Large Language Models Briefly Explained

Imagine yourself in a conversation with an AI that seamlessly predicts the next word in your dialogue, creating responses that feel incredibly human. This is the reality of large language models (LLMs), as explained in “Large Language Models explained briefly” by 3Blue1Brown, published on November 20, 2024. The video illustrates how these models, much like a scriptwriter, predict subsequent words by assigning probabilities to all possible next words. Over time, they train on massive datasets, refining their parameters to generate fluent dialogue. The introduction of transformers by Google in 2017 revolutionized this process by allowing models to process text in parallel, enhancing their performance. This breakthrough is not without its challenges. The computational power required is enormous, taking over 100 million years to train some models at traditional processing speeds. Moreover, the complexity of these models means their decision-making process is often opaque, posing questions about their reliability and the potential for biases. Nonetheless, LLMs hold transformative potential, making advancements in AI conversations exciting yet demanding our scrutiny.