I Built a Self-Improving AI, and So Can You
Experiments in using AI to build AI show that the future doesn’t just belong to the frontier labs.
These days, the frontier AI labs are all racing to build self-improving models . Some believe it’s the surest route to superintelligence —as AI improves itself in a mind-melting loop, the thinking goes, it will eventually surpass human comprehension (and perhaps even control).
After a week or so of experimenting, the answer appears to be a resounding—and surprising—hell yes. What’s more, dabbling with self-improving models shows a different vision for how AI might unfold—one that doesn’t center on a handful of companies that control the whole industry.
To get my feet wet, I experimented with training a small language model from scratch—by which I mean I dumped all the hard work on Claude’s plate.
I installed AutoResearch , which helps an off-the-shelf AI model build and improve a smaller model. AutoResearch is the brainchild of Andrej Karpathy , a superstar AI researcher who helped found OpenAI, led AI work at Tesla, and recently joined Anthropic.
I fired up Claude and gave it the recommended instruction: “Hi, have a look at program.md and let's kick off a new experiment!” While Claude did the hard stuff, I provided silicon (an Nvidia DGX, a desktop “supercomputer” designed for AI experimentation), the electricity (running hot for a few days straight), and a possibly ill-advised willingness to let the model skip all the usual permission checks in order to do its thing (let him cook!)
I checked in on the AutoResearch project every few hours and marveled as Claude adjusted parameters and training regimes, looked at how this changed the smaller model’s output, and went on refining it further.
