IBM pledges $240 million for joint AI lab with MIT

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IBM and MIT are working together to conduct broad research about artificial intelligence with a new joint lab announced today. The MIT-IBM Watson AI Lab will be focused on four research pillars: developing AI algorithms, using physics to create new hardware for AI computation, applying AI to specific industries, and evaluating how AI will affect society.

The idea behind the partnership is to perform research that will be foundational to new artificial intelligence breakthroughs. IBM researchers will work with MIT researchers through the lab, in contrast to both organizations’ independent research efforts into AI.

As part of the agreement, IBM will contribute $240 million over 10 years to the lab, which will operate in addition to and in partnership with IBM’s existing research organizations including the Media Lab and the Computer Science and Artificial Intelligence Lab (CSAIL).

IBM Research vice president Dario Gil said that IBM and MIT plan to publish the fruits of the research from the AI lab, and he expects that the group there will also contribute extensively to open source AI projects. The intellectual property produced at the lab will be jointly owned by MIT and IBM. IBM will have an option to use what’s developed there in its commercial products.

IBM and MIT will also encourage the creation of startups to commercialize the research created in the lab. IBM won’t place preconditions on the resulting businesses, according to Gil, though the company will be free to invest in, collaborate with or acquire them like any other firm.

IBM isn’t the only company pouring resources into core AI research. Deepmind, a startup acquired by Google in 2014, has been working on a wide variety of foundational research. OpenAI, a non-profit group backed by Elon Musk, Microsoft, Amazon Web Services, Peter Thiel, Reid Hoffman, Jessica Livingston, and others, has taken a similar approach.

What sets this new lab apart is the cross-disciplinary nature of its forthcoming research, according to Gil. He sees research projects working across its four pillars, and not being soloed to one particular area. What’s more, those areas of research will require input from physicists, economists and other disciplines outside the scope of traditional AI expertise.

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