INTRODUCTION OF ARTIFICIAL INTELLIGENCE (AI)
Table of Contents
WHAT IS ARTIFICIAL INTELLIGENCE?
Artificial Intelligence refers to the development of human-like intelligence in a machine. This is one of the newest branches of computer science that is concerned with developing smart machines that can perceive, understand, predict and perform the provided task that requires human-like intelligence.
According to the father of Artificial Intelligence John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”.
Artificial Intelligence is the latest approach to building such computers, computer-controlled robots, or developing applications that can think and perform intelligently like intelligent humans.
WHAT ARE THE BEST EXAMPLES OF ARTIFICIAL INTELLIGENCE AT THE PRESENT TIME?
The followings are the best Examples of Artificial Intelligence: –
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- Digital Assistance like Siri, Alexa, Google assistance, and other smart assistants
- Google Map and Navigation
- Facial Detection and Recognition.
- Auto correction of text in MS office and another place
- Self-driving cars like tesla
- Robo-advisors
- E-Payments
- Conversational bots
- Email spam filters
- Netflix and youtube.com recommendations, etc.
How many types of Artificial Intelligence there are?
There are four types of Artificial Intelligence which are: –
- Reactive Machines
- Limited Memory
- Theory of Mind
- Self-Aware
At the present stage, we are past the first type of Artificial Intelligent and very close to getting perfection in the second. But as of now third and fourth types of AI are not even possible these two are the next stage of Artificial Intelligence.
Reactive Machines
Reactive Machines are the most basic and simplest type of Artificial Intelligence that perform basic operations. These are the oldest form of AI but are still very useful. These types of AI are programmed to provide a predictable output based on a limited set of inputs received. Reactive Machines cannot learn from experience as these do not have functionality on memory based.
Examples of Reactive Machine AI:
- Spam Filters
- Netflix and Youtube.com recommendation engine
- Deep Blue, a Chess-Playing supercomputer, etc.
Limited Memory
Limited memory types AI machines are very much capable to learn from experience and previously used data and these machines using that data to make better predictions and decisions. At present time these AI are used widely.
Limited memory AI built such environments that are helpful to train automatically and then updated based on the model behavior. Limited Memory AI became possible due to deep learning algorithm and the deep learning revolution in 2012, an algorithm was developed that was capable to imitate the way our neuron connects.
So much research has been done toward developing Limited Memory AI so far, and these can provide reliable output as these are perfect today.
For Example:
Self-Driving Cars are one of the best Examples of the Limited Memory AI Machine.
Theory of Mind AI
Theory of Mind AI is still under development and research. The researchers are expected to develop it to such a level that it will be capable of making decisions similar to humans and to do this, the researcher will need to develop programs that are capable to understand the feeling emotions, belief thought of individual’s minds and behavior of a different kind of person.
This journey of the researcher is not going to be easy because the human has a mind that works differently in various situations, which means the human mind is not stable.
Self-Aware
Self-Aware AI machine still seems like a fantasy because these are very advanced imagination, but in the future, perhaps Artificial Intelligence achieve the level that can make it possible.
Self-Aware AI machine refers to such machines that can think for themselves, have their thought, feeling, consciousness, plans for their future, etc. they are expected to be aware of their environment.
[…] Learning (ML) is a branch of Artificial Intelligence (AI) used in the development of computer systems that have the ability to learn from previously used […]
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