Posted by Yuanzhong Xu and Yanping Huang, Software Engineers; Google Research, Brain Team Scaling neural networks, whether it be the amount of training data used, the model size or the computation being utilized, has been critical for improving model quality in many real-world machine learning applications, such as computer vision, language understanding and neural machine…
In the two years since OpenAI released its language model GPT-3, most big-name AI labs have developed language mimics of their own. Google, Facebook, and Microsoft—as well as a handful of Chinese firms—have all built AIs that can generate convincing text, chat with humans, answer questions, and more. Known as large language models because of…
Voice technology is one of the biggest trends in the healthcare space. We look at how it might help care providers and patients, from a woman who is losing her speech, to documenting healthcare records for doctors. But how do you teach AI to learn to communicate more like a human, and will it lead…
Computer vision systems sometimes make inferences about a scene that fly in the face of common sense. For example, if a robot were processing a scene of a dinner table, it might completely ignore a bowl that is visible to any human observer, estimate that a plate is floating above the table, or misperceive a…
As a building material, concrete withstands the test of time. Its use dates back to early civilizations, and today it is the most popular composite choice in the world. However, it’s not without its faults. Production of its key ingredient, cement, contributes 8-9 percent of the global anthropogenic CO2 emissions and 2-3 percent of energy…
Summary How do you remove bias from the machine learning models and ensure that the predictions are fair? How can you adopt responsible AI? How do you build trusted AI? And, what are the three stages in which the bias mitigation solution can be applied? This code pattern answers these questions and more to help…
Posted by Michael Ryoo, Research Scientist, Robotics at Google and Anurag Arnab, Research Scientist, Google Research Transformer models consistently obtain state-of-the-art results in computer vision tasks, including object detection and video classification. In contrast to standard convolutional approaches that process images pixel-by-pixel, the Vision Transformers (ViT) treat an image as a sequence of patch tokens…
Humans are pretty good at looking at a single two-dimensional image and understanding the full three-dimensional scene that it captures. Artificial intelligence agents are not. Yet a machine that needs to interact with objects in the world — like a robot designed to harvest crops or assist with surgery — must be able to infer…
Posted by Jaqui Herman and Cat Armato, Program Managers This week marks the beginning of the 35th annual Conference on Neural Information Processing Systems (NeurIPS 2021), the biggest machine learning conference of the year. NeurIPS 2021 will be held virtually and includes invited talks, demonstrations and presentations of some of the latest in machine learning…
While standing in a kitchen, you push some metal bowls across the counter into the sink with a clang, and drape a towel over the back of a chair. In another room, it sounds like some precariously stacked wooden blocks fell over, and there’s an epic toy car crash. These interactions with our environment are…