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In this interactive session, we'll explore the fascinating realm of neural style transfer, a subfield of Generative AI. This talk will involve a deep dive into the technical aspects of style transfer algorithms and their applications in art and design. Audience members will have the opportunity to interact with a live style transfer model and create their own AI-powered artwork.

Introduction:
We'll start by sharing a brief history of Generative AI and the advent of neural style transfer.
Then, we'll understand the core concept of style transfer and its intersection with the field of art and design.
Finally, we'll look at some examples of notable AI-generated artwork.

Technical Dive into Neural Style Transfer:

We will discuss the architecture of neural networks used in style transfer, including Convolutional Neural Networks (CNNs).
We'll look at the concept of 'style' and 'content' in images from a machine learning perspective.
We'll provide a walkthrough of the process of separating style and content in images and recombining them.
We'll present the mathematical formulations and loss functions involved in style transfer.

Challenges and Solutions in Neural Style Transfer:

We'll highlight challenges such as maintaining the balance between content and style, computational requirements, and creating high-resolution images.
We'll discuss the solutions and techniques used to overcome these challenges, like style scale, multi-scale image synthesis, and others.

Interactive Demonstration of Neural Style Transfer:

We'll conduct a live demonstration of a style transfer model where attendees can submit images for content and style, and see the resultant stylized image.
We'll walk through the process happening behind the scenes when the model generates the new image.
Applications and Implications of Neural Style Transfer

We'll discuss various applications of style transfer in art, design, entertainment, and more.
We'll touch on the ethical and copyright implications of AI-generated artwork.