EEDSP
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EEDSP
Digital Signal Processing, Data Analytics, Big Data, HPC, Deep Learning, GPGPU, Distributed and Parallel Computing
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gRPC: a true internet-scale RPC framework is now 1.0 and ready for production deployments

gRPC: a true internet-scale RPC framework is now 1.0 and ready for production deployments | EEDSP | Scoop.it
gRPC 1.0 released
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An introduction to data modeling using Google's Datastore

I come from the relational world like probably everyone who's been doing software for the last 5 years or so. In 2012 NoSQL databases were already a thing, and I had an opportunity to work with Google's Datastore, so I googled the documentation and started from the beginning.
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BigQuery and Dataproc shine in independent big data platform comparison | Google Cloud Big Data and Machine Learning Blog

BigQuery and Dataproc shine in independent big data platform comparison | Google Cloud Big Data and Machine Learning Blog | EEDSP | Scoop.it
Big data expert Mark Litwintschik benchmarks Google BigQuery, Hadoop, Spark, ElasticSearch, Presto and Google Cloud Dataproc with fascinating results.
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Machine Learning in the Cloud, with TensorFlow

Machine Learning in the Cloud, with TensorFlow | EEDSP | Scoop.it
At Google, researchers collaborate closely with product teams, applying the latest advances in Machine Learning to existing products and services - such as speech recognition in the Google app, search in Google Photos and the Smart Reply feature in Inbox by Gmail - in order to make them more useful. A growing number of Google products are using TensorFlow, our open source Machine Learning system, to tackle ML challenges and we would like to enable others do the same. Today, at GCP NEXT 2016, we announced the alpha release of Cloud Machine Learning, a framework for building and training custom models to be used in intelligent applications.
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Train your own image classifier with Inception in TensorFlow

Train your own image classifier with Inception in TensorFlow | EEDSP | Scoop.it
At the end of last year we released code that allows a user to classify images with TensorFlow models. This code demonstrated how to build an image classification system by employing a deep learning model that we had previously trained. This model was known to classify an image across 1000 categories supplied by the ImageNet academic competition with an error rate that approached human performance.
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Distributed TensorFlow Has Arrived

Distributed TensorFlow Has Arrived | EEDSP | Scoop.it
By Matthew Mayo, KDnuggets. KDnuggets has taken seriously its role to keep up with the newest releases of major deep learning projects, and in the recent past we have seen landmark such releases from major technology giants and as well as...
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Home — TensorFlow

Home — TensorFlow | EEDSP | Scoop.it
TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
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Kubernetes V1 Released - Cloud Native Computing Foundation to Drive Container Innovation

Kubernetes V1 Released - Cloud Native Computing Foundation to Drive Container Innovation | EEDSP | Scoop.it

On behalf of the community, it’s our pleasure to announce that Kubernetes, the open source container orchestration system, has reached the v1 milestone (GitHub).  This important release, built by over 400 contributors, means Kubernetes is ready for production use.  While this is huge news, there’s still much work remaining to build out the entire container toolset.

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Large-scale cluster management at Google with Borg

Google's Borg system is a cluster manager that runs hundreds of thousands of jobs, from many thousands of different applications, across a number of clusters each with up to tens of thousands of machines. It achieves high utilization by combining admission control, efficient task-packing, over-commitment, and machine sharing with process-level performance isolation. It supports high-availability applications with runtime features that minimize fault-recovery time, and scheduling policies that reduce the probability of correlated failures. Borg simplifies life for its users by offering a declarative job specification language, name service integration, real-time job monitoring, and tools to analyze and simulate system behavior.

We present a summary of the Borg system architecture and features, important design decisions, a quantitative analysis of some of its policy decisions, and a qualitative examination of lessons learned from a decade of operational experience with it.

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Inceptionism: Going Deeper into Neural Networks

Inceptionism: Going Deeper into Neural Networks | EEDSP | Scoop.it

Artificial Neural Networks have spurred remarkable recent progress in image classification and speech recognition. But even though these are very useful tools based on well-known mathematical methods, we actually understand surprisingly little of why certain models work and others don’t. So let’s take a look at some simple techniques for peeking inside these networks.

