The Smart Machine Age is upon us and is likely to disrupt many different human processes, tasks, and activities over the next 10 years and far longer as the key technologies continue to develop.
The gradual availability of higher computing power at low costs, the explosive volumes of business data, and advances in Similar to humans, machines learn through experience, e.g. seeing data. This process of presenting data to an algorithm and seeing improvement in the performance/accuracy is called machine learning. and Deep Learning is a subdivision of machine learning. It is a set of algorithms which use different layers of non-linear processing, where each layer uses the last layer's output as input and in the end the correct result should be produced. technologies data all signal an era of rapid automation of life around us. In the last decade, Data Management personnel solved business problems with data; in the next decade, highly capable machines using Applications will solve problems with available data in a scale unheard before. Some of the by-products of this Smart Machine Age that we need to prepare for are Smart Workspace, Smart Data Discovery, Virtual Personal Assistants , Interactive User Interfaces, Expert Advisors, and Smart Robots, to name just a few.
Chance or Doomsday?
Stephen Hawking has warned that the full growth of the “artificial intellect” could spell the doomsday for humanity. On the other end of the spectrum, many optimists believe that with full preparation, human society can look forward to a highly fruitful era of alliance between the human and the machine. The forthcoming “digital gold rush” surrounds the “how” of data technology, not just the “what.” Currently, technology product differentiation comes from the usefulness of An algorithm is a fixed set of instructions for a computer. It can be very simple like "as long as the incoming number is smaller than 10, print "Hello World!". It can also be very complicated such as the algorithms behind self-driving cars.. Thus, the algorithm economy provides a great opportunity to all technology providers – signaling the generation of specialized technology start-ups. Everyone wants to join the discussion about “software that thinks.”
Applications are Transforming the Workplace
Four Fundamentals of Workplace Automation predicted that workplace automation can end up saving about “2 trillion in annual wages.” Contrary to popular belief, roles and tasks handled by very senior level people such as Finance Managers, Line of Business Managers, various members of the C-suite, or even CEOs can be automated to a large degree. Automated business processes have been tested to validate higher yield, better quality, more reliability, and lower costs. Over the last couple of years, much of these forecasts have proved to be true, generating fresh concerns relating to job loss and economic instability.
Big Data: The problem solver
Although Deep Learning is still in a nascent stage as far as Advanced Analytics is concerned, it has recently gained a lot of attention from the smart software development community because of its wide application areas. As the algorithm economy continues to gain momentum among global businesses, the challenges facing Deep Learning are still real. Big Data describes data collections so big that humans are not capable of sifting through all of it in a timely manner. However, with the help of algorithms it is usually possible to find patterns within the data so far hidden to human analyzers. going mainstream may successfully help combat the Data Management issues making Big Data and Deep Learning the formidable combination for unlocking any complex data handling problem.