Artificial intelligence refers to the simulation of human intelligence in machines that are programmed to think like human and mimic their actions . The term may also be applied to any machine that exhibits traits associated with
a human mind such as learning and problem solving .
The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal.
Artificial intelligence (Al) is the study of how to make computers perform tasks that humans consider difficult through the creation of intelligent agents. The study of Al began in the 1950, and it has improved dramatically over time with better statistical methods and greater computing power.
Artificial intelligence has been studied for decades and is sill one of the most elusive subjects in computer science. This partly due to how large and nebulous the subject is Al ranges from machines truly capable of thinking to search algorithms used to play board games. It has applications in nearly every way we use computers in society.
Artificial intelligence is now used for all sorts of things, such as intelligent opponents in video games, accurate medical diagnosis, speech commands on mobile phones, and keeping email inboxes clear of spam. People who use Al often want it to perform repetitive tasks that take a lot of time for a person to do , or to solve problems which seem almost impossible to solve with a calculator .
For example, Al can be used to :
1 Read the license plates of cars in a video .
2 Count cells in a microscope picture .
3 Find the optimum number of taxis that a city needs .
4 Intelligently guess the products that someone may want to buy .
The term artificial intelligence was coined in 1950, but Al has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage.
Early Al research in the 1950s explored topics like problem solving and symbolic methods. In the 1960s, the US department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency ( DARPA ) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri , Alexa of Cortana were household names.
The history of Artificial intelligence began in antiquity with mytys, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The seeds of modern Al were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s , a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientist to begin seriously discussing the possibility of building an electronic brain.
The different types of Al depend on the level of intelligence embedded into a robot. we can clearly categorize Al into three types
Artificial Narrow Intelligence (ANI), also known as Narrow Al or weak Al, is a type of Artificial Intelligence focused on one single narrow task. It possesses a narrow range of abilities. This is the only Al in existence today, for now.
Narrow Al is something most of us interact with on a daily basis. Think of Google Assistant, Google Translate, Siri, Cortana or Alexa. They are all machine intelligence that use Natural Language Processing (NLP).
NLP is used in chatbots and other similar applications. By understanding speech and text in natural language they are programmed to interact with humans in a personalized, natural way.
Al systems today are used in medicine to diagnose cancers and other illnesses with extreme accuracy by replicating human like cognition and reasoning.
Artificial General Intelligence ( AGI )
When we talk about Artificial General Intelligence ( AGI ) we refer to a type of Al that is about as capable as a human.
However, AGI is still an emerging field. Since the human brain is the model to creating General Intelligence, it seems unlike that will happen relatively soon because there is lack of a comprehensive knowledge of the functionality of the human brain.
Yet, as history has shown many times, humans are prone to creating technologies that becomes dangerous to human existence. Why then trying to create algorithms to replicate brain function would be different? when this happens, humans will have to accept the consequences this might bring.
Artificial Super Intelligence ( ASI )
Artificial Super Intelligence (ASI) is way into the future. Or, that is what we believe. To reach this point and to be called an ASI, an Al will need to surpass humans at absolutely everything. The ASI type is achieved when Al is more capable than a human.
This type of Al will be able to perform extraordinary well at things such as arts, decision making and emotional relationships. These things are today part of what differentiates a machine from a human. In other words, things that are believed to be strictly human.
As we all know that a normal human brain has more the 100 Billion neurons which connect entire human body through other neuron cells and collect the information from that body part and tell the brain about the problem there , int really works in the same way Artificial Intelligence is designed with a neural network algorithm which further connects with all the networks of the world and gathers the information to its memory.
Artificial Intelligence mainly works on three techniques. They are symbolic Al, Data Driven and Future development Symbolic artificial intelligent covers expert systems, the computer is given a problem and few practices were carried out to check its logical problem solving skills. In fuzzy logic , it is mostly true or false method and applied in control systems. In data driven machine learning , Neural networks and deep learning algorithm are applied process the pool of data by data mining and big data and is applied in NLP. It is important to distinguish between different methods and applu the right one to their level of maturity.
Building an Al system is a careful process of reverse engineering human traits and capabilities in a machine, and using it's computational prowess to surpass what we are capable of. To understand how artificial intelligence actually works , one needs to data driven into the various sub domains of artificial intelligence and understand how those domains could be applied into the various fields of the industry .
Machine Learning : ML teaches a machine how to make inferences and decisions based on past experience. it identifies patterns, analyses past data to infer the meaning of these data points to reach a possible conclusion without having to involve human experience. this automation to reach conclusions by evaluating data, saves a human time for businesses and helps them make a better decision .
Deep learning : Deep learning is an ML technique . it teaches a machine to process inputs through layers in order to classify, infer and predict the outcome .
Neural Networks : Neural Networks work on the similar principles as of Human Neural cells. They are a series of algorithms that captures the relationship between various underying variabes and processes the data as a human brain does.
Computer Vision : Employs pattern recognition and deep learning to understand the content of pictures and videos and to enable machines to use real time images to make sense of what's around them.
Cognitive computing : About creating a "natural, human like interaction " as SAS puts it , including using the ability to interpret speech and resopond to it .
a human mind such as learning and problem solving .
