The last few years has seen a rise in discussion pertaining of Artificial Intelligence (AI) with particular interests on its impact on business and the society. Well, some once said that necessity is the mother of invention and the growth of unstructured data around the world has surely contributed to the need for smart ways to find real-time answers from such data. Talk of the vast amount of information on the internet not to mention trends like the Internet of Things (IOT) that produce data that is difficult to understand for the normal person. The beauty is that there is a way out thanks to the emergence of smart computing techniques like cognitive computing.
What is Cognitive Computing?
Do not get lost with the vocabulary just yet! Cognitive computing is simply defined as the process of simulating the human brain in a computing model. In other words, cognitive computing looks to mimic the way our brains work using Natural Language Processing (NLP), artificial intelligence, pattern acknowledgment and other sophisticated methods, all in the quest to find real-time answers from complex and unstructured data. In this case, the goal is to create systems that solve very complex problems but with little or no human assistance. It is even cooler that data scientists can now leverage cognitive analytics as the backbone in building intelligent systems around the globe. A good example is a cognitive based system known as IBM Watson, designed and developed by IBM. This is just the tip of the iceberg and 2016 has shown us that there is more to come for it. Still, 2016 has seen some amazing trends in cognitive analytics that are worth attention.
7 Predictions for Cognitive Analytics :
1. Cognitive Analytics Transforming the Lives of Many
Cognitive analytics is no longer at the disposal of early adopters-it is spreading like a raging flame! No one seems to be spared from the development of cognitively enriched systems transforming the lives of many across the globe. In fact, 2016 has seen an overshoot in the number of cognitive agents that has been helped by the escalating number of IOT and mobile devices. For example, today any doctor can deploy cognitive analytics to scan through patient’s history, journals, clinical notes and other relevant data thus improving diagnosis and treatment.
2. A Growth in Cognitive Computing Education and Research
It should not be a surprise that we are seeing companies and universities pumping many cash into horning raw talent and advancing cognitive computing skills. IBM has surely been the front-runner – it has collaborated with University of Maryland-Baltimore County and seven other universities in North America in research targeted at developing adoption of cognitive analytics in cyber security.
3. Personalization Taken to The Next Level
Cognitive systems are turning out to be context aware, active, personalized interaction agents. In fact, 2016 has depicted an upsurge in the number of systems that interact with users using voice and visual interactions. It gets even better! Cognitive systems now have the capability to capture and understand geospatial and temporal context hence the consistency in interaction with users.
4. Data Analysis Automation
We all fancy and appreciate the power of automation but surely not in the same level or way data scientists do. No wonder many of them are fascinated by the way cognitive analytics has gone a long way in automating pattern detection and sensing with less complex data sets than before. The automation is all thanks to the fact that cognitive systems are able to leverage unsupervised learning and machine learning to derive meaning from heterogeneous and high-velocity data.
5. Demand for Data Scientists with Skills in Cognitive Analytics
With any new trend, there comes a new demand. Cognitive computing has been no exception given the intensifying demand for data science experts with cognitive application development skills. 2016 year has exuded an unquenchable thirst for the number of professionals adept in Spark, Hadoop, and other tools albeit with a bias in cognitive computing specialization. This has, pushed many data scientists to teach themselves new tricks as they look to fit into those demands.
6. A Paradigm Shift in Governance Initiatives
The growth of cognitive systems has seen a corresponding rise in the call for policy, regulatory and legal frameworks that manage risks and compliance. This year has seen the emergence of cognitive frameworks in the realm of things like algorithmic accountability, decision lineage tracking and cognitive data exchange. Societies have even gone as far as campaigning for strong measures over privacy, identity, and security.
7. Cognitive Analytics as the Basis for Innovation
Businesses are now recognizing the power of information as far as business is concerned. Year 2016 has seen even more businesses unleash cognitive analytic applications into their business functions-many of them are not only hiring data scientist with cognitive computing skills, they have also inculcated these scientists into the heart of their businesses. This can be mirrored by a recent research done by IBM where it was found that either a good number of businesses around the world are using cognitive analytics in short or long-term business functions.
Conclusion:
In today’s competitive world, cognitive analytics can be that stepping-stone you are looking for to jump a notch higher! Those businesses that have made the investments are already reaping the benefits of seeing beyond the clouds of big data whilst translating the insights into actionable business decisions. Just imagine cognitive analytics as the microscope that will let you gain the vision for the seemingly foggy future. Long story short, it is time to start test-driving the potential of cognitive analytics in your business today!
