The Select Committee on Artificial Intelligence outlined ways agencies can approach commercial cloud computing for research and development.
The Select Committee on Artificial Intelligence—an interagency group of AI experts across the federal government—issued several recommendations Nov. 17 regarding how agencies can better tap cloud computing resources for research and development efforts.
The report makes clear cloud computing provides “robust, agile, reliable and scalable computing capabilities” that augment existing AI technologies. However, while cloud computing is near ubiquitous in the private sector, there are still “several technical and administrative challenges” limiting cloud adoption in other arenas, including federal agencies’ research and development areas. Gaining access to cloud computing varies across the federal landscape, and best practices differ depending on environments, according to the report. In addition, “limited access to education and training opportunities” for researchers themselves limit how well they make use of cloud environments.
The committee—at the direction of President Trump in a 2019 executive order—identified four key recommendations regarding how government can address these challenges:
- Launch and support pilot projects to identify and explore the advantages and challenges associated with the use of commercial clouds in conducting federally funded AI research.
- Improve education and training opportunities to help researchers better leverage cloud resources for AI R&D.
- Catalog best practices in identity management and single-sign-on strategies to enable more effective use of the variety of commercial cloud resources for AI R&D.
- Establish and publish best practices for the seamless use of different cloud platforms for AI R&D.
The White House established the select committee of federal AI experts in May 2018. It is chaired by the White House Office of Science and Technology, along with the National Science Foundation and Defense Advanced Research Projects Agency.
NEXT STORY: Army-Funded Algorithm Decodes Brain Signals