The term “cognitive computing” has been in use since 2011, when IBM Watson won Jeopardy in an impressive fashion. Before 2011, the prevailing terminology was “artificial intelligence” (AI), which tends to conjure images of intelligent robot overlords. Cognitive is much more. In fact, Watson used many cognitive services to defeat the best Jeopardy champion we have seen in a long time. Services included natural language parsing to understand the questions in text (although today, I bet Watson could use speech recognition to understand Alex Trebek) and algorithms to search, rate, and rank potential answers to provide an accurate result.
AI still seems like science fiction, but it is already making impressive inroads in business today. In a recent Harvard Business Review article, they reference an Oxford University study stating that “47% of jobs could be automated by 2033.” McKinsey has also predicted 45% of all work that people do today and 90% in some job categories could be automated by AI.
Cognitive use cases
Today, there are already great examples of cognitive use cases for the enterprise and in the consumer world. They range from financial evaluation to sentiment analysis for social media to helping visually impaired people view their surroundings. Perhaps the most famous current use case is that of H&R Block. They were so excited about the impact of cognitive on their business that they bought a Super Bowl commercial to share their story:
Many of the stories we discuss in this space deal with self-driving cars and robots, but there are many good use cases across industries — all of which can apply to the enterprise. (IBM also has a fantastic list on their site; part 1 and part 2 cover cognitive use cases.)
IBM and Anthem announced an evidence-based medicine partnership, which provides expert service to over 34 million people’s health plans. That includes computer vision, cancer prediction, etc. Topcoder has done similar work in dentistry (to increase diagnostic accuracy and create evidence-based treatment plans) and genome-wide association studies (GWAS).
Ecommerce and retail
There are several use cases across ecommerce and retail — from understanding customers to managing inventory and beyond.
- Needing to know your customer. AI can scrape content and put together a 360-degree view. This also includes predicting the lifetime value of a customer.
- Recommendation engines and cross-sell opportunities — based on a customer’s shopping cart, recommend what else they might be interested in buying.
- Shelf stocking (i.e., where to place similar items).
- Fraud management via sophisticated analytical tools and infrastructure to identify patterns and prevent fraudulent activity.
- Inventory management (i.e., computer vision around barcodes); cognitive computing can recognize and track barcodes.
- Forecasting of inventory needs and sales.
Beyond healthcare and retail, there are several other use cases to consider:
The Topcoder Cognitive Community
With new technology demands, today’s organizations face an enormous talent gap. That’s why, with IBM, we’ve built the Topcoder Cognitive Community — a global crowd of cognitive experts. Topcoder provides on-demand access to thousands of developers and data scientists trained in the cognitive technologies companies need to compete now.
Ready to leverage AI, computer vision, machine learning, and more of today’s top technologies for your business? Get started with cognitive today.
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