Posted by Santiago Balseiro, Staff Research Scientist, Google Research, and Associate Professor at Columbia University, and Vahab Mirrokni, Distinguished Scientist, Google Research The emergence of digital technologies has transformed decision making across commercial sectors such as airlines, online retailing, and internet advertising. Today, real-time decisions need to be repeatedly made in highly uncertain and rapidly…
Posted by Xi Chen and Xiao Wang, Software Engineers, Google Research Advanced language models (e.g., GPT, GLaM, PaLM and T5) have demonstrated diverse capabilities and achieved impressive results across tasks and languages by scaling up their number of parameters. Vision-language (VL) models can benefit from similar scaling to address many tasks, such as image captioning,…
There’s a new text-to-image AI in town. With ERNIE-ViLG, a new AI developed by the Chinese tech company Baidu, you can generate images that capture the cultural specificity of China. It also makes better anime art than DALL-E 2 or other Western image-making AIs. But there are many things—like Tiananmen Square, the country’s second-largest city…
Posted by Daniel Rebain, Student Researcher, and Mark Matthews, Senior Software Engineer, Google Research, Perception Team An important aspect of human vision is our ability to comprehend 3D shape from the 2D images we observe. Achieving this kind of understanding with computer vision systems has been a fundamental challenge in the field. Many successful approaches…
The health of the planet is one of the most important challenges facing humankind today. From climate change to unsafe levels of air and water pollution to coastal and agricultural land erosion, a number of serious challenges threaten human and ecosystem health. Ensuring the health and safety of our planet necessitates approaches that connect scientific,…
Posted by Yuxiang Yang, Student Researcher, Robotics at Google An important promise for quadrupedal robots is their potential to operate in complex outdoor environments that are difficult or inaccessible for humans. Whether it’s to find natural resources deep in the mountains, or to search for life signals in heavily-damaged earthquake sites, a robust and versatile…
Posted by Zhengzhong Tu and Yinxiao Li, Software Engineers, Google Research Convolutional neural networks have been the dominant machine learning architecture for computer vision since the introduction of AlexNet in 2012. Recently, inspired by the evolution of Transformers in natural language processing, attention mechanisms have been prominently incorporated into vision models. These attention methods boost…
The internet had a collective feel-good moment with the introduction of DALL-E, an artificial intelligence-based image generator inspired by artist Salvador Dali and the lovable robot WALL-E that uses natural language to produce whatever mysterious and beautiful image your heart desires. Seeing typed-out inputs like “smiling gopher holding an ice cream cone” instantly spring to…
Training a machine-learning model to effectively perform a task, such as image classification, involves showing the model thousands, millions, or even billions of example images. Gathering such enormous datasets can be especially challenging when privacy is a concern, such as with medical images. Researchers from MIT and the MIT-born startup DynamoFL have now taken one…
Posted by Richard C. Gerkin, Google Research, and Alexander B. Wiltschko, Google Did you ever try to measure a smell? …Until you can measure their likenesses and differences you can have no science of odor. If you are ambitious to found a new science, measure a smell.— Alexander Graham Bell, 1914. How can we measure…