For years, AI researchers have been anticipating the moment when AI systems will be able to improve themselves better than humans could. With investors pouring money into a new generation of research-driven AI labs, there are more resources than ever available to pursue the goal. Now one of these neolabs has taken a big step towards making it real.
On Wednesday, Adaption introduced a new product called AutoScientist that helps models learn specific properties quickly by using an automated approach to conventional fine-tuning. The techniques can be applied to a wide range of areas, but the Adaptation team is particularly focused on the potential to speed up and ease the process of training and fine-tuning an AI model at a cross-border level.
According to co-founder and CEO Sara Hooker, who previously worked as VP of AI research at Cohere, AutoScientist represents a new way to approach the AI ​​training process. “What’s super exciting about it is that it co-optimizes both the data and the model, learning the best way to learn any skill,” Hooker told TechCrunch. “It suggests that we can finally allow successful frontier AI training outside of these labs”
AutoScientist builds on the company’s existing data offering, Adaptive Data, which aims to make it easier to build high-quality data sets over time. AutoScientist, meanwhile, is designed to turn these continuously improving datasets into continuously improving AI models. “Our position at Adaption is that the whole stack should be completely adaptable and should basically optimize on the fly for the task at hand,” says Hooker.
Of course, that approach will only be as good as the results. In its launch materials, Adaption boasts that AutoScientist has more than doubled the win rate across different models—impressive numbers, but difficult to put into context. Since the system is built to adapt models to specific tasks, conventional benchmarks such as SWE-Bench or ARC-AGI are not applicable.
Still, Adaption is confident that users will see the difference when they try AutoScientist — so confident that the lab is making the tool free to use for the first 30 days after its release.
“In the same way that code generation unlocked many tasks, this will unlock a lot of innovation at the frontier of different fields,” says Hooker.
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