Applying Advanced Speech Enhancement in Cochlear Implants

Posted by Samuel J. Yang, Research Scientist and Dick Lyon, Principal Scientist, Google Research For the ~466 million people in the world who are deaf or hard of hearing, the lack of easy access to accessibility services can be a barrier to participating in spoken conversations encountered daily. While hearing aids can help alleviate this, simply amplifying...

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Multi-task Prediction of Organ Dysfunction in ICUs

Posted by Subhrajit Roy, Research Scientist and Diana Mincu, Research Software Engineer, Google Research The intensive care unit (ICU) of a hospital looks after the most medically vulnerable patients, many of whom require organ support, such as mechanical ventilation or dialysis. While always critical, the demand on ICU services during the COVID-19...

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Google at ICML 2021

Posted by Cat Armato and Jaqui Herman, Program Managers Groups across Google are actively pursuing research across the field of machine learning, ranging from theory to application. With scalable tools and architectures, we build machine learning systems to solve deep scientific and engineering challenges in areas of language, music, visual processing,...

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High Fidelity Image Generation Using Diffusion Models

Posted by Jonathan Ho, Research Scientist and Chitwan Saharia, Software Engineer, Google Research, Brain Team Natural image synthesis is a broad class of machine learning (ML) tasks with wide-ranging applications that pose a number of design challenges. One example is image super-resolution, in which a model is trained to transform a low resolution...

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Speeding Up Reinforcement Learning with a New Physics Simulation Engine

Posted by C. Daniel Freeman, Senior Software Engineer and Erik Frey, Staff Software Engineer, Google ResearchReinforcement learning (RL) is a popular method for teaching robots to navigate and manipulate the physical world, which itself can be simplified and expressed as interactions between rigid bodies1 (i.e., solid physical objects that do not deform...

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From Vision to Language: Semi-supervised Learning in Action…at Scale

Posted by Thang Luong, Staff Research Scientist, Google Research and Jingcao Hu, Senior Staff Software Engineer, Google Search Supervised learning, the machine learning task of training predictive models using data points with known outcomes (i.e., labeled data), is generally the preferred approach in industry because of its simplicity. However, supervised...

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Reducing the Computational Cost of Deep Reinforcement Learning Research

Posted by Pablo Samuel Castro, Staff Software Engineer, Google Research It is widely accepted that the enormous growth of deep reinforcement learning research, which combines traditional reinforcement learning with deep neural networks, began with the publication of the seminal DQN algorithm. This paper demonstrated the potential of this combination,...

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Quickly Training Game-Playing Agents with Machine Learning

Posted by Leopold Haller and Hernan Moraldo, Software Engineers, Google Research In the last two decades, dramatic advances in compute and connectivity have allowed game developers to create works of ever-increasing scope and complexity. Simple linear levels have evolved into photorealistic open worlds, procedural algorithms have enabled games with...

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Take All Your Pictures to the Cleaners, with Google Photos Noise and Blur Reduction

Posted by Mauricio Delbracio, Research Scientist and Sungjoon Choi, Software Engineer, Google Research Despite recent leaps in imaging technology, especially on mobile devices, image noise and limited sharpness remain two of the most important levers for improving the visual quality of a photograph. These are particularly relevant when taking pictures...

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Achieving Precision in Quantum Material Simulations

Posted by Charles Neill and Zhang Jiang, Senior Research Scientists, Google Quantum AI In fall of 2019, we demonstrated that the Sycamore quantum processor could outperform the most powerful classical computers when applied to a tailor-made problem. The next challenge is to extend this result to solve practical problems in materials science, chemistry...

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