The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal.
Artificial intelligence (Al) is the study of how to make computers perform tasks that humans consider difficult through the creation of intelligent agents. The study of Al began in the 1950, and it has improved dramatically over time with better statistical methods and greater computing power.
Artificial intelligence has been studied for decades and is sill one of the most elusive subjects in computer science. This partly due to how large and nebulous the subject is Al ranges from machines truly capable of thinking to search algorithms used to play board games. It has applications in nearly every way we use computers in society.
Artificial intelligence is now used for all sorts of things, such as intelligent opponents in video games, accurate medical diagnosis, speech commands on mobile phones, and keeping email inboxes clear of spam. People who use Al often want it to perform repetitive tasks that take a lot of time for a person to do , or to solve problems which seem almost impossible to solve with a calculator .
For example, Al can be used to :
1 Read the license plates of cars in a video .
2 Count cells in a microscope picture .
3 Find the optimum number of taxis that a city needs .
4 Intelligently guess the products that someone may want to buy .
Artificial Intelligence History
The term artificial intelligence was coined in 1950, but Al has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage.
Early Al research in the 1950s explored topics like problem solving and symbolic methods. In the 1960s, the US department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency ( DARPA ) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri , Alexa of Cortana were household names.
The history of Artificial intelligence began in antiquity with mytys, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The seeds of modern Al were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s , a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientist to begin seriously discussing the possibility of building an electronic brain.
Types of Artificial Intelligence
The different types of Al depend on the level of intelligence embedded into a robot. we can clearly categorize Al into three types
Artificial Narrow Intelligence ( ANI )
Artificial Narrow Intelligence (ANI), also known as Narrow Al or weak Al, is a type of Artificial Intelligence focused on one single narrow task. It possesses a narrow range of abilities. This is the only Al in existence today, for now.
Narrow Al is something most of us interact with on a daily basis. Think of Google Assistant, Google Translate, Siri, Cortana or Alexa. They are all machine intelligence that use Natural Language Processing (NLP).
NLP is used in chatbots and other similar applications. By understanding speech and text in natural language they are programmed to interact with humans in a personalized, natural way.
Al systems today are used in medicine to diagnose cancers and other illnesses with extreme accuracy by replicating human like cognition and reasoning.
Artificial General Intelligence ( AGI )
When we talk about Artificial General Intelligence ( AGI ) we refer to a type of Al that is about as capable as a human.
However, AGI is still an emerging field. Since the human brain is the model to creating General Intelligence, it seems unlike that will happen relatively soon because there is lack of a comprehensive knowledge of the functionality of the human brain.
Yet, as history has shown many times, humans are prone to creating technologies that becomes dangerous to human existence. Why then trying to create algorithms to replicate brain function would be different? when this happens, humans will have to accept the consequences this might bring.
Artificial Super Intelligence ( ASI )
Artificial Super Intelligence (ASI) is way into the future. Or, that is what we believe. To reach this point and to be called an ASI, an Al will need to surpass humans at absolutely everything. The ASI type is achieved when Al is more capable than a human.
This type of Al will be able to perform extraordinary well at things such as arts, decision making and emotional relationships. These things are today part of what differentiates a machine from a human. In other words, things that are believed to be strictly human.
How Artificial Intelligence ( Al ) Works
As we all know that a normal human brain has more the 100 Billion neurons which connect entire human body through other neuron cells and collect the information from that body part and tell the brain about the problem there , int really works in the same way Artificial Intelligence is designed with a neural network algorithm which further connects with all the networks of the world and gathers the information to its memory.
Artificial Intelligence mainly works on three techniques. They are symbolic Al, Data Driven and Future development Symbolic artificial intelligent covers expert systems, the computer is given a problem and few practices were carried out to check its logical problem solving skills. In fuzzy logic , it is mostly true or false method and applied in control systems. In data driven machine learning , Neural networks and deep learning algorithm are applied process the pool of data by data mining and big data and is applied in NLP. It is important to distinguish between different methods and applu the right one to their level of maturity.
Building an Al system is a careful process of reverse engineering human traits and capabilities in a machine, and using it's computational prowess to surpass what we are capable of. To understand how artificial intelligence actually works , one needs to data driven into the various sub domains of artificial intelligence and understand how those domains could be applied into the various fields of the industry .
Machine Learning : ML teaches a machine how to make inferences and decisions based on past experience. it identifies patterns, analyses past data to infer the meaning of these data points to reach a possible conclusion without having to involve human experience. this automation to reach conclusions by evaluating data, saves a human time for businesses and helps them make a better decision .
Deep learning : Deep learning is an ML technique . it teaches a machine to process inputs through layers in order to classify, infer and predict the outcome .
Neural Networks : Neural Networks work on the similar principles as of Human Neural cells. They are a series of algorithms that captures the relationship between various underying variabes and processes the data as a human brain does.
Computer Vision : Employs pattern recognition and deep learning to understand the content of pictures and videos and to enable machines to use real time images to make sense of what's around them.
Cognitive computing : About creating a "natural, human like interaction " as SAS puts it , including using the ability to interpret speech and resopond to it .
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