A groundbreaking achievement in the field of scientific discovery has been made by researchers at Carnegie Mellon University. For the first time ever, a non-organic intelligent system called “Coscientist” has successfully designed, planned, and executed a chemistry experiment autonomously, according to a report published in the journal Nature. This remarkable development is expected to pave the way for a new era of scientific research, bringing about unforeseen therapies, discoveries, and the creation of new materials.
The Coscientist system, developed by Assistant Professor of Chemistry and Chemical Engineering Gabe Gomes and doctoral students Daniil Boiko and Robert MacKnight, utilizes large language models (LLMs) like OpenAI’s GPT-4 and Anthropic’s Claude to carry out the entire experimental process based on simple, plain language prompts.
One potential application of Coscientist is its ability to find compounds with specific properties. Upon receiving a prompt from a scientist, the system scours the Internet and available documentation data, synthesizes the information, and devises a course of experimentation using robotic application programming interfaces (APIs). The generated experimental plan is then executed by automated instruments. Working in collaboration with Coscientist, human researchers can design and conduct experiments much faster, with improved accuracy and efficiency compared to working alone.
National Science Foundation (NSF) Chemistry Division Director David Berkowitz lauded Gomes and his team’s achievement, referring to Coscientist as a “hyper-efficient lab partner” due to its capability to seamlessly integrate various tasks. In their research published in Nature, the team demonstrated that Coscientist can plan the chemical synthesis of known compounds, navigate hardware documentation, issue high-level commands to cloud labs, control liquid handling instruments, complete tasks requiring multiple hardware modules and diverse data sources, and solve optimization problems by analyzing previously collected data.
The integration of LLMs in Coscientist is set to overcome a significant barrier to utilizing automated labs – the requirement for coding skills. By allowing scientists to interact with automated platforms using natural language, Coscientist opens up opportunities for researchers across academic institutions, democratizing access to advanced scientific research instrumentation that is typically only available at top-tier universities and institutions. This would enable greater participation and collaboration in scientific endeavors.
To demonstrate Coscientist’s potential in executing experiments in an automated robotic lab, the Carnegie Mellon researchers partnered with Emerald Cloud Lab (ECL), a remotely operated research facility founded by Carnegie Mellon alumni. This collaboration showed that Coscientist can successfully conduct experiments in a remote-controlled automated lab.
Building on this groundbreaking work, Carnegie Mellon, in partnership with ECL, plans to establish the first university-based cloud lab in early 2024. The Carnegie Mellon University Cloud Lab will grant researchers and collaborators access to over 200 pieces of equipment. Professor Gomes intends to further develop the technologies described in the Nature paper, enabling their integration with the Carnegie Mellon Cloud Lab and other self-driving labs in the future.
Furthermore, Coscientist offers transparency in the experimental process. It meticulously documents each step, ensuring the research is traceable and reproducible. This feature will be crucial in facilitating collaboration and knowledge sharing within the scientific community.
Kathy Covert, director of the Centers for Chemical Innovation program at the U.S. National Science Foundation, emphasized the potential impact of systems like Coscientist in improving the synthesis of new chemicals. The datasets generated through these systems will be reliable, replicable, reproducible, and reusable by other chemists, greatly amplifying their impact.
While recognizing the significant benefits of AI-enabled science, Gomes also emphasizes the importance of addressing safety concerns associated with large language models. The team conducted investigations to assess the possibility of the AI being manipulated into creating hazardous chemicals or controlled substances, prioritizing the ethical and responsible use of these powerful tools.
By leveraging the vast potential of large language models in advancing scientific research while implementing fail-safes and ethical guidelines to mitigate risks, the scientific community can continue to explore new horizons in discovery and innovation. Coscientist represents a major leap forward in autonomous scientific experimentation, ushering in a new era of collaboration between humans and machines.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
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