Artificial intelligence (AI), sometimes known as machine intelligence, refers to the ability of computers to perform human-like feats of cognition including learning, problem-solving, perception, decision-making, and speech and language. Early AI systems had the ability to defeat a world chess champion, map streets, and compose music. Thanks to more advanced algorithms, data volumes, and computer power and storage, AI evolved and expanded to include more sophisticated applications, such as self-driving cars, improved fraud detection, Facial Recognition, Semantic Analysis and “personal assistants” like Siri and Alexa. Today, medical researchers are using AI to develop technology that will detect a range of diseases, improve radiology imaging, fine-tune radiation treatments, simplify DNA sequencing, and advance precision medicine for more individualized health care. Human Life is getting changes at rapid pace due to advancement of AI. In this article we will learn the basics of AI, We will go through its History in brief also we will be discussing about its types and its application.


Definition
Artificial Intelligence is a branch of Computer Science that deals with development of machines/system that are smart enough to do the tasks that generally require human intelligence. The intelligent machines/system are capable of perceiving the environment around them and take steps that maximizes the chance of success of the allotted task. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.


History
Less than a decade after breaking the Nazi encryption machine Enigma and helping the Allied Forces win World War II, mathematician Alan Turing changed history a second time with a simple question: "Can machines think?". In 1950 Alan Turing published a landmark paper "Computing Machinery and Intelligence"  in which he speculated about the possibility of creating machines that think.[29] He noted that "thinking" is difficult to define and devised his famous Turing Test. If a machine could carry on a conversation (over a teleprinter) that was indistinguishable from a conversation with a human being, then it was reasonable to say that the machine was "thinking".
But the field of AI wasn't formally founded until 1956, at a conference at Dartmouth College, in Hanover, New Hampshire. John McCarthy, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines."
In 1966, the first chat bot was created by Joseph Weizenbaum, named ELIZA after that in 1972 the first AI Robot was build in Japan which was named WABOT-1.
After that came the time period where computer scientist faced severe shortage of funding from government for AI researches which is termed as  AI Winter. Post this from late 90's we can see a rapid development in the field which started with IBM Deep Blue beating the Gary Kasparov, World champion for chess, After this AI also entered in Business world via companies like Twitter, Facebook, Netflix etc. After which the field developed at a very high speed with emergence in Deep Learning, Natural Language Processing, Computer Vision.
AI was now been applied in various field like Bio Technology, Sports, Medical, Tourism etc. Though the term artificial intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage.


Importance of AI
  • With the help of AI we can automate the tedious task that are generally repetitive and if done by human can cause fatigue, tough human supervision is still maintained in this type of automation.
  • It adds intelligence to existing application. The products that you were already using can be improved using AI. Bots and smart machines can be combined with large amounts of data to improve many technologies at home and in the workplace, from security intelligence to investment analysis.
  • In AI the data is used to program the model, i.e. the model learns according to the data it is provided with. It finds structure and regularities in data so that the algorithm acquires a skill. So, just as the algorithm can teach itself how to play chess, it can teach itself what product to recommend next online. And the models adapt when given new data. Back propagation is an AI technique that allows the model to adjust, through training and added data, when the first answer is not quite right.
  • Sometime data has many hidden layer which can never be visualized by Human but AI using neural networks can easily do that.
  • With the introduction of Deep Learning and Big Data the AI models has become very powerful. It achieves incredible accuracy  which was previously impossible. Eg. Google Photos, Google Search, Google assistant are all based on deep learning.
  • Techniques from deep learning, image classification and object recognition can now be used to find cancer on MRIs with the same accuracy as highly trained radiologists.


