How can an LLM write code? 🤔 How can it come up with ideas? 💡 How can it summarize long documents? 📄
It can feel like AI is “thinking”. But what is actually happening is closer to pattern recognition.
An LLM is like someone who has read millions of crime stories. When you start telling a new one, they can quickly guess what usually happens next. Not because they know the truth, but because they have seen similar patterns many times. 🕵️♂️
The same idea applies to everything else:
💻 Writing code - It has seen millions of code examples and learns common patterns
💡 Coming up with ideas - It has seen brainstorming sessions, strategy docs, and idea lists
📄 Summarizing text - It has seen many examples of long texts paired with shorter summaries
So instead of thinking from scratch, an LLM predicts what a good next response usually looks like, based on patterns learned from a huge amount of text.
In a way, LLMs are extremely powerful pattern recognition engines that learned from human knowledge at scale. 🌍
What analogy do you use to explain AI to non technical people?
Originally posted on LinkedIn.