Introducing Petastorm: Uber ATG’s Data Access Library for Deep Learning

In recent years, deep learning has taken a central role in solving a wide range of problems in pattern recognition. At Uber Advanced Technologies Group (ATG), we use deep learning to solve various problems in the autonomous driving space, since many of these are pattern recognition problems. Many of our models require tens of terabytes […]

Google Duplex: An AI System for Accomplishing Real World Tasks Over the Phone

At the core of Duplex is a recurrent neural network (RNN) designed to cope with these challenges, built using TensorFlow Extended (TFX). To obtain its high precision, we trained Duplex’s RNN on a corpus of anonymized phone conversation data. The network uses the output of Google’s automatic speech recognition (ASR) technology, as well as features […]

Swift for TensorFlow

Swift for TensorFlow is a result of first-principles thinking applied to machine learning frameworks, and works quite differently than existing TensorFlow language bindings. Whereas prior solutions are designed within the constraints of what can be achieved by a (typically Python or Lua) library, Swift for TensorFlow is based on the belief that machine learning is […]

Listening for illegal logging chainsaws using TensorFlow

Our team has built the world’s first scalable, real-time detection and alert system for logging and environmental conservation in the rainforest. Building hardware that will survive in the rainforest is challenging, but we’re using what’s already there: the trees. We’ve hidden modified smartphones powered with solar panels—called “Guardian” devices—in trees in threatened areas, and continuously […]

Deploy TensorFlow models

Don’t follow the TensorFlow docs since they explain how to setup a docker image and compile TF serving that takes forever. We can do much better. Some guy made a docker image with everything already compile on it, so we are going to use that one. Source: towardsdatascience

Kaggle Tensorflow Speech Recognition Challenge

From November 2017 to January 2018 the Google Brain team hosted a speech recognition challenge on Kaggle. The goal of this challenge was to write a program that can correctly identify one of 10 words being spoken in a one-second long audio file. Having just made up my mind to start seriously studying data science […]

Semantic Image Segmentation with DeepLab in Tensorflow

Today, we are excited to announce the open source release of our latest and best performing semantic image segmentation model, DeepLab-v3+ [1], implemented in Tensorflow. This release includes DeepLab-v3+ models built on top of a powerful convolutional neural network (CNN) backbone architecture [2, 3] for the most accurate results, intended for server-side deployment. As part […]

Talent vs. Luck: the role of randomness in success and failure

The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent, intelligence, skills, efforts or risk taking. Sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant […]