Machine Learning Does Not Have the Mad Skills
July 25, 2017
Machine learning and artificial intelligence are computer algorithms that will revolutionize the industry, but The Register explains there is a problem with launching it: “Time To Rethink Machine Learning: The Big Data Gobble Is OFF The Menu.” The technology industry is spouting that 50 percent of organizations plan to transform themselves with machine learning, but the real truth is that it is less than 15 percent.
The machine learning revolution has supposedly started, but in reality, the cannon has only be fired and the technology has not been implemented. The problem is that while companies want to use machine learning, they are barely getting off the ground with big data and machine learning is much harder. Organizations do not have workers with the skills to launch machine learning and the tech industry as a whole has a huge demand for skilled workers.
Part of this inaction comes down to the massive gap between ML (and AI) myth and reality. As David Beyer of Amplify Partners puts it: ‘Too many businesses now are pitching AI almost as though it’s batteries included.’ This is dangerous because it leads companies to either over-invest (and then face a tremendous trough of disillusionment), or to steer clear when the slightest bit of real research reveals that ML is very hard and not something the average Python engineer is going to spin up in her spare time.
Organizations also do not have the necessary amount of data to make machine learning feasible and they also lack the corporate culture to do the required experimentation for machine learning to succeed.
This article shares a story that we have read many times before. The tech industry gets excited about the newest shiny object, it explodes in popularity, then they realize that the business world is not ready for implementing the technology.
Whitney Grace, July 25, 2017
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