The news: Nvidia is entering the text-to-image free-for-all with its eDiff-I artificial intelligence generator in an emerging market for Big Tech conglomerates, per VentureBeat.
Cambrian explosion of AI art generators: One of the biggest tech stories of 2022 is how generative AI has quickly evolved from a fringe application into advanced image generation thanks to the likes of OpenAI’s DALL-E 2, Google’s Imagen, Midjourney, and Stable Diffusion.
How it works: These tools use a vast collection of data image supersets to generate AI-created images, graphics, photos, and even short videos based on a string of text descriptions.
AI-generated art has taken various industries by storm, but the caveat is that this is very nascent technology that could be a legal and ethical minefield.
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Nvidia is combining its expertise in graphics and imaging with eDiff-I’s text-to-image synthesis, which its developers say provides “an instant style transfer and intuitive painting-with-words capabilities.”
- eDiff-I’s image synthesis pipeline is a combination of three diffusion models — a base model that can synthesize samples of 64 x 64 resolution and two super-resolution stacks that can upsample the images progressively to 256 x 256 and 1024 x 1024 resolution.
- “It definitely adds to the complexity of training the model, but doesn’t significantly increase computational complexity in production use,” Scott Stephenson, CEO at Deepgram, told VentureBeat.
Nvidia’s competitive advantage: Most competing AI art generators such as DALL-E 2 and Imagen use only a single encoder such as CLIP or T5. eDiff-I’s architecture uses both encoders in the same model.
- This could result in larger AI-generated images that use less processing power. eDiff-I also produces higher-resolution images thanks to an advanced denoising algorithm.
- Nvidia’s tight integration of hardware, software, apps like Canvas, and plugins for industry tools like Adobe’s Photoshop, gives it a leg up on the competition.
- The involvement of a hardware vendor like Nvidia could spur competition from the likes of Samsung, Qualcomm, and Intel, further propelling innovation in the space.
Too fast to regulate: As one of the success stories in technology, generative AI has seen the backing of Big Tech companies like Microsoft, Google, and Amazon.
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Generative AI is not as capital intensive to develop compared to hardware and software—it can quickly be improved even during a recession.
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The sudden ubiquity of the technology can overwhelm regulators studying the ethics and legality of AI-created art. For example, regulators in the UK are struggling to determine how copyright law will address AI art.
Our take: Nvidia’s entry into the generative AI art segment qualifies it as a quickly emerging technology with real-world implications.
- Unlike nebulous metaverse-related technologies that seem years away from fruition, expect competition to intensify as companies find myriad ways to productize AI.