AutoML-Zero: Evolving Code that Learns

Posted by Esteban Real, Staff Software Engineer, and Chen Liang, Software Engineer, Google Research, Brain Team Machine learning (ML) has seen tremendous successes recently, which were made possible by ML algorithms like deep neural networks that were discovered through years of expert research. The difficulty involved in this research fueled AutoML,...

4h

Duality — A New Approach to Reinforcement Learning

Posted by Ofir Nachum and Bo Dai, Research Scientists, Google Research Reinforcement learning (RL) is an approach commonly used to train agents to make sequences of decisions that will be successful in complex environments, including for example, settings such as robotic navigation, where an agent controls the joint motors of a robot to seek a path...

1d

Google at ACL 2020

Posted by Cat Armato and Emily Knapp, Program ManagersThis week, the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), a premier conference covering a broad spectrum of research areas that are concerned with computational approaches to natural language, takes place online.As a leader in natural language processing and...

3d

SmartReply for YouTube Creators

Posted by Rami Al-Rfou, Research Scientist, Google Research It has been more than 4 years since SmartReply was launched, and since then, it has expanded to more users with the Gmail launch and Android Messages and to more devices with Android Wear. Developers now use SmartReply to respond to reviews within the Play Developer Console and can set up...

2w

SpineNet: A Novel Architecture for Object Detection Discovered with Neural Architecture Search

Posted by Xianzhi Du, Software Engineer and Jaeyoun Kim, Technical Program Manager, Google Research Convolutional neural networks created for image tasks typically encode an input image into a sequence of intermediate features that capture the semantics of an image (from local to global), where each subsequent layer has a lower spatial dimension. However,...

2w

Leveraging Temporal Context for Object Detection

Posted by Sara Beery, Student Researcher, and Jonathan Huang, Research Scientist, Google Research Ecological monitoring helps researchers to understand the dynamics of global ecosystems, quantify biodiversity, and measure the effects of climate change and human activity, including the efficacy of conservation and remediation efforts. In order to monitor...

2w

Sensing Force-Based Gestures on the Pixel 4

Posted by Philip Quinn and Wenxin Feng, Research Scientists, Android UX Touch input has traditionally focussed on two-dimensional finger pointing. Beyond tapping and swiping gestures, long pressing has been the main alternative path for interaction. However, a long press is sensed with a time-based threshold where a user’s finger must remain stationary...

3w

Presenting a Challenge and Workshop in Efficient Open-Domain Question Answering

Posted by Eunsol Choi, Visiting Faculty Researcher and Tom Kwiatkowski, Research Scientist, Google ResearchOne of the primary goals of natural language processing is to build systems that can answer a user's questions. To do this, computers need to be able to understand questions, represent world knowledge, and reason their way to answers. Traditionally,...

3w

RepNet: Counting Repetitions in Videos

Posted by Debidatta Dwibedi, Research Scientist, Robotics at Google Repeating processes ranging from natural cycles, such as phases of the moon or heartbeats and breathing, to artificial repetitive processes, like those found on manufacturing lines or in traffic patterns, are commonplace in our daily lives. Beyond just their prevalence, repeating processes...

3w

Improving Speech Representations and Personalized Models Using Self-Supervision

Posted by Joel Shor, Software Engineer and Oran Lang, Software Engineer, Google Research, Israel There are many tasks within speech processing that are easier to solve by having large amounts of data. For example automatic speech recognition (ASR) translates spoken audio into text. In contrast, "non-semantic" tasks focus on the aspects of human speech...

3w