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Ingress

Ingress | EEDSP | Scoop.it
The world around you is not what it seems. Our future is at stake and you must choose a side. Join my faction in Ingress - a global game of mystery, intrique and conquest.
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EEDSP
Digital Signal Processing, Data Analytics, Big Data, HPC, Deep Learning, GPGPU, Distributed and Parallel Computing
Curated by Shiwon Cho
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Considering Your First #BigData Implementation? Size don't matter, even smaller companies can do it! Here's how:

Considering Your First #BigData Implementation? Size don't matter, even smaller companies can do it! Here's how: | EEDSP | Scoop.it
Considering Your First #BigData Implementation? Size don't matter, even smaller companies can do it! Here's how:
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The Top 7 Technology Trends for 2018

The Top 7 Technology Trends for 2018 | EEDSP | Scoop.it
Which technology trends will create the Year of Transition? Here are the top 7 technology trends for 2018 that will affect organisations and governments.
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Best of arXiv.org for AI, Machine Learning, and Deep Learning - November 2017 - insideBIGDATA

Best of arXiv.org for AI, Machine Learning, and Deep Learning - November 2017 - insideBIGDATA | EEDSP | Scoop.it

Best of http://arXiv.org for AI, Machine Learning, and Deep Learning – November 2017

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Projects – Stanford Literary Lab

Projects – Stanford Literary Lab | EEDSP | Scoop.it
This project arises from a systematic comparison of hundreds of dramatic networks from a dozen different literatures and historical periods. At this stage, we are using computer models to identify the fundamental properties of dramatic networks – with particular attention to the correspondence between genres and patterns of growth – and reflect on the relationship between modeling parameters and aesthetico-critical categories.
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What’s the Difference Between Deep Learning Training and Inference? | The Official NVIDIA Blog

What’s the Difference Between Deep Learning Training and Inference? | The Official NVIDIA Blog | EEDSP | Scoop.it
Let's break let’s break down the progression from deep-learning training to inference in the context of AI how they both function.
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Fully-Parallel Text Generation for Neural Machine Translation - Salesforce research

Fully-Parallel Text Generation for Neural Machine Translation - Salesforce research | EEDSP | Scoop.it
A neural machine translation system that can produce an entire sentence at a time in a fully parallel way, overcoming a limitation of all current neural MT models.
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The State of ML and Data Science 2017

The State of ML and Data Science 2017 | EEDSP | Scoop.it

A big picture view of the state of data science and machine learning that shares who is working with data, what's happening at the cutting edge of machine learning across industries, and how new data scientists can best break into the field.

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Hybrid Fortran Pulls Legacy Codes into Acceleration Era

Hybrid Fortran Pulls Legacy Codes into Acceleration Era | EEDSP | Scoop.it

Hybrid Fortran software components and build workflow.


GPU accelerated supercomputing is not a new phenomenon with many high performance computing codes already primed to run on Nvidia hardware in particular. H

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What’s the Difference Between Deep Learning Training and Inference? | The Official NVIDIA Blog

What’s the Difference Between Deep Learning Training and Inference? | The Official NVIDIA Blog | EEDSP | Scoop.it

This is the second of a multi-part series explaining the fundamentals of deep learning by long-time tech journalist Michael Copeland.

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Word embeddings in 2017: Trends and future directions

Word embeddings in 2017: Trends and future directions | EEDSP | Scoop.it
This post gives an overview of the deficiencies of pre-trained word embeddings in 2017 and how recent approaches have tried to resolve them.
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Introducing NNVM Compiler: A New Open End-to-End Compiler for AI Frameworks | Amazon Web Services

Introducing NNVM Compiler: A New Open End-to-End Compiler for AI Frameworks | Amazon Web Services | EEDSP | Scoop.it
You can choose among multiple artificial intelligence (AI) frameworks to develop AI algorithms. You also have a choice of a wide range of hardware to train and deploy AI models. The diversity of frameworks and hardware is crucial to maintaining the health of the AI ecosystem. This diversity, however, also introduces several challenges to AI […]
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NVIDIA Deep Learning Accelerator

NVIDIA Deep Learning Accelerator | EEDSP | Scoop.it
The NVIDIA Deep Learning Accelerator (NVDLA) is a free and open architecture that promotes a standard way to design deep learning inference accelerators.
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CUTLASS: Fast Linear Algebra in CUDA C++ | Parallel Forall

