Artificial Intelligence definition for beginners
Definition and Terminology of Artificial Intelligence (Ai). For beginners, it can be difficult to understand the concept of artificial intelligence. After all, it’s difficult to understand that a computer or piece of software has the ability to think, learn, and act like a human! But don’t worry – we’ve got your back! In this article, we will see what Ai means and the common terms associated with it so you can gain a better understanding of this revolutionary tech.
What is Ai?
Artificial Intelligence, or for short(Ai), is an attempt to make computers
look like they have human intelligence. A basic definition of Ai could be that
it is any machine that can think for itself in a human-like way, meaning that
it has no need for direct input from its user as it can function on its own.
But what does Ai mean more specifically?
How do you know if something is considered AI? Here’s a list of
common terms you may see associated with AI: Natural language processing: NLP
is how AI relates to things like how humans interact with each other verbally.
The goal here is to figure out what a person means when they say something
versus just looking at individual words and their meaning alone.
For example, humans don't go around talking about
ambiguous loss; we talk about grief. With NLP algorithms, AI tries to
understand how people are expressing themselves through speech and writing in
order to give them information back or react appropriately. Machine learning:
In essence, machine learning allows machines to learn based on experience
rather than having everything programmed into them ahead of time by people.
Using specialized programs known as algorithms ,
machines are able to learn a specific behavior—from recognizing someone's face
after being shown photos of them before down to predicting which letter comes
next based off what's been written so far in whatever text document is open—and
use past experiences to decide how best move forward toward achieving whatever
end result was wanted by those who programmed it in the first place.
History of Artificial intelligence( Ai)
Artificial intelligence (Ai) is not a new concept,
with roots dating back to over 100 years ago. However, it wasn’t until 1956
that computer scientist John McCarthy coined the term artificial intelligence
at a conference held at Dartmouth College in New Hampshire.
Although AI was first theorized by Alan Turing in
his 1950 paper Computing Machinery and Intelligence, it wasn’t until 1957 that
IBM created its supercomputer named IBM 701 which had voice recognition
capabilities designed by Arthur Samuel.
The first expert system called MYCIN was developed
around 1972 as an attempt to create computers capable of processing human
language commands—comprising over 600 rules based on various medical systems
used to determine appropriate treatment plans for patients—without actual human
intervention.
Components of Ai
Here are some of the components that make up AI.
While it is not an all-inclusive list, it does outline some of its major areas.
Algorithms: These are instructions for a computer to follow in order to carry
out various tasks or solve problems. An algorithm helps automate repetitive
tasks so a machine can complete them quickly and more accurately than people.
Machine Learning : This type of artificial intelligence uses algorithms to
learn from data so it can improve its performance over time.
Machine learning has become more prominent as
technology improves, making machines more capable of interpreting vast amounts
of data to make accurate predictions and decisions on their own—even without
being told exactly what to do or how to do it by humans.
Probabilistic Reasoning/ Bayesian Networks :
Probabilistic reasoning and Bayesian networks use mathematical equations to
predict how likely certain events will occur in order to identify patterns and
determine probable outcomes based on prior knowledge. Natural Language
Processing (NLP): NLP allows computers to understand natural human language;
much like search engines let us look up anything online, NLP lets computers
read almost any text or spoken language. This advancement makes Ai increasingly
usable because we no longer have to speak commands into our devices but rather
we can type sentences just like we would with a person. Robotics : The
development of robotics spans several decades but came into its own after
advancements in sensors, motion control technologies and processor speed made
machinery move more reliably – at least most of the time!
Deep Learning
Many organizations are now able to use artificial
intelligence for many purposes, including image recognition, natural language
processing and even making business decisions. This is thanks to a branch of AI
called deep learning. Deep learning is about extracting patterns from large datasets
and using those patterns to solve problems or make predictions about new data.
Companies such as Google, Facebook, Microsoft and
Amazon have built deep-learning tools that run in their cloud computing
services. These tools can be used by companies without expertise in deep
learning.
Although these services may be free now, they might
become expensive with time; it’s best to learn how they work today so you’ll be
prepared when that happens. After all, artificial intelligence will only become
more powerful—and vital—in our increasingly digital world.
If you want to understand how AI works, what it
means for your organization and where it could take us next, then join us at
our webinar on February 8th 2017! We’re discussing Artificial Intelligence
& Deep Learning: The Next Big Thing? Register here! Don't miss out! We'd
like to wish you all a happy New Year in advance – we hope 2017 brings lots of
health and happiness your way!
Machine Learning
Artificial intelligence is an evolving set of
technologies that lets machines learn from data, identify patterns, and make
decisions with minimal human intervention. Machine learning is a subset of
artificial intelligence in which computers can learn without being explicitly
programmed.
This allows software to automatically evolve over
time by leveraging large datasets rather than relying on expert programmers to
code algorithms. Unlike traditional programming methods, artificial
intelligence focuses on finding optimal solutions through pattern recognition
rather than direct coding. In practice, machine learning algorithms attempt to
maximize performance metrics like accuracy while minimizing cost functions like
error rates or energy usage through iterative trial-and-error processes called
training loops.
Ultimately, artificial-intelligence approaches are
utilized whenever machines need to classify objects and take appropriate
actions without explicit instructions.
Natural Language Processing (NLP)
Let’s start with Natural Language Processing, in
short NLP. Also known as NLP, NLP is a field of AI devoted to understanding
human language. This means that natural language processing AI is looking for
patterns and meaning in text.
The two most common methods of accomplishing NLP
are: statistical models that look for keywords or typical sentence structures,
and machine learning algorithms that determine which words tend to follow other
words within a piece of text.
Algorithms like these have become indispensable
tools for all sorts of industries—from social media companies to retailers who
want to know what their customers are saying about them online. At its core,
Natural Language Processing seeks to answer one simple question: if we use
computer code and big data to learn how humans communicate verbally, can we
program machines with that knowledge? A lot of times, you might even hear
people talking about deep learning when they're talking about NLP.
That's because deep learning is another one of those
major fields in AI right now. Essentially, deep learning uses neural networks
and artificial neurons to allow computers to teach themselves different skills
through trial-and-error—just like a baby learns by trying new things over time.
Deep learning has been developed at least in part out of necessity; when IBM's
Watson supercomputer started launching Jeopardy!
Why Ai?
Artificial intelligence is one of those buzzwords that have been around for years, but what does it mean? There are multiple definitions out there for Ai but these three all convey a similar meaning. A,I is defined as
1. Theory and
development of computer systems capable of performing tasks that normally
require human intelligence
2.The
capability of a machine to imitate intelligent human behavior.
3. Human
intelligence in machines, software etc., especially when regarded as a promising
substitute for human beings.
How can artificial intelligence benefit us?:
Artificial intelligence has been used by humans
throughout history in many ways. From early cave drawings depicting hunters
chasing wildlife with spears to today’s automated stock trading algorithms -
we’ve relied on artificial intelligence at every step of our history. Now it is
time to utilize Ai more than ever before.
