Today, a great amount of tasks and functions we are able to perform with efficiency is the result of years and years of evolution in the field of Artificial Intelligence(AI). Artificial Intelligence, since its conception has come a long way and is evolving every day. Everything from efficient web search to self-driving cars is the result of successful Artificial Intelligence evolution.
In this blog let us find out what is Artificial Intelligence. Also, how Machine Learning and Deep Learning are parts of Artificial Intelligence.
What is Artificial Intelligence?
The main aim behind artificial intelligence and its evolution is to create machines which are intelligent. The curiosity behind Artificial Intelligence has been there for a very long time. What was once seen as science fiction is coming closer to becoming a reality. Both machine learning and deep learning are subsets of Artificial Intelligence. However, Artificial Intelligence is not just about them. It is everything from a computer program playing a game to a self driving car. The expanse at which Machine Learning operates is vast. Machine Learning and Deep learning are merely two aspects of the vast expanse of Artificial Intelligence.
What is Machine Learning?
The idea behind Machine Learning is to make computers learn without being told to do so. It’s , is similar to how we humans learn. Think of how we learn to walk. As infants, we found it difficult to walk. However, as we grew, we learn from our experiences of falling and taking bad steps. But eventually, after some time, our brains learn to walk comfortably, and thus we become the faultless walkers that we are now. Similarly in ML, such experiences serve as data. (For example- this data could be information from the sensors of a car as it learns to drive.) Thus, we use past data to make the computer learn. Based on this “learning”, it makes predictions about future events.
The aim is to make Machine Learning systems capable enough to apply training and knowledge extracted from large data sets perform functions like facial recognition, speech recognition, object recognition, translation, and many other tasks. It differs from hand coding as Machine Learning systems are not programmed mechanically with specific instructions to complete a task. They are capable of learning to recognize patterns and make predictions on its own.
What is Deep Learning?
Deep Learning is a branch of Machine Learning that is a Neural Network, but that makes use of a large number of hidden layers. The more hidden layers, the more accurately predicted the outcome. In Deep Learning, a number of layers do not lead to diminishing effects because the effect of ‘Higher level of Abstractions’ overcomes this drawback to making astoundingly accurate predictions. It could be made possible for a deep learning algorithm to be instructed to “learn” what a dog looks like. It would take a very massive data set of images for it to understand the very minor details that distinguish a cat from, say, a cheetah or a panther or a fox.
How are the three connected?
The ideas and concepts of Artificial Intelligence has been around for a very long period. The birth of computers too was a part of the AI revolution. The revolution however, has not stopped even after numerous breakthroughs. There has always been the need to make what exists better and closer to the optimal AI dream. Artificial intelligence forms the basis of both Machine Learning and Deep Learning. Machine Learning started evolving around 1980’s and has been growing since then. The continuous need to keep improving and expanding in the sector of Artificial Intelligence led to the birth of the new field, Deep Learning. This field is still in its initial phase and is yet to cause a noteworthy impact. However, once Deep Learning achieves what it aims to do, we will be a lot closer to what was assumed to be only fiction.