GenerativeAI & ChatGPT Introduction
"Welcome to our educational series on generative AI! Whether you're a college student or an early professional, this video is designed to provide you with an exciting introduction to the world of generative artificial intelligence. Join us as we explore the applications, workings, and potential of generative AI. Discover how it is revolutionizing various industries and learn tips for getting started in this fascinating field."
As for learning links, here are a few resources that can help your viewers dive deeper into generative AI:
1. OpenAI's Generative Models: Visit OpenAI's website to explore their cutting-edge generative models, including GPT-3, CLIP, and DALL-E. These models have produced remarkable outputs in text, image, and art generation.
2. TensorFlow Tutorials: TensorFlow is a popular deep learning framework used in generative AI. The official TensorFlow website offers comprehensive tutorials and guides for learning TensorFlow and its applications in generative models.
3. PyTorch Resources: PyTorch is another widely used deep learning framework that provides powerful tools for generative AI. The official PyTorch website offers tutorials, documentation, and a wealth of resources to help you get started with PyTorch and generative models.
4. Generative Adversarial Networks (GANs): GANs are a key component of generative AI. The "Generative Adversarial Networks" paper by Ian Goodfellow et al. is a seminal work that introduced GANs. You can find the paper on the arXiv website
5. Generative AI Research Papers: Explore research papers on generative AI to stay up-to-date with the latest advancements. Websites like arXiv and papers with code provide a vast collection of research papers and code implementations.
“Welcome to our educational series on generative AI! Whether you’re a college student or an early professional, this video is designed to provide you with an exciting introduction to the world of generative artificial intelligence. Join us as we explore the applications, workings, and potential of generative AI. Discover how it is revolutionizing various industries and learn tips for getting started in this fascinating field.”
As for learning links, here are a few resources that can help your viewers dive deeper into generative AI:
1. OpenAI’s Generative Models: Visit OpenAI’s website to explore their cutting-edge generative models, including GPT-3, CLIP, and DALL-E. These models have produced remarkable outputs in text, image, and art generation.
2. TensorFlow Tutorials: TensorFlow is a popular deep learning framework used in generative AI. The official TensorFlow website offers comprehensive tutorials and guides for learning TensorFlow and its applications in generative models.
3. PyTorch Resources: PyTorch is another widely used deep learning framework that provides powerful tools for generative AI. The official PyTorch website offers tutorials, documentation, and a wealth of resources to help you get started with PyTorch and generative models.
4. Generative Adversarial Networks (GANs): GANs are a key component of generative AI. The “Generative Adversarial Networks” paper by Ian Goodfellow et al. is a seminal work that introduced GANs. You can find the paper on the arXiv website
5. Generative AI Research Papers: Explore research papers on generative AI to stay up-to-date with the latest advancements. Websites like arXiv and papers with code provide a vast collection of research papers and code implementations.
