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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”.
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Emerging Technologies for the Enterprise Conference 2017: Day Two Recap
Day Two of the 12th annual Emerging Technologies for the Enterprise Conference was held in Philadelphia. This two-day event included keynotes by Blair MacIntyre (augmented reality pioneer) and Scott Hanselman (podcaster), and featured speakers Kyle Daigle (engineering manager at GitHub), Holden Karau (principal software engineer at IBM), and Karen Kinnear (JVM technical lead at Oracle).
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Google Reveals Details of TensorFlow Processor Unit Architecture
Google's hardware engineering team that designed and developed the TensorFlow Processor Unit detailed the architecture and benchmarking experiment earlier this month. This is a follow up post on the initial announcement of the TPU from this time last year.
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TensorFlow 1.0 Released
Google recently announced TensorFlow version 1.0. Python API is now stable and experimental APIs for Java and Go have been added. XLA delivers significant performance increase. Keras can also be integrated with TensorFlow using a build-in module. tf.transform, tf.layers, tf.metrics, and tf.losses all add new features to the framework..
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Android Things Brings TensorFlow-Based Machine Learning and Computer Vision to IoT Devices
Recently released Developer Preview 2 (DP2) for Android Things makes it easier to use TensorFlow for machine learning and computer vision on IoT devices. Additionally, it extends USB audio for several IoT platforms, adds Intel Joule support, and enables direct use of native drivers through a new Native PIO API.
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Spark Summit EU Highlights: TensorFlow, Structured Streaming and GPU Hardware Acceleration
Apache Spark integration with deep learning library TensorFlow, online learning using Structured Streaming and GPU hardware acceleration were the highlights of Spark Summit EU 2016 held last week in Brussels.