32 episodes

The Massachusetts Institute of Technology is an independent, coeducational, privately endowed university in Cambridge, Massachusetts. Our mission is to advance knowledge; to educate students in science, engineering, technology humanities and social sciences; and to tackle the most pressing problems facing the world today. We are a community of hands-on problem-solvers in love with fundamental science and eager to make the world a better place.

Massachusetts Institute of Technology (MIT) MIT News

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The Massachusetts Institute of Technology is an independent, coeducational, privately endowed university in Cambridge, Massachusetts. Our mission is to advance knowledge; to educate students in science, engineering, technology humanities and social sciences; and to tackle the most pressing problems facing the world today. We are a community of hands-on problem-solvers in love with fundamental science and eager to make the world a better place.

    Audio Article: Leveraging the power of neurodiversity

    Audio Article: Leveraging the power of neurodiversity

    More than 75 percent of the the quality engineering startup Ultranauts' employees are on the autism spectrum, allowing the company to tap into the unique strengths of each team member as it helps large enterprises and mature startups improve the quality of their data, analytics, and software.

    Read the article: https://news.mit.edu/2020/ultranauts-neurodiversity-1201

    • 7 min
    Audio Article: Computer-aided creativity in robot design

    Audio Article: Computer-aided creativity in robot design

    A new MIT-developed system called RoboGrammar makes it possible to simulate and determine which robot design, out of thousands of possibilities, will work best based on what parts you have laying around your shop and what terrain it needs to traverse.

    Read the article: https://news.mit.edu/2020/computer-aided-robot-design-1130

    • 7 min
    Audio Article: A hunger for social contact

    Audio Article: A hunger for social contact

    Since the coronavirus pandemic began in the spring, many people have only seen their close friends and loved ones during video calls, if at all. A new study from MIT finds that the longings we feel during this kind of social isolation share a neural basis with the food cravings we feel when hungry.

    Read the article: https://news.mit.edu/2020/hunger-social-cravings-neuroscience-1123

    • 7 min
    New AI model detects asymptomatic Covid-19 infections through device-recorded coughs

    New AI model detects asymptomatic Covid-19 infections through device-recorded coughs

    For more information read the article: https://news.mit.edu/2020/covid-19-cough-cellphone-detection-1029

    TRANSCRIPT:

    [AUDIO RECORDING OF A PERSON COUGHING]

    NARRATOR: Asymptomatic people who are infected with Covid-19 exhibit, by definition, no discernible physical symptoms of the disease. But it seems those who are asymptomatic may not be entirely free of changes wrought by the virus. The differences between a cough of an asymptomatic patient and a healthy individual are not decipherable to the human ear, but it turns out that they can be picked up by artificial intelligence. 

    NARRATOR: For example, here is a cough of a healthy individual:[AUDIO RECORDING OF A HEALTHY INDIVIDUAL]

    NARRATOR: And now here is a cough of an asymptomatic person with Covid-19: [AUDIO RECORDING OF AN ASYMPTOMATIC COVID-19 POSITIVE PATIENT]

    NARRATOR: To make things even more challenging, listen to a person who has symptoms and is Covid-19 positive: [AUDIO RECORDING OF A COVID-19 POSITIVE PATIENT WITH SYMPTOMS]

    NARRATOR: It is very hard, frankly almost impossible, for a person to distinguish these three cough’s, even after you’ve listened to them multiple times. But a team of MIT researchers report they have developed an AI model that can distinguish asymptomatic people with Covid-19 from healthy individuals without the disease through forced-cough recordings. 

    NARRATOR: To develop their model, the researchers used tens of thousands of samples of coughs submitted by people voluntarily though web browsers and devices such as cellphones and laptops. When they fed the model new cough recordings, it accurately identified 98.5 percent of coughs from people who were confirmed to have Covid-19, including 100 percent of coughs from the asymptomatic, who reported they did not have symptoms but had tested positive for the virus.

    NARRATOR: When the AI model is fed the cough of a Covid asymptomatic person [AUDIO RECORDING OF AN ASYMPTOMATIC COVID-19 PATIENT] they found it was able to pick up patterns in the four biomarkers — vocal cord strength, sentiment, lung and respiratory performance, and muscular degradation — that are specific to Covid-19.

    NARRATOR: When the model is fed the cough of a covid-positive individual who IS exhibiting symptoms [AUDIO OF A SYMPTOMATIC COVID-19 POSITIVE PATIENT] it is actually harder for artificial intelligence to discriminate. The researchers think it is because there are many conditions that create symptoms, such as the flu or asthma and therefore the results are confounded. For this reason, they stress that their AI model is not meant to diagnose symptomatic people, OR determine whether their symptoms are due to Covid-19 or other conditions. The tool’s strength lies in its ability to discern asymptomatic coughs from healthy ones.
     
    NARRATOR: The team is now working on incorporating the model into a user-friendly app which if FDA-approved and adopted on a large scale could potentially be a free, convenient, noninvasive prescreening tool to identify people who are likely to be asymptomatic for Covid-19. A user could log in daily, cough into their phone and instantly get information on whether they might be infected and therefore should confirm with a formal test.

    • 3 min
    Audio Article: What are the odds your vote will not count?

    Audio Article: What are the odds your vote will not count?

    In elections, every vote counts. Or should count. But a new study by an MIT professor indicates that in the 2016 U.S. general election, 4 percent of all mail-in ballots were not counted — about 1.4 million votes, or 1 percent of all votes cast, signaling a significant problem that could grow in 2020.

    Read the article: http://news.mit.edu/2020/odds-mail-vote-not-count-1019

    • 8 min
    Audio Article: How many votes will be counted after election night?

    Audio Article: How many votes will be counted after election night?

    A study co-authored by MIT political scientist, Charles Stewart, quantifies the "blue shift" effect by state, analyzes its causes, and shows why the 2020 election might indeed be decided after Nov. 3.

    Read the article: http://news.mit.edu/2020/votes-counted-after-election-1015

    • 10 min

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