Artificial intelligence has been one of the most controversial domains in the genre of computer science, since it was first proposed in the year 1950. Defined as a part of computer science, and concerned with designing systems, it exhibits the characteristics associated with human intelligence. In fact to be precise, AI has transformed machines into self-thinkers, with human like intelligence and reasoning.
Deep learning is a sub-set of AI, and has allowed for various practice applications of AI in our daily lives. Gaming indeed is one of the most common areas where deep learning has actually made a huge impact. One of the instance is the: 2016 defeat of South Korean Go master Lee Sedol by Google DeepMind’s AlphaGo program. With all the underlying basis of intelligence and cognition deep learning also promises to transform global businesses. The promising start has already begun, which was otherwise beyond human capabilities few years ago. According to a Forrester research report, investment in AI will increase by 300 percent in 2017, a sign of things to come.
As promised, deep learning will transform the modern workplace. Some of the initial areas to witness change are:
Manufacturing has always been considered as one of the most intensive and loss-prone verticals. In fact, even some minor systematic or manual lapse are capable of triggering defective products causing heave damage. Hence, fine-tuning manufacturing assembly lines along with deep learning techniques enables a system to produce much greater number of fine finished products that pass quality control tests, making manufacturing increasingly profitable.
The domain of healthcare is one of the major industry where deep learning can gain wider influence. Deep learning algorithms can indeed spot early patterns among patients who are likely to develop life-threatening diseases like cancer in the next one to two years. With such advanced techniques, timelines suggestions for conducting and reviewing PET or PET-CT (Positron Emission Tomography–Computed Tomography) are also given. Hence, with the development of deep learning techniques, critical parameters, predicting hospitalization among other chronic diseases like diabetes can also be detected early.
Finance is one of those sectors where deep learning has indeed made a remarkable impact. Most of the finance companies utilize proprietary systems, to accurately predict the frequent market changes and execute trades. However, all these systems are primarily based on the concept of probability in completely determining the highest and lowest performing stocks. Such kind of variations will be better predicted by deep learning systems by processing enormous quantities of data and trades at breakneck speeds. Similarly, it would also help credit companies accurately determine credit lenders and identify future defaulters.
In the recent times ADAS or Advanced Driver Assistance Systems is a genre that leverages deep learning techniques with immense opportunities. Some of the popular use cases can be object detection, pedestrian detection, and traffic sign detection. In fact, there are many more aspects in autonomous driving which requires the help of deep learning. Critical scenarios like detecting driver drowsiness and triggering alert, lane departure warning, blind spot detection and predictive braking falls under such category. Therefore, deep learning is definitely required for next generation vehicles to deliver readiness to customers.
The future of brands belongs to an enhanced and highly personalized customer service. Deep learning in the genre has helped many organizations improve their emails, coupons and offers that every customer receives—all designed to serve customers better and build lasting customer relationships. In fact, such trends can compare the previous buying trends with an enormous database of millions of other users, and provide relevant or allied product purchase suggestions. Along with this recognizing customers personalized choices adds a new dimension to the aspect of customer service and product recommendation.
Recently the idea of using drones for package delivery has been making rounds. In fact, as per the global ecommerce giant Amazon being already into the business with seriously considering this idea and applying deep learning mechanisms into delivery system, supply chain systems will now work faster, accurately and efficiently. Such conditions will allow retail, supply chain and logistics companies to reach areas that were otherwise beyond proximity.
Hence, for business owners and top executives of global businesses, embracing AI through practical deep learning models is definitely the way ahead. While it need not be in the form of investing millions for sophisticated deep learning applications, a modest start can always go a long way toward eventually changing the world of business.
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