How LLMs Actually Work

Seventy years ago, a handful of scientists promised that within a generation, machines would think like humans. They were wrong by decades — and the whole enterprise collapsed completely, twice, so thoroughly that researchers themselves called it a "winter."

This audiobook follows the real path to today's ChatGPT: how artificial intelligence became machine learning, how machine learning became deep learning, and how a two-thousand-seventeen paper titled "Attention Is All You Need" gave today's language models their engine. No math required — just analogies that show what it actually means for a machine to "learn," why it "lies" with total confidence, and why even its own creators can't always predict what it will do next.

Then the numbers that show where we actually stand today: fifteen trillion words of training data, nuclear plants restarting exclusively for data centers, a Nobel Prize in Chemistry awarded to an AI tool, and humanoid robots learning to make coffee in a matter of hours. The book doesn't take a position on where all this leads — it shows you the facts, and the open questions, and lets you decide.