Welcome to the DSC Weekly Digest, a production of Data Science Central. Every week, we pick out the newest and brightest articles on the topic of data … and how it informs our lives, powers our applications, and provides insights into our world.
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This week, William Vorhees asks an interesting question
If you define AI as the use of experience (data) rather than the use of explicit algorithmsto drive specific actions by computers , this should come as no surprise. While the concept of Stage 5 self-driving AI cars have gone back to the drawing board, existing cars have become considerably more aware of, and responsive to their environmenment. AI has quietly crept into the business analytics tools, office productivity suites, and visualization applications used by companies everywhere. AI is increasingly balancing out network traffic, has become a key part of any loan or sales transaction, and has become a significant component both in the fight against Covid-19 and in medicine in general.
That;s the sign of a maturing technology, not a novel one. This is not to say that there aren’t still many places where AI could be successfully employed, but, increasingly, this technology is being used in places where it is most appropriate. More to the point, we’ve reached a stage where employers are looking at AI not as a new and potentially unproven flash in the pan, but instead, something to build a cohesive strategy around and incorporate into other aspects of running a business.
The demand for AI and machine learning specialists will likely continue to grow for a while, but the expectations even here are changing, with the expectations that hiring managers are increasingly looking at machine learning in particular as one of an ensemble of skills expected of their technical staff. AI is becoming common place, but the demand for people who understand the technology will continue high for a while.
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