Artificial intelligence (AI) has been the subject of science fiction for decades, and now it’s finally becoming reality with businesses of all sizes jumping on board to explore its capabilities. But what exactly is AI? And how does it work? This article will help you understand the basics of AI and how it can help your business by making your product smarter and more convenient to use.

1. Artificial intelligence (AI) has been the subject of science fiction for
decades, and now it’s finally becoming reality with businesses of all
sizes jumping on board to explore its capabilities. But what exactly is AI?
And how does it work? This article will help you understand the basics of
AI and how it can help your business by making your product smarter
and more convenient to use.
Contents
1. What is Artificial Intelligence
2. History of AI
3. Definition of Artificial Intelligence
4. Difference between AI and Machine Learning
5. Applications of AI in different fields
6. How do neural networks used in AI work
7. Issues with AI technologies

2. What is Artificial Intelligence
Artificial intelligence (AI) is the simulation of human intelligence by
machines. AI can be used to make a computer system smart – that is,
able to understand complex tasks and carry out complex commands.
The most well-known example of AI is the voice-activated assistant Siri,
which was introduced as part of the iPhone 4S in 2011. Other examples
of AI include self-driving cars, spam filters, and recommendation
systems like those used by Netflix and Amazon.
History of AI
Few people know that the history of artificial intelligence (AI) goes back
centuries. In fact, some of the earliest AI concepts were proposed by
Greek philosophers like Aristotle and Plato. It wasn’t until the 1950s that
AI really began to take shape as a field of study. This was thanks to the
work of computer scientists like Alan Turing and John McCarthy, who
coined the term artificial intelligence.
One of the earliest AI programs created was called Eliza and functioned
as a psychotherapist – something it could do in part because it could
recognize words from limited context. Over time, more sophisticated
machines emerged. For example, in 1979, there emerged an intelligent

3. robot called Shakey which used path planning algorithms for navigation.
Nowadays, we are seeing many advances in machine learning – where
computers can learn without being explicitly programmed. They can be
trained using large data sets to predict or label objects with near-human
accuracy.
Definition of Artificial Intelligence
Most people have heard of artificial intelligence (AI), but few know
exactly what it is. AI is a process of programming computers to make
decisions for themselves. This can be done in a number of ways, but the
most common is through the use of algorithms.
Difference between AI and Machine Learning
AI, or artificial intelligence, is a process of creating intelligent machines
that can think and work on their own. Machine learning, on the other
hand, is a subset of AI that deals with the creation of algorithms that can
learn from data and improve on their own. AI systems make use of
machine learning to constantly adjust to new data and improve its
performance over time. There are two types of AI systems: supervised
AI, which relies on human input for feedback about errors; and

4. unsupervised AI, which has no such dependency. Within these two types
are a number of different subtypes (such as deep learning) that do
various things like recognize speech or images based on training sets
given by humans. AI systems have been in development since 1950s
when a mathematician named John McCarthy coined the term artificial
intelligence. He defined AI as the science and engineering of making
intelligent machines. It's believed that we'll eventually reach a point
where computers will be able to perform any intellectual task that a
human being can.
A major advancement in AI came in 1956 when Alan Turing published an
essay called Computing Machinery and Intelligence proposing an
experiment called the Turing Test. The test consisted of asking
questions via text messages between two people, one human and one
computer-controlled chatbot without telling them apart. If the person
was unable to tell whether they were communicating with another
person or a machine then the computer would be considered intelligent.
Applications of AI in different fields
AI has been making waves in the business world for some time now,
with applications in fields as diverse as retail, healthcare, finance, and
manufacturing. Here are just a few examples of how AI is being used in
different industries Retail In order to reduce costs, Amazon introduced
an army of autonomous robots to their warehouses. Robots are also
useful when dealing with products that have irregular shapes and sizes
because they can use mechanical claws to pick up these items without
damaging them. Healthcare Some hospitals use AI-powered virtual
assistants like IBM's Watson in order to review patient records more
efficiently so that doctors can spend more time providing care rather
than administrative tasks like paperwork.
How do neural networks used in AI work

5. Neural networks are used in artificial intelligence (AI) to help machines
learn. Learning in this context means being able to identify patterns in
data so that the machine can make predictions or recommendations.
Neural networks are inspired by the way the brain works, and they are
composed of a series of interconnected nodes, or neurons. Each node
represents a unit of information, and the connections between nodes
represent relationships between those units of information. Nodes are
connected to each other in layers, with the input layer receiving data
from outside the network, and the output layer producing predictions or
recommendations based on that data. The hidden layers in between
these two extremes are where the actual learning takes place.
Issues with AI technologies
There are a number of issues but we discuss some of the points with
AI technologies that need to be considered.
● AI technologies can be biased. This means that they may make
decisions that are not in the best interests of everyone involved.
● AI technologies can be opaque. This means that it can be difficult
to understand how they make decisions.
● AI technologies can be weaponized. This means that they can be
used to harm people or to control them.
● AI technologies can be expensive. This means that they may only
be affordable to a small number of people or organizations.

6. ● AI technologies can be vulnerable to attack. This means that they
may not be able to protect data or systems from being hacked.