It’s easy to get confused when GenAI models are complex and can fit into multiple categories at once. In practice, many tools don’t belong to just one category. For example, GPT-4 is a transformer-based model, a multimodal model, and a large language model (LLM) all at once. *Popular Generative Models (simplified): GANs (Generative Adversarial Networks): Two neural networks compete, improving content generation over time. Transformer-based models: Learn from long-range dependencies between words. Diffusion Models: Generate complex data by adding and refining noise iteratively. VAEs (Variational Autoencoders): Encode data into a compact form, enabling creative content generation through latent space interpolation.

Hello all I am thrilled to share that I am embarking on an exciting new journey focused on growing and learning in the fields of Artificial Intelligence (AI) and Data Science. These rapidly evolving areas are not only shaping the future of technology but also redefining how we approach and solve problems in almost every industry. As I dive deeper into this journey, I look forward to gaining new skills, understanding cutting-edge technologies, and applying these insights to create innovative solutions. The potential of AI and Data Science is boundless, and I am eager to explore this world of possibilities. I’m also excited about the opportunity to connect with and learn from others in this space. Whether you’re a seasoned expert or just starting out, I’d love to share experiences, exchange ideas, and support each other’s growth. Thank you for being part of my community and I can’t wait to see where this journey takes us all.