Several weeks ago, we discussed the power of Watson and its transformative capabilities towards the insurance industry. Well attended, the webinar discussed the simplification of complex processes in gaining a competitive advantage in an industry long wary of technology innovation.
Insurance is not the only industry wary of cognitive disruption, with higher education, automotive, real estate, and eCommerce also seeing interest in the area. According to a recent survey by IBM, about 73% of CEOs say cognitive computing will play an important role in the near future of their organizations, with the same sentiment echoed by other top executives as well. Likewise, only about half of these CEOs are planning to adopt cognitive computing by 2019.
It’s understandable that building cognitive infrastructure is a daunting task. IBM Watson took decades to build, cost hundreds of millions of dollars and involved thousands of engineers and researchers. Given the substantial investment required to build cognitive apps, the average enterprise may not have the tolerance or the capital, especially with other priorities top of mind. Even more so, many organizations are still figuring out how to define what cognitive computing is in comparison to business intelligence and machine learning.
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This guide provides practical key insights and important factors to consider to make informed decisions in your multicloud journey.
- Business intelligence (BI) is an umbrella term that refers to a variety of software applications used to analyze an organization’s raw data. End users are still required to interpret this data in making business decisions.
- Machine learning (ML) is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
- Cognitive computing is an effort to mimic the human brain’s learning process, thought process, reasoning, analysis, and decision making. Cognitive systems work with unstructured data to build conclusions that traditional BI and ML systems are unable to create.
Cognitive data will gain more importance as the world creates more unstructured data from photos, audio, images, and sensor information. According to additional research from IBM, this type of data is estimated to grow to about 90 percent by 2020.
Ultimately, cognitive computing will become a normalized part of our daily lives. It is about machines collaborating with mankind to create business results and improve humanity. If your organization doesn’t jump on it soon, your competition surely will.
Are you looking to integrate cognitive computing into your strategy? Speak to one of our specialists at firstname.lastname@example.org today and download our DevOps guide for additional IT best practices.