As humans struggle to keep up with the tens of thousands of new scientific research papers that are now submitted to archives and journals each year, one startup says we should quit while we’re behind. Autoscience, part of the wave of so-called autonomous labs that have cropped up using AI to improve AI, has developed a system of agents that read publicly available research papers, plug into companies’ machine learning tools, and run experiments to improve models.
“Reading 10 papers a week is very hard. AI systems can read 17,000 and figure out which ones were relevant for your specific modeling problem,” Autoscience CEO Eliot Cowan told Semafor.
We’ve already passed the threshold of having too many papers for humans to parse through — an issue researchers already need AI to solve, he said.
The company, which just raised $14 million in seed funding from General Catalyst, Toyota Ventures, and Perplexity Fund, is among a growing number of self-driving labs that are drawing investor attention for their ability to use technologies that reason on new hypotheses. OpenAI began experimenting with the technology, and a Singapore-based lab running pharmaceutical and biotechnology experiments raised $45 million in December.
