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Is data the new fuel for the future economies? When used and interpreted properly, data can be used to make significant advances and improvements to entire countries, to businesses and to our private lives. It can be used to predict behavior, diagnose illnesses and help us make critical decisions.
The amount of data we produce every day is truly mind-boggling. There are 2.5 quintillion bytes of data (1 billion x 1 billion or 18 zeros) created each day at our current pace. However, this pace is accelerating with the growth of the Internet of Things (IoT). 90 percent of the data in the world was generated in the last two years alone. With each click, swipe, share and like, businesses are using data to make decisions about the future.
When we talk about data in today’s definition of Computer Science, it’s not just the storage of 1s and 0s. It is collection, storage, mining, protection, encryption, interpretation, diagnosis, learning, and prediction. Each category has its own technology, algorithms and specialists.
Data comes in many formats such as structured from traditional text-based sources, unstructured like video from computer vision and pure analogue from numerous sensors placed in ‘Things’. Personally, I am fascinated by the latest advancements in Deep Learning technology and the remarkable predictions and interpretations being discovered at a rapid pace. Faster computers, like the GPUs from NVidia, now accelerate Deep Learning capabilities and are reviving what some believed was the stagnation of Moore’s Law.
Being a subset of Machine Learning, Deep Learning is an artificial Neural Network that can learn a long chain of casual links. It has transformed many sub fields of Artificial Intelligence, including Computer Vision, Speech Recognition, Natural Language processing and much more.
Some examples of real applications driven by deep learning can be found in medicine, in security, in transport, in manufacturing and more. Where, Deep Learning and AI are breaking into the healthcare industry by assisting Doctors. Microsoft, for example, is working on a project called Hanover, which aim to memorize all research papers on cancer drugs and treatments and help predict the most effective combination of drugs for each patient.
In transport, deep learning from products like Norma, can optimize routes for vehicles and fleets, optimize vehicle utilization and reduce fuel consumption. An example of how deep learning can assist in security can be found in ICetana, the system that uses AI assisted video monitoring. Through learning of the norm, say in an airport, the system can identify abnormal behaviors, such as gun shots, altercations, suspicious packages, suspicious behavior and more.
Of course, all this data needs to be placed in storage technologies, which have fast retrieval capabilities such as flash, possibly encrypted and could be in the cloud. Our solutions for data, will be on show at various exhibitions, online and in our Experience Centers.