According to my point of view the technology that is going to completely change the 21st century would be Artificial Intelligence. A.I. is a part of our lives that is why it is important to understand the different concepts of Artificial Intelligence.
With this is mind I welcome you in this oeuvre.
The field of artificial intelligence, and its application in day-to day life, has seen remarkable evolution in the past three to five years. Artificial intelligence (AI) is an enabler that potentially facilitates machines doing everything that humans can do. This includes perceiving, reasoning, rationalising, and problem solving while working within a context or interacting with the environment with more efficiency and accuracy.
History of AI
What is AI?
Stages of AI
Types of AI
Domains of AI
History of Artificial Intelligence
The concept of AI goes back to classical ages, Under Greek Mythology the concept of machines and mechanical men were thought of an example Talos.
Talos was a giant animated bronze warrior programmed to guard the island of Crete.
Now let’s back to 19th century….
1950 - ALAN TURING
Alan Turing proposed the Turing Test, a test to determine whether or not a computer can intelligently think like a human being. It was the 1st serious proposal in the philosophy of artificial intelligence.
1951- Game AI
1951 marked the era for Game artificial intelligence. This period was called Game AI because here a lot of computer scientist developed programs for checkers and for chess. However these programs were later rewritten and redone in a better way.
1956- The birth of AI
During this year John McCarthy 1st coined the term “Artificial Intelligence” in 1956 at the Dartmouth conference, from emulating how the human brain works to solving focused, complex problems to doing all that a human can do such as seeing, hearing, communicating, acting, learning, perceiving, thinking, deciding, demonstrating emotion and compassion, interacting with environment, and more.
1959- 1st AI Laboratory
MIT AI Lab was 1st set up in 1959, the research on AI began.
1960- General Motors Robot
First robot was introduced to General motor assembly line.
1961- First Chatbot
The 1st AI Chatbot ELIZA was introduced in 1961.
1997- IBM Deep Blue
IBM’s Deep Blue beats world champion Garry Kasparov in the game of chess.
2005- DARPA Grand Challenge
2005 was marked for the year when Stanford racing team’s Autonomous Robotic car called Stanley won the 2005 DARPA Grand Challenge.
2011- IBM Watson
IBM’s question answering machine/system- WATSON, defeated the 2 greatest the Jeopardy! champions, Brad Rutter and Ken Jennings.
So that was the history of AI, since the emergence of AI in 1950s, we have seen an exponential growth in its potential.
AI covers domains such as Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Expert Systems, Intelligent Process Automation and so on..
Moving On to our next agenda.
What is Artificial Intelligence?
Essentially, AI is the field of computer science that involves enabling computers to behave like humans or perform tasks that usually require human intelligence, such as decision making, object detection, solving complex problems and so on.
so now lets understand the different stages of AI.
Stages of Artificial Intelligence
So under the stages of AI we have-
Artificial narrow intelligence (ANI) is about solving a problem against a given request with a narrow range of abilities. A feature like Siri in smartphones can be considered an example in this case. This is also called weak AI.
Artificial general intelligence (AGI) is referred to as strong AI and refers to a machine that is as capable as humans. The Pillo robot is an example of a robot that can diagnose an illness and administer pills as well.
Artificial super intelligence (ASI) is the stage in the evolution of Artificial Intelligence wherein machines will possess the ability to think and make decisions just like us humans.
There are currently no existing examples of Super AI, however, it is believed that we will soon be able to create machines that are as smart as humans.
Most of the existing AI today is ANI, AGI and ASI are still being developed.
The core functions and features of an AI system at the center and related sub-fields that support implementing these functions.
Types of Artificial Intelligence
Based on the functionality of AI base system Artificial intelligence can be categorised into 4 types.
Reactive AI was the first kind of AI that was talked about. These types of machines do not have memory and do not use information from past experiences.
In these machines, the current context is directly perceived as it is and acted upon. This makes the machine behave the same way every time it encounters a situation. The benefit of this is a reliable and consistent outcome. An example is Deep Blue.
Limited memory AI machines look into the past and use it as a pre-programmed representation of the world and then apply it to the current data set. For example, in self-driving cars, decisions on when a car should change lanes is based on data such as lane markings, speed limits or road directions, current speed of the car, and relative neighbouring car speeds.
Theory of mind AI machines are intelligent machines that use advanced technologies that have more to do with understanding human emotions. The theory of mind is a psychological term that refers to the fact that living beings have emotions and thoughts that determine their behaviour.
Self-aware AI machines are an extension of theory of mind AI. They can configure representations, which means we will have machines that are conscious and aware given a context. This is also called human-aware AI or human interaction AI. There are no prototypes built of these machines.
This type of AI is a little far fetch but in future achieving the stage of Super intelligence might be possible. Genius like Elon Musk, Stephen Hawking have constantly warned us about evolution of AI.
NOTE: So guys, Do you ever think we will reach the stage of Artificial Super Intelligence..
Domains of AI
Artificial Intelligence can be used to solve real-world problems by implementing the following processes/ techniques:
Machine Learning- Machine Learning is the science of getting machines to interpret, process and analyse data in order to solve real-world problems.
Under Machine Learning there are three categories:
Supervised Learning, Unsupervised Learning, Reinforcement Learning
Deep Learning- is an area of machine learning that focuses on unifying machine learning with artificial intelligence.
Natural Language Processing- Natural language processing (NLP) refers to an area of specialisation in computer science that deals with analysing and deriving useful or meaningful information from natural language or human language.
Robotics-Robotics is a computer science discipline that deals with the design, programming, engineering, and development of physical robots or machines that are built to execute tasks that are usually done by humans.
Expert Systems-An expert system is an AI-based computer system that learns and reciprocates the decision-making ability of a human expert.
Fuzzy Logic-Fuzzy logic is a computing approach based on the principles of “degrees of truth” instead of the usual modern computer logic i.e. boolean in nature.
Fuzzy logic is used in the medical fields to solve complex problems that involve decision making. They are also used in automatic gearboxes, vehicle environment control and so on.
So that is all in this blog, I hope you liked and understood somethings.
About the author
I’m Aryan Bindal Pursuing B.Tech. in CSE from Indian Institute of Information Technology, Sonepat . I am passionate about how Machine Learning can change our lives and makes our world smarter and better. I enjoy a good cup of coffee, watching good movies and T.V. shows. Playing video-games or do anything music related.
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