AI Categories
Artificial intelligence generally false under two broad categories: 
  • Narrow(Weak AI)
When Machine Intelligence is limited to a specific field it is then know as Narrow or Weak AI. Suppose an AI system which is trained to classify between Apple and Orange will fail when we ask it to classify between watermelon and muskmelon. Weak AI can stimulate human cognition and benefit us by automating time consuming tedious tasks and by analyzing data in a way that humans can't. It helps to turn big data into usable information by detecting patterns and making predictions. As narrow AI are trained on an specific dataset so they fail to perform on task outside the one they are designed for. Narrow AI is not driven by emotions like humans and thus operated in a predefined range even though it is appearing to do a more sophisticated task.
Eg of weak AI are Apple Siri, Netflix recommendation system, Spam Filter, A Weather predicting model, etc.
If we take the example of Google assistant which isn't appears to us as Weak  because  it interacts with us process our language and respond to us  but the reason it is an example of weak AI is because it is nowhere close to human like intelligence, It lacks self-awareness, consciousness and what it does, is it process human language, enter it into search engine and returns the result, the thing that it is programmed to do.
  • Artificial General Intelligence(Strong AI) 
when we hear of Artificial Intelligence, what comes in our mind is robots working with humans as it has been  depicted in the movie Transformer, and this AI is actually called strong AI as machines can successfully perform any intellectual task that generally requires human supervision and this is possible because these machines have a mind of there own and are capable of taking decisions independently. The goal of strong AI is to develop Artificial Intelligence to a point where machine intellectual capacity becomes equivalent to human intelligence. 
Strong AI is also called True Intelligence or Artificial General Intelligence (AGI).  AGI is expected to be able to reason, solve problems, make judgments under uncertainty, plan, learn, integrate prior knowledge in decision-making, and be innovative, imaginative and creative. Consciousness, objective thoughts, self-awareness, sentience, and sapience are also some important features of strong AI.
At present strong AI is just a concept, It is just a perception of AI where AI is equated to humans and stipulates that a computer can be programmed to actually be a human mind, to be intelligent in every sense of the word, to have perception, beliefs and have other cognitive states that are normally only ascribed to humans. However, since humans cannot even properly define what intelligence is, it is very difficult to give a clear criterion as to what would count as a success in the development of strong artificial intelligence. Weak AI, on the other hand, is very achievable because of how it stipulates what intelligence is. Rather than try to fully emulate a human mind, weak AI focuses on developing intelligence concerned with a particular task or field of study.

Other way of classifying Artificial Intelligence

Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, categorizes AI into four types, from the kind of AI systems that exist today to sentient systems, which do not yet exist. His categories are as follows:
  • Reactive Machines
The most basic types of Artificial machines are reactive Machines, they neither have the ability to form any memory and can neither use their past experiences to influence there present actions. IBM's deep blue which defeated the world chess champion Gary Kasparov is a perfect example of this type of machines. Deep Blue had the ability to only identify the chess pieces and knew how each can move and was able to identify all possible moves of it and its opponent and chooses the best possibility among them but it didn't had any memory to remember any past move. Besides Deep Blue Google's AlphaGo is also an example of this kind of machines. These machines behaves exactly the same way every time they encounter the same situation which can be very good for ensuring an AI system is trustworthy.

  • Limited Memory
Apart from having capabilities of Reactive Machines, Limited Memory machines also has the ability to learn from its past experiences and take their present decision on basis of them. Nearly all AI application that exists today are of this category. These systems are trained on large volume of training data to build a reference model for solving future problems. For example am image recognition system is trained using thousands of images, and when a image is scanned by it in future it classify that basis on the learning experience. Self Driving Cars are also an example of this type of AI.

  • Theory of Mind
This type of AI machine are still work in process and is a concept as of now. When developed this type of AI will be able to understand people's emotion,  expectations, beliefs and will be able to interact socially with other peoples.

  • Self Awareness
Self-aware AI, which, self explanatory, is an AI that has evolved to be so akin to the human brain that it has developed self-awareness. Creating this type of Ai, which is decades, if not centuries away from materializing, is and will always be the ultimate objective of all AI research. This type of AI will not only be able to understand and evoke emotions in those it interacts with, but also have emotions, needs, beliefs, and potentially desires of its own.  This type of AI also doesn't exist at present and if developed will be an milestone in AI field.


