Artificial Intelligence: A Comprehensive Overview, Slides of Information Technology

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LITE | Chapter 4

ARTIFICIAL

INTELLIGENCE

1 What is Artificial Intelligence

2 AI Structure

3 History of AI

4 Types of AI

5 Examples of AI

Contents

6 Importance of AI

It was first coined by John McCarthy in 1956 at the Dartmouth Conference, where he defined it as " the science and engineering of making intelligent machines". What is Artificial Intelligence?

Automation is about setting up robots to follow a set of pre-defined rules. Artificial Intelligence is about setting up robots to make their own decisions (though still based on human input). AI can be used in automation, but most automation uses conventional software to transfer data from one location to another. difference between AI and automatic machine

STRUCTURE OF ARTIFICIAL INTELLIGENCE Kahkashan, Rehman & Ahirwar, Dr. Anamika. (2020). Depiction the Artificial Intelligence with Machine Learning. Solid State Technology. 63. 4734-4739.

In order for the software to learn automatically from patterns or features in the data, artificial intelligence (AI) combines massive amounts of data with quick, iterative processing and intelligent algorithms. AI is a broad field of study that includes many theories, methods and technologies, as well as the following major subfields: Machine Learning, and Deep Learning. HOW Artificial intelligence works

a subset of AI the science of programming machines to think and act like humans without being explicitly programmed to aims to enable computers to learn automatically without human intervention and adjust actions uses algorithms that can make predictions through pattern recognition mACHINE LEARNING

SUPERVISED Learning

creating models that

can learn from

marked datasets to

make predictions

eg. spam filtering

and face recognition

REINFORCEMENT Learning

uses feedback data

to improve the

performance of a

model

eg. games like Chess

and Go

mACHINE LEARNING CategorieS UNSUPERVISED Learning

given an unlabeled

dataset, the algorithm

must find some way

to learn without the

guidance of humans

eg. fraud transactions

self-driving cars speech recognition pattern recognition computer programming image recognition contextual recommendations fact checking Applications are: DEEP LEARNING

Banking Healthcare Human Resources (HR) Marketing and Sales Supply Chain Applications are: Predictive Analytics

Natural Language Processing (NLP) is a subfield of AI that focuses on enabling machines to understand and interpret human language. NLP is used in applications such as chatbots, virtual assistants, and language translation. Natural Language Processing With NLP, PCs can decode, display and generate human language and communicate. Its ultimate aim is to make predictable organized attempts with the computers we use every day by teaching systems to understand the human language and to react intelligently.

Expert Systems a computer program that uses artificial intelligence (AI) technologies to simulate the judgment and behavior of a human or an organization that has expertise and experience in a particular field relies on having a good knowledge base. Experts add information to the knowledge base, and nonexperts use the system to solve complex problems that would usually require a human expert.

CaDet (Cancer Decision Support Tool) is used to identify cancer in its earliest stages. DENDRAL helps chemists identify unknown organic molecules. DXplain is a clinical support system that diagnoses various diseases. MYCIN identifies bacteria such as bacteremia and meningitis, and recommends antibiotics and dosages. PXDES determines the type and severity of lung cancer a person has. R1/XCON is an early manufacturing expert system that automatically selects and orders computer components based on customer specifications. Examples of expert systems