Creating Intelligence
NSF Center for Big Learning
Recent advances in machine learning are ushering in a new era in intelligent computing. The NSF Industry/University Collaborative Research Center for Big Learning (CBL) at the University of Oregon (UO) aims to design novel algorithms and develop efficient systems for deep learning applications in the era of big data. CBL will catalyze diverse expertise of faculty members, students, industry partners, and federal agencies to create state-of-the-art deep learning methodologies, technologies, and applications across broad domains of business, healthcare, and Internet-of-Things. CBL will provide training for new scientists and graduate students, as well as a rich environment for cross-disciplinary engagement.
The CBL consists of four founding sites geographically distributed across the country: University of Florida (UF, South) as lead; Carnegie Mellon University (CMU, East); University of Missouri at Kansas City (UMKC, Central); and University of Oregon (UO, West), with more than 60 multidisciplinary faculty members and more than 40 industry partners.
An AI masters clinical medical knowledge at the level of certified doctors through a human-like learning process and can provide help with clinical diagnosis based on EMRs.
The workshop is hold by NVIDIA Deep Learning Institute (DLI) on November 29 during NSF CBL Semiannual Meeting. It trains developers, data scientists, and researchers on how to use artificial intelligence and accelerated computing to solve real-world problems across a wide range of domains.
CBL Semiannual Meeting (Fall 2018) will be held at the University of Oregon’s Ford Alumni Center on November 27 and November 28, 2018.
The Center for Big Learning is being launched with a $750,000 grant from the National Science Foundation.
CBL Kickoff Meeting will be held at the University of Florida’s Emerson Alumni Hall on May 31 to June 1, 2018.
