OpenAI dropped GPT-5.5 a few hours ago. And you’d expect it fits perfectly into the usual AI launch cycle of big labs. You can try it for free in Codex, so go try it and share your thoughts. By the way, in this post I’m going to talk about research from MIT.

GPT-5 starts breaking around 272,000 tokens. If you feed it more, it begins to hallucinate dates, forget the start of your document, and confidently make things up that aren’t there.

But three MIT researchers fed it 10 million tokens and it kept going.

And no, they didn’t tweak the model’s weights or use a new architecture. They simply wrapped GPT-5 in a Python loop and made it talk to itself.

The paper is called "Recursive Language Models." And if you've been reading me for a while, you know why I'm writing about it today.

A few weeks back, I said AGI needed breakthroughs in two specific areas. Continual learning and context. I said context wasn't really a size problem, it was an algorithmic one. That we needed a way to process a million pages as effortlessly as a single paragraph.

This paper might be the first real attempt at that.

Every AI you've used has a ceiling. ChatGPT, Claude, Gemini, whatever. They all have a number. A maximum amount of stuff they can hold in their head at once. That's the context window.

And inside that window, the quality degrades.