Stable Diffusion 3 - RAW First Impression!

Stable Diffusion 3, a new image AI, has generated significant hype. This video provides a critical first impression of the AI's capabilities. The host discusses the potential of the AI, noting its ability to accept multimodal inputs and the range of model sizes available, which can democratize access to these tools. Several image examples are reviewed, highlighting the AI's strengths, such as handling long text inputs and creating detailed and consistent images, as well as its limitations, including issues with smaller details and hand rendering. Comparisons are made with Mid Journey, another AI, which, while aesthetically pleasing, does not always follow prompts as closely. The video concludes that while Stable Diffusion 3 shows promise, it is not without its flaws and is expected to improve with community training.

Takeaways

• 🚀 Stable Diffusion 3 has been announced with much hype and promises to bring new capabilities to AI-generated images.
• 📸 The AI can handle complex text inputs, as demonstrated by an image of a robot with a lengthy and correctly spelled phrase.
• 🤖 There are still limitations with the AI, particularly with smaller details such as the hands of the robot in the example image.
• 🎨 The AI shows potential for multi-modal inputs, which could include 3D shapes or other forms beyond text, images, and video.
• 🌐 Different model sizes will be available, from 800 million to 8 billion parameters, aiming to democratize access to AI models.
• 🔍 The AI sometimes struggles with maintaining consistency in artistic style, as seen in an image where the cat's style changes.
• 📹 An animated example showcased impressive consistency and detail, including light and shadow effects, although minor issues like misplaced sushi were noted.
• 🖥️ A '90s desktop computer image with graffiti in the background was generated accurately, demonstrating the AI's ability to follow detailed prompts.
• 🧵 An image of an embroidered cloth with a tiger and text was mostly accurate but lacked shadow detail from the candlelight.
• 🏺 The AI successfully created an image with transparent glass bottles of different colors and numbers, showing precision in color and detail.
• 🤡 In a complex scene with clowns, the AI struggled with details like hands and facial features, revealing areas for improvement.
• 🌫️ A creative example featured text made from the smoke of a train, highlighting the AI's potential for innovative image generation.

Q & A

What is the main focus of the video regarding Stable Diffusion 3?

The main focus of the video is to critically analyze the images generated by Stable Diffusion 3, compare it with Mid Journey, and discuss its capabilities, limitations, and potential for improvement.

How does the video describe the hype around Stable Diffusion 3?

The video acknowledges the hype around Stable Diffusion 3 but aims to take a critical look at the images produced so far, which may be cherry-picked and potentially overpromising.

What is the significance of the different model sizes for Stable Diffusion 3?

The different model sizes, ranging from 800 million to 8 billion parameters, help democratize access to these models, allowing them to be used on various systems with different GPUs and power capabilities.

What new feature does Stable Diffusion 3 introduce with multimodal inputs?

Stable Diffusion 3 introduces the ability to accept multimodal inputs, which could include images, text, video, and potentially other inputs like 3D shapes, offering more control over composition, colors, and artistic output.

How does the video address the limitations of Stable Diffusion 3 in handling complex images?

The video points out that while Stable Diffusion 3 is good at handling text, it still has limitations with complex images, such as detailed backgrounds and smaller elements within the image, which may not receive as much detail from the AI.

What is the video's stance on the artistic style consistency in the generated images?

The video notes that while some images have a consistent artistic style, there are instances where elements like the cat and the sushi do not match the style of the image, indicating room for improvement in style consistency.

How does the video compare Stable Diffusion 3 with Mid Journey in terms of following prompts?

The video suggests that while Stable Diffusion 3 follows prompts more closely, Mid Journey produces more aesthetically pleasing images that may not always adhere strictly to the prompt.

What is the video's opinion on the potential of Stable Diffusion 3 for video creation?

The video expresses excitement about the potential of Stable Diffusion 3 for video creation, hinting that it could be very mind-blowing due to its strong text handling capabilities.

How does the video address the issue of hands and anatomy in the generated images?

The video highlights that hands and anatomy are often problematic in the generated images, with hands appearing deformed or missing and anatomy not always being correct, such as the cat's head being too small.

What does the video suggest about the future improvements of Stable Diffusion 3?

The video suggests that the shortcomings seen in the generated images will likely be fixed over time with community training and further development of the AI models.

How does the video encourage viewer engagement with the content?

The video encourages viewer engagement by asking for opinions in the comments, inviting likes for the video, and prompting viewers to follow the creator on Twitter and support on Patreon for additional content and rewards.

Outlines

00:00

🎉 Introduction to Stable Diffusion 3 and Comparisons

The video begins with an introduction to Stable Diffusion 3, a new AI image-generating technology that has generated significant hype. The speaker expresses excitement but also a desire to critically evaluate the technology, comparing it to Mid Journey, another AI tool. The focus is on examining the quality of images produced by both, including those that may have been cherry-picked for promotional purposes. The speaker also discusses the accessibility of the models, which range from 800 million to 8 billion parameters, and their potential for open-source use across various systems. The importance of community training in improving the models is highlighted, and the video promises to reveal surprising findings in the comparison.

