava instead? Done. How about an N64 game? How do you compete with that as a human when AI can pull that out of thin air in seconds?

    • MysticKetchup@lemmy.worldEnglish
      1·
      1 year ago

      Nah that Guardians of the Galaxy art is exactly what I’m talking about. It makes basic mistakes even a child could point out and looks more long a knockoff. And refining it is just rolling the dice to get a better result, whereas an artist you can actually give feedback they can understand.

      The game assets look a little better, but if you look carefully you’ll notice that they don’t tile correctly. It’s 90% there but the last 10% is the hardest part and it’s important especially for large projects and not just single static images. Not too mention they look generic as fuck, you’re not going to get the next Hollow Knight or Darkest Dungeon with an amazing original style from AI, you’re only going to get existing styles mashed together. The more specific the vision for the artstyle the harder it will be to generate it.

      Also the idea of a Tiktok feed of AI generated content is exactly why I hate AI art. Sure, go ahead and use it to help existing artists generate cheap assets that would otherwise be random brush strokes. But replacing them? The idea that AI generated slop will have anything close to the quality and meaning of even cheap art is ridiculous. Why would anyone want that when they could have actual art made by real people, more of which exists today than anyone could go through in their entire life?