Recursive Self-Improvement Shakes the AI Industry

A new startup is pushing the boundaries of artificial intelligence with its latest model, which has impressed even those who were once skeptical of the technology. The company, Recursive, is using a method called fully recursive self-improvement, or RSI, to build AI models that can improve themselves over time. This technique involves using AI to build AI, which has the potential to revolutionize the way we develop and refine AI models. The company's CEO, Richard Socher, claims that his team used an AI system called the Eureka Machine to automate most elements of the model's development. This enabled a small team of researchers to build a world-class model in just a few months.

The Eureka Machine devised a number of innovations, including a new way of training the base model, new model architectures, and code optimized for specific silicon chips. Recursive shared benchmark scores that suggest Flint, the latest model from the company, outperforms other models of similar size and architecture on coding tasks. AI is already widely used to help build, test, and improve AI thanks to its amazing coding skills. This can speed up the process of refining a model and testing new ideas without the need for as much input from humans.

It is also possible to create a loop through which AI decides what improvements to make and then begins another round of improvement. For the moment this technique is limited, but if AI can contribute to every aspect of model development, then the process could theoretically continue indefinitely. Some experts worry that letting AI improve itself in this manner could ultimately lead to disaster. These doomsayers claim that AI capable of improving indefinitely could escape human control and might decide that humans are an impediment to its goals.

Those concerns gained wider notice this September when a researcher quit Anthropic and warned that advances in AI, including recursive self-improvement, could lead to human extinction within a few years, a concern then echoed by a number of other experts. The idea of RSI has become so controversial that several bills in Congress propose to ban it. Recursive sees these fears as more sci-fi than reality and believes legislation to prevent RSI is an unnecessary impediment to progress.

Socher says Flint was built using a system incapable of escaping human control. He says the goal is for the Eureka Machine itself to achieve full recursive self-improvement, but this would still be overseen by humans who could stop the process if it goes awry. “We hope that this shows people that indeed we have all the steps in place” to build such a system, he says. Recursive has raised $650 million at a $4.65 billion valuation from Google Ventures, Greycroft, Nvidia, and AMD Ventures. Socher was previously the chief scientist at Salesforce, and his cofounders include Jeff Clune, a professor at the University of British Columbia who researches ways of building AI systems capable of learning indefinitely.