05:04

📚 Analyzing the Image Quality and AI's Artistic Limitations

This paragraph delves into a detailed analysis of the images generated by Stable Diffusion 3, noting the impressive text incorporation but also pointing out the AI's limitations in rendering fine details, such as the hands of a robot or background elements. The speaker discusses the potential for multimodal inputs, which could enhance control over the composition and style of the generated images. A comparison is made with Mid Journey, noting that while Stable Diffusion 3 has some issues with detail, it still produces aesthetically pleasing and artistically expressive images. The paragraph also touches on the importance of community contributions in refining the models for better stylistic outcomes.

10:05

🔍 Close Examination of AI-Generated Images and Their Fidelity to Prompts

The speaker continues the critique by examining the accuracy and adherence of AI-generated images to the prompts given to them. Several examples are discussed, where the AI's performance varies. Some images are praised for their accuracy and aesthetic appeal, while others are noted to have issues with elements like shadowing or the positioning of objects. The paragraph also explores the challenges AI faces with more complex prompts and the differences in artistic expression between Stable Diffusion 3 and Mid Journey. The speaker concludes by emphasizing the ongoing journey towards perfect AI image generation and the potential for improvement through community engagement and model training.

Keywords

💡Stable Diffusion 3

Stable Diffusion 3 is an advanced AI image generation model that has recently been announced. It is part of the broader theme of the video, which is to critically assess the capabilities of this new AI technology. The video discusses its potential to be a leading image AI on the market and compares its outputs with those of other models like Mid Journey.

💡Cherry Picked

Cherry picking refers to the selection of images that are most likely to present an AI model in the best light. In the context of the video, the term is used to express skepticism about the images presented by the developers of Stable Diffusion 3, suggesting that they may not represent the average performance of the model.

💡Multimodal Inputs

Multimodal inputs describe the ability of an AI to accept and process different types of data, such as text, images, and potentially 3D shapes or videos. In the video, it is mentioned that Stable Diffusion 3 accepts multimodal inputs, which could enhance the control over the composition and style of the generated images.

💡Parameters

Parameters in the context of AI models are variables that the model learns from its training data. The video discusses the range of model sizes from 800 million to 8 billion parameters for Stable Diffusion 3, highlighting the flexibility and scalability of the model to cater to different computational resources.

💡Community Models

Community models refer to AI models that are developed or improved by a community of users, rather than a single entity. The video suggests that the limitations of Stable Diffusion 3 will be improved over time through community training and contributions.

💡Digital Painting Style

Digital painting style is a term used to describe the visual aesthetic of an image that resembles traditional painting but is created using digital tools. In the video, the style is mentioned when discussing how the AI can generate images with different artistic styles, such as a cat in a digital painting style.

💡Graffiti

Graffiti is a form of visual art, often created in public spaces, involving the use of paint or markers on walls or other surfaces. In the video, graffiti is used as an example of an element in the generated images, showcasing the AI's ability to incorporate complex background elements.

💡Aesthetics

Aesthetics refers to the visual or sensory aspects of an image that are pleasing or appealing. The video frequently discusses the aesthetic quality of the images generated by Stable Diffusion 3 and compares them with those produced by Mid Journey, noting the differences in artistic expression.

💡Prompt

A prompt is a set of instructions or a description given to an AI to guide the generation of an image. The video script includes several examples of prompts used to test the capabilities of Stable Diffusion 3, such as creating images of specific scenes or objects.

💡Shadows and Lighting

Shadows and lighting are critical elements in image generation that contribute to the realism and depth of an image. The video points out that while Stable Diffusion 3 can create visually appealing images, it sometimes struggles with accurately rendering shadows and lighting, such as the candlelight not casting a shadow in one example.

💡Hands and Anatomy

Hands and anatomy are often challenging aspects for AI image generation models to depict accurately. The video script notes that in some of the generated images, the hands of characters appear deformed or unrealistic, indicating a current limitation in the model's ability to render complex anatomical details.

Highlights

Stable Diffusion 3 has been announced with a lot of hype around it.

The video provides a critical look at the images generated by Stable Diffusion 3 so far.

Stable Diffusion 3 is expected to democratize access to AI models with different sizes ranging from 800 million to 8 billion parameters.

The AI can accept multimodal inputs, potentially including images, text, video, 3D shapes, and more.

The generated images showcase impressive text rendering capabilities.

However, the AI still has limitations in rendering smaller details and complex structures in images.

The video compares Stable Diffusion 3 with Mid Journey, highlighting the strengths and weaknesses of each.

Mid Journey is praised for its artistic style and expressiveness, but criticized for not following prompts as well.

Stable Diffusion 3 demonstrates impressive consistency and detail in a video where different elements are replaced.

The AI struggles with rendering hands and certain objects accurately in images.

The generated images often showcase the AI's shortcomings when not using cherry-picked examples.

The AI's performance is expected to improve over time through community training and model updates.

Stable Diffusion 3 brings massive potential to the table, especially with text in images.

Most of the text generated by the AI is legible and makes sense.

The video teases the potential of Stable Diffusion 3 for video creation.

The AI's ability to generate images with specific requirements and compositions is impressive.

However, the generated images still have room for improvement in terms of accuracy and consistency.

The video concludes that we are still on a journey towards perfect AI image generation.