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Dear friends,
We hope that you and your family are well and coping in this new era of physical distancing. Like so many others, we are watching the Covid-19 pandemic unfold and looking for ways to contribute. To tap the ingenuity of the MIT community, we and the MIT-IBM Watson AI Lab recently issued a call for AI-related research proposals to address Covid-19 and its economic and social consequences.
In this newsletter we would like to share some work that was in progress before this crisis, and is ongoing, and new work that is emerging as we respond. Please stay in touch and send us your ideas for marshaling AI to confront the challenges ahead.
James DiCarlo, MIT Quest co-director, Science Lead
Aude Oliva, MIT Quest co-director, Application Lead
Nick Roy, MIT Quest co-director, Engineering Lead |
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Using Music and AI to Crack the Coronavirus
MIT's Markus Buehler recently translated the structure of the novel coronavirus into music to visualize its vibrational properties, which could help to pinpoint sites on the protein for antibodies or drugs to target. In this Q&A, Buehler discusses his broader work developing AI models to design new proteins for sustainable, non-toxic applications.
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Uncovering the Hidden Power of Vitamin A
In a new study in Cell Reports, researchers discover that vitamin A palmitate, a common supplement, and gum resin, a popular glazing agent for pills and chewing gum, could make hundreds of drugs more effective, from blood-clotting agents to anti-cancer drugs. “Machine learning gives you a way to narrow down the search space,” MIT's Giovanni Traverso tells MIT News.
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How Green Is Your AI?
Training a big AI model is energy-intensive, but doesn’t have to be. MIT’s first Green AI Hackathon, co-sponsored by the MIT Research Computing Project and our own MIT-IBM Watson AI Lab, drew several dozen students and generated a list of promising ideas for shrinking the carbon footprint of modern AI models. Check out some of the energy-saving hacks.
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Building AI Tools for Impact
Progress in AI is moving rapidly, and MIT's Undergraduate Research Opportunities Program (UROP) gives students a chance to join the action. Last fall, 20 students worked with us, and in other MIT research labs, to improve AI literacy in K-12 education, understand face recognition, and speed up tasks like processing archival material. Meet six of our UROP students.
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Sizing up Patient-Specific Risk
Computer models that predict a patient’s chance of dying after suffering a heart attack or stroke can help doctors prescribe life-saving treatments. But a wrong prediction can be disastrous. A new study co-authored by MIT's Collin Stultz, and funded by the MIT-IBM Watson AI Lab, describes a method for evaluating model predictions on specific patients.
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Demystifying AI
Through MIT App Inventor, grad student Natalie Lao is teaching kids how to build AI models on their phones. Beyond MIT, she has co-founded a startup to fight disinformation and co-produced a set of machine learning tutorials. With the MIT-IBM Watson AI Lab, we are proud to support her work. Learn more!
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