Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible.

My own notes from a few months back.

• Survey of LLMS
• Self-attention and transformer networks
• What are embeddings
• The Illustrated Word2vec - A Gentle Intro to Word Embeddings in Machine Learning (YouTube)

• Attention is all you Need
• Scaling Laws for Neural Language Models
• BERT
• Language Models are Unsupervised Multi-Task Learners
• Training Language Models to Follow Instructions
• Language Models are Few-Shot Learners

• Why host your own LLM?
• How to train your own LLMs
• Training Compute-Optimal Large Language Models

• The case for GZIP Classifiers and more on nearest neighbors algos
• Meta Recsys Using and extending Word2Vec
• The State of GPT (YouTube)
• What is ChatGPT doing and why does it work

• Building LLM Applications for Production
• Challenges and Applications of Large Language Models
• All the Hard Stuff Nobody talks about when building products with LLMs

• Evaluating ChatGPT

• Generative Interfaces Beyond Chat (YouTube)