The National Science Foundation (NSF) recently released news impacting one of our labs, and quite possibly the future of computing and information technologies. The NSF’s Directorate for Computer and Information Science and Engineering (CISE) granted a major award to Stanford University’s Department of Applied Physics in support of its work to gain a deeper understanding of the nature and uses of Coherent Ising Machines (CIMs).
We’re excited about this for a few reasons. First, we’re pleased for our friends and colleagues at Stanford and the other institutions (Caltech, Cornell, Microsoft, NASA, NII in Tokyo, and USRA) associated with this project. The CISE Expeditions in Computing awards are granted every few years to a small handful of projects. This is a tremendous honor for the Stanford-led team.
Another reason is that the award is a kind of validation. The NSF’s peer-review process represents a consensus decision on what merits funding. To that end, let’s recognize this year’s other five-year, $10 million Expeditions awards: one went to a very timely UVA-led initiative to study global pervasive computational epidemiology; the other, to an MIT-led team looking at how better to leverage code to generate scientific theories from data. Both very worthy areas of research. The potential of CIMs to transform computing stands in this same circle, and the award to the Stanford-led team implicitly endorses foundational work that NTT has done, going back to our proposal of coherent optical communications four decades ago.
At NTT Research, we not only stand on the shoulders of giants who have led the way, we have one of those pioneering scientists on our team. The director of our PHI Lab, Professor Yoshihisa Yamamoto, who will serve as an unfunded external collaborator with the CIMs Discoveries team, is one of the key innovators of the CIM-based approach to computing.
To further explore CIMs and the intersection of quantum physics, neuroscience and optical technologies, NTT Research has to date established joint research projects with eight collaborating institutions. But we can only do so much. That’s another reason we’re happy to have seen this news. This NSF support of related research indicates that a de-facto public-private investment strategy is driving the potential breakthroughs that CIMs may deliver. While investment – including funds for basic research – is always good at the macro level, on the micro level, you never know for sure. Some projects dead-end, others flourish. Yet these NSF decisions represent a few safe bets. In the years ahead, maybe partly as a result of this funding, we are likely to see advances in how we track and understand infectious disease; how we can use machine learning to improve the very process of scientific discovery; and what our most advanced computing infrastructure will look like, how it will perform and what problems it will be able to solve.
