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Abstract

WILL ARTIFICIAL INTELLIGENCE OUST MEDICAL PRACTIONAIRS & DRUG DISCOVERY THINK TANKS?

Dr. Amit Gangwal*

ABSTRACT

2017 was the year when artificial intelligence (AI) took small steps towards becoming a big part of our lives even as critics warned about its long term effects. Experts envisage a closer integration of robotics (hardware with AI) in coming year along with further march in deep learning. Deep learning is a subset of machine learning that has networks which has capacity of unsupervised learning from data that is unstructured or unlabeled. Also called deep neural learning/deep neural network. AL has already entered homes in the form of digital assignments and is also, inter alia, at heart of the driverless cars that are tipped to transform how people travel & commute. This is high time to become champions of change by incorporating AI chapters inschool and college curriculum. This is vital because almost all type of jobs will require some basic knowledge about AI and data analytics/science. Career or business mapping should be done keeping in mind onslaught and/or boons of AI. The title of this article is apposite because AI has the power to snatch or finish expertise required in particular domain. This will perhaps end monopoly game. It has been published in Times of India news paper before few days that because of monopoly technology & competency trap; Xerox had to re-plan its business strategy. Imagine now owing to advent of AI what will happen in coming years. Here I am sharing one example from automobile industry. How technologies are changing basics of automobile industries. Fuel run cars then electric cars and then (not finally) driver less cars. Interesting thing to note here is that driverless car was not the idea of classical automobile industries. We may also say traditional car making organizations were not as fast as non car making organization like Google, Uber, Tesla etc. This was AI who lent an edge to Google and other companies. Similarly AI will change the way clinical trials are conducted, doctors diagnose and treat the patients and lot many routine and highly specialized things will be changed and will be controlled by AI devices. I am not encroaching into the technical terminologies (of AI) of which I am not expert of, as various top notch technology giants are engaged in it. Here I am sharing few most commonly used/involved technical jargons and these are: random forests (or random decision forests), support vector machine, regression analysis, classification, linear algebra (vectors, matrices, derivatives), calculus, basic probability theory, python programming etc.

Keywords: .


[Full Text Article]

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