It felt like an overnight arrival
In November 2022 a chatbot was put on a public website. Within two months it had a hundred million users, which was faster than anything before it. To almost everyone it looked as though AI had been invented that winter.
It had not. Three separate things had been building, and one of them finally reached the public.
One: a design from 2017 that could be scaled
In 2017 a group of researchers published a design for handling sequences of words called the transformer. Its important property was not that it was cleverer in some abstract way. It was that the work could be split across thousands of chips running at the same time, instead of having to grind through a sentence word by word.
That sounds like an engineering detail. It was the whole thing. It meant that throwing more money and more chips at the problem now translated into better models, which had not reliably been true before.
Two: scale did not run out of steam
Through 2018 to 2022 the models got bigger, the training text got bigger, and the electricity bills got enormous. The expectation was that this would plateau. Mostly it did not. Quality kept climbing, and abilities appeared that nobody had specifically built in, like writing usable code or handling a language that barely featured in training.
This was a surprise to the field, and it is worth sitting with. The recipe was not a new idea about the mind. It was the same idea, made very large. That is uncomfortable for people who expected intelligence to require a deeper insight, and it is a real reason the last few years have been hard to predict.
Three: a text box with no manual
Here is the part usually missed. A comparably capable model, GPT-3, had existed since 2020. It was available to developers with an account and some code. Almost nobody outside that world ever touched it.
What arrived in November 2022 was not a more powerful model. It was a doorway: a free web page, a box, no instructions, no setup, no jargon. Your aunt could use it, and did.
So the thing everyone noticed was access. The thing underneath it was scale. Those are different events, and collapsing them is how people end up believing a scientific miracle occurred in one particular quarter.
What follows from getting this right
Progress here is partly an industrial story. Chips, data centres, electricity, water, capital. Whether the next jump happens depends as much on supply chains and power grids as on ideas. That also means the number of organisations that can build a frontier model is small, and it is worth noticing who they are.
Sudden visibility is not sudden capability. The same gap exists right now. Things that will feel like an overnight arrival in three years are already working in labs and behind developer accounts today.
The pace is genuinely disputed. Some serious researchers think scaling continues to deliver for years. Others think the useful text has largely been used and the returns are already bending. Both camps are made of people who understand this far better than any confident article you will read. If someone tells you which way it goes, they are guessing with more vocabulary than you.
Before you move on