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Solving brain dynamics gives rise to flexible machine-learning models

Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world …

Ensuring AI works with the right dose of curiosity

It’s a dilemma as old as time. Friday night has rolled around, and you’re trying to pick a restaurant for dinner. Should you visit your most beloved watering hole or try a new establishment, in the hopes of discovering something …

A whole new world of learning via MIT OpenCourseWare videos

Like millions of others during the global Covid-19 lockdowns, Emmanuel Kasigazi, an entrepreneur from Uganda, turned to YouTube to pass the time. But he wasn’t following an influencer or watching music videos. A lifelong learner, Kasigazi was scouring the video-sharing …

Video on the record

Among the Pulitzer Prizes awarded in 2021 was a citation for a teenager who changed history with her cell phone. The Pulitzer committee acknowledged Darnella Frazier “for courageously recording the murder of George Floyd, a video that spurred protests against …

In machine learning, synthetic data can offer real performance improvements

Teaching a machine to recognize human actions has many potential applications, such as automatically detecting workers who fall at a construction site or enabling a smart home robot to interpret a user’s gestures.

To do this, researchers train machine-learning models …

Study urges caution when comparing neural networks to the brain

Neural networks, a type of computing system loosely modeled on the organization of the human brain, form the basis of many artificial intelligence systems for applications such speech recognition, computer vision, and medical image analysis.

In the field of neuroscience, …

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