Artificial Intelligence has seeped into the lives of everyone with an internet connection. Binge-watching television shows and online shopping carts full of suggested add-ons are commonplace, even though most consumers aren’t aware of what’s powering the recommendations. Algorithms are constantly hard at work, learning in real-time while users are sitting on the couch watching their favorite streaming shows or as they are adding items to their wish list at a favorite online retailer. Predictive analytics is permeating all industries as organizations start to harness the power of data collection to enable smart decisions.
Just collecting or having access to larger data sets will not produce a result. We cannot keep up with the Data Tsunami of 100 terabytes plus today made up of streaming video, text, pictures and voice. Also capturing the legacy data in paper and other media format is impossible. We are unprepared for knowledge extraction and the demands for faster decision-making that our customers, markets and our planet, will require for high performance and competitive advantage and most likely the survival of various organizations will depend on this in the future. Innovation will be accelerated by this convergence—faster drug discovery, safer self-driving cars, alternative energy and many new innovations yet to be invented may ensue.
In many aspects, AI is like a freight train racing down the tracks. Steady advances in hardware and software are sparking immense progress in how machines help interact with customers. Google’s voice recognition technology, for instance, improved to 98% in 2014 from 84% just two years earlier. Facebook’s DeepFace technology now recognizes faces with 97% accuracy. Voice recognition systems themselves now perform tens of millions of online searches every month.
As machines get smarter, companies across the globe are beginning to explore ways to leverage AI to work more efficiently, safely, accurately and cost-effectively, and to improve consumer engagement and customer experience at the same time. AI will be used to replace simple human tasks and augment more complex ones in the foreseeable future. In fact, we are already seeing humans being replaced by AI in mundane customer service roles so that they can be leveraged for more complex tasks.The use of machine learning, expert systems and analytics in combination with big data, is the natural evolution of what has been two different disciplines. They are converging.What might the future hold for Big Data Intelligence, the post-convergence of big data and AI? What seemingly impossible challenges could we tackle that we are struggling with understanding? Better jobs, more sustainable environment, smarter economy, more secure world, ending Cancer? We have to think like this to shape the future.
A fine example which stands out is in the heart of the hospitality industry. This industry has not always been at the leading end of high-tech innovation or adoption. Until recently, most of the bookings, transactions and administrative tasks at a hotel were handled manually.With the recent advent of cloud and cluster computing, and by using scale-out methodology, hotels now have admittance to revenue management systems (RMS) that control machine learning and artificial intelligence (AI) technology to automatically gather and calculate large quantities of compound and dissimilar data, convert it into a more easily understood format, and define the best possible room rate in real-time, as the market evolves.
Using machine learning-based RMS, revenue managers no longer need to be involved in the manual application of revenue management tasks.These sophisticated RMS can efficiently examine through the signals sensed from market variables, discover patterns and anomalies, make predictions for guest arrivals and calculate optimal prices in real-time, as the market changes. Quite an interesting change.
You don’t want to make the mistake of seeing these trends, such as the convergence of big data and AI as distinct events or silos. That would defeat the competitive advantages that the coming convergence would offer. We need to think differently — co-evolution is smarter than one off or unrelated trends that represent one industry or market. The connectivity of trends is important to recognize.
I can’t resist thinking of the future – advancements, abilities and limitations. It’ll be interesting to see how tomorrow’s healthcare providers, pharmaceutical companies and medical equipment manufacturers will create data-driven products that will act as 24×7 care teams for patients. One of the fine names that stick out is Practo in India, which seems to have revolutionized the healthcare sector with their GEN Y tools and practices.
Imagine a scenario, where your doctor will prescribe a virtual doctor to watch over your vitals and other behaviors. Your phone will ring and a soothing voice will inform you to go home and relax as it monitors your heart rate and blood pressure.
However, coming back to reality – when it comes to big data and AI, I feel we are at the early stages in India, estimating the emergence of what the potential and convergence value can be. There will be a much bigger evolution of big data analytics and AI as we step into the near future, even one minute or one year from today.
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