Artificial Intelligence Sub Types

AI is incorporated into a variety of different types of technology, These are
  • Machine Learning
It is a type of Artificial Intelligence that provides systems the ability to learnand improve from their experiences without being explicitly programmed. The process of learning starts with data being fed to the machine so that machines can discover pattern and logic in the data and can take future action based on its experiences. The Primary aim of machine learning is to allow computers to learn on its own without human intervention. It also gives machines the ability to improve with time as machine will be fed with more and more data over time and will learn from it.
Types of Machine Learning
    • Supervised Learning :  It is based on the principal that the machine will be guided by tha data that is fed into it, the data that is fed into the machines is labelled which helps the machine to learn. Consider a dataset having labelled photographs of Cat and Dog is given to the machine then on basis of this data the machine will be able to classify a new photograph of either cat and dog and will classify it as one of them.
    • Unsupervised Learning :  It is based on the principle that machine will be able to find the pattern in the data on its own by creating clusters in it.  Consider if the machine is fed by photographs of Cat and Dog then it will segregate them into two clusters but will not be able to tell which one is cat or Dog and when a new photograpg is given to it then it will classify as any one of them.
    • Reinforcement Learning :  It is the ability of an agent to interact with the environment and find out what is the best outcome. It follows the concept of hit and trial method. The agent is rewarded or penalized with a point for a correct or a wrong answer, and on the basis of the positive reward points gained the model trains itself. And again once trained it gets ready to predict the new data presented to it.
  • Computer Vision
It is a type of Artificial Intelligence that gives machine the ability to replicate human vision and and enable them to identify and process objects in images and videos as humans can do. It is the way by which digital world can interact with our physical world. Applications of Computer Vision are Self Driving Cars, Face Recognition, Augmented Reality & Mixed Reality.
  • Natural Language Processing
Natural Language Processing is the ability by which computers can understand and comprehend human language, It  is a way of computers to analyze, understand and derive meaning from a human languages such as English, Spanish, Hindi, etc. Its application are Automatic summarization, Sentiment Analysis, Text Classification etc.
  • Robotics
Robotics is a branch of AI, which is composed of Electrical Engineering, Mechanical Engineering, and Computer Science for designing, construction, and application of robots.  Today many tasks are being performed by robots especially in manufecturing industry which were earlier performed by Humans. With the development of AI Robots have now become more intelligent and can also be seen in Resteurants, Military, Space Exploration etc.
  • Automation
With the development of AI not only there is increase in usage of Mechanical bots but also digital bots. These Digital bots are generally software programme that can do the the things that previously required humans. They can interact with the user interface, capture data, and manipulate application as wwe humans did. These are very helpful in case of repetitive tedious tasks which earlier required a human being and thus freeing the human resource for a more productive task.


Applications of Artificial Intelligence

There are many applications for artificial intelligence being used today, and many more that are being researched. A few of the most popular uses of artificial intelligence systems today are in industries like healthcare, automotive technology, and video games, to name a few. Below are a few of the common uses of artificial intelligence in the industries where it is already gaining popularity.
  • Healthcare
In healthcare, the number of applications for artificial intelligence is expanding rapidly. Artificial intelligence is currently being used to interpret lab results in blood tests and genetic testing. There are also efforts being made to use AI to interpret medical imaging, such as X-rays and MRI results. 
  • Aviation
Artificial intelligence is commonly used in flight simulations and simulated aircraft warfare. Many aircrafts are also equipped with sensors which feed data to a system that uses AI to evaluate the mechanical 'health' of the aircraft.
  • Automotive
Artificial intelligence is a growing component of the automotive industry. Many companies, like Tesla, are incorporating self-driving technology into their vehicles. Self-driving vehicles use AI to read data of the vehicle's surroundings and respond to other drivers, lines on the road, and similar feedback read by the vehicle's sensors.
  • Finance
Financial institutions have been using artificial intelligence to analyze market trends and even automate trades based on various market indicators and triggers. Many banks and financial institutions have also been using AI algorithms and neural network systems to identify fraudulent bank and credit charges, and then trigger human managed investigations.
  • Video Games
Many debate how much AI is truly used in video games. This is because machine learning techniques are rarely used and games typically only choose between a handful of automated responses, rather than actually "learning" to defeat their opponents. However, as gameplay has grown in complexity, so has the AI programming that governs it. AI is most commonly seen when the game player interacts with non-player characters in a game. Actions of these characters are often governed by complex AI algorithms that depend on the game player's actions.
  • Applications to Other Industries
As stated above, artificial intelligence is really the application of machine learning, predictive analysis, and automation, so its applications are vast. AI has been spreading rapidly to technology driven industries, so it is quickly becoming an important element of several other major industries, including:
    • Manufacturing - AI is being used to automate the building of vehicles and other large machinery and equipment
    • Marketing - AI solutions are being used to analyze user behavior and more effectively target potential customers
    • Employee Recruiting - AI technology is now frequently used to match employers to job seekers
    • Transportation - GPS systems and city planners use AI programs to identify and suggest the most efficient routes
As time goes on and artificial intelligence techniques become more widely understood and accessible, more industries will surely benefit from the efficiency and scaling effects that AI can provide.






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