With all that computers are now capable of doing, it’s easy to forget that they’re not capable of thinking. However, they can now do things that until recently only people could do. They can recognize handwriting, identify faces, and can perform tasks that call for cognitive skills, like planning, learning, and reasoning based on incomplete or unstructured information.
Cognitive technologies, coming out of artificial intelligence, have been evolving for decades. As fantastical as it might have seemed a generation ago, these technologies are replicating a wide range of human capabilities, from deduction and reasoning to learning and sensory perception:
- Decision-making: machine learning and deep learning are making it possible for systems to interpret information and make intelligent, informed decisions
- Processing: knowledge representation technologies are helping intelligent systems extend their search for connections
- Sensory perception: through such technologies as speech processing and computer vision, systems are deriving clearer insights — with speed — from information contained in multimedia, and making it possible to deliver dramatically improved user experiences
Such gains — and many more to come in short order as the pace of technological advancement intensifies — have piqued the interest of companies that see in cognitive, AI and analytics the possibility of breaking tradeoffs between cost, speed, and quality. Even now, many enterprises are running solutions based on cognitive with great results.
Demand for cognitive computing technologies is sharply rising. According to a leading B2B research organization, the cognitive market will have grown to over $12.5 billion by 2019 — a fivefold increase from 2014. A few years ago, IDC predicted that by this year half of all consumers would be interacting with cognitive technology on a regular basis.
A recent survey of early adopters showed the real business benefits of cognitive computing. Among the findings:
- Sixty-five per cent say adopting cognitive computing is very important to their company’s success
- Fifty-eight per cent say it is essential to their digital transformation
- Over half say it will help them unlock the hidden value of their dark data (data not used to derive insights or for decision-making)
- Fifty per cent say it is already helping their organization gain major competitive advantage
Until recently, the task of deriving intelligent, actionable insights from greater and richer volumes of data residing in multiple sources was challenging, and was generally reserved for scientific and larger companies with deep pockets. However, rapid technological advancements have made it possible for applications to make highly complex and contextual decisions with speed and high precision.
Organizations within many diverse industries are beginning to see that they can leverage cognitive applications and transform the way they process information to interact with users. Huge volumes of unstructured data is generated every day in many industries (e.g., medical). Swiftly coming up actionable insights from this raw information transforms its value, and presents companies with potential new revenue streams and business outcomes that promise higher levels of customer satisfaction.
A free IBM publication, “Organizational Transformation: Leveraging Modern Infrastructure to Deliver Cognitive, AI, and Analytics Capabilities,” explores the power of cognitive applications and how the leveraging of these technologies can help effect transformation. Among the areas this white paper will explore:
- Best practices and guidelines for organizations looking to capitalize on the rapidly growing cognitive market
- An overview of Deep Learning in Watson Machine Learning, including the Platform and API layers, Core Services, and Experiment Assistant
- Challenges and opportunities facing AI platform vendors going forward