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 a large, sparse (i.e., mostly empty) matrix of user-item interactions with a product of two…
Good data is the bedrock of a self-service data consumption model, which in turn unlocks insights, analytics, personalization at scale through AI. Yet many organizations face immense challenges setting up a robust data foundation. Dive into a pragmatic perspective on abstracting the complexity and untangling the conflicts in data management for better AI. About the…
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 languages and over numerous platforms. The process of creating high quality content can include several…
How many times have you tried to find the perfect piece of clothing, a tutorial to recreate nail art or even instructions on how to take care of a plant someone gifted you — but you didn’t have all the words to describe what you were looking for? At Google, we’re always dreaming up new…
People shop across Google more than a billion times a day — and we have a pretty good sense of what they’re browsing for. For instance, our Search data shows that the early 2000’s are having a moment. We’re seeing increased search interest in “Y2k fashion” and products like bucket hats and ankle bracelets. Also…
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 policies from scratch in environments with hard exploration challenges. For example, consider the setting depicted…
The human brain seems to care a lot about faces. It’s dedicated a specific area to identifying them, and the neurons there are so good at their job that most of us can readily recognize thousands of individuals. With artificial intelligence, computers can now recognize faces with a similar efficiency — and neuroscientists at MIT’s…
When OpenAI revealed its picture-making neural network DALL-E in early 2021, the program’s human-like ability to combine different concepts in new ways was striking. The string of images that DALL-E produced on demand were surreal and cartoonish, but they showed that the AI had learned key lessons about how the world fits together. DALL-E’s avocado…
In machine learning, understanding why a model makes certain decisions is often just as important as whether those decisions are correct. For instance, a machine-learning model might correctly predict that a skin lesion is cancerous, but it could have done so using an unrelated blip on a clinical photo. While tools exist to help experts…
Robots are already adept at certain things, such as lifting objects that are too heavy or cumbersome for people to manage. Another application they’re well suited for is the precision assembly of items like watches that have large numbers of tiny parts — some so small they can barely be seen with the naked eye….