Intel Democratizes Deep Learning Application Development with Launch of Movidius Neural Compute Stick

Introducing the world’s first USB-based #deeplearning inference kit:  #Intel

  • Today, Intel launched the Movidius™ Neural Compute Stick, the world’s first USB-based deep learning inference kit and self-contained artificial intelligence (AI) accelerator that delivers dedicated deep neural network processing capabilities to a wide range of host devices at the edge.
  • Designed for product developers, researchers and makers, the Movidius Neural Compute Stick aims to reduce barriers to developing, tuning and deploying AI applications by delivering dedicated high-performance deep-neural network processing in a small form factor.
  • More: Movidius Press Kit | Movidius Neural Compute Stick Product Brief | Intel at CVPR Fact Sheet

    As more developers adopt advanced machine learning approaches to build innovative applications and solutions, Intel is committed to providing the most comprehensive set of development tools and resources to ensure developers are retooling for an AI-centric digital economy.

  • Whether it is training artificial neural networks on the Intel® Nervana™ cloud, optimizing for emerging workloads such as artificial intelligence, virtual and augmented reality, and automated driving with Intel® Xeon® Scalable processors, or taking AI to the edge with Movidius vision processing unit (VPU) technology, Intel offers a comprehensive AI portfolio of tools, training and deployment options for the next generation of AI-powered products and services.
  • “The Myriad 2 VPU housed inside the Movidius Neural Compute Stick provides powerful, yet efficient performance – more than 100 gigaflops of performance within a 1W power envelope – to run real-time deep neural networks directly from the device,” said Remi El-Ouazzane, vice president and general manager of Movidius, an Intel company.

Today, Intel launched the Movidius™ Neural Compute Stick, the world’s first USB-based deep learning inference kit and self-contained artificial intelligence (AI) accelerator that delivers dedicated deep neural network processing capabilities to a wide range of host devices at the edge. Designed for product developers, researchers and makers, the Movidius Neural Compute Stick aims to reduce barriers to developing, tuning and deploying AI applications by delivering dedicated high-performance deep-neural network processing in a small form factor.
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Deep Learning: Definition, Resources, Comparison with Machine Learning

#DeepLearning: Definition, Resources, Comparison with #MachineLearning #abdsc

  • It is about designing algorithms that can make robots intelligent, such a face recognition techniques used in drones to detect and target terrorists, or pattern recognition / computer vision algorithms to automatically pilot a plane, a train, a boat or a car.
  • Many deep learning algorithms (clustering, pattern recognition, automated bidding, recommendation engine, and so on)  — even though they appear in new contexts such as IoT or machine to machine communication — still rely on relatively old-fashioned techniques such as logistic regression, SVM, decision trees, K-NN, naive Bayes, Bayesian modeling, ensembles, random forests, signal processing, filtering, graph theory, gaming theory, and many others.
  • Some are new, such as indexation algorithms to automate digital publishing, improve search engines, or create and manage large catalogs such as Amazon’s product listing.
  • Example of deep learning algorithms for clustering

    As a result, many deep learning practitioners call themselves data scientist, computer scientist, statistician, or sometimes engineer.

  • Below are some resources to help you get started with deep learning: articles on this topic started to appear in large numbers around 2015, though many date back to before 1990.

Deep learning is sometimes referred to as the intersection between machine learning and artificial intelligence. It is about designing algorithms that can make…
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The Air Force and IBM are building an AI supercomputer

The Air Force and @IBM are building an #AI supercomputer #techradio

  • IBM and the USAF announced on Friday that the machine will run on an array of 64 TrueNorth Neurosynaptic chips.
  • The TrueNorth chips are wired together like, and operate in a similar fashion to, the synapses within a biological brain.
  • That is, these chips don’t require a clock, as conventional CPUs do, to function.VIDEOWhat’s more, because of the distributed nature of the system, even if one core fails, the rest of the array will continue to work.
  • This 64-chip array will contain the processing equivalent of 64 million neurons and 16 billion synapses, yet absolutely sips energy — each processor consumes just 10 watts of electricity.Like other neural networks, this system will be put to use in pattern recognition and sensory processing roles.
  • The Air Force wants to combine the TrueNorth’s ability to convert multiple data feeds — whether it’s audio, video or text — into machine readable symbols with a conventional supercomputer’s ability to crunch data.This isn’t the first time that IBM’s neural chip system has been integrated into cutting-edge technology.

