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Why the Focus on Artificial Intelligence and Machine Learning?

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The adoption of artificial intelligence and machine learning

Earlier in this series, we learned why IBM is focusing on investments and acquisitions in the IoT (Internet of Things) space. Let’s see how AI (artificial intelligence) and ML (machine learning) could drive the expected $2 trillion in spending during the next new computing cycle.

The SMAC (social, mobile, analytics, and cloud) revolution is rapidly transforming the technology space. The influx of data, the majority of which is unstructured, coupled with the advances in processing power and cognitive technology, has led to the necessity of machine learning to facilitate better-informed decisions.

In today’s scenario, understanding the content of images as well as organizing and extracting relevant information from raw media and data pose a significant challenge. The specialty of deep learning is that it can be deployed in structured and unstructured data and context.

AI is an umbrella term that encompasses natural language processing, machine learning, and robotics. AI enables sensing, prediction, analysis, and solutions for various IT (information technology) issues.
AI Forrester

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Artificial intelligence: Major driver in 2017

AI is a consumer-driven technology that enables us to gauge customer sentiment. It’s little wonder that deep learning, machine learning, and AI have all taken the world by storm.

To understand how AI and cognitive computing are related, cognitive computing can be thought of as “a complete architecture of multiple AI subsystems that work together,” according to Lynne Parker, director of the Information and Intelligent Systems at the National Science Foundation.

Citing Forrester’s recent report, Forbes stated that businesses that use AI, big data, and IoT technologies to reveal new business insights “will steal $1.2 trillion per annum from their less informed peers by 2020.” Moreover, across all businesses, AI will see an increase of more than 300% in investment between 2016 and 2017. Later in this series, we’ll discuss acquisitions by IBM, Alphabet (GOOG), Microsoft (MSFT), Apple (AAPL), and Salesforce (CRM) in this space.

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