Last Updated on December 24, 2019 at 5:37 am by admin

Common Myths, Assumptions, & The Relevant Truths About Artificial Intelligence

The term Artificial intelligence otherwise known as AI was first coined by John McCarthy has in the year 1955. Over the years, AI has been highly successful in emerging out into live reality from merely being depicted in the fiction movies. At present, AI has become an integral part of our day-to-day human life with its applications spread across varied domains. It has now played a crucial role in the business processes so as to enhance the customer experience.

In response to the rising demand for AI we are getting to hear progressively more myths when it comes to business applications. In this blog post we will be discussing about the Following are common myths, assumptions, and the relevant truths about AI.

An AI Strategy Is Not One Size Fits All

When speaking of strategies for AI, we should first understand “What does AI mean to you & What are customers actually trying to do?” A majority of the people are of the misconception that the same AI strategy is flexible to use for every use case. Most of the customers wish for smart systems that can which can watch and learn what their knowledge workers are doing as part of their daily routines. This can be seen in the applications of RPA.

With the integration of AI , knowledge worker can direct the system to automate the learned behavior after getting comfortable with past recommendations.

AI And Machine Learning Are Not Interchangeable

For most of the people both AI & Machine Learning technologies are one & the same. However this is a simple misconception while the reality being that Machine Learning is the application of AI. Most of the enterprises go with the combination of RPA and Machine Learning & AI which enables them to automate various tasks by adding a level of learned intelligence. As a result, the generated results would be very much enhanced & up with the level of expectations.

Algorithms Are Not More Important Than Data

This is a concept where people mostly debate on. To carry out their functions precisely algorithms need data, yet algorithms enable you to do whatever you want with data. This doesn’t mean that algorithms are more superior, the fact is that the design of an algorithm is depended on the data structure they are supposed to work with thus making algorithms as the most crucial element.

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