Machine learning and artificial intelligence are two terms that we often find being mentioned together. Both these are fairly new developments but are finding extensive use in both domestic and industrial applications. ML and AI are so closely related to each other that these terms are often used interchangeably. However, both are different and it is worth understanding how they differ.
Why Are ML And AI important?
Why is it necessary for us to know how these two differ? That is because both these sciences are affecting our lives in a huge way. Whether it is at our homes or in our offices, the use of these developments is increasing to a great extent. AI is what makes your homes and devices smarter. This is what helps companies use chatbots for interaction with customers.
On a much larger scale, these technologies are helping industries perform better as devices can think for themselves and correct errors. AI is helping cars to run without a driver. ML is being used in factories to teach machines to work by themselves with minimal interference from humans. Those who are studying to obtain a machine learning course certification learn in detail about how it works. One can know more about this course here.
As both these are highly important for making human lives better in many ways, it is necessary to understand them better and know how they are different. We must first start by knowing each of these deeply so that we can appreciate their association and differences.
Understanding Machine Learning
It is an application of artificial intelligence that is used for teaching computers to create programs by themselves based on earlier experience. It also enables machines to improve on what they have learned. When a customer regularly purchases from an e-commerce site, it learns this person’s purchase behavior and suggests products he or she is likely to buy. An IIIT Allahabad ML course online explains this phenomenon using many such examples. You can know more about this course that also touches on data analytics here.
What experts try to do is to make machines learn and take decisions as humans do. For this purpose, they are fed with a huge amount of information. ML models are created using various algorithms. These models help to train computers on what action should be taken using details that are fed to them. Models are created depending on details provided to machines and the expected outcome.
ML is different from traditional programming in that machines are only fed data and results expected out of them. They are left to do the programming by themselves. There is widespread interest in this technology because it can help automate many tasks humans now spend much time on. It will also help in processing huge amounts of business data to give insights that can be used for making better decisions.
What Is Artificial Intelligence?
While human intelligence is considered to be natural, that shown by devices is called artificial intelligence. It is a concept where computers are trained to think and act like humans. One might find this to be similar to machine learning where they are taught to learn from experience as humans do. ML is a subset of AI and that explains the similarity. When many companies advertise that their products use AI, they are actually only trained for ML.
Students trying to obtain a machine learning course certification can explain that AI takes in data to analyze and find patterns and relationships. Using these it is possible to make future predictions. When chatbots analyze a large number of conversations, they learn how to respond to various types of queries. The exchanges with chatbots are almost human-like. Programs that recognize images also use this technology. AI works with three cognitive skills namely learning, reasoning and self-correction.
AI is very useful for enterprises because they are able to use available data to find insights that were not accessible earlier. This technology also helps in making repetitive tasks easy and more accurate. Humans are prone to make errors when doing a chore repeatedly. Many companies use AI to see where customers are finding difficulty in using their services and constantly make improvements. Google uses this science to make its online services more user-friendly.
How Are ML And AI Different?
One can learn from an IIIT Allahabad ML course online that though both are highly connected technologies there are differences in their methods and what is expected from them. For example, we are programming a car to avoid obstacles on a road by showing various routes that can be taken safely. From these data, ML will ensure that only safe routes are taken in the future. But it cannot identify these obstacles. If they are placed in different locations, the car will not be able to navigate safely.
While ML can only teach a car to take safe routes, AI can help it identify these obstacles. Even if they are moved to different spots, the car will run smoothly without hitting them. This is what makes AI different from ML. With AI we are trying to make gadgets think like humans instead of just learning from experience. Machine learning helps computers give accurate results using past data. AI enables them to think and solve complex problems as we do.
With machine learning, the objective is to only enable them to perform as they have been trained. But when it comes to AI, experts expect computers to complete a wide range of tasks that humans do. AI has a very wide scope and only a very minute part of its possibilities have been exploited till now. But ML is being used in whatever ways it is capable of. With ML there is only learning and self-correcting while in AI there is learning, reasoning, and self-correcting.
In short, it can be said that while machine learning uses experience to learn, AI uses it for learning and acquiring knowledge to be used in new situations. Despite their differences, they are both inseparably connected and will complement each other.