It wouldn’t be wrong if we’d say that Machine Learning is certainly a buzzword for this era. Ever wondered the technology world would be revolving around Machine language & Artificial Intelligence? Yet, that is evident when we read it almost every other day about it.
Of course, when products, applications, and services are evolving with these technologies then there is a must to drop these words in front of the investors and others in order to seem relevant. It is a well-known fact that machine learning has been in existence from the time of World War II and that it continued to evolve over time. It was only limited because of the limitations of the hardware. Of course, the concept, its algorithms, the idea, and product development strategies were all there.
Scott Aaronson, a computer scientist at MIT expressed his opinion as something like this: “The way machine learning is being discussed today is very similar to how people discussed computers in the 1950s. People discussed computers and humanoids in the same breath but they did not foresee the Internet coming. Similarly, machine learning is certainly big, and it does deserve the hype it is receiving. Yet, it is overhyped because machine learning isn’t new. It is just computer algorithms that have been branded as something futuristic, while it has been there all along.”
Its History:
Back in 1959, machine learning was compared to AI as there were analogy theories on machine learning and computers as it was believed that machine learning was something that gave computers the power to learn without being programmed explicitly.
Later around the 1980s & 90s, when the theory was not enough, machine learning was defined to be more than just theoretical. Computers were developed to operate autonomously; However, machine learning has been more realistic and objective in nature and is concerned with what can actually be achieved in real terms today.
What Machine Learning Can Do For Your Business?
The best way to get started with machine learning is to understand what it can do for your business. Machine learning can automate routine decisions, routing the more complex and challenging questions to humans, or your business can use it to tackle analysis in areas where there’s so much data that you could never have enough human resources to try to understand patterns. Using machine learning for preventive maintenance, logistics, scheduling, predicting and matching supply and demand, just in time supply chain management, dynamic pricing, and even disaster management, will apply to a wide range of industries, especially in the transportation, manufacturing, and energy markets.
Is Machine Learning Really Overpromoted?
There is a lot of hype and talk about different technologies today. It’s important to remember that no particular technology is superior to another and that every field has its role to play in the development of society. Similarly, machine learning has been around for decades and it is only now that it is receiving a lot of attention. This neither means that it doesn’t deserve the attention that it is getting nor does it mean that the hype is right. The hype can be translated to mean that machine learning is very relevant today than it was yesterday. And most certainly, it is going to remain as important as it seems today. On that note, it probably deserves the hype that it is receiving.
Start Now, Tomorrow Is Too Late To Stay Competitive
Machine learning is becoming a key tool and it’s already having an impact on every industry and every market. It’s already delivering business value, and that comes with strong ROI and low total cost of ownership according to the Computer Economics Technology Trends 2018 study. A large number of organizations saw a positive return on their investment within 18 months, and the systems they deployed came in or even under, the amount originally budgeted. So, in simple words if you’re not investing in AI and machine learning, that business value is going to your competitors — and now is the time to start getting that advantage for your own business.
