Page 15 - Ai Book - 8

CORE COMPONENTS OF ARTIFICIAL INTELLIGENCE

Nowadays, Artificial Intelligence, one of the booming technologies, brings a tremendous change in our lives.
In this session, we will explore the core components of an AI based system such as Machine Learning, Deep
Learning, Robotics and Computer Vision.

Machine Learning

Machine learning is a concept used by AI which helps the
systems to learn on their own on the basis of previous data and
experiences. We humans learn from our experiences or from
the knowledge of our ancestors, and then we create our own
knowledge. In the same way, an AI-powered machine also learns
from its previous information. We don’t need to pre-program
our AI machines every time we need to use it for work. Machine
learning enables machines to improve its tasks with experience.
The machine learns from its mistakes and experiences, takes
them into consideration for the next execution. It improvises
itself with its own experiences.
There are some examples of machine learning:

u Image Recognition: Classifying and identifying objects or scenes in images. Example: Distinguishing between
cats and dogs in photographs.

u Recommendation Systems: Suggesting items or content based on user preferences. Example: Recommending
movies on streaming platforms such as Netflix.

u Healthcare Diagnosis: Predicting diseases or conditions based on medical data. Example: Anticipating the
likelihood of diabetes using patient records.

u Autonomous Vehicles: Enabling vehicles to make decisions and navigate without human intervention.
Example: Self-driving cars processing sensor data to navigate traffic.

u Fraud Detection: Identifying and preventing fraudulent activities in real-time. Example: Flagging unusual
transactions in credit card processing for potential fraud.

Deep Learning

Deep Learning is an advanced form of Machine Learning, acting
like a technological superhero. It employs “deep neural networks,”
inspired by the human brain, with layers of interconnected nodes
processing information hierarchically. Unlike traditional Machine
Learning, Deep Learning allows computers to learn automatically
from vast data sets, recognising complex patterns. It has achieved
remarkable feats, such as AlphaGo beating world champions in
the game of Go. This technology also powers voice assistants
like Siri and Alexa, enabling them to understand and respond to
natural language. In essence, Deep Learning provides computers with sophisticated thinking processes, allowing
them to handle complex tasks with a level of intelligence at par with human problem-solving.
There are some examples of deep learning:

u Speech Recognition: Teaching computers to convert spoken language into text. Example: Developing voice-
activated virtual assistants such as Siri.

u Autonomous Vehicles: Empowering vehicles to navigate and make decisions using complex neural networks.
Example: Self-driving cars processing data to understand their surroundings.

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