Computer is probably one of the groundbreaking inventions of all times. Many of our difficult works were made easy by the computer. As time passed the computer also evolved. It became more faster.
Two of the most interesting terms in the computer world are “Artificial Intelligence” and “Machine Learning”. You may know these terms, but do you know what they mean?
Artificial Intelligence (AI) means that the machines can perform tasks that are “intelligent”. In AI the machines are not programmed to do a set of defined motions but can perform actions by adapting to the surrounding and the data it receives.
Machine Learning is basically a branch of AI that is more focussed specific on a particular concept. The concept is to make a machine that can analyze data and perform their tasks accordingly without constant supervision from humans.
These were the basic difference, now let us take a deeper look into both of these subjects.
The Overview: AI vs Machine Learning
AI and Machine Learning are relatively new concepts. The inception of the idea dates back to a few imaginative individuals from decades or even centuries ago. But these imaginations could be fulfilled only recently. With today’s resources, these imaginative ideas can now become a reality.
The concept of AI first came to light with the invention of the first computer. These computers were not capable of making decisions on their own. But these machines were able to make calculations since they are “logical machines” . The people who were building these computers knew that they were making a brain-like machine.
However, today our technology has advanced by a huge margin. Now we can build a brain-like machine more efficiently. Over the years our understanding of our own brain has also increased. With this understanding, our approach to develop AI has also changed. Computers can now do complex calculations, but we are more inclined towards building a more machine that can do its work more like a human being.
Classification of AI
There are basically two types of AI, they are applied AI and generalized AI.
The most common form of AI is the Applied AI. It is used in everything from automated driving to intelligent stock-trading systems.
Generalized AI is not common as it is difficult to make. Theoretically it can do all the things that we humans are capable of. Even though generalized AI are not common, many scientists are making significant development in this field.
Generalized AI is the reason for the development of machine learning.
The Evolution of Machine Learning
The development in machine took place due to certain developments in the field of AI.
The first true evolution occurred when the researchers realized that it would be more effective to teach a computer the process of learning rather than teaching it all the work it is needed to do.
The second crucial development was the introduction of the internet. The internet provides a great platform to store information. With this the machines can now access data which they were not able to access before due to the limited storage.
With these two breakthroughs it was clear that it is a better option to design a computer that can “think” on their own and give them access to the online information to help them learn.
The development of neural network became important because it will help the computers to learn to think like humans. With the help of neural networks, a computer can mimic a human brain, but at the same time is faster and more accurate than a human brain.
Neural networks are a type of computer system that helps the computers to classify information like a human brain. For example, a computer with neural networks can look at a picture, identify the elements in it and then categorize it based on what they saw.
These networks make decisions based on the data it has access to. These data do not allow them to make an accurate decision, but rather they give decision that is most likely to be accurate.
These systems uses a feedback loop for “learning”. It sees if its decisions were correct or not, then based on the result it changes its approach to solve a problem.
What we can do with Machine Learning?
The application of machine learning is almost limitless. With Machine learning, a computer can decide whether a given text has positive or negative content. It can also figure out if a song will make the listener happy or sad. These machines can even make compositions on their own from the piece they have listened to.
Communication is a major field in which machine learning is used. Natural Language Processing is a field of AI that uses machine learning heavily. One day the companies can apply this in automated customer service, and may turn out to be more efficient than having an actual human.
ML or Artificial Intelligence: Which One Will be Best For You
Machine Learning and Artificial Intelligence has created a lot of buzz in today’s business landscape. To decide which one to go for, first you need to determine your requirements for your company.
The application for both of these are great. However, recently ML has got a significant amount of more publicity than AI. Hence many companies are investing on ML. But AI is also capable of doing simple tasks that do not require an ongoing learning.
The fact that we will one day develop human-like AI was seen as an inevitability by many researchers. Today we are more closer to developing an effective AI than we ever were. Many of the progress we see today is due to the change in perspective of how we see the workings of an AI, that was possible due to ML. I hope that after reading the article you can now understand Artificial Intelligence and Al a lot better.