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分散システム処理モデルに関する動向について(MapReduceからBorgまで)

分散システム処理モデルに関する動向について(MapReduceからBorgまで) | EEDSP | Scoop.it
今回は、Googleから公開されたBorgなる論文を大規模分散システムの処理モデル的な観点から考察してみたいと思います。端的に言えば、Borgも含めた最近のクラウド環境の分散システムには重要なパラダイムシフト的な潮流があります。
大規模分散システムの処理モデル的な観点で、最初に近年のクラウド環境の分散システム動向を整理しつつ、最後にBorgから直近の分散システムの潮流を考察してみます。
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A QUIC update on Google’s experimental transport

A QUIC update on Google’s experimental transport | EEDSP | Scoop.it

Last year we announced QUIC, a UDP-based transport protocol for the modern Internet.  Over the last quarter, we’ve been increasing the amount of traffic to Google services that is served over QUIC and analyzing QUIC performance at scale. Results so far are positive, with the data showing that QUIC provides a real performance improvement over TCP thanks to QUIC's lower-latency connection establishment, improved congestion control, and better loss recovery.

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Google Takes Unconventional Route with Homegrown Machine Learning Chips

Google Takes Unconventional Route with Homegrown Machine Learning Chips | EEDSP | Scoop.it
At the tail end of Google’s keynote speech at its developer conference Wednesday, Sundar Pichai, Google’s CEO mentioned that Google had built its own chip
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Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source

Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source | EEDSP | Scoop.it
At Google, we spend a lot of time thinking about how computer systems can read and understand human language in order to process it in intelligent ways. Today, we are excited to share the fruits of our research with the broader community by releasing SyntaxNet, an open-source neural network framework implemented in TensorFlow that provides a foundation for Natural Language Understanding (NLU) systems. Our release includes all the code needed to train new SyntaxNet models on your own data, as well as Parsey McParseface, an English parser that we have trained for you and that you can use to analyze English text.
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Jeff Dean on Large-Scale Deep Learning at Google - High Scalability -

Jeff Dean on Large-Scale Deep Learning at Google - High Scalability - | EEDSP | Scoop.it

This quote is from Jeff Dean, currently a Wizard, er, Fellow in Google’s Systems Infrastructure Group. It’s taken from his recent talk: Large-Scale Deep Learning for Intelligent Computer Systems.

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Google Launches Cloud Dataproc, A Managed Spark And Hadoop Big Data Service

Google Launches Cloud Dataproc, A Managed Spark And Hadoop Big Data Service | EEDSP | Scoop.it
Google is adding another product in its range of big data services on the Google Cloud Platform today. The new Google Cloud Dataproc service sits between..
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AlphaGo: using machine learning to master the ancient game of Go

AlphaGo: using machine learning to master the ancient game of Go | EEDSP | Scoop.it

The game of Go originated in China more than 2,500 years ago. Confucius wrote about the game, and it is considered one of the four essential arts required of any true Chinese scholar.

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Google Cloud Vision API changes the way applications understand images

Google Cloud Vision API changes the way applications understand images | EEDSP | Scoop.it

Have you ever wondered how Google Photos helps you find all your favorite dog photos? With today’s release ofGoogle Cloud Vision API, developers can now build powerful applications that can see, and more importantly understand, the content of images. The uses of Cloud Vision API are game changing to developers of all types of applications and we are very excited to see what happens next!

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Improving Facebook's performance on Android with FlatBuffers

Improving Facebook's performance on Android with FlatBuffers | EEDSP | Scoop.it
In last six months, we have transitioned most of Facebook on Android to use FlatBuffers as the storage format.
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Google Files AI Patents

Google Files AI Patents | EEDSP | Scoop.it

Google has just revealed the fact that it has applied for at least six patents on fundamental neural network and AI. This isn't good for academic research or for the development of AI by companies. 

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Google Cloud Source Repositories

Google Cloud Source Repositories | EEDSP | Scoop.it

Google Cloud Source Repositories are fully-featured Git repositories hosted on Google Cloud Platform.

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Application of PageRank algorithm to analyze packages in R

Application of PageRank algorithm to analyze packages in R | EEDSP | Scoop.it
This article explains practical application of PageRank algorithm used by search engines to analyze packages in R with few commands on R like miniCran, pkgdep.
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Google Cloud Bigtable

Google Cloud Bigtable | EEDSP | Scoop.it

Cloud implementation of Bigtable. 

Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.

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