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Demystifying AI, Machine Learning and Deep Learning

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Sometimes its ok and good for everyone to un-develop something existing to uncover the hidden gems which are already there and are useful. May be its like Un-Develop to Innovate? Alan Turing published "Turing Test" that speculates the possibility of creating machines that think. In order to pass the test, a computer must be able to carry on a conversation that was indistinctive from a conversation with a human being. AI apart from its traditional definition also includes things like planning, understanding language, recognizing objects and sounds, learning, and problem solving.


This is Why China Has the Edge in Artificial Intelligence

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People watch the intelligent service robot in the Wenling Branch of Agriculture Bank of China on August 28, 2016 in Wenling, Zhejiang Province of China. The intelligent service robot, 'Binbin,' can provide information service, autonomous navigation and guidance for requested positions and is capable of human-robot interaction. With decades of lab research, artificial intelligence (AI) technology is finally coming to its anticipated fruition. The time is right to open a Pandora's Box for laboratory AI, introducing it to solve real business needs and address real-world problems. It is also the time for some scientists in the field to consider starting their entrepreneurial journey.


Getting Started with Big Data Integration using HDFS and DMX-h

@machinelearnbot

The data researchers no longer depend only on interviews, surveys, observational studies to collect data. Instead, they have switched to the faster ways of data collection which includes leveraging internet, cameras, smartphones, drones, bots and many more. Later, the collected data is used by organization / governments to make business decisions. But, before that, they require a device or system which can store and secure such big data sets. One such system is Hadoop File Distribution System, commonly known as HDFS.


3 Companies Using Artificial Intelligence to Their Advantage

International Business Times

This article originally appeared in Motley Fool. Artificial intelligence (AI) is already impacting our lives in many ways. From intelligent video curation on Alphabet's (NASDAQ:GOOG) (NASDAQ:GOOGL) YouTube and Google web search to Apple's (NASDAQ:AAPL) Siri personal assistant, AI is already making our lives easier. AI can also help corporations and customers fight against rapidly evolving cyberthreats. For instance, FireEye's (NASDAQ:FEYE) Helix cybersecurity platform is able to automate threat detection and prevention with the help of this emerging technology.


With marketing and AI coming together, what does the future hold?

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Marketing and Artificial Intelligence have had a great relationship for more than five years now. Although both fields emerged around the same time, marketing caught on because of the lack of technology requirement. We didn't need to have computers to process sales and marketing strategies. Now that we've experienced the tip of the iceberg when it comes to AI, we can imagine a better future with AI and marketing together. Most brands have been using AI as a tool to create value for their customers from a purely technological standpoint.


Machine Learning with Small Data

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Machine learning and big data are broadly believed to be synonymous. The story goes that large amounts of training data are needed for algorithms to discern signal from noise. As a result, machine learning techniques have been most used by web companies with troves of user data. For Google, Facebook, Microsoft, Amazon, Apple (or the "Fearsome Five" as Farhad Manjoo of the New York Times has dubbed them), obtaining large amounts of user data is no issue. Data usage policies have become increasingly broad, allowing these companies to make use of everything from our keystrokes to our personal locations as we use company products.


AI Definitions: Machine Learning vs. Deep Learning vs. Cognitive Computing vs. Robotics vs. Strong AI….

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AI is the compelling topic of tech conversations du jour, yet within these conversations confusion often reigns – confusion caused by loose use of AI terminology. The problem is that AI comes in a variety of forms, each one with its own distinct range of capabilities and techniques, and at its own stage of development. Some forms of AI that we frequently hear about, such as Artificial General Intelligence, the kind of AI that might someday automate all work and that we might lose control of – may never come to pass. Others are doing useful work and are driving growth in the high performance sector of the technology industry. These definitions aren't meant to be the final word on AI terminology, the industry is growing and changing so fast that terms will change and new ones will be added.


3 Companies Using Artificial Intelligence to Their Advantage

#artificialintelligence

Artificial intelligence (AI) is already impacting our lives in many ways. From intelligent video curation on Alphabet's (NASDAQ:GOOG) (NASDAQ:GOOGL) YouTube and Google web search to Apple's (NASDAQ:AAPL) Siri personal assistant, AI is already making our lives easier. AI can also help corporations and customers fight against rapidly evolving cyberthreats. For instance, FireEye's (NASDAQ:FEYE) Helix cybersecurity platform is able to automate threat detection and prevention with the help of this emerging technology. The early adoption of AI by Alphabet, Apple, and FireEye could help them steal a march over rivals.


6 Types of Artificial Neural Networks Currently Being Used in Machine Learning

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Artificial neural networks are computational models which work similar to the functioning of a human nervous system. There are several kinds of artificial neural networks. These type of networks are implemented based on the mathematical operations and a set of parameters required to determine the output. This neural network is one of the simplest form of ANN, where the data or the input travels in one direction. The data passes through the input nodes and exit on the output nodes.


How Big Tech Is Profiting by Selling AI-as-a-Service

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Artificial intelligence (AI) is still in its infancy, but it is truly a transformational technology. Thus far, mainly the companies with the largest stores of data have been able to benefit from the science. When talking about AI, most are referring to machine learning and, more specifically, deep learning, a technique that requires the processing of massive amounts of data in order to train these systems. So far these innovations haven't been largely available to smaller companies, but that is changing. The widespread adoption of cloud computing is beginning to alter that dynamic, as companies are working to incorporate these capabilities into their cloud offerings.