Supercomputers today are capable of performing incredible feats, from accurately predicting the weather to uncovering insights into climate change, but they sti…
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The Evolution of Artificial Intelligence

The Evolution of Artificial Intelligence 

#AI @Internetmeds

  • The third one was in 1969 when the word information technology was introduced in the world, and the fourth one is the revolution of Artificial Intelligence which we are experiencing right now.
  • Artificial Intelligence is the set of tools and programs that make any software smart enough that the observer would feel that he is dealing with a human, not with the software.
  • Artificial Narrow Intelligence: The first stage of AI as the name suggests is functionally very narrow.
  • Artificial General Intelligence: AGI may only be one step further from ANI but this step is the biggest achievement of humanity.
  • Artificial Super Intelligence: ASI is the final stage of AI predicted by the scientist in which the machines with ASI can able to pass the average human intelligence.

This world has seen four major revolutions that changed its entire face. The first revolution was in 1784 when the first steam engine introduced in the world. The second one was in 1870when the electricity was invented. The third one was in 1969 when the word information technology was introduced in the world, and the fourth one is the revolution of Artificial Intelligence which we are experiencing right now. The present revolutionary era is based on the extreme automation and global connectivity for which Artificial Intelligence is imperative. Just like the other three revolutions, the changes and developments that this revolution is creating will be the bedrock of our future and our way of interacting with technology and with each other.
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Facebook uses Artificial Intelligence to help spot potentially suicidal users

  • On Wednesday, Facebook announced that it is ready to take a first and significant step in building a safer and more supportive Facebook community by significantly strengthening its own suicide prevention tools (Facebook has had suicide reporting and tools for a decade).
  • Noting that live suicides had occurred on similar platforms before, Facebook is now testing a system that relies on pattern recognition based on posts previously reported for suicide risk.
  • Now, when suicide-like behavior is detected, Facebook will provide the at-risk user with resources that range from the ability to contact a friend or helpline to a few potentially helpful tips for dealing with depression without halting their stream.
  • However, Vanessa Callison-Burch, a Facebook product manager, told BBC that the social media company is hoping to avoid invading anyone’s privacy or tampering with personal dynamics between friends.
  • While Facebook’s system is still new, it is reassuring to see that the social media company is dedicated to protecting its users from adding to this troubling statistic.

On Wednesday, Facebook announced that it is ready to take a first and significant step in building a safer and more supportive Facebook community by
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Deep Learning: Definition, Resources, Comparison with Machine Learning

#DeepLearning: Definition, Resources, Comparison with Machine Learning

  • Many deep learning practitioners call themselves data scientist, computer scientist, statistician, or sometimes engineer.
  • Deep learning is sometimes referred to as the intersection between machine learning and artificial intelligence.
  • In my opinion, deep learning also tries to automate some data science processes.
  • Deep learning simplified (video)
  • An Introduction to Deep Learning and it’s role for IoT/ future cities

Deep learning is sometimes referred to as the intersection between machine learning and artificial intelligence. It is about designing algorithms that can make…
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The AI Revolution: Deep Learning Will Change American Business

The AI revolution: Why you need to learn about deep learning

  • Within AI is a set of techniques called machine learning, enabling computers to get better at tasks with practice.
  • And within machine learning is deep learning, involving algorithms by which computers train themselves using multi-layered neural networks and vast quantities of data.
  • Even the Internet metaphor doesn’t do justice to what AI with deep learning will mean, in Ng’s view. ‘
  • Many CEOs tell me their greatest fear is being blindsided by a competitor they never even thought of as a competitor, threatening to make the CEO’s business irrelevant by using technology and a business model the CEO hadn’t imagined.
  • Computing power’s steady advance combined with specific new chip designs, fast-improving algorithms, and virtually limitless data available online are together sparking “deep learning’s Cambrian explosion,” says Frank Chen , a partner at the Andreessen Horowitz venture capital firm.

A lot of CEOs regretted not planning for the Internet earlier. Now some believe leaders should start thinking about deep learning.
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