Probably the Best Model of 2023 So Far.

Sebastian Kamph
23 Oct 202314:16

TLDRThe speaker enthusiastically discusses their new favorite AI model, Think Diffusion XL, which they believe surpasses the Juggernaut variants in realism. They mention that the model has been trained on over 10,000 hand-captioned images, leading to improved accuracy. The video showcases various prompts and the resulting AI-generated images, highlighting the model's ability to create realistic portraits and scenes. The speaker also provides tips on refining prompts for better results and expresses their excitement about the potential of Think Diffusion XL for creating high-quality, realistic art.

Takeaways

  • 🌟 The speaker reveals a new favorite AI model, surpassing their long-standing preference for Juggernaut variants.
  • 🔍 This new model has been trained further than Juggernaut, with more input images, aiming for heightened realism in generated images.
  • 💰 The speaker has been sponsored and paid by the creators of the new model but emphasizes that their positive opinion is genuine.
  • 🏷️ Over 10,000 hand-captioned and tagged images were used in the training process to improve the model's understanding of prompts.
  • 🎨 The model is capable of various art styles and realism, with a 4K data set that aids in generating high-resolution images.
  • 🖌️ The speaker uses 'Ruin Focus' for simplicity and to obtain good-looking images, also mentioning the potential of 'Automatic 1111' for more advanced features.
  • 👽 In testing the model, the speaker creates various prompts, such as 'alien warrior close-up portraits' and 'fantasy warrior in epic battle', to assess the model's performance.
  • 👁️ Specific prompts like 'blue eyes' or 'green eyes' can enhance the detail of certain features in the generated images.
  • 🌈 The impact of different styles (e.g., cinematic, vibrant) on the final image is discussed, with the speaker sharing tips on achieving desired visual effects.
  • 🔄 The speaker compares the new model with Juggernaut and other base models, noting that the Think Diffusion model provides a more realistic experience without an overly saturated look.
  • 📢 The speaker invites feedback and suggestions from the audience, showing openness to explore other models and continue the discussion on AI-generated images.

Q & A

  • What is the speaker's new favorite model they've discovered?

    -The speaker's new favorite model is Think Diffusion XL, which they believe has been trained further than the Juggernaut variants and produces more realistic images.

  • How does the speaker evaluate the quality of AI-generated images?

    -The speaker evaluates the quality of AI-generated images based on their realism, considering it the hardest part of AI-generated art. They strive to get the most realistic images possible.

  • What is the significance of the training images and human tagging mentioned in the script?

    -The training images and human tagging are significant because they help the model understand and respond to specific prompts more accurately. Over 10,000 images are used, each hand captioned and tagged, reducing potential errors from computer tagging and improving the model's training.

  • What are some of the features that set Think Diffusion XL apart from the average model?

    -Think Diffusion XL has several features that set it apart, including a larger training dataset, more training steps, and the use of human-tagged data. It also does not require a refiner and can produce images without censoring or being limited to a 1024x1024 resolution.

  • How does the speaker use the Think Diffusion XL model to generate images?

    -The speaker uses Think Diffusion XL by inputting various prompts, such as 'woman closeup portrait in cyberpunk scene raining neon lights' or 'alien warrior close-up portraits in sci-fi scene beautiful exotic alien world landscape'. They experiment with different prompts and styles to see the variety of images generated.

  • What is the role of prompting in generating images with Think Diffusion XL?

    -Prompting plays a crucial role in guiding the model to generate specific types of images. By using precise keywords and phrases, the model can produce images that align with the desired style, theme, or subject matter.

  • What is the speaker's strategy for refining AI-generated images?

    -The speaker's strategy includes using a tool like Ruin Focus for simple and good-looking images and Automatic 1111 for more advanced features. They also suggest adjusting the prompt to be more specific or playing with the clip skip value to vary the results.

  • How does the speaker address the issue of similar-looking images?

    -The speaker advises adjusting the clip skip value to introduce more variation in the generated images if they look too similar to each other.