CUTLASS: Fast Linear Algebra in CUDA C++ | Parallel Forall | EEDSP | Scoop.it
CUTLASS provides CUDA C++ techniques to develop fast linear algebra algorithms using high-performance matrix multiplication as a building block.
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TensorRT 3: Faster TensorFlow Inference and Volta Support | Parallel Forall

TensorRT 3: Faster TensorFlow Inference and Volta Support | Parallel Forall | EEDSP | Scoop.it
TensorRT 3 is a deep learning inference optimizer. New features include TensorFlow model import, a Python API, and support for Volta GPU Tensor Cores.
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Building a Microservices Ecosystem with Kafka Streams and KSQL

Building a Microservices Ecosystem with Kafka Streams and KSQL | EEDSP | Scoop.it
How to build fine grained, streaming microservices with the Apache Kafka Streams API and KSQL.
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Better Random Number Generation for OpenSSL, libc, and Linux Mainline | Amazon Web Services

Better Random Number Generation for OpenSSL, libc, and Linux Mainline | Amazon Web Services | EEDSP | Scoop.it
by Colm MacCarthaigh In 2015, AWS introduced s2n, a new open source implementation of the TLS/SSL protocols that protect the privacy and integrity of data moving over a network. s2n was designed to be secure, simple, small, and fast. The project is thriving, and we use it extensively. In February, our CISO Stephen Schmidt shared […]
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AMD Rolls Out ROCm 1.7 Platform For Supercomputing 17 - Phoronix

AMD Rolls Out ROCm 1.7 Platform For Supercomputing 17 - Phoronix | EEDSP | Scoop.it

AMD has unveiled the Radeon Open Compute platform (ROCm) 1.7 release as part of their wares at this week's Supercomputing 17 (SC17) conference in Denver. The ROCm 1.7 update introduces multi-GPU support for "the latest Radeon GPU hardware" (presumably referring to Vega) while also supporting TensorFlow and Caffe via AMD's MIOpen libraries.

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SLING: A Natural Language Frame Semantic Parser

SLING: A Natural Language Frame Semantic Parser | EEDSP | Scoop.it
Posted by Michael Ringgaard, Software Engineer and Rahul Gupta, Research Scientist Until recently, most practical natural languag
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Apache Kafka Goes 1.0 - Confluent

Apache Kafka Goes 1.0 - Confluent | EEDSP | Scoop.it
The mission-critical deployments, the robust feature set, the long history all say that Kafka is an Enterprise-capable product. Apache Kafka is going 1.0!
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Eager Execution: An imperative, define-by-run interface to TensorFlow

Eager Execution: An imperative, define-by-run interface to TensorFlow | EEDSP | Scoop.it

Posted by Asim Shankar and Wolff Dobson, Google Brain Team Today, we introduce eager execution for TensorFlow.

 Eager execution is an imperative, define-by-run interface where operations are executed immediately as they are called from Python. This makes it easier to get started with TensorFlow, and can make research and development more intuitive.

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High-Performance GPU Computing in the Julia Programming Language | Parallel Forall

High-Performance GPU Computing in the Julia Programming Language | Parallel Forall | EEDSP | Scoop.it
A new extension for the Julia programming language for mathematical computing enhances the Julia compiler to generate native code for CUDA GPUs
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Deep Voice 3: 2000-Speaker Neural Text-to-Speech

Deep Voice 3: 2000-Speaker Neural Text-to-Speech | EEDSP | Scoop.it
Today, we are excited to announce Deep Voice 3, the latest milestone of Baidu Research’s Deep Voice project. Deep Voice 3 teaches machines to speak by imitating thousands of human voices from people across the globe.

The Deep Voice project was started to revolutionize human-technology interactions by applying modern deep learning techniques
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New Optimizations Improve Deep Learning Frameworks For CPUs

New Optimizations Improve Deep Learning Frameworks For CPUs | EEDSP | Scoop.it
Today, most machine learning is done on processors. Some would say that acceleration of learning has to be done on GPUs, but for most users that is not goo
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abseil / abseil.io

abseil / abseil.io | EEDSP | Scoop.it

Google has developed many abstractions that either match or closely match features incorporated into C++14, C++17, and beyond. Using the Abseil versions of these abstractions allows you to access these features now, even if your code is not yet ready for life in a post C++11 world.

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