As an MIT graduate and senior leader within IBM Research, I have always felt a close kinship between these two institutions. Both are renowned for their technical excellence, and both are strongly committed to pushing the frontiers of science and technology to solve problems that matter to the world. MIT’s motto “Mens et Manus” (Latin for mind and hand) echoes our values here at IBM, to leverage the talent we have and create real technology with impact. That is why I am so excited about the creation of the MIT-IBM Watson AI Lab, the partnership we have formed spanning the next 10 years, through which we will achieve fundamental scientific breakthroughs at the heart of AI today and into the future.
The official seal of MIT, depicting its motto “Mens et Manus,” which is Latin for mind and hand.
Together with our fellow scientists at MIT, we selected four key pillars for our collaboration: core algorithmic advancements that enable learning and reasoning to broaden what AI systems can do, computational innovations tailored to AI and achieved through a mastery of physics, applications of AI to important domains like healthcare and cybersecurity, and achieving shared prosperity through AI technology. Each one of these areas touches upon our fundamental beliefs about the future of AI and where we believe it can and should go. And all four leverage technical strengths shared across MIT and IBM.
AI technology today has been extraordinarily successful at performing individual tasks effectively, though with considerable effort and oversight by the people who train the models. Through this collaboration, we will target innovations that will move us beyond specialized tasks to more general approaches to solving more complex problems, with the added capability of robust, continuous learning. We will explore not only how to best leverage big data when available, but also learn from limited data to personalize and augment human intelligence.
Today, it takes an enormous amount of time to train high-performing AI models to sufficient accuracy. For very large models, it can be upwards of weeks of compute time on GPU-enabled clusters. That’s why we selected the Physics of AI as a critical area to explore in partnership with MIT. Our teams will explore new materials, devices and architectures for analog AI computation, as well as the intersection of quantum computing and machine learning. The latter involves both 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.
While a significant amount of the work we plan to do together is focused on achieving fundamental scientific breakthroughs, we are also extremely committed to leading in the application of AI to solve crucial problems in healthcare and security. And given the value of face-to-face collaboration, the fact that Watson Health and IBM Security headquarters are in Kendall Square, just a few blocks from MIT, puts us in a great position to make strides in these areas.
Finally, through our partnership with MIT, we will pursue an agenda of advancing shared prosperity through AI to achieve broad economic and societal benefits for the largest number of people. Some of the questions we’ll address together include the creation of AI systems that can detect and mitigate human biases, building trustworthiness and explainability into AI systems, ensuring that AI systems complement worker skills that might be in short supply and exploring how productivity gains will be distributed across firms, workers and consumers. We intend to build upon the Principles for the Cognitive Era that we laid out earlier this year, as well as our work as a founding member of the Partnership on AI, a consortium that focuses on guiding the development of AI to the benefit of society. As the creators of this technology, we take responsibility for ensuring that it is developed the right way and for the right reasons.
To add to our enthusiasm around each one of these pillars individually is our belief that bringing them all together will offer profound opportunities. We intend to develop the next generation of AI algorithms using accelerated computation, achieved through our mastery of physics, which we apply ethically and in pursuit of shared prosperity, e.g. for better health outcomes and a safer future. It is an exciting time to be involved in AI research, and an even more exciting time for MIT and IBM. I know we will build amazing things together, and I sincerely look forward to sharing them with the world.
To tackle bias in AI, our IBM Research team in collaboration with the University of Michigan has developed practical procedures and tools to help machine learning and AI achieve Individual Fairness. The key idea of Individual Fairness is to treat similar individuals well, similarly, to achieve fairness for everyone.
MIT Brain and Cognitive Sciences, in collaboration with the MIT-IBM Watson AI Lab, has developed a new Embodied AI benchmark, the ThreeDWorld Transport Challenge, which aims to measure an Embodied AI agent’s ability to change the states of multiple objects to accomplish a complex task, performed within a photo- and physically realistic virtual environment.
To better simulate how the human brain makes decisions, we’ve combined the strengths of symbolic AI and neural networks. Specifically, we combined the learning representations that neural networks create with the symbol-like entities represented by high-dimensional and distributed vectors. The idea is to guide a neural network to represent unrelated objects with dissimilar high-dimensional vectors.