  • What is the speaker's opinion on the use of cinematic style in AI-generated images?

    -The speaker prefers the use of cinematic style as it provides a more realistic and desaturated look, which is more prevalent in film. They find this style more appealing and believe it enhances the overall quality of the images.

  • How does the speaker compare Think Diffusion XL to other models like Juggernaut and Dream Shaper?

    -The speaker compares Think Diffusion XL favorably to other models, noting that it provides a more realistic experience without an overly saturated plastic feel that is common in other models. They also mention that Think Diffusion XL can produce high contrast and vibrant colored images when prompted with words like 'cinematic'.

  • What advice does the speaker give to those interested in trying out Think Diffusion XL?

    -The speaker encourages people to try out Think Diffusion XL and share their thoughts or preferences. They also invite suggestions for other models that might be better or different from the ones they've tried.

Outlines

00:00

🎨 Discovery of a Superior AI Model for Realism

The speaker discusses their new favorite AI model for generating realistic images, which surpasses the Juggernaut variants in training and input images. They emphasize the importance of realism in AI-generated art and share their experience with the new model, called Think Diffusion XL. The model has been trained on over 10,000 hand-captioned images, leading to more accurate results. The speaker also mentions their sponsorship by the model's creators and provides a comparison of the new model with average models, highlighting features like the 4K dataset and human-tagged training data. They demonstrate the model's capabilities through various prompts, aiming to showcase its potential without cherry-picking the results.

05:01

🌌 Experimenting with Cinematic Styles and Alien Concepts

The speaker continues their exploration of the Think Diffusion XL model by experimenting with different styles and prompts, focusing on cinematic and vibrant colors. They discuss the impact of specific prompt words on the model's output and how certain styles, like cinematic, can override others, affecting the final image. The speaker shares their attempts at creating alien and warrior-themed images, adjusting prompts for better results. They also touch on the possibility of enhancing the generated images further using other tools and emphasize the model's ability to produce detailed and realistic portraits, including eyes and skin textures.

10:03

🏹 Refining Prompts and Comparing Models for Optimal Results

In the final paragraph, the speaker refines their prompts and compares different models to find the best settings for creating high-quality images. They discuss the influence of various styles and settings, such as 'Cinematic film still' and 'HDR vibrant,' on the output. The speaker shares their process of iteration and adjustment, aiming to achieve the most realistic and visually appealing results. They also mention other models like Juggernaut and Dream Shaper, and how Think Diffusion XL stands out for its less saturated and more realistic output. The speaker concludes by encouraging others to share their experiences and preferences, highlighting the versatility and potential of the Think Diffusion XL model.

Mindmap

Keywords

💡AI-generated images

AI-generated images refer to visual content created by artificial intelligence algorithms, without human intervention. In the context of the video, the speaker is discussing their experience with a new AI model that generates highly realistic images, which they consider to be their new favorite model. The speaker is impressed by the model's ability to produce images that closely resemble real-life textures and details, such as skin and hair, making it difficult to distinguish from human-created art.

💡Realism

Realism in art refers to the accurate and true-to-life depiction of subjects. In the video, the speaker emphasizes their preference for AI models that can produce realistic images, which they consider a challenging aspect of AI-generated art. The speaker is particularly interested in the level of detail and the lifelike quality of the images, which is achieved through extensive training data and precise tagging of images.

💡Training data

Training data consists of a collection of input images and associated tags or captions used to train AI models in image generation. The speaker notes that the new AI model they are discussing has been trained on over 10,000 hand-captioned images, which helps the model understand and produce images based on the correct keywords when prompted. This manual tagging process is crucial for reducing errors that might arise from computer-tagging and ensures the model's ability to generate high-quality, relevant images.

💡Prompting

Prompting is the process of providing specific keywords or phrases to an AI model to guide the type of image it generates. In the video, the speaker talks about how they use prompts to direct the AI to create particular scenes or characters with specific attributes, such as a 'cyberpunk scene with neon lights' or an 'alien warrior with battle scars.' The effectiveness of the prompts directly influences the quality and accuracy of the AI-generated images.

