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,…
Turns out, even language models “think” they’re biased. When prompted in ChatGPT, the response was as follows: “Yes, language models can have biases, because the training data reflects the biases present in society from which that data was collected. For example, gender and racial biases are prevalent in many real-world datasets, and if a language…
When OpenAI launched ChatGPT, with zero fanfare, in late November 2022, the San Francisco–based artificial-intelligence company had few expectations. Certainly, nobody inside OpenAI was prepared for a viral mega-hit. The firm has been scrambling to catch up—and capitalize on its success—ever since. It was viewed in-house as a “research preview,” says Sandhini Agarwal, who works…