#StableDiffusion3

[govindhtech]

Stable Image Ultra, SD3 Large, Core On Amazon Bedrock

Stable Image Ultra, Stable Diffusion 3 Large(SD3 Large), and Stable Image Core are the three new text-to-image models from Stability AI that you may use with Amazon Bedrock now. These models may be used to quickly create high-quality images for a variety of use cases across marketing, advertising, media, entertainment, retail, and more. They also notably increase performance in multi-subject prompts, image quality, and typography.

Stability AI in Amazon Bedrock

Utilizing Stability AI’s most sophisticated text-to-image models

Presenting the most recent text-to-image models from Stability AI

Three Points of Stability The most recent state-of-the-art text-to-image models powered by AI are now accessible in Amazon Bedrock, offering scalable, fast visual content production capabilities.

Stable Image Ultra

Provides the most exquisite, lifelike results, ideal for big format applications and professional print media. Stable Image Ultra is very good at reproducing realistic details.

Stable Diffusion 3 Large(SD3 Large)

Finds a happy medium between output quality and generation speed. Perfect for producing digital assets such as newsletters, websites, and marketing materials in large quantities and with excellent quality.

Stable Image Core

Designed to produce images quickly and affordably, this tool is excellent for quickly iterating over ideas when brainstorming. The next generation model, after Stable Diffusion XL, is called Stable Image Core.

Introducing Stability AI

Leading global provider of open source generative AI, Stability AI creates innovative AI models for language, audio, image, and code with low resource needs.

Advantages

Modern architectural design

SOTA open architecture with 6.6B parameter ensemble pipeline and 3.5B parameter base model stage for image production.

Cinematic photorealism

Native 1024×1024 image generation including excellent detail and cinematic photorealism.

Intricate arrangements

Refined to produce intricate compositions with only the most basic natural language cues.

Use cases

Marketing and promotion

Make countless marketing assets and customized ad campaigns.

Entertainment and media

Create countless creative resources and use pictures to spark ideas.

Metaverse and gaming

Make up new worlds, scenes, and characters.

Features of the Model

Realistic photography

Stable Image Ultra produces photos with outstanding lighting, color, and detail, allowing for both photorealistic and excellent results in a variety of styles.

Quick comprehension

Consistency Long and intricate prompts requiring spatial thinking, compositional parts, actions, and styles can be understood by AI models.

Fonts

Unprecedented text quality is achieved with Stable Image Ultra while less spelling, kerning, letter formation, and spacing mistakes are present. In this instance, SD3 Ultra can precisely create certain text, objects, and lighting conditions.

Superior Illustrations

High-quality paintings, illustrations, and other visuals can be produced with SD3 Large, guaranteeing precise and captivating images for a variety of publications.

Rendering of Products

Consistency AI models can be utilized to produce excellent concept art, product renderings, and eye-catching visuals for print and billboard advertisements.

Versions of the models

Stable Image Ultra

Improved photorealism and inventiveness are provided by Stable Image Ultra, which produces outstanding images with incredibly accurate 3D imagery that includes minute elements like hands, lighting, and textures. Because of its ability to produce photos with various subjects, the model is perfect for producing intricate sceneries.

Languages Spoken: English

Does Not Support Fine Tuning:

Media and entertainment, game development, retail, publishing, education and training, and marketing/advertising agencies are among the use cases that are supported.

Stable Diffusion 3 Large (SD3 Large)

Spelling, picture quality, and multi-subject prompt performance are all significantly enhanced by this model. With its 8 billion parameter ensemble pipeline, SD3 Large offers a revolutionary state-of-the-art architecture for image generation that offers never-before-seen quality, user-friendliness, and the capacity to produce intricate compositions with only rudimentary natural language prompting.

Languages Spoken: English

Does Not Support Fine Tuning:

Media and entertainment, game development, retail, publishing, education and training, and marketing/advertising agencies are among the use cases that are supported.

Stable Image Core

With this 2.6 billion parameter model, the flagship service that produces high-quality photographs in a variety of styles without the need for prompt engineering, you may create images quickly and economically. Improved scene layout, including item positioning, adaptability, and readability at various sizes and applications, are among the capabilities.

Languages Spoken: English

Does Not Support Fine Tuning:

Media and entertainment, game development, retail, publishing, education and training, and marketing/advertising agencies are among the use cases that are supported.

Stable Diffusion XL 1.0

The next generation of models is called Stable Image Core; the prior model was called SDXL.

Languages Spoken: English

No fine-tuning is supported.

Use cases that are supported include marketing and advertising, media and entertainment, gaming, and the metaverse.

These models tackle common challenges such as rendering realistic hands and faces, and they do a fantastic job of delivering images with amazing photorealism, outstanding detail, color, and lighting. Given complicated instructions involving composition, style, and spatial reasoning, the models can interpret them thanks to their advanced quick understanding.

