What are some of the best resources for learning about generative AI?

Here are some of the best resources for learning about generative AI:

Online courses: There are a number of online courses available on generative AI, offered by universities, companies, and other organizations. Some popular courses include:
Generative AI with Large Language Models by Stanford University
Generative AI by Google AI
Generative AI for Everyone by Coursera
Generative AI with TensorFlow 2 by Udemy
Books: There are also a number of books available on generative AI, covering both the theoretical and practical aspects of this technology. Some popular books include:
Generative Deep Learning: Teaching Machines to Create by David Foster
Deep Learning for Coders with Python by Francois Chollet
Generative Adversarial Networks by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
The Hundred-Page Machine Learning Book by Andriy Burkov
Research papers: If you are interested in learning about the latest advances in generative AI research, you can read research papers published in academic conferences and journals. Some popular conferences and journals where generative AI research is published include:
The International Conference on Learning Representations (ICLR)
The Conference on Neural Information Processing Systems (NIPS)
The Conference on Computer Vision and Pattern Recognition (CVPR)
The Conference on Empirical Methods in Natural Language Processing (EMNLP)
arXiv
In addition to the above, here are some other resources for learning about generative AI:

Blogs: There are a number of blogs that cover generative AI news and research. Some popular blogs include:
AI Weekly
Towards Data Science
Machine Learning Mastery
Papers with Code
Community forums: There are a number of community forums where you can ask questions and discuss generative AI with other people. Some popular forums include:
Stack Overflow
Reddit
Discord