Topic Tag: Google

home Forums Topic Tag: Google

 Introducing the CVPR 2018 Learned Image Compression Challenge

  

Posted by Michele Covell, Research Scientist, Google Research Image compression is critical to digital photography — without it, a 12 megapixel image would take 36 megabytes of storage, making most websites prohibitively large. While the signal-processing community has significantly improved imag…


 TFGAN: A Lightweight Library for Generative Adversarial Networks

     

Posted by Joel Shor, Senior Software Engineer, Machine Perception (Crossposted on the Google Open Source Blog) Training a neural network usually involves defining a loss function, which tells the network how close or far it is from its objective. For example, image classification networks are often…


 TensorFlow-Serving: Flexible, High-Performance ML Serving

We describe TensorFlow-Serving, a system to serve machine learning models inside Google which is also available in the cloud and via open-source. It is extremely flexible in terms of the types of ML platforms it supports, and ways to integrate with systems that convey new models and updated version…


 Evaluation of Speech for the Google Assistant

     

Posted by Enrique Alfonseca, Staff Research Scientist, Google Assistant Voice interactions with technology are becoming a key part of our lives — from asking your phone for traffic conditions to work to using a smart device at home to turn on the lights or play music. The Google Assistant is desi…


 Tacotron 2: Generating Human-like Speech from Text

     

Posted by Jonathan Shen and Ruoming Pang, Software Engineers, on behalf of the Google Brain and Machine Perception Teams Generating very natural sounding speech from text (text-to-speech, TTS) has been a research goal for decades. There has been great progress in TTS research over the last few year…


 A Summary of the First Conference on Robot Learning

 

Posted by Vincent Vanhoucke, Principal Scientist, Google Brain Team and Melanie Saldaña, Program Manager, University Relations Whether in the form of autonomous vehicles, home assistants or disaster rescue units, robotic systems of the future will need to be able to operate safely and effectively …


 Introducing Appsperiments: Exploring the Potentials of Mobile Photography

  

Posted by Alex Kauffmann, Interaction Researcher, Google Research Each of the world’s approximately two billion smartphone owners is carrying a camera capable of capturing photos and video of a tonal richness and quality unimaginable even five years ago. Until recently, those cameras behaved …


 Understanding Medical Conversations

   

Posted by Katherine Chou, Product Manager and Chung-Cheng Chiu, Software Engineer, Google Brain Team Good documentation helps create good clinical care by communicating a doctor’s thinking, their concerns, and their plans to the rest of the team. Unfortunately, physicians routinely spend more…


 Feature Visualization

 

Posted by Christopher Olah, Research Scientist, Google Brain Team and Alex Mordvintsev, Research Scientist, Google Research Have you ever wondered what goes on inside neural networks? Feature visualization is a powerful tool for digging into neural networks and seeing how they work. Our new articl…


 Latest Innovations in TensorFlow Serving

  

Posted by Chris Olston, Research Scientist, and Noah Fiedel, Software Engineer, TensorFlow Serving Since initially open-sourcing TensorFlow Serving in February 2016, we’ve made some major enhancements. Let’s take a look back at where we started, review our progress, and share where we are head…


 Fishing for Clickbaits in Social Images and Texts with Linguistically-Infused Neural Network Models

   

This paper presents the results and conclusions of our participation in the Clickbait Challenge 2017 on automatic clickbait detection in social media. We first describe linguistically-infused neural network models and identify informative representations to predict the level of clickbaiting present…


 WaveNet launches in the Google Assistant

WaveNet launches in the Google Assistant by DeepMind


 Intelligence Quotient and Intelligence Grade of Artificial Intelligence

Although artificial intelligence is currently one of the most interesting areas in scientific research, the potential threats posed by emerging AI systems remain a source of persistent controversy. To address the issue of AI threat, this study proposes a standard intelligence model that unifies AI …


 Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning

  

Developing a safe and efficient collision avoidance policy for multiple robots is challenging in the decentralized scenarios where each robot generate its paths without observing other robots’ states and intents. While other distributed multi-robot collision avoidance systems exist, they ofte…


 Consensus measure of rankings

 

A ranking is an ordered sequence of items, in which an item with higher ranking score is more preferred than the items with lower ranking scores. In many information systems, rankings are widely used to represent the preferences over a set of items or candidates. The consensus measure of rankings i…


 3D Deformable Object Manipulation using Fast Online Gaussian Process Regression

 

In this paper, we present a general approach to automatically visual-servo control the position and shape of a deformable object whose deformation parameters are unknown. The servo-control is achieved by online learning a model mapping between the robotic end-effector’s movement and the objec…


 The Google Brain Team’s Approach to Research

 

Posted by Jeff Dean, Google Senior Fellow About a year ago, the Google Brain team first shared our mission “Make machines intelligent. Improve people’s lives.” In that time, we’ve shared updates on our work to infuse machine learning across Google products that hundreds of millions of users…


 Opportunistic Self Organizing Migrating Algorithm for Real-Time Dynamic Traveling Salesman Problem

Self Organizing Migrating Algorithm (SOMA) is a meta-heuristic algorithm based on the self-organizing behavior of individuals in a simulated social environment. SOMA performs iterative computations on a population of potential solutions in the given search space to obtain an optimal solution. In th…


 Build your own Machine Learning Visualizations with the new TensorBoard API

  

Posted by Chi Zeng and Justine Tunney, Software Engineers, Google Brain Team When we open-sourced TensorFlow in 2015, it included TensorBoard, a suite of visualizations for inspecting and understanding your TensorFlow models and runs. Tensorboard included a small, predetermined set of visualization…


 Harness the Power of Machine Learning in Your Browser with Deeplearn.js

  

Posted by Nikhil Thorat and Daniel Smilkov, Software Engineers, Google Big Picture Team Machine learning (ML) has become an increasingly powerful tool, one that can be applied to a wide variety of areas spanning object recognition, language translation, health and more. However, the developmen…


 Network learning via multi-agent inverse transportation problems

Despite the ubiquity of transportation data, methods to infer the state parameters of a network either ignore sensitivity of route decisions, require route enumeration for parameterizing descriptive models of route selection, or require complex bilevel models of route assignment behavior. These lim…


 Launching the Speech Commands Dataset

    

Posted by Pete Warden, Software Engineer, Google Brain Team At Google, we’re often asked how to get started using deep learning for speech and other audio recognition problems, like detecting keywords or commands. And while there are some great open source speech recognition systems like Kaldi th…


 Expressions in Virtual Reality

   

Posted by Steven Hickson, Software Engineering Intern, and Nick Dufour, Avneesh Sud, Software Engineers, Machine Perception Recently Google Machine Perception researchers, in collaboration with Daydream Labs and YouTube Spaces, presented a solution for virtual headset ‘removal’ for mixed realit…


 An Update to Open Images – Now with Bounding-Boxes

   

Posted by Vittorio Ferrari, Research Scientist, Machine Perception Last year we introduced Open Images, a collaborative release of ~9 million images annotated with labels spanning over 6000 object categories, designed to be a useful dataset for machine learning research. The initial release feature…


 Building Your Own Neural Machine Translation System in TensorFlow

   

Posted by Thang Luong, Research Scientist, and Eugene Brevdo, Staff Software Engineer, Google Brain Team Machine translation – the task of automatically translating between languages – is one of the most active research areas in the machine learning community. Among the many approaches to machi…