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Artificial Intelligence and SEO

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Artificial Intelligence White Papers Software Downloads, Definition and Webcasts

We focus on how advances in artificial intelligence, virtual reality and data analytics are helping to propel HR and the workplace into the future. What lies beyond the hype? Once it was big data, then cloud, now it is artificial intelligence, and that sub-set of it which is machine learning, that’s generating more heat than light. EZINE: Take a look at this edition of ComputerWeekly to learn more Uber, Volkswagen, and other companies that have experience with software ethics issues, how they’ve dealt with them, and what the consequences have been. WHITE PAPER: According to Gartner, by 2018, 25% of security products used for detection will have some form of machine learning built into them. Explore this 155 page e-book to learn more about artificial intelligence and machine learning for security professionals. WHITE PAPER: It’s time to learn the truth behind artificial intelligence – rather than what Hollywood has deemed “Killer robots.” Learn the facts behind 4 pervasive AI myths. Learn why chatbots can be employed to boost your business, how to use bots to get ahead, and uncover the 3 ways a bot can be used for engagement. WHITE PAPER: Machine learning enables organizations to quickly create, deploy and continuously monitor a high volume of analytic models to make better use of data to drive better business outcomes. What’s the connection to IT service intelligence? Learn potential benefits of including machine learning processes into an ITSI solution. Sponsored by IBM. RESOURCE CENTER: How can machine learning put your enterprise data to work in analytics? In this resource center, learn how to enact machine learning for your enterprise data, how to extract maximum insights from your data, and uncover how IBM can help organizations harness their enterprise data via deep learning. We learn how Wales has become a hotspot for cyber security innovation. Learn how to implement modern, cloud-based strategies for data management.
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Data Mining Vs Artificial Intelligence Vs Machine Learning

Data Mining: can cull existing information to highlight patterns, and serves as foundation for AI and machine learning. Artificial Intelligence: broad term for using data to offer solutions to existing problems. Machine Learning: goes beyond AI, and offers data necessary for a machine to learn & adapt. A quick education on the difference between data mining, artificial intelligence, and machine learning can give you a basic understanding of why they’re the real stars of market research, and, if used together, can present a formidable tactic that one can use to conquer any data question or conundrum. Data mining is actually one of the newer methods that market research companies are employing, but it serves as a foundation for both artificial intelligence and machine learning. What are the patterns? Which statistics are the most surprising? What is the correlation between A and B? That mined data can then be used as the basis for both artificial intelligence and machine learning. Data mining, artificial intelligence, and machine learning are so intertwined that it’s difficult to establish a ranking or hierarchy between the three. Data mining is an integral part of coding programs with the information, statistics, and data necessary for AI to create a solution. Often confused with artificial intelligence, machine learning actually takes the process one step further by offering the data necessary for a machine to learn and adapt when exposed to new data. Machine learning is capable of generalizing information from large data sets, and then detects and extrapolates patterns in order to apply that information to new solutions and actions. Obviously, certain parameters must be set up at the beginning of the machine learning process so that the machine is able to find, assess, and act upon new data. It’s a basic description of data mining, artificial intelligence, and machine learning, to be sure.
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Artificial Intelligence

Over time, and with many trials and errors, businesses have created complex technology that’s beginning to think like humans – problem-solving technology that can find truth from the meaning of words. It’s the first wave of a future where machines will be able to use artificial intelligence to interact with us. Artificial intelligence is the key to machines understanding human languages. For Inbenta, AI is the foundation on which our self-service and customer service and support products are designed and integrated for businesses worldwide. Inbenta AI works because we take your content and organize it in our knowledge base. It’s basically an electronic brain that’s able to efficiently organize your content to answer all the potential questions a human being might ask – in this case, your customers, employees, vendors, etc. What it amounts to is having living answers inside your site, waiting for someone to ask a question. To quickly access the answers to a user question, you need a contextual trigger to connect the dots, the same way people need a point of reference to create exchange between one another. For Inbenta it’s a specialized intelligent search engine that searches based on the contextual meaning of a user question, instead of keywords. A software that fully understands human language and conversation exactly as it’s written or spoken. We believe that one day, customer support departments will be run entirely by knowledge managers, computational linguists, human-machine interface specialists and AI. The actual job of call center agent will no longer exist. So we build search, service and support technologies to make a positive impact for our customers, their customers and beyond.
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