Category google-researches

Posted by Danijar Hafner, Student Researcher, Google Research Research into how artificial agents can make decisions has evolved rapidly through advances in deep reinforcement learning. Compared to generative ML models like GPT-3 and Imagen, artificial agents can directly influence their…

Posted by Been Kim, Research Scientist, Google Research, Brain Team, and Alison Lentz, Senior Staff Strategist, Google Research, Mural Team Advances in computer vision and natural language processing continue to unlock new ways of exploring billions of images available on…

Posted by Yundi Qian, Software Engineer, Google Research and Mircea Trofin, Software Engineer, Google Core The question of how to compile faster and smaller code arose together with the birth of modem computers. Better code optimization can significantly reduce the…

Posted by Dan Walker and Dan Liebling, Software Engineers, Google Research People don’t write in the same way that they speak. Written language is controlled and deliberate, whereas transcripts of spontaneous speech (like interviews) are hard to read because speech…

Posted by Ethan Dyer and Guy Gur-Ari, Research Scientists, Google Research, Blueshift Team Language models have demonstrated remarkable performance on a variety of natural language tasks — indeed, a general lesson from many works, including BERT, GPT-3, Gopher, and PaLM, has…

Posted by Jarrod McClean, Staff Research Scientist, Google Quantum AI, and Hsin-Yuan Huang, Graduate Student, Caltech In efforts to learn about the quantum world, scientists face a big obstacle: their classical experience of the world. Whenever a quantum system is…

Posted by Sara Beery, Student Researcher, and Jonathan Huang, Research Scientist, Google Research, Perception Team Over four billion people live in cities around the globe, and while most people interact daily with others — at the grocery store, on public…

Posted by Shaina Mehta and Kristen Borg, Program Managers This week marks the beginning of the premier annual Computer Vision and Pattern Recognition conference (CVPR 2022), held both in-person in New Orleans, LA and virtually. As a leader in computer vision research…

Posted by Laura Downs and Anthony Francis, Software Engineers, Robotics at Google Many recent advances in computer vision and robotics rely on deep learning, but training deep learning models requires a wide variety of data to generalize to new scenarios.…

Posted by Basil Mustafa, Research Software Engineer and Carlos Riquelme, Research Scientist, Google Research, Brain team Sparse models stand out among the most promising approaches for the future of deep learning. Instead of every part of a model processing every…