Introduction
The goal of C3.ai DTI is to develop the field of Digital Transformation Science by supporting its intellectual growth, facilitating its translational application, and leveraging laboratory and research facilities at UC Berkeley, UIUC, and consortium institutions.
C3.ai DTI’s research focuses on the intersection of artificial intelligence, machine learning, Internet of things, cloud computing, big data analytics, economics, organizational behavior, public policy, and ethics. C3.ai DTI research analyzes new business operation models, develops methods for organizational change management, investigates methods for protecting privacy, and advances dialog related to the ethical implications of AI. Central to the Institute’s research is the development and validation of algorithms and designs that can dramatically improve societal systems, for example, in healthcare, transportation, education, and national security.
Funding
C3.ai DTI is funded over the first five years with a $57,250,000 cash pledge from C3 AI and $310 million in Azure and C3 AI compute, storage, processing, and AI resources, totaling $367,250,000 in cash and in-kind funding. In addition, significant scientific supercomputing resources are being made available by the National Center for Supercomputing Applications (NCSA) at UIUC and Lawrence Berkeley National Laboratory’s National Energy Research Scientific Computing Center (NERSC). Annually, C3.ai DTI will fund approximately 26 projects, up to $500,000 each, proposed by scientists affiliated with the DTI consortium and selected through a call for proposals managed by UC Berkeley and UIUC. The university leads and an external program committee will review the proposals and make the awards, in consultation with the Advisory Board.
Award Criteria
Projects will be reviewed on the basis of their scientific merit; prior accomplishments by the principal investigators and co-principal investigators; the use of AI, machine learning, data analytics, and cloud computing; potential for impact; and suitability for testing the methods at scale. Interdisciplinary and multi-institution projects will be favored. Recipients will be encouraged to conduct breakthrough research and to pursue and establish larger research projects with federal and other funding sources. Award recipients will disseminate the results of their research during the award period, and all research results, methods, and algorithms, including algorithms and software, will be made available in the public domain (non-exclusive royalty-free).