Probably the Best Model of 2023 So Far.

The video transcript discusses the Think Diffusion XL model, which the speaker considers to be the best AI model of 2023 so far. The model has been trained on over 10,000 hand-captioned images, leading to high-quality, realistic outputs. The speaker praises the model's ability to generate detailed and vibrant images, especially when prompted correctly. They also mention the model's 4K dataset and its training on various art styles and realism. Comparisons are made to other models, highlighting Think Diffusion XL's more muted and realistic colors, as opposed to the overly saturated look of some alternatives. The speaker shares their experience using the model with different prompts and styles, noting that it outperforms their previous favorite, the Juggernaut variant, in terms of realism and detail. They conclude by encouraging viewers to try the model and share their thoughts.

Takeaways

• 🌟 The speaker has discovered a new favorite AI model, which surpasses their long-time preference for Juggernaut variants.
• 🔍 This new model has been trained further than Juggernaut and utilizes more input images, making it superior in the speaker's opinion.
• 🎨 The focus of the speaker is on achieving the most realistic images possible, as they find realism to be the most challenging aspect of AI-generated art.
• 📈 The model in question is Think Diffusion XL, which was released on the same day the video was uploaded.
• 💰 The speaker has been sponsored by the creators of Think Diffusion XL and has been testing the model extensively.
• 🏷️ The training data for the model consists of over 10,000 hand-captioned and tagged images, which helps to refine the model's understanding and responses to prompts.
• 🎭 The model is capable of producing images in various art styles and realism, with a 4K dataset that enhances the quality of the generated images.
• 👁️ The speaker demonstrates the model's capabilities by generating images with specific prompts, such as a woman in a cyberpunk scene and an alien warrior.
• 🌈 The importance of prompt crafting is emphasized, as the speaker suggests adjusting prompts for better results, such as specifying eye color or style.
• 🖌️ The speaker also discusses the use of automatic 1111 for additional features and style implementation, which can improve the final images.
• 🔥 The Think Diffusion XL model stands out for its realistic output, especially in close-up images where the level of detail and lifelike quality is impressive.

Q & A

What is the title of the video discussing the best model of 2023?

The title of the video is 'Probably the Best Model of 2023 So Far.'

What is the name of the AI model that the speaker considers to be their new favorite?

The speaker's new favorite AI model is 'Think Diffusion XL'.

How many training images were used for the Think Diffusion XL model?

The Think Diffusion XL model was trained with over 10,000 images.

What is the advantage of having human-tagged training data for the AI model?

Human-tagged training data helps to reduce possible errors that computer tagging might introduce, leading to more accurate training and better responses to prompts.

What is the resolution of the dataset used for training the Think Diffusion XL model?

The Think Diffusion XL model was trained with a 4K dataset, which is higher than the average model's 1024 x 1024 resolution.

How does the speaker describe the realism of the images generated by the Think Diffusion XL model?

The speaker describes the realism of the images as very high, noting that they would not have guessed the images were AI-generated, especially when looking at the details like skin and hair.

What is the significance of the 'cinematic style' prompt in the context of the AI model?

The 'cinematic style' prompt results in more desaturated and color-graded images, similar to high-production films, which can look more realistic.

What is the speaker's approach to generating images without cherry-picking?

The speaker's approach is to generate images and show the results as they come, without selecting or omitting any, to provide a fair representation of the model's capabilities.

How does the speaker suggest improving images that need more detail?

The speaker suggests using a tool like 'automatic 1111' to inpaint details and add depth to certain elements of the image, such as the character's face or armor.

What is the main difference between the Think Diffusion XL model and the average model according to the speaker?

The main difference is that the Think Diffusion XL model has been trained with more images, has a higher resolution dataset, and does not require a refiner or additional processing, making it more efficient and effective for generating high-quality images.

What does the speaker suggest for users who want to experiment with different styles and prompts?

The speaker suggests trying out short and simple prompts, adjusting the clip skip value, and experimenting with various styles to find the desired outcome.

How does the Think Diffusion XL model handle prompts for specific features like eye color?

The model uses the training dataset for specific features when prompted, resulting in more accurate and realistic representations, such as better-rendered eyes when the specific eye color is requested.

Outlines

00:00

🎨 Discovering a Superior AI Model for Realism

The speaker introduces their new favorite AI model, Think Diffusion XL, which surpasses the Juggernaut variants in training and input images. They emphasize the model's ability to produce highly realistic images, which is considered a challenging aspect of AI art generation. The video discusses the model's training on over 10,000 hand-captioned images, which aids in accurate prompting. The speaker shares their experience with the model, noting the improvements in image quality and realism over time. They also mention their financial relationship with the model's creators but clarify that their positive opinion is genuine. Several image prompts are tested, including a close-up portrait of a woman in a cyberpunk scene with neon lights and an alien warrior with battle scars and face painting, showcasing the model's versatility and attention to detail.

