It can be hard to keep track of all the numbers, statistics, and charts swirling around the internet -- we’re inundated with information that can be rapidly disseminated and dissected. To carve through some of the sludge, here’s a selected highlight of recent computer science related efforts to fight COVID-19.
A company, founded by Marilyn Matz SM ’80 and CSAIL's Michael Stonebraker, helps pharmaceutical companies, research institutes, and biotech companies turn data into insights.
MIT researchers have designed a scalable system that secures the metadata — such as who’s corresponding and when — of millions of users in communications networks, to help protect the information against possible state-level surveillance.
MIT startup PatternEx starts with the assumption that algorithms can’t protect a system on their own. The company has developed a closed loop approach whereby machine-learning models flag possible attacks and human experts provide feedback. The feedback is then incorporated into the models, improving their ability to flag only the activity analysts care about in the future.
A system created by MIT researchers could be used to automatically update factual inconsistencies in Wikipedia articles, reducing time and effort spent by human editors who now do the task manually.
“I never thought about the kilowatt-hours I was using. But this hackathon gave me a chance to look at my carbon footprint and find ways to trade a small amount of model accuracy for big energy savings,” says Mohammad Haft-Javaherian.
A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) tested the boundaries of text. They came up with “TextFooler,” a general framework that can successfully attack natural language processing (NLP) systems — the types of systems that let us interact with our Siri and Alexa voice assistants — and “fool” them into making the wrong predictions.
With billions of books, news stories, and documents online, there’s never been a better time to be reading — if you have time to sift through all the options. “There’s a ton of text on the internet,” says Justin Solomon, an assistant professor at MIT. “Anything to help cut through all that material is extremely useful.”
