Understanding antibodies to avoid pandemics

Structural biologist Pamela Björkman shared insights into pandemic viruses as part of the Department of Biology’s IAP seminar series.

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MIT.nano’s Immersion Lab opens for researchers and students

Facility within MIT.nano offers equipment and capabilities for visualizing data, creating immersive environments.

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Instagram's redesign shifts toward shopping – here's how that can be harmful

Instagram's Shop button signals the growing commodification of human interactions on social media.

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Thousands of ocean fishing boats could be using forced labor – we used AI and satellite data to find them

Forced labor is a widespread problem in fisheries on the high seas. Between 2012 and 2018, an estimated 100,000 people may have been victims of forced labor on thousands of different boats.

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Making smart thermostats more efficient

A smart thermostat quickly learns to optimize building microclimates for both energy consumption and user preference.

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What children can teach governments about making graphs

There have been some shockingly bad graphs circulating during the pandemic.

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Want cheaper nuclear energy? Turn the design process into a game

Researchers show that deep reinforcement learning can be used to design more efficient nuclear reactors.

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Seasonal changes in UV may increase spread of COVID-19

Seasonal changes in UV may alter the spread of COVID but not as much as social distancing.

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science-technology covid-19 coronavirus pandemic seas harvard-center-for-the-environment harvard-data-science-initiative

Making data-informed Covid-19 testing plans

A new web-friendly modeling tool helps organizations build tailored Covid-19 testing strategies that can save money and reduce coronavirus spread.

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covid-19 pandemic data research mechanical-engineering school-of-engineering electrical-engineering-computer-science-eecs idss health-sciences-and-technology analytics mit-schwarzman-college-of-computing

It takes a lot of energy for machines to learn – here's why AI is so power-hungry

Training neural networks burns through a lot of energy. As the AI field grows, it's working to keep its carbon foot print from growing with it.

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