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simonwillison.net
| | blog.moonglow.ai
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| | Parameters and data. These are the two ingredients of training ML models. The total amount of computation ("compute") you need to do to train a model is proportional to the number of parameters multiplied by the amount of data (measured in "tokens"). Four years ago, it was well-known that if
| | blog.adnansiddiqi.me
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| | Learn the basics of Large Language Models (LLMs) in this introduction to GenAI series. Discover how LLMs work, their architecture, and practical applications like customer support, content creation, and software development.
| | www.danieldemmel.me
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| | Part two of the series Building applications using embeddings vector search and Large Language Models
| | www.danieldjohnson.com
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| Writeup for my first major machine learning project.