Stability AI Enhances Amazon Bedrock with Advanced Text-to-Image Models

Stability AI launches three most advanced text-to-image models on Amazon Bedrock - SiliconANGLE

Stability AI launches three most advanced text-to-image models on Amazon Bedrock Generative artificial intelligence startup Stability AI Ltd. announced today that three of its most advanced text-to-image AI models are now available on Amazon Web Services Inc.'s cloud infrastructure through Amazon Bedrock. The company said that it is bringing Stable Image Ultra, Stable Diffusion 3 Large and Stable Image Core to Amazon's cloud so that businesses will be able to train, fine-tune and deploy them at scale more easily. Amazon Bedrock is a fully managed service that permits developers to build generative AI applications through access to a variety of pretrained foundation models from leading AI companies. Aside from access to models, the service also enables users to fine-tune models, integrate and deploy generative AI solutions into apps, and experiment securely and safely with models. "Generative AI is poised to be the most transformational technology of our time, and we believe our collaboration with Stability AI will further improve our customers' experiences by providing them with access to best-in-class AI models," said Baskar Sridharan, vice president of AI and infrastructure at AWS. Stability AI's offered models each have their own strengths and unique benefits for customers and are designed for particular use cases. Stable Image Ultra is best for photorealistic, large-scale outputs, it generates crisp, clear images with few artifacts, making it suitable for professional applications that need ultra-realistic imagery. Examples could include luxury brands looking to render picture-perfect models of handbags and clothing to model for print or online ads, since they need to look stunning and visually appealing for an audience that will view them in vivid color. Stable Diffusion 3 Large produces high-quality creative assets quickly and with little effort, making it the choice for high-volume use. The go-to example is for marketing campaigns where producing numerous images and digital assets would be needed, especially for different regions and audiences that require text and other variations. The model also has a place working alongside video game production teams to help create character concepts, environment textures and item models to help speed up the development process. Stable Image Core provides fast and affordable image generation from text prompts for rapid content generation at scale. It's a text-to-image model optimized for speed. That makes the model the best choice for operations where images are needed fast and cheap, such as an online retailer that is constantly receiving new stock and needs to list items as quickly as possible to keep a catalog up to date, but doesn't need ultra-realistic quality.

Stability AI adds its top 3 text-to-image models to Amazon Bedrock

Stability AI has added three new image generators to Amazon Bedrock, a platform for building apps. Stable Image Ultra, Stable Diffusion 3 Large, and Stable Image Core are all now live on the service. The trio are Stability's "top three text-to-image models," the company said. By adding them to Bedrock, the London startup hopes to reach new audiences -- and customers. Scott Trowbridge, VP of business development at Stability, told TNW that the move will "drive enterprise adoption of our models." Amazon, meanwhile, receives another boost to Bedrock. Launched last year, Bedrock provides a fully-managed service for developing generative AI apps. Harnessing the AWS cloud infrastructure, the platform promises simple and scalable deployment. With Stability's new models on board, Bedrock can now also offer enhanced visual outputs. Baskar Sridharan, VP of AI and Infrastructure at AWS, has high hopes for the collaboration. "It unlocks an exciting opportunity for [customers] to quickly, securely, and responsibly innovate with generative AI," he said. Each of the three models has specific strengths. Stable Image Ultra is ideal for photorealistic, large-scale output. SD3 Large is better for high-quality, high-quantity creative assets, while Stable Image Core combines speed and affordability. Stability expects them to gain traction in various industries, from media and marketing to retail and game development. Sridharan adds a bolder prediction. "Generative AI is poised to be the most transformational technology of our time," he said.

Stability AI brings new Stable Diffusion models to Amazon Bedrock

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Stability AI has been struggling of late trying to find its business footing in an increasingly competitive market for text-to-image generative AI tools. Today the company announced a significantly expanded effort with Amazon Web Services (AWS) that will see three text-to-image generative AI models come to the Amazon Bedrock service. Previously Stability AI had just made its older, though still very capable SDXL model available on Amazon Bedrock. Stability AI is now bringing a trifecta of its most sophisticated text-to-image models to Amazon Bedrock including Stable Image Ultra, Stable Diffusion 3 Large and Stable Image Core. Each model brings its own set of strengths to the table, catering to a wide range of use cases from ultra-realistic imagery to high-volume asset generation. For enterprise users, the promise is the option of getting the right model for a given task. The new Stability AI models will join a growing list of models that Amazon Bedrock provides. AWS already makes multiple image models available on Amazon Bedrock including its own Titan model. When Stability AI got its start, the only model was Stable Diffusion. That has changed in recent years and especially this year as multiple variations of the company's Stable Diffusion model have emerged. Functionally the differences are much like how other generative AI models have evolved with different sizes. Larger models tend to be more powerful, as well as require more resources and cost than smaller models. Looking at the lineup, Stable Diffusion 3.0 was first revealed as a preview in February of this year. Full availability occurred in April via an API. In June, the company announced its Stable Diffusion Medium model, at the same time rebranding the original sized model as Stable Diffusion Large. At the same time, Stability AI quietly released Stable Diffusion Ultra via API though no formal announcement was made. "Stable Image Ultra is our flagship model, blending the power of the SD3 Large with advanced workflows to deliver the highest quality images," Scott Trowbridge, VP of business development at Stability AI told VentureBeat. "This premium model is designed for industries that require unparalleled visual fidelity, such as marketing, advertising and architecture." Stable Image Core on the other hand is based on SDXL. The goal of the core model is to provide a faster and more affordable model. Stability AI is not making Stable Diffusion 3 Medium available, at least not initially, on Amazon Bedrock. "SD3 Medium is a two billion parameter model, making it perfect for running on consumer PCs and laptops as well as enterprise-tier GPUs," Trowbridge said. "The model is available for self-hosting and via our API." Stability AI has been trying to grow its go-to-market options over the last 12 months. In December 2023, the company introduced a new membership model, as a way to create some form of commercial business and revenue. The company also has its Stable Assistant chatbot that provides access to models. Stability AI charges users based on usage, via the API or Stable Assistant. Stability AI has also undergone multiple operational challenges this year. In March, the company's founder and CEO Emad Mostaque resigned. He was finally replaced in June, with new CEO Prem Akkaraju alongside a new infusion of capital. It's also not entirely clear, at least as of today, how the cost of running the models on Amazon Bedrock will compare with the other methods for running the Stability AI models. Stability AI did not directly respond to a question from VentureBeat about how the costs compare. In any event, having more paths to market and usage of its models represents more potential overall revenue that Stability AI can grow. The Amazon Bedrock deal is likely not the only one Stability AI will make with a cloud provider. "Stability AI is always considering ways to expand accessibility to our models, including via cloud service providers, system integrators and other model service providers," Trowbridge said.

