Periodic Labs, a groundbreaking startup, has emerged from stealth mode with an impressive $300 million seed funding round aimed at creating robotic AI scientists capable of conducting experiments independently. This ambitious undertaking aims to automate scientific discovery, with a focus on materials development and chemical research.
Among them, legendary investors and proponents of sustainability Bill Brown and Howard G. Current AI notable backers included Andreessen Horowitz, DST, Nvidia, Accel, Elad Gil, Jeff Dean, Eric Schmidt, and Jeff Bezos. This strong infusion of financial support is an important signal of the expanding desire to leverage powerful AI capabilities to accelerate scientific discovery.
Periodic Labs is on a mission to create the world’s best AI scientists. Pioneering our mission forward, these scientists will be working in autonomous laboratories – self-driving labs. Their goal is to better address hard-to-solve scientific problems while accelerating the supply of new and improved materials. Specifically, the goal includes developing new superconductors that are better than today’s tech, as well as less energy-intensive to create.
Periodic Labs isn’t the only ones on this path, either. At the University of Toronto’s Acceleration Consortium, members have been studying similar efforts for months. Google Brain and DeepMind previously had an artificial intelligence materials and chemistry team under Cubuk. He led a collaborative AI project, known as GNoME, which was meant to advance scientific research through the use of AI.
The transformative potential of AI in science as a whole is already at our doorstep. In just 2023, researchers have discovered more than two million new crystals through AI-based techniques. These inventions are an exciting step towards powering the next generation of technology. Until recently, most progress towards scientific AI has resulted from models trained on the web. There is a rising swell of acknowledgment about the shortcomings of these models.
“Until now, scientific AI advances have come from models trained on the internet,” said a spokesperson from Periodic Labs. “We have exhausted this source.”
This new paradigm toward creating dedicated AI systems represents a major evolution in the ways that scientific research can be done. By leveraging innovative technologies beyond traditional web sources, Periodic Labs hopes to push the boundaries of material science and chemistry.
The implications of this research are vast. Novel superconductors would upend entire industries by dramatically increasing energy efficiency and performance. Periodic Labs is doing outstanding work on this front. The team remains committed to its original core mission though: developing autonomous AI scientists capable of exploring the uncharted territories of science.