Machine Learning and Artificial Intelligence are being used in the same context. Sometimes, people swap ML for AI and AI for ML without giving it a second thought. After all, both of these things are related to machines and talk about decreasing human ‘touch’ in basically everything. However, in reality, they are more different than they are alike.
In simple words, AI is a branch of computer science that discusses the creation of technology which could replace the human workforce by working and acting like their creators. On the other hand, Machine Learning encompasses the usage of algorithms and other data to perform certain tasks on its own, i.e. without any explicit instructions from its human counterpart. That said, there is more to AI and ML than just a few sentences.
What is Artificial Intelligence (AI)?
For so long, AI has fascinated yet scared people at the same time. To make matters worse, the release of countless movies that discussed a global AI domination further made people fearful for their safety. However, there is no need to worry since AI is still not intelligent enough to decide the fate of humanity yet.
As we are deciphering the reality around us, we are constantly learning about our mind and how it relates to the surrounding. Just like this, our concept related to AI is constantly changing. Today, instead of feeding AI with complex calculations, it is more about providing AI with perfect conditions that enable it to mimic human decision-making process. All of this is being done in a bid to help AI become more human-like.
Even after so much work that has been done in the AI field; nobody knows for sure what AI is! As mentioned earlier, AI is the science of making computer programs that can mimic human intelligence. This very definition hints at the vague nature of AI.
To put it correctly, AI is continuously changing and constantly shifting paradigms to broaden its horizon and integrate new features to appear more human-like. This is partly due to the fact that the technology that relates to AI is constantly becoming more advanced while reducing the older versions to being redundant.
In a human mind, an AI system or devices that could handle almost everything is very real. However, in reality, we are far from achieving this because the current AI is not yet advanced to handle tasks on its own without human intervention. This downside of AI has led to the rise/development of Machine Learning.
What do we know about Machine Learning?
If Artificial Intelligence is a car then Machine Learning is its engine that is enabling the car to move forward. The concept behind ML is simple, i.e. if you want something to learn, why not teach the thing how to learn instead of just feeding information to it?
Computer engineers realized that they could achieve much better results by coding computers in a way that they start to think like humans. Once that was achieved, they plugged the enhanced computers into the internet where abundant knowledge was readily available to help with the learning process.
The idea that fueled the creation of ML could be attributed to Arthur Samuel who wanted to equip computers in a way that they learn on their own. This realization was made possible with the emergence of the internet since it contains a surplus amount of data from which the machines could learn.
Machine Learning is all the rage and many organizations are using it for financial trading, online searches, marketing personalization, and more. Since 49% of the organizations are thinking of integrating ML into their business model and 51% have already adopted it, the demand to have ML experts on hand is increasing day by day. If you want to benefit from the increased interest in ML and become an expert in it, then there are various helpful online courses.
One such website offering useful ML courses is HackerEarth. This online platform is unique in its approach since it not only offers online theoretical courses, but it also offers various practical exercises where the individuals can test their ML knowledge. Their courses cover various aspects of ML that include data visualization and manipulation, advanced techniques, statistics, etc. Each of the courses is divided into separate sub-groups, each of which contains detailed tutorials with examples. That said, HackerEarth provides several ML challenges through which the early learners can strengthen their skills by putting theory into practice!
Artificial Intelligence and Machine Learning: Are they the same?
Everyone who is not familiar with the capabilities of AI and ML would consider them to be synonymous with one another. However, only an expert would be in a better position to tell the difference. AI is broad and vague with no end in sight. Nobody seems to be sure about what AI can do or what the future holds for it. On the other hand, ML may just be a small part of AI; however, experts know what ML entails, how it works or how it can be enhanced further to benefit the people using it.
Machine Learning is essentially a subset of AI, the majority of which is still unexplored. So, to answer the question, they are not the same. Although AI and ML are related to each other, they are vastly different in their approaches and applications.
What Does It All Mean?
Artificial Intelligence still has a lot to offer. With the majority of its applications still hidden from the human mind, one could only rely on their imagination to figure out what the future holds for AI. So, until experts figure out the true potential of AI, organizations can design their networks in a way that helps them in extracting benefits from ML.
Today, many organizations, from healthcare to the banking industries, are using ML to their advantage since it offers creative insights and automates dull tasks effectively. That said, the marketing industry is not far behind with many of them integrating ML with custom CRM development process to enhance user experience.
Despite the benefits of AI and its associated subsets, we are far away from achieving a technological utopia. Many of the acclaimed advantages and benefits of AI and ML exist only in theory because experts lack the means required to actualize it.
The point is, nobody knows when AI and ML will be capable of achieving perfect results without human intervention. However, the exciting progress in this field indicates that we may not be far away from total AI domination.