Analysis
This insightful article breaks down the inner workings of Large Language Models (LLMs), revealing their surprisingly simple mechanics. It offers a clear, visual explanation of how these models generate text, making the complex world of AI more accessible and understandable.
Key Takeaways
- •LLMs function by selecting the next token based on probability, not understanding.
- •Self-attention enables LLMs to consider relationships between all tokens, mimicking understanding.
- •LLMs are best suited for pre-decision tasks, like structuring ambiguous text or generating drafts.
Reference / Citation
View Original"LLM = converter of context → probability → generation"