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IBM and MIT to Pursue Joint Research in AI, Establish New MIT–IBM Watson AI Lab

By   /  September 8, 2017  /  No Comments

by Angela Guess

A new press release states, “IBM and MIT today announced that IBM plans to make a 10-year, $240 million investment to create the MIT–IBM Watson AI Lab in partnership with MIT. The lab will carry out fundamental artificial intelligence (AI) research and seek to propel scientific breakthroughs that unlock the potential of AI. The collaboration aims to advance AI hardware, software and algorithms related to deep learning and other areas, increase AI’s impact on industries, such as health care and cybersecurity, and explore the economic and ethical implications of AI on society. IBM’s $240 million investment in the lab will support research by IBM and MIT scientists. The new lab will be one of the largest long-term university-industry AI collaborations to date, mobilizing the talent of more than 100 AI scientists, professors, and students to pursue joint research at IBM’s Research Lab in Cambridge—co-located with the IBM Watson Health and IBM Security headquarters in Kendall Square, in Cambridge, Massachusetts—and on the neighboring MIT campus. For information about employment opportunities with IBM at the new AI Lab, please visit  MITIBMWatsonAILab.mit.edu.”

The release continues, “The lab will be co-chaired by IBM Research VP of AI and IBM Q, Dario Gil, and Anantha P. Chandrakasan, dean of MIT’s School of Engineering. IBM and MIT plan to issue a call for proposals to MIT researchers and IBM scientists to submit their ideas for joint research to push the boundaries in AI science and technology in several areas, including: (1) AI algorithms: Developing advanced algorithms to expand capabilities in machine learning and reasoning. Researchers will create AI systems that move beyond specialized tasks to tackle more complex problems, and benefit from robust, continuous learning… (2) Physics of AI: Investigating new AI hardware materials, devices, and architectures thatwill support future analog computational approaches to AI model training and deployment, as well as the intersection of quantum computing and machine learning. The latter involves using AI to help characterize and improve quantum devices, and also researching the use of quantum computing to optimize and speed up machine-learning algorithms and other AI applications.”

Read more at IBM.

Photo credit: IBM

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