Stability AI's text-to-image models arrive in the AWS ecosystem

This is a toolbox story. AWS Bedrock is an AI toolbox, and it's getting loaded up with a few new power tools from Stability AI. Let's talk about the toolbox first, and then we'll look at the new power tools developers can reach for when building applications. Also: 6 digital twin building blocks businesses need - and how AI fits in TL;DR: Developers can now call on text-to-image features from within their Bedrock-powered apps. That means they can easily incorporate AI-generated images within their own code. AWS (Amazon Web Services) is Amazon's powerful cloud service. The company offers a wide range of services and capabilities within the giant AWS umbrella. The key thing to know is that all of the services are on-demand and scalable. That means you don't have to build a data center and forklift in a pile of server racks before you can start deploying applications. In the context of our story, if you want to incorporate powerful AI capabilities in your code, you don't have to develop those capabilities from scratch, train the AI large language models (LLMs), or even figure out what server configurations you'll need. All you need to do is enter your credit card digits, read some documentation, and start writing code. I built my first Internet company back before there were cloud services. Trust me when I say that something like AWS is a vast and amazing game changer compared to building out server infrastructure on your own, especially for founders working on a startup's budget. This is powerful for developers because they don't have to implement those models. They just have to learn the protocols for talking to them and then use them, paying as they go. But there's another huge win with a service like this: you can try different models and see what works best for your application. If you had to build out your own infrastructure and then set up and configure each model, you'd probably just pick one and live with it because the work to switch is just too time-consuming and stressful. But with Bedrock, you just switch a few parameters, and you're off to the races and testing different foundation models. It's easy and fast and gives you a way to compare and contrast AI solutions in action, rather than just guessing from what's on a spec list. This announcement is about Stability AI adding three new power tools to the toolbox that is AWS Bedrock. Each of these models takes a text prompt and produces images, but they differ in terms of overall capabilities. You can see how the tool analogy fits here. When you open your toolbox, you're able to choose which power tool fits your project. Sometimes, you want a hammer drill; other times, you want a power screwdriver. Likewise, sometimes you want a graphics tool that generates an insane level of detail. Other times, you just want fairly cheap and fast. Also: 6 digital twin building blocks businesses need - and how AI fits in By adding all three models to Bedrock, Amazon and Stability AI are giving developers those choices at any time and anywhere they need them. Let's use one example. My wife runs an e-commerce hobby-related company. Every month, she posts a theme on social media that inspires her followers to create a project. Back before good text-to-image generative AI, I created an image for her based on some brand assets using Photoshop. It took me a few hours, and the images were never all that great. Also: How I used ChatGPT and AI art tools to launch my Etsy business fast But then I got a Midjourney subscription. Now, each month, she gives me the theme, and I write a quick Midjourney prompt. Then, she chooses from four or more images for the one that best fits the theme. Instead of hours, it takes me minutes. And instead of looking like I pasted up clipart, each theme image is ideal in how it represents her business and theme. She then takes those images, copies and pastes them, and posts them on social media and her site. But what if we used Bedrock with Stable Diffusion? We could add a feature to her e-commerce dashboard for the theme of the month right from within the dashboard. She could just type in a prompt, get back a few samples, and click to have those images posted to her site. The process would all be integrated within her dashboard workflow. Doing that integration wouldn't require a ton of AI theory and practice. All it would require would be a series of API calls from her current dashboard to Bedrock and handling the image assets that came back from those calls. The AI task could be integrated right into the rest of her very vertical application, specifically tuned to her business. Also: 6 digital twin building blocks businesses need - and how AI fits in So, that's the potential. Think about it for media and entertainment, where marketers could quickly produce marketing assets; retail, where managers could quickly produce photorealistic product visuals; advertising, where very high-end images with great detail need to be created fairly quickly and easily; and in-game design, where game designers could build a full library of assets using these tools. Of course, some would argue this eliminates artists and takes jobs. Without a doubt, that will be the case in some applications. But the opposite is also true. My wife's small business would never hire a dedicated artist. Instead, I put on my art director hat (one of the many roles I wore as a small company founder back in the day) and produced fairly mediocre images. The AI just simply upped our game and saved us time at the same time.