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Ask HN: Is there a great book for understanding LLMs?

Jan 05, 2024 - news.ycombinator.com
The article recommends three resources for those interested in learning about Language Learning Models (LLMs). The first is "Deep Learning" by Goodfellow, Bengio, and Courville, which is known for its approachability and comprehensive coverage of deep learning topics, including neural networks. The second is "Artificial Intelligence: A Guide for Thinking Humans" by Melanie Mitchell, which provides an overview of AI and discusses its societal and philosophical implications.

The third resource is a paper by OpenAI on GPT-3, available on the arXiv repository, which offers an in-depth look at the model's architecture, capabilities, and limitations. The author also suggests reading original papers and blog posts from OpenAI about ChatGPT, regularly checking new content on arXiv, and following AI researchers on Twitter for the latest insights.

Key takeaways:

  • For a comprehensive understanding of deep learning, the book "Deep Learning" by Goodfellow, Bengio, and Courville is recommended.
  • "Artificial Intelligence: A Guide for Thinking Humans" by Melanie Mitchell is a less math-intensive book that provides an overview of the field of AI and its societal implications.
  • OpenAI's paper on GPT-3, available on the arXiv repository, offers an in-depth look at the model's architecture, capabilities, and limitations.
  • For the latest insights, it is suggested to check out new content on arXiv and follow relevant AI researchers on Twitter.
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