💡4K data set

A 4K data set refers to a collection of images with a resolution of approximately 4,000 pixels on the horizontal axis, providing high-definition visual data for training AI models. The speaker mentions that the AI model they are discussing uses a 4K data set, which allows for the creation of detailed and high-resolution images. This is significant because it means the model can produce images with a level of detail that is on par with professional-grade visual content.

💡Cinematic style

Cinematic style in the context of AI-generated images 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 in the video uses the term to describe the type of images they can generate with the AI model by prompting it with the word 'cinematic,' resulting in images that have a more subdued color palette and a film-like quality, which they find more realistic and appealing.

💡Face paintings

Face paintings are a form of body art where colors and designs are painted onto the skin, often used for cultural events, performances, or aesthetic purposes. In the video, the speaker uses 'face paintings' as a prompt to guide the AI in generating images of characters with intricate facial designs. This is an example of how specific and detailed prompts can lead to more nuanced and elaborate AI-generated images.

💡Alien warrior

An alien warrior is a fictional character concept that typically involves a creature from an extraterrestrial civilization engaged in combat or warfare. The speaker in the video uses 'alien warrior' as a prompt to explore the AI model's capability to create unique and imaginative extraterrestrial characters, complete with battle scars and exotic features, showcasing the model's versatility and creativity in generating science fiction-inspired imagery.

💡Think Diffusion XL

Think Diffusion XL is the name of the AI model that the speaker has been testing and discussing in the video. It is noted for its ability to generate highly realistic images and is compared favorably to other models like Juggernaut. The speaker appreciates the model's extensive training data and its capability to produce images with a cinematic style and high levels of detail, making it stand out among other AI models they have used.

💡Ruin Focus

Ruin Focus appears to be a tool or software mentioned by the speaker that they have been using to generate simple and good-looking images. While the exact nature of Ruin Focus is not detailed in the transcript, it is implied to be a user-friendly platform that the speaker prefers for its simplicity, possibly related to image generation or editing.

💡Automatic 1111

Automatic 1111 seems to be a feature or another AI model mentioned by the speaker for generating images with more advanced features. The speaker discusses using it to venture into creating images with specific styles and to refine the images produced by the AI model. This suggests that Automatic 1111 is a tool or platform that offers additional capabilities for enhancing or fine-tuning AI-generated content.

Highlights

The speaker has found a new favorite AI model that surpasses the Juggernaut variants in their opinion.

The new model has been trained further than Juggernaut and has more input images, which contributes to its improved performance.

The speaker values realism in AI-generated images and believes the new model gets closer to achieving that goal.

The model uses over 10,000 hand-captioned and tagged images for training, which enhances its ability to understand and produce desired outputs.

The speaker has been sponsored by the creators of the new model but emphasizes that their positive opinion is genuine.

The model is trained for all art styles and realism, and it utilizes a 4K dataset for higher quality images.

The speaker demonstrates the model's capabilities by generating images with various prompts, showcasing its versatility.

The prompt 'woman closeup portrait in cyberpunk scene raining Neon Lights' produces images that are close to the speaker's vision.

The speaker notes that the model can generate images with a cinematic style, which results in a more desaturated and film-like appearance.

The speaker experiments with prompts for 'alien warrior close-up portraits' and receives images that, while not perfect, show the model's potential.

The speaker suggests that using specific terms in prompts, like 'blue eyes', can lead to more accurate and realistic results.

The model's ability to generate detailed and realistic skin textures is praised by the speaker.

The speaker tests the model with a 'fantasy warrior in epic battle' prompt, resulting in images with a painterly vibe.

The speaker discusses the importance of adjusting the clip skip value to avoid generating similar images.

The speaker compares the new model to Juggernaut and other base models, noting that the new model offers a more realistic experience without an overly saturated look.

The speaker concludes by encouraging others to try the model and share their preferences or suggestions for improvement.