AI influencers are getting filthy rich... let's build one

The video introduces the rise of AI influencers, showcasing how individuals can create their own using open-source generative image models and UI tools for financial gain. It explains the process of building AI influencers through specific prompts, image blending, and adjustments to enhance realism while also discussing the potential for AI technology in creating various content types.

The video introduces Itana, an AI Instagram model from Barcelona who generates income through subscription tiers. The narrator discusses the rise of AI influencers and how anyone can now create their own using open source generative image models. These models have evolved over the past decade to produce high-resolution and realistic images capable of deceiving viewers. Despite ethical concerns about AI influencers exploiting vulnerable audiences, the narrator focuses on the technical aspects of building these AI models for financial gain.

The narrator explains that while paid products like Mid-Journey and DALL-E from OpenAI exist, there are open-source alternatives within the generative AI ecosystem. Stable Diffusion XL is a well-known base model that can be fine-tuned through the creation of checkpoints using specialized training data. Websites like Civit AI offer pre-optimized checkpoints for users to access. Various UI tools, such as Stable Diffusion Web UI, Comfy UI, and Fucos, allow users to work with these models without coding knowledge.

The narrator demonstrates the installation process for the Fucos UI, which is free and intuitive for beginners. By utilizing a base model like Juggernaut XL, users can generate realistic images with specific prompts and imperfections to enhance realism. The AI influencer creation process involves blending multiple images and text, adjusting parameters like performance and aspect ratio, and fine-tuning the image through style mixing. The narrator showcases the generation of an AI influencer image through specific prompts and adjustments.

The video emphasizes that AI influencer creation extends beyond images, mentioning the potential of Stable Diffusion Video for text-to-video applications. Despite the closed-source nature of some platforms, stable diffusion technology allows for the expansion of AI-generated content possibilities. The narrator concludes the video by highlighting the advancements in AI technology and teasing the potential applications for creating various content types with AI models. The focus remains on the technical aspects of building AI influencers rather than ethical considerations.

In summary, the video discusses the accessibility of creating AI influencers using open-source generative image models and UI tools. It showcases the process of building AI influencers through specific prompts, image blending, and adjustments to enhance realism. The narrator acknowledges concerns about AI influencers but focuses on the technical aspects of AI model creation for financial gain. The video ends by mentioning the potential for AI technology to create text-to-video platforms and other content types using stable diffusion technology, highlighting the continuous evolution of AI applications in content creation.