Supercharging American Innovation: Harnessing Advances in AI and Robotics to Transform Science

By: Theresa Mayer

Science is being revolutionized by AI. The U.S. has the opportunity to remain a global leader by transforming the way we do scientific research and translate it to high-impact innovations. Carnegie Mellon University researchers are leading the way by harnessing and integrating advances in AI, robotics, and autonomy in new ways to accelerate the pace of innovation.

Why it matters: The journey from basic research to impact often begins in quiet, brightly lit laboratories, where researchers in lab coats conduct controlled experiments using sophisticated instruments. It can take years or decades for their ideas and insights to become proven technologies and solutions.

What if we could significantly shorten that time frame, enabling individuals to move from medical diagnosis to an affordable and accessible personalized therapeutic in less than a week? Advances in AI could make this a reality, greatly reducing the time from lab to market.

  • Countries around the world — from Canada to China — have recognized the huge potential and are making major investments to position them for this paradigm shift.
  • The U.S. must supercharge our national AI infrastructure and research to have the world's best science and technology enterprise and secure our nation’s economic prosperity and security well into the future.

What we’re doing: Carnegie Mellon University is joining with federal agencies and partners across national labs, academia, and industry to spearhead a grass-roots initiative to build a national network of AI-enabled autonomous experimentation laboratories. This project would transform fragmented capabilities into a unified and integrated system that shortens the path from ideation to innovation to impact by dramatically accelerating discovery to translation from decades to months.

How it works: The national network is designed to connect autonomous agents across institutional boundaries, unlocking research spaces inaccessible to traditional approaches while providing broad access to cutting-edge technologies. These labs bring together AI, robotics, and computational workflows with large-scale computing, data storage and access to experimental facilities — all of which work in concert to allow researchers from across the nation to remotely run experiments and collect and analyze data. 

  • This interconnected network of labs would accelerate the speed from idea to innovation, providing solutions to today’s challenges in scientific research, improving reproducibility and transparency, enhancing access and participation across a broad population and fostering interdisciplinary and agile collaboration.
  • The goal is to hypercharge American innovation, shortening the timeframe for scientific problem-solving from decades or years to months or weeks.
  • A network of AI-enabled autonomous experimentation laboratories could help researchers design and deploy bespoke materials, improve screening and prediction of drug toxicity earlier in the pipeline and develop safe and effective replacement materials for forever chemicals in a fraction of the time. 

To bring this vision to life, the U.S. needs to set bold new science priorities and support an integrated and coordinated fabric of computing, data, experimental infrastructure at a national scale, long-term research funding and workforce development programs that train scientists to work alongside AI. U.S. researchers also need new AI-ready data standards, compute capacity and regulatory flexibility to keep pace with the rapid evolution of AI-driven research.

The bottom line: As the global race to automate scientific discovery and translation accelerates, the U.S. must pursue a focused national effort that extends our leadership in basic and applied research.

Go deeper: Read the research paper on the Autonomous Interconnected Science Lab Ecosystem (AISLE) project, and other related work: