Artificial intelligence (AI)
Artificial intelligence is developing at a very high speed, and the technology has already started becoming a part of our reality. AI is a technology that makes a machine or a computer program to think like humans.
This technology is the most promising technological development in recent times. It is all set to shape our future more intelligently. This technology will make it possible for a machine or a program to do things that require human intelligence like problem-solving and learning.
Machine learning (ML) is a part of AI. This language enables the machines to learn from examples. Deep learning (DL) is a part of Machine Learning that mimics the human brain behavior. Machines use DL to train themselves to perform tasks like humans.
How is AI technology revolutionary?
AI technology is making machines smarter, and now computers are increasingly doing more such tasks that could otherwise be done by humans only due to their human intelligence.
Many people think that AI is specially developed to replace human skills and their daily work. However, the reality is that AI technology is being developed to make our lifestyles better by increasing productivity and making things faster and smarter.
Things are developing at a higher speed, and we are ready to enter an era where man and machine will collaborate like never before, and this will make our lives more comfortable and smarter.
Several countries have announced their national AI strategies to get the most out of this revolutionary technology.
AI technology's concepts
Machine Learning (ML) is the most common application and a subfield of AI. A computer system that has machine language programming is fed data. The computer system uses these data to understand the patterns to make decisions or predictions. Machine learning is the most in-demand IT skill of today's time.
Deep Learning (DL) is another concept of AI. It is more powerful and requires much more computing power. This language aims to make machines think like humans. It is more potent than ML and involves a lot of data but provides more accuracy.
There are mainly three types of algorithms Supervised learning, Unsupervised learning, and Reinforcement learning. These algorithms can accurately find out if the prediction is accurate or not. For example, if you provide an algorithm, thousands of videos and images of cats and dogs. The algorithm will learn about both the animals using the pictures and videos and will use this learning to predict whether a new image or video fed into the system is of a cat or dog.