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What is Artificial Intelligence? Introduction, History & Types of AI

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AI (Artificial Intelligence) is a machine’s ability to perform cognitive functions as humans do, such as perceiving, learning, reasoning, and solving problems. The benchmark for AI is the human level concerning in teams of reasoning, speech, and vision.


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Introduction to Artificial Intelligence Levels

Nowadays, AI is used in almost all industries, giving a technological edge to all companies integrating AI at scale. According to McKinsey, AI has the potential to create 600 billion dollars of value in retail bring 50 per cent more incremental value in banking compared with other analytics techniques. In transport and logistics, the potential revenue jump is 89% more.

Concretely, if an organization uses AI for its marketing team, it can automate mundane and repetitive tasks, allowing the sales representative to focus on relationship building, lead nurturing, etc. A company named Gong provides a conversation intelligence service. Each time a Sales Representative makes a phone call, the machine records, transcribes and analyzes the chat. The VP can use AI analytics and recommendation to formulate a winning strategy.

In a nutshell, AI provides cutting-edge technology to deal with complex data that a human being cannot handle. AI automates redundant jobs allowing a worker to focus on the high level, value-added tasks. When AI is implemented at scale, it leads to cost reduction and revenue increase.


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History of Artificial Intelligence

Artificial Intelligence is a buzzword today, although this term is not new. In 1956, avant-garde experts from different backgrounds decided to organize a summer research project on AI. Four bright minds led the project; John McCarthy (Dartmouth College), Marvin Minsky (Harvard University), Nathaniel Rochester (IBM), and Claude Shannon (Bell Telephone Laboratories).

Here is a brief history of Artificial Intelligence:

1923

Karel Čapek plays named.“Rossum’s Universal Robots, the first use of the word “robot” in English.

1943:
Foundations for neural networks laid.

1945
Isaac Asimov, a Columbia University alumni, use the term Robotics.

1956
John McCarthy first used the term Artificial Intelligence. Demonstration of the first running AI program at Carnegie Mellon University.

1964
Danny Bobrow’s dissertation at MIT showed how computers could understand natural language.

1969
Scientists at Stanford Research Institute Developed Shakey. A robot equipped with locomotion and problem-solving.

1979
The world’s first computer-controlled autonomous vehicle, Stanford Cart, was built.

1990
Significant demonstrations in machine learning

1997
The Deep Blue Chess Program beat the then world chess champion, Garry Kasparov.

2000
Interactive robot pets have become commercially available. MIT displays Kismet, a robot with a face that expresses emotions.

2006
AI came into the Business world in the year 2006. Companies like Facebook, Netflix, Twitter started using AI.

2012
Google has launched an Android app feature called “Google now”, which provides the user with a prediction.

2018
The “Project Debater” from IBM debated complex topics with two master debaters and performed exceptionally well.

Goals of Artificial Intelligence

Here are the main Goals of AI:

✅It helps you reduce the amount of time needed to perform specific tasks.

✅Making it easier for humans to interact with machines.

✅Facilitating human-computer interaction in a way that is more natural and efficient.

✅Improving the accuracy and speed of medical diagnoses.

✅Helping people learn new information more quickly.

✅Enhancing communication between humans and machines.

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Types of Artificial Intelligence

There are three main types of artificial intelligence: rule-based, decision tree, and neural networks.

1⃣Narrow AI is a type of AI that helps you perform a dedicated task with intelligence.

2⃣General AI is a type of AI intelligence that can perform any intellectual task efficiently like a human.

3⃣Rule-based AI is based on a set of pre-determined rules that are applied to an input data set. The system then produces a corresponding output.

4⃣Decision tree AI is similar to rule-based AI in that it uses sets of pre-determined rules to make decisions. However, the decision tree also allows for branching and looping to consider different options.

5⃣Super AI is a type of AI that allows computers to understand human language and respond in a natural way.

6⃣Robot intelligence is a type of AI that allows robots to have complex cognitive abilities, including reasoning, planning, and learning.

Subfields of Artificial Intelligence

Here, are some important subfields of Artificial Intelligence:

Machine Learning: Machine learning is the art of studying algorithms that learn from examples and experiences. Machine learning is based on the idea that some patterns in the data were identified and used for future predictions. The difference from hardcoding rules is that the machine learns to find such rules.

Deep Learning: Deep learning is a sub-field of machine learning. Deep learning does not mean the machine learns more in-depth knowledge; it uses different layers to learn from the data. The depth of the model is represented by the number of layers in the model. For instance, the Google LeNet model for image recognition counts 22 layers.

Natural Language Processing: A neural network is a group of connected I/O units where each connection has a weight associated with its computer programs. It helps you to build predictive models from large databases. This model builds upon the human nervous system. You can use this model to conduct image understanding, human learning, computer speech, etc.

Expert Systems: An expert system is an interactive and reliable computer-based decision-making system that uses facts and heuristics to solve complex decision-making problems. It is also considered at the highest level of human intelligence. The main goal of an expert system is to solve the most complex issues in a specific domain.

Fuzzy Logic: Fuzzy Logic is defined as a many-valued logic form that may have truth values of variables in any real number between 0 and 1. It is the handle concept of partial truth. In real life, we may encounter a situation where we can’t decide whether the statement is true or false.

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