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Generative and diffusion AI are coming to 2D and 3D

January 13th, 2023


Generative and diffusion AI are coming to 2D and 3D

Generative and diffusion AI are set to revolutionize the field of computer graphics with the capacity to radically transform both 2D and 3D design.

In terms of 2D design, generative AI has already shown that it can generate images that are amazingly lifelike, outperforming what humans can do in a matter of years. This technology has the ability to significantly speed up the design process, enabling creators to easily generate a large number of variations and apply innovative techniques to produce design and art.

It won't be a binary shift, but a gradual merging of new tools and methods to create 2D and 3D content. Therefore, it's important to understand that while AI may be able to generate highly realistic designs, it is still the human designer who must create the content and ideas. Designers will be able to create highly unique and exponentially more content.

How will AI improve 3D? Already, there are prototypes that can generate NERF 3D models from collections of generated 2D images. AI methods are rapidly improving, for example Stability.ai released v2 after 3.5 months of its first Stable Diffusion release. 3D design is exponentially harder than 2D design because of the 3rd dimension, but we can expect that in 5-7 years generative AI will be able to generate high detail 3D models.

Many groundbreaking applications will be created. For example, with AI, designers will soon be able to in-paint or out-paint smoothly, blending generated content into their 3D scenes. UV mapping and creating materials will also become a thing of the past, as designers will only need to create the geometry and then describe how to texture their object.

AI is simply a tool to assist and enhance the work of the designer, not to replace them. Designers should start learning generative and diffusion AI to stay competitive in the field. If they master the AI toolset and methods faster than others, they will have a significant advantage in the industry.

One big issue is designers' data being used to train these models. All designers should be asked before their data is used for training. Frameworks should be developed for attributing designers for their work. This would introduce new opportunities for designers, allowing them to monetize and sell their styles.

Ultimately, the use of generative and diffusion AI represents a paradigm shift in the way we approach computer graphics design. Rather than working with the fundamentals of design, we will be able to focus more on the conceptual level, combining and fusing objects into a virtual existence. It's like finding the best virtual world to work in and creating the most beautiful and realistic designs.

CGTrader is staying up to date with the latest developments in the field of AI and is planning to do further research to write more informative articles about how AI can be integrated into its offerings to improve our 3D modeling processes, our features, and overall experience for our users. We are always looking for ways to stay ahead of the curve and embrace new technological advances, and AI is no exception. By closely following the AI movement and its developments, we can ensure that we will be well informed and equipped to provide our community with the best possible products and services, always endorsing the creations of our designers.

Comments

Tell us what you think!

iterateCGI wrote
iterateCGI
Glad to hear the team is looking closely at what is going on in the AI field and looking forward to more news from this. It has indeed great potential to relieve technical friction in the creation process of 3D content. Also glad to hear there is a clear stance from CGtrader that art/data should not be taken unconsented to train AI models, and that there instead should be some framework to make it possible to license out specifically created data for learning AI’s new tricks. This stance restores a bit of my fate towards onlooking the future, because as things are going now, it looks like the first to steal the data is the winner, and that current copyright law is not equipped to answer this. Hopefully someone is fast to build a user friendly infrastructure around this so that we can avoid a Napster event for visual arts, and all enjoy/benefit from these next level technologies.
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