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ԭ researchers created BikeButler, a demo web app that lets users find personalized bike routes in Seattle. Cyclists plug in their destination and origin — just like in other mapping apps — and can then toggle sliders for eight attributes to create personalized route options.

ԭ researchers developed a system called VueBuds that uses tiny cameras in off-the-shelf wireless earbuds to allow users to talk with an AI model about the scene in front of them. For instance, a user might look at a Korean food package and say, “Hey VueBuds, translate this for me.” They’d then hear an AI voice say, “The visible text translates to ‘Cold Noodles’ in English.

A team led by ԭ researchers has created DopFone, a system that uses an off-the-shelf smartphone’s existing speaker and microphone to accurately estimate fetal heart rate. The phone mimics a Doppler ultrasound, emitting a tone and listening for the subtle variations in its echo caused by fetal heart beats. A machine learning model then estimates the heart rate.

A UW and Ai2 research team built OpenScholar, an open-source AI model designed specifically to synthesize current scientific research. In tests, OpenScholar cited sources as accurately as human experts, and 16 scientists preferred its response to those written by subject experts 51% of the time.

UW researchers analyzed the checkout data from the last 20 years of the 93 authors included in the post-1945 volume of “The Norton Anthology of American Literature,” which is assigned in U.S. English classes more than any other anthology. Sci-fi was especially popular.

New research from the UW and the Toyota Research Institute explores how drivers trade off between cognitive tasks, driving and using the vehicle’s touch screen. Researchers placed participants in a driving simulator and had them complete memory tests while interacting with the simulator’s touch screen.

In a new UW study, 528 participants worked with simulated AI systems to select job candidates. The researchers simulated different levels of racial biases for resumes from white, Black, Hispanic and Asian men. Without suggestions, participants’ choices exhibited little bias. But when provided with recommendations, participants mirrored the AI’s biases.