In 2022, the field of AI-driven image generation reached a notable milestone with technologies like DALL-E, MidJourney, and Stable Diffusion leading the charge, producing image quality that won widespread approval. Now, as we traverse through 2024, the adoption of these technologies is on an upward trajectory, making it crucial for developers to delve deeper into this domain.

In this session, we'll spotlight some of the prominent image generation tools that have captured the industry's attention. While bypassing the nitty-gritty of the underlying math, we'll touch on the AI strategies propelling text-guided image generation, making it digestible for a broad spectrum of developers.

A significant portion of these AI models are accessed via cloud-based APIs, and we'll provide a hands-on demonstration on leveraging such an API for image generation tasks. On the flip side, we'll also explore self-hosted alternatives like "Stable Diffusion" that facilitate running models locally, a boon for businesses and individuals seeking greater control over their data and computational resources.

Pushing the envelope further, we'll delve into advanced use cases including optimizing image output to adhere to a specific style, or tweaking a model to generate images that bear your likeness.

While the crux of this session is rooted in practical application, we won't shy away from addressing the risks associated with this domain. We'll briefly discuss the evolving landscape of Responsible AI, shedding light on risk mitigation strategies in this context.

Join us in this engaging exploration as we dissect the current landscape of AI-driven image generation, offering you a practical understanding and hands-on experience, all while keeping a prudent eye on the associated risks and responsible AI practices.