Posted by Harsh Mehta, Software Engineer, Google Research Matrix factorization is one of the oldest, yet still widely used, techniques for learning how to recommend items such as songs or movies from user ratings. In its basic form, it approximates…
Posted by Tal Remez, Software Engineer, Google Research and Micheal Hassid, Software Engineer Intern, Google Research Recent years have seen a tremendous increase in the creation and serving of video content to users across the world in a variety of…
Posted by Ikechukwu Uchendu, AI Resident and Ted Xiao, Software Engineer, Robotics at Google Reinforcement learning (RL) can be used to train a policy to perform a task via trial and error, but a major challenge in RL is learning…
Posted by Gil Shamir and Dong Lin, Research Software Engineers, Google Research Ever queried a recommender system and found that the same search only a few moments later or on a different device yields very different results? This is not…
Posted by Sharan Narang and Aakanksha Chowdhery, Software Engineers, Google Research In recent years, large neural networks trained for language understanding and generation have achieved impressive results across a wide range of tasks. GPT-3 first showed that large language models…
Posted by Ye Jia and Michelle Tadmor Ramanovich, Software Engineers, Google Research Automatic translation of speech from one language to speech in another language, called speech-to-speech translation (S2ST), is important for breaking down the communication barriers between people speaking different…
Posted by Boris Babenko, Software Engineer and Naama Hammel, Clinical Research Scientist, Google Health Three years ago we wrote about our work on predicting a number of cardiovascular risk factors from fundus photos (i.e., photos of the back of the…
Posted by Mohammad Saleh, Software Engineer, Google Research, Brain Team and Anjuli Kannan, Software Engineer, Google Docs For many of us, it can be challenging to keep up with the volume of documents that arrive in our inboxes every day:…
Posted by Amir Yazdanbakhsh, Research Scientist and Aviral Kumar, Student Researcher, Google Research Advances in machine learning (ML) often come with advances in hardware and computing systems. For example, the growth of ML-based approaches in solving various problems in vision…
Posted by William J. Huggins, Research Scientist, Google Quantum AI The intersection between the computational difficulty and practical importance of quantum chemistry challenges run on quantum computers has long been a focus for Google Quantum AI. We’ve experimentally simulated simple…