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Artificial intelligence is more about the future

Amid the infiltration of artificial intelligence into business and society, spawning fears from some of Armageddon, humankind's greatest AI threat may very well come from within.

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Guide to using advanced analytics and AI in business applications

AI hype is becoming reality as the technology gains ground in businesses. Get tips on machine learning, cognitive computing and other advanced analytics initiatives in this guide.

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Data bias runs amok in machine learning

AI holds massive potential for good, but it also amplifies negative outcomes if data scientists don't recognize data biases and correct them in machine learning data sets.

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Cognitive computing patches doctor-patient relationship

Cognitive computing and healthcare data aggregation may prove to be important bedside companions to doctors treating their patients in the era of medical specialization.

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    Big data and predictive analytics pair up on challenges

    Big data and predictive analytics may seem synonymous, but understanding the constraints of each discipline is the key to extracting business value from projects that combine them.

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    unstructured data

    Unstructured data is information, in many different forms, that doesn't hew to conventional data models and thus typically isn't a good fit for a mainstream relational database.

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    deep learning

    Deep learning is an aspect of artificial intelligence (AI) that is concerned with emulating the learning approach that human beings use to gain certain types of knowledge.

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  • Advanced analytics software

    IBM analytics software needs less confusing message

    IBM's analytics software is strong technically but disjointed and hard to understand, say analysts who think simplifying things should be a priority at the company's Think 2018 conference.

  • Data visualization software

    Hyper engine could boost analytics with Tableau

    The Hyper in-memory data engine added in Tableau 10.5 could make Tableau analytics capabilities more expansive, enabling the software to support new use cases, like IoT analytics.

  • Predictive analytics

    Feed your predictive analytics projects the right data

    More data doesn't always benefit predictive analytics projects. Data sources must be scrutinized and understood before being used in a predictive model, experts warn at the AI World conference.

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