05:01

🌈 Exploring Styles and Techniques for Enhanced Realism

The speaker continues to experiment with different styles and prompts to enhance the realism of the AI-generated images. They discuss the impact of the 'cinematic' style on the image's saturation and color grading, noting that it can sometimes override specific prompt details like face paintings. The speaker suggests ways to adjust prompts for better results, such as simplifying them or adjusting the clip skip value. They also share their findings on prompting for specific eye colors to achieve more realistic eye details. The video includes examples of various prompts, such as a fantasy warrior in an epic battle with flowing magic light, and a Viking warrior with face paintings and green eyes. The speaker also touches on the potential for post-processing the AI-generated images using tools like automatic1111 for additional detail and refinement.

10:03

📈 Comparing Models and Discussing Personal Preferences

The speaker concludes the video by comparing Think Diffusion XL with other models like Juggernaut, Realistic Stock Photo, and Dream Shaper. They highlight the advantages of Think Diffusion XL, such as its less desaturated and less glossy output compared to other models, which contributes to a more realistic and less plastic-like feel. The speaker also discusses the use of the 'cinematic' prompt to achieve a more film-like color grade and the potential for high-contrast, vibrant images. They invite viewers to share their thoughts and preferences and to try out the model for themselves. The video ends with an encouragement to explore and enjoy the creative process with AI-generated art.

Keywords

💡Juggernaut variants

Juggernaut variants refer to a type of model or system that is powerful and dominant in its field. In the context of the video, it's a model that the speaker has favored for a long time, likely for its robust performance in generating images. However, the new model discussed is presented as even more advanced.

💡Realism

Realism in the context of this video pertains to the quality of AI-generated images closely resembling real-life visuals. The speaker emphasizes the challenge of achieving realistic images and how the new model brings them a step closer to true-to-life representations, as evidenced by the skin and hair details in the generated images.

💡AI-generated image

An AI-generated image is a visual output created by an artificial intelligence system without direct human input. The video discusses the quality and capabilities of such images, particularly how they can be mistaken for non-AI created visuals due to their high quality and detail.

💡Think Diffusion XL

Think Diffusion XL is the name of the new model being discussed. It is highlighted as superior to previous models due to its extended training and larger dataset. The speaker has been testing this model and shares their positive experiences with it in the video.

💡Hand-captioned images

Hand-captioned images are photographs that have been manually described or tagged with text. In the context of the video, this human input is crucial for training the AI model to understand and reproduce specific elements when prompted, thus enhancing the accuracy and relevance of the generated images.

💡Training data

Training data is the set of information used to teach a machine learning model to make predictions or decisions without being explicitly programmed. The video mentions that the new model has been trained on over 10,000 hand-captioned images, which is significantly more than the average model, leading to improved performance.

💡4K dataset

A 4K dataset refers to a collection of images or data with a resolution of 4,000 pixels on the horizontal axis. The video script mentions that the new model is trained on a 4K dataset, which is a higher resolution than the typical 1024 x 1024 datasets, allowing for more detailed and high-quality image generation.

💡Prompting

Prompting in the context of AI image generation is the process of providing the model with a description or set of keywords that guide the creation of the image. The video discusses how effective prompting can leverage the model's training data to produce desired results, such as specific styles or elements within the generated images.

💡Cinematic style

Cinematic style in the video refers to a visual aesthetic that mimics the look and feel of film, often characterized by a more desaturated and color-graded appearance. The speaker discusses how prompting for a cinematic style can influence the final output of the AI-generated images, making them appear more realistic and film-like.

💡Refined output

Refined output is the final, polished result of an AI image generation process that may involve multiple stages of refinement. The video mentions that the new model produces high-quality images without the need for additional refinement, indicating its advanced capabilities.

💡Viking Warrior

Viking Warrior is an example of a specific subject that the speaker uses to test the AI model's ability to generate detailed and contextually accurate images. The video showcases how the model can create images of a Viking Warrior with specific characteristics like green eyes and face paintings, demonstrating its versatility and attention to detail.

Highlights

The presenter has found a new favorite AI model, which surpasses the Juggernaut variants in training and input images.

The new model, Think Diffusion XL, is praised for its realistic image generation capabilities.

Think Diffusion XL has been trained on over 10,000 hand-captioned images, which aids in accurate prompting.

The model boasts 1.8 million training steps compared to the average model's 250,000.

Think Diffusion XL supports easy prompting and is trained for all art styles and realism.

It utilizes a 4K dataset, a feature not common among most models.

The model does not train on uncensored or not safe-for-work images, ensuring a safe output.

Human tagging of training data reduces potential errors from computer tagging.

The presenter demonstrates the model's ability to generate detailed and realistic close-up portraits.

The skin and hair details in the generated images are highly realistic, indistinguishable from human-made art.

Prompting for specific eye colors results in better quality eyes in the generated images.

The model can generate images with a cinematic style, offering a desaturated and color-graded look.

Removing the cinematic style from prompts allows for more vibrant and colorful images.

The presenter suggests using shorter and simpler prompts for better results.

Think Diffusion XL does not require a refiner or additional processing, delivering images straight from the model.

The model's outputs are compared favorably against other models like Juggernaut, Dream Shaper, and the Excel base model.

Think Diffusion XL provides a more muted and realistic color palette without an overly saturated or plastic feel.

The presenter encourages viewers to try the model and share their preferences or suggestions for improvement.