The National Science Foundation has developed Community Research Infrastructure in Computer and Information Science and Engineering (CCRI). The shared research infrastructure provided access for researchers and students in artificial intelligence from around the U.S.
To enable knowledge-sharing and collaboration tools in the community that improve and grow the nation’s cutting-edge AI workforce, the universities will collectively give researchers and students hands-on training and educational opportunities.
Around US$16.1m fund has been allocated to five joint initiatives spearheaded by faculty at the Universities of Central Florida, Pennsylvania, Minnesota, Twin Cities, UCLA, and Pennsylvania State. They will research high-quality information on human-machine interactions in team settings, autonomous vehicles, and news recommendations. The transformational resources’ projects will include platforms for conducting artificial intelligence research on social robotics and immersive virtual environments.
“A key aspect in the success of the AI research revolution is ensuring that researchers have access to the data and platforms they need to continue driving innovation and scalability in AI technologies and systems,” NSF Director Sethuraman Panchanathan emphasised. Since cutting-edge research in artificial intelligence is what drives innovation, “this infrastructure must be available to a full breadth and diversity of talent interested in AI R&D.”
Autonomous driving artificial intelligence research was boosted by UCLA’s open-source simulation platform. The project’s researchers hope to create a flexible driving simulation environment that will encourage new developments in several areas of autonomous driving. Most current research on autonomous driving is conducted on high-priced commercial vehicles, an inefficient and potentially dangerous way to test AI and ML systems. New artificial intelligence algorithms for autonomous driving will be developed and evaluated risk-free and efficiently using the team’s proposed driving simulator infrastructure.
On the other hand, The University of Central Florida-led Virtual Experience Research Accelerator (VERA) project will prioritise the pooling of resources for conducting studies in extended reality (XR) settings such as virtual reality, augmented reality, and mixed reality. With the help of VERA, researchers from all over the country will be able to conduct high-impact research, regardless of their proximity to XR labs and equipment, thanks to its collaborative design with and for the XR community.
Researchers hope to establish a shared environment for studying AI and robots using standardised infrastructure. The project aimed at Unifying, Expanding, and Sustaining a Research Community Around a Modular Social Robot Platform led by the University of Pennsylvania. This project aims to facilitate online data collecting, collaboration, and the development of novel approaches to AI decision-making by constructing and distributing fifty humanoid robots to research teams around the United States. The group aims to build a network of cooperative roboticists who can teach and be taught by one another.
Researchers also aim to create a centralised news recommendation platform that can be used by academics throughout the country to observe and analyse real-time, one-off, and repeatable interactions between humans and AI. Based on previous actions, the system tailors the user’s experience. Through mechanisms such as an online shopper’s product rankings and recommendations based on their previous purchases, recommender systems can have far-reaching effects. Most online news sites are backed by recommender algorithms, influencing which stories readers see. Given the significance of these systems, researchers must have the means to conduct experiments to compare various algorithm and interface designs and their effects on end users. ‘Experiments on News Recommender Infrastructure, Algorithms, and User Interfaces were conducted with real people’ will be led by the University of Minnesota, Twin Cities.
An Open Data System for Analysing Nonverbal Expressions of Emotion: Penn State spearheads a project to analyse online videos to learn more about how people express themselves. The infrastructure built for this research has the potential to significantly enhance the study of sentiment and emotion analysis using non-text inputs, which have yet to be studied. When dealing with human subjects, the interdisciplinary research team will consult research ethics specialists to ensure all bases are covered.