Inspired by recent community math efforts, I've open-sourced my work on Maximum Agreement Forest: splitting evolutionary trees into the fewest matching pieces, useful for studying gene transfer between bacteria and hybridization in plants, among other applications. Point your agents towards my repo and help improve the current state of the art.

I'm experimenting with mapping out all the ongoing community efforts to improve, validate, or extend the mathematical results OpenAI released earlier this week. Check it out below! math-frontier-atlas.netlify.…

Thanks everyone for the feedback, the integer multiplication tracker now has a zoom feature, so hopefully you will be able to see the most recent progress better! Let me know in the comments if you have other ideas to add! beyond-n-log-n.netlify.app

I've just made a live tracker for the community effort for optimizing the "Integer multiplication below n log n" mathematical problem, so everybody can see the progress on it: beyond-n-log-n.netlify.app

I've made a Valheim bot that uses Open Jev for system 1, and gpt-luna for system 2 thinking. Its joined brain can be visualized and you can observe as it makes decisions in real time.

One of the reasons I'm optimistic about AI progress is that it unlocks our creativity in new ways to communicate our research: over the weekend I built a working 3D video game for fun that lets you control a miniature spaceship inside a cancer cell, grabbing proteins and letting the original algorithm used in our synthetic lethality project calculate the probability of those being a good candidate for further evaluation. Funnily enough, this is a super inefficient way to run the algorithm, but it's a good way to show what our research is about to people who are not familiar with the field, instead of just showing a graph or a list of numbers. And if you are lucky, you can actually pick the right combination, but good luck, there are around 400 million to choose from. Some technical details: - Okay, to be fair, it was codex from OpenAI and gpt 5.6-sol-xhigh that built the game, I just supplied the vision, the general direction and encouraged the AI on the way. I have zero expertise in game or 3D asset development, but this is also kind of the point. - All assets, animation, textures were generated by codex. The whole build time was around 4 hours, and utilized ~30 subagents - I used @mattshumer_ 's Gauntlet Loop for sub agent orchestration, link to it is in the comments - The game currently does not use real physical simulations on how the molecules move in the cell, very limited amount of genes/proteins to pick, etc, and is illustrative at this point. If there is interest I'll keep working on it and open-source it so anybody can try it out. What do you think about this approach to communicate research? What will you build?

I built a debugger and visualization platform for deep and wide recursive agent swarms, so you can monitor how your harness evolves in real time. RLM Agent Observatory shows topology, execution history, per-agent output, causal traces, and learned knowledge in one live view. Focusing on Prime Agent today, but more frameworks coming next. 🧵