Machine Learning and Artificial Intelligence: Back to Basics

The first thing that people think about when they hear Artificial Intelligence (AI) is the humanoid robots that they see in fictional movies. Also, they think that this a far cry in the future. How wrong they are! That’s right, AI has already become a part of our normal lives right now. You can even see them as a part of many business activities. AI is more than a fictional dream – it is today’s reality.

One of the main misconceptions of AI is that people confuse it with ML (Machine Learning). Both are completely different technologies and have different impacts on businesses. If both AI and ML are making your head spin, you have help. Below you can find the basics of these two technologies which will give you a clear idea of how they work.

ML and AI – what are they?

Understanding these concepts may seem hard because of all the technical jargon present in them. To put it simply, Machine Learning is all about algorithms that make a machine smarter. On the other hand, AI is all about how to make machines smarter using science. Even though great researchers build smart machines using AI, it is with the help of ML that those machines can work.

You can see Machine Learning when you make a typo while searching for something. Using ML, Google can ask you whether did you mean something else.

Applications in businesses

Most people think that the use of both AI and ML are only in the future. But they don’t realise that right now it’s a part of everyone’s lives. Yes, most businesses rely on these technologies to give their customers the best. Around 58% of businesses in America use AI, according to a recent survey.

You can see the use of AI mainly in voice response technologies like voice recognition and virtual personal assistants. Other areas like robotics, analytics-focused applications, and decision support systems depend on this technology.

Problems present in this field

With all the huge benefits that both technologies offer right now, there are also some problems present. Suppose one department in an organization uses both ML and AI. The information regarding it will not be present to another part of the same organization. Due to internal organization rules, collaboration is difficult for many departments. This is mainly seen in the banking system where records are strictly confidential.

On the other hand, the shortage of expert data scientists is also a problem that slows the growth of this field. With fewer people working, the project takes a huge time to complete. In the end, the total development progress at a very slow pace when compared to the huge demand it has.

The next step for ML and AI

The use of both of them is a huge digital transformation that will be a plus for enterprises. For that to come true, both of them should be an integrated component in the organization itself. And the first step to make this a reality is to unite ML and AI with the software that the organization uses to support their work. This includes all aspects from the supply chain to sales. Of course, such a merge needs specific technical hardware to help data ingestion present in different formats. Surely, this will help data scientists to dig deep into this field.

That’s all the basics that you should know about Machine Learning and Artificial Intelligence. With how the research is making progress, you can expect exciting developments in this field in the near future.


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