Enthought CEO Dr. Eric Jones and President Bill Cowan were recently invited by the UK government to participate in a timely conversation around artificial intelligence and computational science and engineering with the world’s leading researchers from the renowned Alan Turing Institute and the Oden Institute. At the January event held in London, Jones and Cowan were asked to provide insights on the scientific application of digital twins and the challenges of translating research to value in industry.

“Scientific research in academia is critically important because there is a freedom to test and explore that doesn’t necessarily exist in the business world,” said Cowan. “What’s learned in academic settings can seed innovations in industry that change the world.” Cowan also shared that while research can greatly expand the body of knowledge, successful application in industry requires a change in mindset and strategy. 

R&D for science-driven companies should focus on what brings value to the business, requiring setting different goals and incentives, accelerating timelines through optimized workflows, and upskilling scientists to leverage modern tools like machine learning and AI. One key challenge is the ability to translate between the science and technical domains, all while prioritizing business value, particularly when those knowledge sets are siloed within the organization. Cowan noted that this translation interface is where Enthought has seen customer’s historical failures and a key place where our approach has had a tremendous impact. 

Similar themes were discussed by Jones on the “Spotlight on Digital Twins Research” panel. “There’s a lot of interesting science we can do, and companies today are sold on the latest technologies like artificial intelligence and digital twins,” said Jones. “But most are not seeing ROI because they’re not focused on the business value. The science is clearly important, but it’s only one part of the bigger picture.”

Jones emphasized how the approach to scientific research and innovation, in both academia and industry, needs to move from being human-centric to compute-centric. Human-centric research is built around the limitations of humans, with the goal of making the next new discovery. When research and development is compute-centric, not only are the traditional limitations lifted, the purpose of the research sits at a higher level—to build intuition in order to make new discoveries continually. Most research labs are not set up for the compute-centric approach, not yet “future-proofed,” but more and more science-driven companies are prioritizing and investing in more holistic technology initiatives like digital transformation to be competitive. 

The London event concluded in strong agreement that continued conversations are critical to advancing what’s possible in AI and computational science and engineering. “Enthought has been helping companies solve their complex scientific challenges for over 20 years,” said Cowan. “Collaborations with our academic counterparts only strengthen the field and our work to digitally transform science.”