AI & Machine Learning: Mathematical Models as the Core Technology

Yes, it's accurate to say that the core technology behind machine learning and AI is the mathematical model. Machine learning algorithms rely on mathematical models to analyze and understand data. To build a ChatGPT-level AI, you'll need expertise in natural language processing, machine learning, deep learning, and computer vision.

Here's a list of university-level modules that can contribute to building a ChatGPT-level AI:

1. Natural Language Processing (NLP)
2. Machine Learning
3. Deep Learning
4. Computer Vision
5. Neural Networks
6. Data Science
7. Natural Language Generation (NLG)
8. Information Retrieval
9. Speech Recognition
10. Reinforcement Learning

Recommended textbooks for learning these modules:

1. 'Speech and Language Processing' by Jurafsky and Martin for NLP
2. 'Machine Learning' by Bishop for Machine Learning
3. 'Deep Learning' by Goodfellow, Bengio, and Courville for Deep Learning
4. 'Computer Vision: Algorithms and Applications' by Richard Szeliski for Computer Vision
5. 'Neural Networks and Deep Learning' by Michael Nielsen for Neural Networks
6. 'Data Science from Scratch' by Joel Grus for Data Science
7. 'Natural Language Generation in Interactive Systems' by Verena Rieser and Sebastian Varges for NLG
8. 'Information Retrieval: Implementing and Evaluating Search Engines' by W. Bruce Croft, Donald Metzler, and Trevor Strohman for Information Retrieval
9. 'Automatic Speech Recognition: A Deep Learning Approach' by Dong Yu and Li Deng for Speech Recognition
10. 'Reinforcement Learning: An Introduction' by Richard S. Sutton and Andrew G. Barto for Reinforcement Learning.