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In order to power the next generation of generative AI, Stability AI looks to the AWS cloud

One of the most exciting developments in artificial intelligence frameworks and models for 2022 is the proliferation of new methods for generating content such as photos and text, which can be used by both individuals and businesses.

Stability AI, which received $101 million in October, is one company developing generative AI solutions. Stability AI creates free and public base models, such as the widely used Stable Diffusion model. Using a text prompt defining the intended picture, anybody may make artistic images using Stable Diffusion. Training and inferring results from a generative AI model like Stable Diffusion takes a lot of processing power.

Stability AI made the official announcement during this week’s AWS re:Invent conference in Las Vegas that AWS will be its go-to cloud platform for developing generative AI tools. Turns out Stability AI has some experience with AWS, having been utilising it before.

During a discussion at re:Invent 2022, Stability AI founder and CEO Emad Mostaque said, “Last week, we published Stable Diffusion 2.0, developed at Stability AI, which is another step forward to clean our dataset with higher quality, less bias, and quicker [speeds].” “AWS was where we did all of the development.”

Integrating generative AI into the cloud is a natural progression

The public cloud is used by many generative AI providers, not only Stability AI, for model foundation development.

OpenAI, the group responsible for the GPT-3 big language model for text and the DALL-E for picture production, already uses the public cloud. Nonetheless, OpenAI has depended mostly on Microsoft Azure to aid in the development and distribution of its capabilities, rather than AWS.

OpenAI’s dependence on Microsoft Azure goes beyond mere technical requirements. Furthermore, there is a monetary reward for doing so. Microsoft has put $1 billion into OpenAI this year to advance AI-related Azure technology.

Google’s Imagen text-to-image endeavour is only one of several generative AI projects employing Google Cloud.

The latest iteration of Stable Diffusion utilises cloud computing to produce artificially intelligent pictures more quickly.

The process of constructing Stable Diffusion includes a wide variety of actions and parts. Essentially, it all comes down to information.

According to Mostaque, Stable Diffusion took in 100,000 GB of photos and labels and reduced them to 2 GB of data for the AI model using data compression.

The process of constructing Stable Diffusion includes a wide variety of actions and parts. Essentially, it all comes down to information.

According to Mostaque, Stable Diffusion took in 100,000 GB of photos and labels and reduced them to 2 GB of data for the AI model using data compression.

Stable Diffusion 2.0 gives users more say over the generation of high-resolution photographs. Additionally, Stable Diffusion 2.0 is significantly quicker than its predecessor. Mostaque said that it took the first version around 5.6 seconds to produce a picture. As of right now, that time has been reduced to 0.9 seconds. He predicted that the technology will continue to advance toward producing high-resolution photos in real time.

Amazon Web Services’ SageMaker for creating generative AI

Now, Stability AI is using the AWS SageMaker toolkit to expand and enhance its foundational models, including Stable Diffusion.

According to Mostaque, the EleutherAI community (which Stability backs) has developed a popular language model foundation called GPT Neo X. SageMaker is being trained on a cluster of one thousand Nvidia A100 GPUs by Stability in order to speed up model execution.