Title: Big Data and Artificial Intelligence -Are they the same?
1Big Data and Artificial Intelligence - Are they
the same?
2What is Artificial Intelligence?
- Artificial intelligence is the intelligence
exhibited by machines and computer systems. The
term is often applied to a machine's ability to
behave intelligently. AI is a broad term that
encompasses both the idea of a machine thinking
like humans and the idea of a machine solving
problems in ways that would be difficult for
humans to do so. AI can be seen as an application
of computer science that focuses on making
machines perform tasks that require intelligence
when done by people, such as visual perception,
speech recognition, decision-making, and
translation between languages. While AI is not
new, it has recently become more popular because
it has evolved to be more accessible to people
who don't have a background in computer science.
3What is Big Data?
Big Data is a term used to describe large data
sets that are so large or complex that
traditional data processing application software
cannot process them on time. A big data set can
be anything from the text of all the books in the
Library of Congress to an image from a security
camera in a busy intersection. The term "big
data" is often used interchangeably with other
terms such as "high volume, high velocity, and
large variety."
4Some of the benefits of AI and Big Data There
are many benefits of AI and big data. Some of
them are discussed below - Increased accuracy
in decision making AI helps reduce the
number of errors in decision making. It also
helps generate better outcomes. - Better
customer experience AI helps to serve
customers better by providing them with a
personalized experience. - Reduced costs
With the help of AI, companies can save
money on things such as marketing campaigns,
customer service, and more. - Increased
productivity With the help of AI,
employees can get more done in less time without
any human error or fatigue.
5What Is the Difference Between Big Data And AI?
- There are two main differences between big data
and AI. - The first is that AI is a subset of big data. Big
data can be thought of as the raw data that an
organization collects and stores in its databases
to analyze patterns and trends. AI, on the other
hand, is a set of algorithms that can be used to
analyze this data and make predictions based on
what it finds. - The second difference between these two concepts
is that while big data focuses on analyzing large
amounts of raw information, AI uses a variety of
algorithms to analyze this information and make
predictions based on what it finds.
6- The difference between
- Big Data and AI can be summarized in three
points
1) The amount of data available The amount of
data available for analysis is much larger with
Big Data than with AI. ? 2) The type of data AI
can process unstructured data like text, images,
videos, or audio files which is not possible with
Big Data. ? 3) The time needed for
analysis With Big Data you need more time for
analyzing your data than with AI. ?
7How Do Artificial Intelligence and
Big Data Interact Together?
AI and Big Data come together to provide a better
understanding of customer needs. AI can use data
from the past and present to predict customer
needs in the future. It can also help with
finding new customers by looking at what
competitors are doing. ? AI and Big Data are not
just for large companies, they can be used by
smaller businesses too. AI can help with finding
new customers, it can find out what
product people are looking for and then provide
them with that product at a cheaper price than
their competitors.
8AI and Big Data are two of the most important
technological advancements that have been made in
recent years. The relationship between AI and
Big Data is a symbiotic one. AI needs the data
to learn from, and Big Data needs the
intelligence provided by AI to make sense of it
all. AI is a type of technology that learns from
data, so it is no surprise that there is an
intimate relationship between AI and Big
Data. Big Data refers to datasets that are so
large or complex that traditional data processing
applications are inadequate to deal with them.
Data may be stored in any format such as text,
images, sound, or video. Big Data can come from
many sources such as sensors, social media posts,
computer logs, and more.