Artificial Intelligence

Artificial Intelligence

In terms of computer science, artificial intelligence also known as machine intelligence is a level of high intelligence displayed by machines in contrast to the natural intelligence displayed by humans

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What is Artificial Intelligence ?

Initially, the term was used to describe machines/computers that imitated ‘’cognitive’’ functions that humans associated with the human mind like learning and problem-solving

When a machine becomes extremely capable, some of its tasks considered to utilize intelligence are removed from the definition of AI, a phenomenon known as the AI effect. In today’s world machine capabilities considered as AI include successfully recognizing human speech, competing at the highest level in strategic game autonomously operating cars, intelligent routing in content delivery networks and also military simulations.

Artificial intelligence can be categorized into 3 different kinds of system. These are analytical, human-inspired and humanized artificial intelligence.

Analytical AI

It features characteristics consistent with cognitive intelligence by generating a cognitive representation of the world and then uses a learning strategy based on past experiences to inform future decisions.

Human-inspired AI

It has elements from both cognitive and emotional intelligence. It understands human emotions. along with the cognitive elements and utilizes them in their decision making.

Humanized AI

It displays the characteristics of all types of competencies (like cognitive, emotional and social intelligence). It also possesses the ability to be self-conscious and is self-aware in its interactions with others.

Ignite offers Artificial Intelligence course for students

Ignite’s Artificial Intelligence course is designed to help individuals crack the mystery of Artificial Intelligence and its business applications. The course offers an overview of AI concepts & workflows, machine learning & deep learning and performance metrics.

Here you’ll learn the differences between supervised, unsupervised and reinforcement learning; become familiar with use cases and also learn how clustering and classification algorithms assist in identifying AI business applications.

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