From AI Hype to Markov Chains: A Return to Basics

The author recounts their journey through four stages of the AI hype cycle concerning large language models: initial amazement, subsequent frustration, persistent confusion, and ultimate boredom. Tired of the constant stream of new models, the author decided to return to fundamentals and explore Markov chains. The article details how to build text autocompletion using Markov chains, covering the construction of transition matrices, probability calculations, and application to text generation. This piece not only explores the principles of Markov chains but also reflects the author's reflections on the current state of AI development and their desire to explore more foundational technologies.
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