Myths about ML : busted
Machine Learning is undeniably one of the most substantial and dominant technologies in today's world. Moreover, we are far from seeing its full potential. There's no doubt, it will continue to be making headlines for the foreseeable future. It is a miracle that is reconstructing how we interact with businesses, devices, and each other.
From retailers and advertisers recommending appropriate products to cars that can drive themselves, and phones that recognize their owner's face, this ML has made remarkable progress. Meanwhile, artificial intelligence and machine learning must be the two most misunderstood concepts in tech today. Clarifying those myths in this article.
Machine learning will soon create superhuman intelligence.
The movie industry has exploited the idea of machine learning taking over the human race. This technology is growing at an exponential and while the thought of machines taking over the race in the next several years is highly unlikely it is only a matter of time before the technology evolves and the machines are thinking and growing on their own.
Machine learning will replace people.
A popular myth that artificial intelligence technology and its many applications (including machine learning) will eventually eliminate the need for human workers. While it will most certainly change the jobs being performed and how they are handled, the main purpose of ML isn't to replace but rather to augment personnel. In actuality, it's predicted that it will make obsolete. This means a greater opportunity for humans to learn new skills and apply their cognitive and creative talents to more meaningful initiatives.
Image datasets are representative of real images doesn't mean they give a correct answer
We like to think that neural networks(a subset of ML) are now better than humans at the task of object recognition. This is not true. They might outperform humans on a select image, given actual images found in the wild, they are most definitely not going to be better than a regular adult human at recognizing objects. This is because images found in current image datasets are not actually drawn from the same distribution as the set of all possible images naturally occurring in the wild. A machine might learn a red fruit is an apple, given an image of red cherry, the system might say it again an apple.
Machine learning can't predict previously unseen events
The discussion goes, if something has never happened before it's prediction probability must be 0, what else could it be? That's false as events are composed of many smaller components, all of which have relationships and similarities. The power of machine learning is identifying these relationships, and using them to predict rare events with high accuracy.
Machine Learning Performs On A Real-Time Basis
There are many myths about machine learning that you have likely heard, but this is probably the most well-known one. Many people believe that machine learning always performs everything on a real-time basis. The systems that are built for learning are the systems that can perform in real-time. When machine learning is being performed at a high level, technologies that are ML-based are developed to operate on a series of algorithm data, These ML-based technologies are also developed to build systems and models that can be used by businesses and organizations based on the series of algorithm data. There are models that can be used in real-time, but the analysis that is being used to build those models are not used in real-time.
Anyone can build a machine learning platform.
Google "how to build machine learning" and you'll surely get pages of results featuring various open-source tools and courses. But the fact remains that machine learning is a highly technoscientific technique. For it to be successful, you must understand exactly how to prepare and partition data for testing and training, know how to choose the most appropriate algorithm, and – most importantly – know how to turn that information into a productive system. Furthermore, you must also monitor that system to ensure consistently relevant results.
These are the myths surrounding machine learning that we have been seeing recently. ML is now more powerful than it used to be and we need to accept that it will be helping us make more intelligent decisions. Machine learning continues to make progress in many industries, and your business or organization can be one of the many businesses that can obtain value from machine learning applications.
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Yukta Peswani
Content Writer & blogger at Studylink. Using blogs as my best networking tool and creating content that truly counts. In love with blogging and Sundae Sundays!
