Posted by Danny Driess, Student Researcher, and Pete Florence, Research Scientist, Robotics at Google Recent years have seen tremendous advances across machine learning domains, from models that can explain jokes or answer visual questions in a variety of languages to those that can produce images based on text descriptions. Such innovations have been possible due…
Government should not “abdicate” its responsibilities and leave the future path of artificial intelligence solely to Big Tech, Aleksander Mądry, the Cadence Design Systems Professor of Computing at MIT and director of the MIT Center for Deployable Machine Learning, told a Congressional panel on Wednesday. Rather, Mądry said, government should be asking questions about the…
Meredith Broussard is unusually well placed to dissect the ongoing hype around AI. She’s a data scientist and associate professor at New York University, and she’s been one of the leading researchers in the field of algorithmic bias for years. And though her own work leaves her buried in math problems, she’s spent the last…
Matthew Kearney was drawn to MIT by the culture of its cross-country team. Growing up in Austin, Texas, he loved spending time outdoors and playing soccer, but by high school running had become his primary sport. While looking at colleges, he wanted to find a place with both strong academics and a strong team community….
Posted by Tom Denton, Software Engineer, Google Research, Brain Team Worldwide bird populations are declining at an alarming rate, with approximately 48% of existing bird species known or suspected to be experiencing population declines. For instance, the U.S. and Canada have reported 29% fewer birds since 1970. Effective monitoring of bird populations is essential for…
One of the 12 labors of Hercules, according to ancient lore, was to destroy a nine-headed monster called the Hydra. The challenge was that when Hercules used his sword to chop off one of the monster’s heads, two would grow back in its place. He therefore needed an additional weapon, a torch, to vanquish his…
A new study from researchers at MIT and Brown University characterizes several properties that emerge during the training of deep classifiers, a type of artificial neural network commonly used for classification tasks such as image classification, speech recognition, and natural language processing. The paper, “Dynamics in Deep Classifiers trained with the Square Loss: Normalization, Low…
Posted by Shangbang Long, Software Engineer, Google Research The last few decades have witnessed the rapid development of Optical Character Recognition (OCR) technology, which has evolved from an academic benchmark task used in early breakthroughs of deep learning research to tangible products available in consumer devices and to third party developers for daily use. These…
Posted by Yu Zhang, Research Scientist, and James Qin, Software Engineer, Google Research Last November, we announced the 1,000 Languages Initiative, an ambitious commitment to build a machine learning (ML) model that would support the world’s one thousand most-spoken languages, bringing greater inclusion to billions of people around the globe. However, some of these languages…
Posted by Krzysztof Choromanski, Staff Research Scientist, Robotics at Google, and Xuesu Xiao, Visiting Researcher, George Mason University Despite decades of research, we don’t see many mobile robots roaming our homes, offices, and streets. Real-world robot navigation in human-centric environments remains an unsolved problem. These challenging situations require safe and efficient navigation through tight spaces,…