A variety of application scenarios are covered by the three new Stability AI models in Amazon Bedrock:

Stable Image Ultra: Ideal for large format applications and professional print media, Stable Image Ultra generates photorealistic outputs of the highest caliber. In terms of portraying remarkable detail and realism, Stable Image Ultra shines.

Stable Diffusion 3 Large(SD3 Large): Balances generating speed and output quality with Stable Diffusion 3 Large(SD3 Large). perfect for producing digital products in large quantities and with excellent quality, such as newsletters, websites, and marketing collateral.

Stable Image Core: Ideal for quick and economical image development, this tool allows you to quickly refine concepts while brainstorming.

Because of their unique Diffusion Transformer architecture, which implements two separate sets of weights for image and text but allows information flow between the two modalities, Stable Image Ultra and Stable Diffusion 3 Large(SD3 Large) have improved text quality in generated images significantly over Stable Diffusion XL (SDXL). In particular, there are fewer spelling and typographical errors.

Some photos made using these models are shown here.

Stable Image Ultra – Prompt: photo, realistic, stormy sky, stormy seated woman in field watching kite fly, concept art, complicated, expertly composed.Image credit to AWS

Stable Diffusion 3 Large(SD3 Large) – Prompt: detailed, gloomy lighting, rainy and dark, neon signs, reflections on wet pavement, and a male investigator standing beneath a streetlamp in a noir city. The artwork is done in the style of a comic book.Image credit to AWS

Stable Image Core: An expertly rendered, high-quality, photorealistic 3D model of a white and orange sneaker floating in the center of the image.Image credit to AWS

Case studies utilizing Amazon Bedrock’s new Stability AI models

Text-to-image models have the ability to revolutionize a wide range of sectors and help marketing and advertising departments create high-quality pictures for campaigns, social media posts, and product mockups much more quickly. They can also greatly streamline creative workflows in these departments. Companies may react to market trends faster and launch new projects faster by speeding up the creative process. Further, by offering quick visual depictions of ideas, these models can improve brainstorming sessions and encourage more creativity.

Artificial intelligence-generated images can assist in producing customized marketing materials and a variety of product presentations at scale for e-commerce enterprises. These tools may generate wireframes and prototypes fast in the field of interface and user experience design, speeding up the iterative process of design. Employing text-to-image models can result in substantial cost reductions, enhanced efficiency, and a competitive advantage in visual communication across a range of company operations.

Things to consider

The three new Stability AI models Stable Image Ultra, Stable Diffusion 3 Large(SD3 Large), and Stable Image Core are now accessible in the US West (Oregon) AWS Region on Amazon Bedrock. Amazon Bedrock has expanded its range of solutions to enhance creativity and expedite content creation processes with this launch. To determine the charges for your use case, see the Amazon Bedrock pricing page.

Read more on govindhtech.com

[techtuv]

Stable Diffusion 3: AI's New Creative Peak

With the rapid transformation of the artificial intelligence world, it's evident that the struggle for dominance among tech giants leads to spurts of innovation. The newest milestone in AI has been achieved with the release of Stable Diffusion 3 by Stability AI. This new breed of image generation technology is poised to cement the presence of stable AI in a competitive market where dominant rivals, such as OpenAI's Dall-E and Google's recent forays into AI, are abundant. Stable Diffusion 3 boasts some great advances, providing better performance for multi-prompt handling and improved image quality.

Stability AI and OpenAI, technology firms at the forefront of innovation, continue to advance at a rapid pace, deepening our knowledge of generative AI. Generative AI represents systems such as Stable Diffusion and Dall-E that are capable of producing new content when prompted by the user. Suiting both creators and developers, these models are changing the way content is produced. Google, another key player, is also advancing in this area, as demonstrated by the Gemini project, which would further increase the competitive nature of the field.

As these advancements in generative AI continue to unfold, we can expect even more remarkable innovations that will shape the future of creative expression and content generation.

Click for details

[allof-tech]

Unleash your inner artist with Stable Diffusion 3! Generate stunning visuals from text descriptions. Early access now! Join the waitlist & explore:

[heartfullofpoetry]

A tribute to Exhuma. A tomb and a firefox. Created using StableDiffusion3.

[ollj-blog]

StableDiffusion3 has much better chances at correct Dragoon anatomy. CompfyUI is VERY easy to set up (windows installer)

[govindhtech]

Is TensorRT Acceleration Coming For Stable Diffusion 3

NVIDIA TensorRT

Thanks to NVIDIA RTX and GeForce RTX technology, the AI PC age is arrived. Along with it comes a new language that can be difficult to understand when deciding between the many desktop and laptop options, as well as a new method of assessing performance for AI-accelerated tasks. This article is a part of the AI Decoded series, which shows off new RTX PC hardware, software, tools, and accelerations while demystifying AI by making the technology more approachable.

