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Tensorflow with Javascript Brings Deep Learning to the Browser
Google launched Tensorflow.js, a Javascript implementation of its open-source Tensorflow deep-learning framework during the recent TensorFlow Dev Summit 2018. Tensorflow.js enables training models directly in the browser by leveraging the WebGL JavaScript API for faster computations.
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How Booking.com Uses Kubernetes for Machine Learning
Sahil Dua explained how Booking.com was able to scale machine learning (ML) models for recommending destinations and accommodation to their customers using Kubernetes, at the QCon London conference. In particular, he stressed how Kubernetes elasticity and resource starvation avoidance on containers helps them run computationally (and data) intensive, hard to parallelize, machine learning models.
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Facebook Releases Open Source "Detectron" Deep-Learning Library for Object Detection
Recent releases from Facebook and Google implement the most current deep-learning algorithms to take a crack at the challenging problem of machine object detection.
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Q&A on Machine Learning and Kubernetes with David Aronchick of Google from Kubecon 2017
InfoQ caught up with David Aronchick, product manager at Google and contributor to Kubeflow about the synergy between Kubernetes and Machine Learning at Kubecon 2017.
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Machine Learning and Artificial Intelligence - Two Conferences to Attend in 2018
The IEEE publishes an annual list of the Top 10 Technology Trends for each upcoming year. Making the list for 2018 are multiple topics surrounding artificial intelligence and machine learning. Deep learning comes in as the IEEE hottest trend for 2018.
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Modern Big Data Pipelines over Kubernetes
Container management technologies like Kubernetes make it possible to implement modern big data pipelines. Eliran Bivas, senior big data architect at Iguazio, spoke at the recent KubeCon + CloudNativeCon North America 2017 Conference about big data pipelines and how Kubernetes can help develop them.
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Building GPU Accelerated Workflows with TensorFlow and Kubernetes
Daniel Whitenack spoke at the recent KubeCon + CloudNativeCon North America 2017 Conference about GPU based deep learning workflows using TensorFlow and Kubernetes technologies. He discussed the open source data pipeline framework Pachyderm.
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TensorFlow Lite Supports On-Device Conversational Modeling
TensorFlow Lite, the light-weight solution of open source deep learning framework TensorFlow, supports on-device conversation modeling to plugin the conversational intelligence features into chat applications. The TensorFlow team recently announced the release of TensorFlow Lite, which can be used in mobile and embedded devices.
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TensorFlow Serving 1.0 Release Detailed at Google I/O
Google's Noah Fiedel details new programming model for TensorFlow Serving in a stable 1.0 release. Subject matter addresses common challenges with portability, servablility, and reproducibility improvements.
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Google Announces Tensor2Tensor for TensorFlow
Google Brain team open-sourced Tensor2Tensor, a set of utilities and wrappers for modularizing TensorFlow workflow components to create a more portable, and repeatable environment for TensorFlow-based deep neural network programs.
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Overview of Changes in Tensorflow Version 1.3
Although it has only been a month since the release of version 1.2.1, there have been many changes to the software in version 1.3. Developers can find an extensive release report on the Github page of Tensorflow. This article will list the most important changes developers have to know about before and after upgrading to Tensorflow v1.3.
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Google Released Facets: A Visualisation Tool for Big Data
Google open-sourced Facets: a data visualisation tool to explore data for machine learning scientists. Facets aim is to make big data set understandable and interpretable. Facets wants to be the visualisation tool researchers use to find nuances and insights in large data sets.
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Second-Generation TPU Offers Both Training and Model Serving, Free Research Tier on GCP
Google introduces the second-generation TPU at Google I/O and releases photos leading to much speculation about the new architecture. GCP offers a research-tier and an alpha release application process for access to a 1000 TPU cluster for free.
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Google Released MobileNets: Efficient Pre-Trained Tensorflow Computer Vision Models
Google released several pre-trained computer vision models for mobile phones in the Tensorflow Github repository. Developers can choose from several models that differ in amount of parameters, computations for processing one image, and accuracy. Developers can trade accuracy for battery power for their specific application.
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Google Announces Tensorflow Lite: A Neural Network Library for Mobile Phones
Dave Burke, VP of engineering at Google, announced a new version of Tensorflow optimised for mobile phones. This new library, called Tensorflow Lite, would enable developers to run their artificial intelligence applications in real time on the phones of users. The library is designed to be “fast and small while still enabling state-of-the-art techniques”.