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In machine learning, synthetic data can offer real performance improvements

Machine-learning models trained to classify human actions using synthetic data can outperform models trained using real data in certain situations. This could help scientists identify when it’s better to use synthetic data for training, which could eliminate bias, privacy, security, and copyright issues that often impact real datasets.
Hilde Kuehne Souyoung Jin Samarth Mishra Rogerio Feris Aude Oliva Venkatesh Saligrama
Source: mit.edu

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At the Forefront of Machine Learning | Arts & Sciences

At the Forefront of Machine Learning Computer scientist Derry Wijaya builds tools to translate "low-resource" languages and track how media perspectives shape public opinion May 19, 2020 | By Jeremy Schwab In an analog world, translating from one language to another was often done with the help of a dictionary. In today’s digital world, with access to incredibly fast computer algorithms and a vast amount of data, researchers are building a new landscape for language translation. An...
United States Jeremy Schwab Kate Saenko Derry Wijaya Carnegie Mellon University Bu College Of Communication
Source: bu.edu

It takes a lot of energy for machines to learn - Why AI is so power-hungry?

This month, Google forced out a prominent AI ethics researcher after she voiced frustration with the company for making her withdraw a research paper. The paper pointed out the risks of language-processing artificial intelligence, the type used in Google Search and other text analysis products. Among the risks is the large carbon footprint of developing this kind of AI technology. By some estimates, training an AI model generates as much carbon emissions as it takes to build and drive five ca...
New York United States San Francisco Kate Saenko University Of Massachusetts Amherst Boston University

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

By Kate Saenko Dec 15, 2020 This month, Google forced out a prominent AI ethics researcher after she voiced frustration with the company for making her withdraw a research paper. The paper pointed out the risks of language-processing artificial intelligence, the type used in Google Search and other text analysis products. Among the risks is the large carbon footprint of developing this kind of AI technology. By some estimates, training an AI model generates as much carbon emissions as it take...
New York United States San Francisco Kate Saenko University Of Massachusetts Amherst Google Search
Source: gcn.com

Kate Saenko

Kate Saenko is an Assistant Professor at the Department of Computer Science at Boston University, and the director of the Computer Vision and Learning Group and member of the IVC Group. She also leads the new AI Research (AIR) initiative, which is housed at the Hariri Institute for Computing. She received her PhD from MIT. Previously, she was an Assistant Professor at the Department of Computer Science at UMass Lowell, a Postdoctoral Researcher at the International Computer Science Institute, a...
Kate Saenko Umass Lowell Science At Harvard University Department Of Computer Science School Of Engineering Department Of Computer Science At Boston University

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