Imagine creating an artificial intelligence whose only purpose is to discover how to build a better artificial intelligence. It sounds like science fiction, but that is exactly what startup Weco AI claims to have achieved with AIDE².
According to the company, the system spent eight days working on its own and ended up outperforming a version researchers had spent two years manually refining. If the results are confirmed by independent groups, this could become one of the first practical examples of Recursive Self-Improvement (RSI).
Until now, virtually every major advance in artificial intelligence has followed a familiar cycle: researchers develop new techniques, train models, analyze results, and repeat the process over and over. AIDE² attempts to change that logic.
While one agent solves AI research problems, another observes its work and tries to discover ways to make it more efficient. Instead of leaving all the improvements to engineers, the AI itself takes part in that process.
Weco AI claims that, after around 100 optimization cycles, the system created seven progressively better versions of itself. Besides improving performance across different tasks, it also reduced a known problem called reward hacking, where an AI learns to "cheat" an evaluation instead of actually solving the challenge.
Before imagining an artificial intelligence about to take control of the world, the researchers themselves are quick to push back on that idea: that's not what happened here.
The company classifies the result as an example of RSI Level 1, within a four-level scale proposed by its researchers.
Level 0: AI still improves more slowly than human researchers.
Comments (0)
Comments are moderated and if they violate our Terms and Conditions of use, the comment will be deleted. Persistence in violation will result in a ban of your account.