Big Data, and then what?
“We’re not looking ahead to, or preparing for, the 4th Industrial Revolution. It’s here and you’re either going to be a part of carving the path for businesses, or you’re going to spend the next century playing catch up.” Nico Steyn, CEO IoT.nxt.
Automation, digitisation and integration – they all result in pools of data from which companies envisage doing great things. But what happens to all that data? Where does it go, and who sorts through it to turn it into knowledge once it gets there?
For big data to be useful, you need a combination of predictions and data science, and dashboards to visualise the data, providing the end user with a data exploration tool. You need an interface that “understands what a user wants”. You need to go beyond machine learning to cognitive computing.
“Siri, for example, can answer questions but also understands context— whether the user is in a car or at home, moving quickly and therefore driving, or more slowly while walking. This information contextualizes the potential range of responses, which are therefore more personalized.” – Earley Information Science (EIS)
Involving the simulation of human thought processes in a computerized model, cognitive computing involves data mining, pattern recognition and natural language processing that are used to mimic how the human brain works.
“Take IBM. The company is pouring $1 billion into its Watson computer system, the one that answered questions correctly on the game show Jeopardy! IBM now imagines computers that can carry on intelligent phone calls with customers, or provide expert recommendations after digesting doctors’ notes. IBM wants to provide “cognitive services”—computers that think, or seem to (see “Facing Doubters, IBM Expands Plans for Watson”).
Take a look at Watson in action:
Different from the programmable systems that proceeded it, cognitive computing systems like Watson enable people to unlock insights hidden in volumes of structured and unstructured data by interpreting text and discerning context based on the industry Watson is at play in.
“Of course, the limitation here is that they can only ever do things that we know how to teach them to do. But considering the fact that computers can process information far faster than we could ever hope to do ourselves, might it be more efficient to simply give them all the data we have available, and let them work out the best method of solving problems for themselves?” – Forbes
Well, Watson can.
There are 3 pillars supporting this mammoth feat in engineering:
- Natural Language Processing
- A ‘Voracious appetite for data, and,
- The ability to learn.
“We believe that the world has entered a new era in the history of computing, which we call the cognitive era. IBM is committed to advancing cognitive technologies and a new way of solving problems to help transform companies, industries and professions, and to improve the day-to-day lives of individuals everywhere.” – IBM
Think this all sounds futuristic? It’s not. This technology is well within reach and vital for the future of your business.
Still not sure if you should digitalise? It’s about time we chatted.
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