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Monster Mash: A Sketch-Based Tool for Casual 3D Modeling and Animation

Posted by Cassidy Curtis, Visual Designer and David Salesin, Principal Scientist, Google Research 3D computer animation is a time-consuming and highly technical medium — to complete even a single animated scene requires numerous steps, like modeling, rigging and animating, each of which is itself a sub-discipline that can take years to master. Because...

Announcing the 2021 Research Scholar Program Recipients

Posted by Negar Saei, Program Manager, University Relations In March 2020 we introduced the Research Scholar Program, an effort focused on developing collaborations with new professors and encouraging the formation of long-term relationships with the academic community. In November we opened the inaugural call for proposals for this program, which...

Constructing Transformers For Longer Sequences with Sparse Attention Methods

Posted by Avinava Dubey, Research Scientist, Google Research Natural language processing (NLP) models based on Transformers, such as BERT, RoBERTa, T5, or GPT3, are successful for a wide variety of tasks and a mainstay of modern NLP research. The versatility and robustness of Transformers are the primary drivers behind their wide-scale adoption, leading...

Recursive Classification: Replacing Rewards with Examples in RL

Posted by Benjamin Eysenbach, Student Researcher, Google Research A general goal of robotics research is to design systems that can assist in a variety of tasks that can potentially improve daily life. Most reinforcement learning algorithms for teaching agents to perform new tasks require a reward function, which provides positive feedback to the agent...

Progress and Challenges in Long-Form Open-Domain Question Answering

Posted by Aurko Roy, Research Scientist, Google Research Open-domain long-form question answering (LFQA) is a fundamental challenge in natural language processing (NLP) that involves retrieving documents relevant to a given question and using them to generate an elaborate paragraph-length answer. While there has been remarkable recent progress in factoid...

Leveraging Machine Learning for Game Development

Posted by Ji Hun Kim and Richard Wu, Software Engineers, Stadia Over the years, online multiplayer games have exploded in popularity, captivating millions of players across the world. This popularity has also exponentially increased demands on game designers, as players expect games to be well-crafted and balanced — after all, it's no fun to play a...

Massively Parallel Graph Computation: From Theory to Practice

Posted by Jakub Łącki and Vahab Mirrokni, Research Scientists, Google Research Graphs are useful theoretical representations of the connections between groups of entities, and have been used for a variety of purposes in data science, from ranking web pages by popularity and mapping out social networks, to assisting with navigation. In many cases, such...

Contactless Sleep Sensing in Nest Hub

Posted by Michael Dixon, Software Engineer and Reena Singhal Lee, Product Manager, Google Health People often turn to technology to manage their health and wellbeing, whether it is to record their daily exercise, measure their heart rate, or increasingly, to understand their sleep patterns. Sleep is foundational to a person’s everyday wellbeing and...

LEAF: A Learnable Frontend for Audio Classification

Posted by Neil Zeghidour, Research Scientist, Google Research Developing machine learning (ML) models for audio understanding has seen tremendous progress over the past several years. Leveraging the ability to learn parameters from data, the field has progressively shifted from composite, handcrafted systems to today’s deep neural classifiers that are...

A New Lens on Understanding Generalization in Deep Learning

Hanie Sedghi, Google Research and Preetum Nakkiran, Harvard University Understanding generalization is one of the fundamental unsolved problems in deep learning. Why does optimizing a model on a finite set of training data lead to good performance on a held-out test set? This problem has been studied extensively in machine learning, with a rich history...

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