AI a revolutionary invention

 The concept of intelligent beings has been around for a long time. The ancient Greeks, in fact, had myths about robots as the Chinese and Egyptian engineers built automatons. However, the beginnings of modern AI has been traced back to the time where classical philosophers’ attempted to describe human thinking as a symbolic system. Between the 1940s and 50s, a handful of scientists from various fields discussed the possibility of creating an artificial brain. This led to the rise of the field of AI research — which was founded as an academic discipline in 1956 — at a conference at Dartmouth College, in Hanover, New Hampshire. The word was coined by John McCarthy, who is now considered as father of Artificial Intelligence.

How do we measure if the Artificial Intelligence is acting like a human?

  • Turing Test
  • The Cognitive Modelling Approach
  • The Law of Thought Approach
  • The Rational Agent Approach

What is the Turing Test in Artificial Intelligence?

  • Natural Language Processing to communicate successfully.
  • Knowledge Representation to act as its memory.
  • Automated Reasoning to use the stored information to answer questions and draw new conclusions.
  • Machine Learning to detect patterns and adapt to new circumstances.

Cognitive Modelling Approach

  • Introspection: observing our thoughts, and building a model based on that
  • Psychological Experiments: conducting experiments on humans and observing their behavior
  • Brain Imaging: Using MRI to observe how the brain functions in different scenarios and replicating that through code.

The Laws of Thought Approach

The Rational Agent Approach



How Artificial Intelligence (AI) works?

  • 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 underlying variables and processes the data as a human brain does.
  • Natural Language Processing: NLP is a science of reading, understanding, interpreting a language by a machine. Once a machine understands what the user intends to communicate, it responds accordingly.
  • Computer Vision : Computer vision algorithms tries to understand an image by breaking down an image and studying different parts of the objects. This helps the machine classify and learn from a set of images, to make a better output decision based on previous observations.
  • Cognitive Computing : Cognitive computing algorithms try to mimic a human brain by analysing text/speech/images/objects in a manner that a human does and tries to give the desired output.

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