ARC-AGI-3 is the latest challenge in Francois Chollet’s ARC Prize. While currently still under development, the authors released a sample of the challenges and are running a small competition. In this post I’d like to discuss my attempt at ‘hand-writing’ some solutions and what it told me about a real solution. If you’d like to know more about the ARC-AGI-3 challenge, I previously wrote about it here.

When we write code we typically leverage something like Git or Mercurial to track changes we make to files. These systems make it easy to see what has changed at a glance without picking through every line of code. Personally, I use VSCode’s Git integration. But who writes code themselves these days? When producing code with LLMs we still want to be able to track diffs easily.

I’ve been a long-time user of Notion for knowledge management. For reference, I have around 1000 pages covering various topics from physics, to sports, to dreams and aspirations. I manage my to-do lists there, travel plans and goal tracking. It’s a terrific visual tool and readily accessible everywhere. But I want more.

Recently I ran an experiment in which I tried to get LLMs to output explicit world models in the form of Python code which could be used as the core of a MCTS policy for control in basic gymnasium environments. This is different to typical world model learning which would be something like a parameterised neural network. The reason why we would care about something like this is for on-the-fly reasoning, such as in ARC-AGI-3 where agents must act in a completely new environment.

ARC-AGI 2 was just released in March, but we’re already getting an announcement of the upcoming ARC-AGI 3, a benchmark said to be the next step on the way to AGI. The expected release date is early 2026, with beta testing about to begin.

AI 2027 was recently released and is another great forecast of how the next few years could play out, similar to another favourite of mine, Situational Awareness. While listening to the authors on the Dwarkesh Podcast I tried to look a bit deeper on my own thoughts. Why do I also believe AGI is coming soon? Why does it still seem so fantastical, despite my belief? To help myself, I decided to jot down the key points that have influenced that thinking. It’s far from an exhaustive list, but are some of the latest facts that help me to stay grounded in my predictions.