Blog

Apr 24, 2018   |   Jack Dashwood

Fake it ‘Till You Make It: Synthetic Datasets Assisting Machine Learning in Data Scarce Environments

Deep learning approaches are being applied across a broad spectrum of disciplines, having demonstrated that by combining big data with supervised learning, that we can train systems to perform artificial intelligence (AI)-centric tasks previously considered impossible with traditional approaches. One of the biggest drivers of the machine learning trend has been the availability of large…

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#Intel Movidius

Apr 20, 2018   |   Bhushan Desam

Intel® Xeon® Processor: A Workhorse for Enterprise AI

Is your enterprise implementing artificial intelligence (AI) to be more efficient and to bring predictive capabilities for making better business decisions? Like many customers that we speak to, you may be considering various use cases that may involve tabular data, images, text, or sensor data from IoT and other sources. A common concern that many…

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#Product News #Xeon Processor

Apr 18, 2018   |   Avijit Chakraborty, Adam Procter, Sharath Nittur Sridhar, Jayaram Bobba, Robert Adams, Leona Cook, Jennifer Myers

High-performance TensorFlow* on Intel® Xeon® Using nGraph™

We recently announced the open source release of Intel® nGraph™, a C++ library, compiler and runtime suite for running Deep Neural Networks on a variety of devices. Today we are pleased to announce availability of simplified bridge code that can be used to link TensorFlow-based projects to pre-optimized nGraph backends. The bridge code implementation delivers…

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#Framework Optimizations #nGraph #Open source #TensorFlow

Apr 12, 2018   |   Yinyin Liu

Deep Learning Foundations to Enable Natural Language Processing Solutions

Natural language processing (NLP) is one of the most familiar AI capabilities, having become ubiquitous through consumer digital assistants and chatbots as well as commercial applications like textual analysis of financial or legal records. Intel technology is enabling a variety of NLP applications through the advancement of hardware and software capabilities for deep learning and…

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#Intel AI Lab #NLP

Apr 09, 2018   |   Intel AI

The Artificial Intelligence Conference in Beijing: Solving Real-World Problems with Frameworks Optimized for Intel Architecture

Intel is co-presenter of The Artificial Intelligence Conference in Beijing, China on April 10–13, 2018.  The event explores and shares the latest innovations in applied AI. Intel’s keynotes and sessions will share practical use cases and applications, and provide the technical knowledge needed to develop and implement successful AI applications across a variety of industries today.…

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#Events

Apr 06, 2018   |   Prakash Mallya

AI Development in India’s Ecosystem

A recent Intel India commissioned report, undertaken by the International Data Corporation (IDC) that surveyed 194 Indian organizations across sectors, unveiled an increasing appetite toward the adoption of Artificial Intelligence (AI)—which in turn, is expected to spike organization spends on such technology over the next 18 months. The report shows that India is gearing up…

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#What We Solve

Apr 06, 2018   |   Raddaoui Ala

Let's Flow within Kubeflow

In this blog post, we will go through how to train MNIST using distributed Tensorflow* and Kubeflow* from scratch. Introduction Machine learning (ML) and deep learning (DL) have been around for more than half a century now, yet it is just as of late that these ideas have begun to flourish—thanks to advancements in compute…

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#Kubernetes #Open source #TensorFlow

Apr 02, 2018   |   Bharat Kaul

Neuroscience to Computer Science: An Update from AI Research at Intel

Artificial Intelligence (AI) is poised to have a transformative effect on human civilization. Enabled by decades of research, AI adoption is now accelerating due to the availability of exascale computing, the explosion of big data, and the emergence of algorithms that can take advantage of these compute and data resources. The disruptive transformation may manifest…

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#Research

Mar 27, 2018   |   Balaji Subramaniam, Ajay Deshpande

Kubernetes Volume Controller (KVC): Data Management Tailored for Machine Learning Workloads in Kubernetes

In this blog post, we describe Kubernetes Volume Controller (KVC). It is an open source project we’ve developed, which provides basic volume and data management in Kubernetes tailored towards machine learning (ML) workloads and pipelines.   Why Should I Care? Data is an important component in ML workloads and pipelines. Typically, data scientists and ML…

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#CTO Office #Technical Blog

Mar 26, 2018   |   David Austin

A Titanic Win at Kaggle’s Iceberg Classifier Challenge

Recently, my teammate Weimin Wang and I competed in Kaggle’s Statoil/C-CORE Iceberg Classifier Challenge. The competition challenged participants to classify images acquired from C-band radar and was the most participated in image classification competition that Kaggle has ever hosted—so I’m very excited to announce that we won 1st place out of 3,343 teams! Now we’d…

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#Image Classification