While frames per second (FPS) and related statistics are easily understood by PC gamers, new measures are needed to measure AI performance.

Emerging as the Best

Trillions of operations per second, or TOPS, is the initial baseline. The key term here is trillions; the processing power required for generative AI jobs is truly enormous. Consider TOPS to be a raw performance indicator, like to the horsepower rating of an engine.

Take Microsoft’s recently unveiled Copilot+ PC series, for instance, which has neural processing units (NPUs) capable of up to 40 TOPS. For many simple AI-assisted tasks, such as asking a nearby chatbot where yesterday’s notes are, 40 TOPS is sufficient.

However, a lot of generative AI tasks are more difficult. For all generative tasks, the NVIDIA RTX and GeForce RTX GPUs offer performance never seen before; the GeForce RTX 4090 GPU offers more than 1,300 TOPS. AI-assisted digital content production, AI super resolution in PC gaming, image generation from text or video, local large language model (LLM) querying, and other tasks require processing power comparable to this.

Put in Tokens to Start Playing

TOPS is just the start of the tale. The quantity of tokens produced by the model serves as a gauge for LLM performance.

The LLM’s output is tokens. A word in a sentence or even a smaller piece like whitespace or punctuation might serve as a token. The unit of measurement for AI-accelerated task performance is “tokens per second.”

Batch size, or the quantity of inputs processed concurrently in a single inference pass, is another crucial consideration. The ability to manage many inputs (e.g., from a single application or across multiple apps) will be a critical distinction, as an LLM will be at the basis of many modern AI systems. Greater batch sizes demand more memory even though they perform better for concurrent inputs, particularly when paired with larger models.

NVIDIA TensorRT-LLM

Because of their massive amounts of dedicated video random access memory (VRAM), Tensor Cores, and TensorRT-LLM software, RTX GPUs are incredibly well-suited for LLMs.

High-speed VRAM is available on GeForce RTX GPUs up to 24GB and on NVIDIA RTX GPUs up to 48GB, allowing for larger models and greater batch sizes. Additionally, RTX GPUs benefit from Tensor Cores, which are specialised AI accelerators that significantly accelerate the computationally demanding tasks necessary for generative AI and deep learning models. Using the NVIDIA TensorRT software development kit (SDK), which enables the highest-performance generative AI on the more than 100 million Windows PCs and workstations powered by RTX GPUs, an application can quickly reach that maximum performance.

RTX GPUs achieve enormous throughput benefits, particularly as batch sizes increase, because to the combination of memory, specialised AI accelerators, and optimised software.

Text to Image More Quickly Than Before

Performance can also be assessed by measuring the speed at which images are generated. Stable Diffusion, a well-liked image-based AI model that enables users to quickly translate text descriptions into intricate visual representations, is one of the simplest methods.

Users may easily build and refine images from text prompts to get the desired result with Stable Diffusion. These outcomes can be produced more quickly when an RTX GPU is used instead of a CPU or NPU to process the AI model.

When utilising the TensorRT extension for the well-liked Automatic1111 interface, that performance increases even further. With the SDXL Base checkpoint, RTX users can create images from prompts up to two times faster, greatly simplifying Stable Diffusion operations.

TensorRT Acceleration

TensorRT acceleration was integrated to ComfyUI, a well-liked Stable Diffusion user interface, last week. Users of RTX devices may now create images from prompts 60% quicker, and they can even utilise TensorRT to transform these images to videos 70% faster utilising Stable Video Diffuson.

The new UL Procyon AI Image Generation benchmark tests TensorRT acceleration and offers 50% faster speeds on a GeForce RTX 4080 SUPER GPU than the quickest non-TensorRT implementation.

The much awaited text-to-image model from Stable Diffusion 3 Stability AI will soon receive TensorRT acceleration, which will increase performance by 50%. Furthermore, even more performance acceleration is possible because to the new TensorRT-Model Optimizer. This leads to a 50% decrease in memory use and a 70% speedup over the non-TensorRT approach.

Naturally, the actual test is found in the practical application of refining an initial prompt. By fine-tuning prompts on RTX GPUs, users may improve image production much more quickly it takes seconds instead of minutes when using a Macbook Pro M3 Max. When running locally on an RTX-powered PC or workstation, users also benefit from speed and security with everything remaining private.

The Results Are Available and Can Be Shared

Recently, the open-source Jan.ai team of engineers and AI researchers integrated TensorRT-LLM into their local chatbot app, then put these optimisations to the test on their own system.Image Credit to NVIDIA

TensorRT-LLM

The open-source llama.cpp inference engine was utilised by the researchers to test TensorRT-LLM’s implementation on a range of GPUs and CPUs that the community uses. They discovered that TensorRT is more effective on consecutive processing runs and “30-70% faster than llama.cpp on the same hardware.” The group invited others to assess the performance of generative AI independently by sharing its methodology.

Read more on Govindhtech.com