Personal Assistant Systems
Trump Pledges to Issue 500 Refunds to Nearly a Million Obamacare Enrollees. Are You Eligible?
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The Planet Mercury Has Been Shrinking--More Than Scientists Expected
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Voters Are Turning to AI for Election Help. The Answers Aren't Always Right
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AI Is Developing a Culture of Its Own. That Could Be Dangerous
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Thousands of Food-Packaging Chemicals Lack Safety Data
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'Buy Canadian': Meet the Consumers Boycotting American Products as Trade Rift Widens
Canadian Prime Minister Mark Carney has championed the "Buy Canadian" movement, saying the power lies in "decisions taken at the kitchen table, not the boardroom table." Canadians are responding en masse, embracing patriotic shopping, even with the challenges it can present.
How to Treat Age Spots Without Damaging Your Skin
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How Two Citizen Sleuths Spent Decades Trying to Solve the Double Homicide of A Killer Story
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TIME Convenes Leaders Shaping the Future of Health for Third Annual TIME100 Health Leadership Forum
TIME convenes the third annual TIME100 Health Leadership Forum in New York City, featuring conversations on equity, longevity, and solution-driven care with leaders taking action toward a world with more reliable healthcare solutions.
Improving the process for large-scale recommender systems: an interview with Haruka Kiyohara
In their paper Credit-assigned Policy Gradient for Early Stage Retrieval in Two-stage Ranking, and study how to improve early-stage retrieval in two-stage decision processes. We caught up with first author Haruka to find out more. This is a project that she worked on during an internship with the Central Applied Science (CAS) team at Meta. What is the topic of the research in your paper and why is it an interesting area for study? This paper studies how to improve early-stage retrieval in two-stage decision processes.