THIS IS AN INTRODUCTORY PPT OF EMERGING TECHNOLOGIES AND NEED IN REAL LIFE. THIS WIL EXPLAIN BSICS ABOUT ALL EMERGING TECHNOLOGY AND THEIR APPLICATION IN VARIOUS SECTOR
4. A R T I F I C I A L
INTELLIGENCE
According to the father of Artificial Intelligence John McCarthy,
it is “The science and engineering of making intelligent
machines, especially intelligent computer programs”.
Artificial Intelligence is a way of making a computer, a
computer-controlled robot, or a software think intelligently, in
the similar manner the intelligent humans think.
AI is accomplished by studying how human brain thinks, and
how humans learn, decide, and work while trying to solve a
problem, and then using the outcomes of this study as a basis of
developing intelligent software and systems.
6. TYPES ARTIFICIAL INTELLIGENCE
the
ability to learn and apply its intelligence to solve any problem like human can do
Artificial Super Intelligence (ASI) is the hypothetical AI, i.e. we have not been able to
achieve it but we know what will happen if we achieve it. So basically it is the imaginary AI
7. TYPES ARTIFICIAL INTELLIGENCE
Based On
Functionality
Reactive Machines:-
-Purely reactive machines.
-Do not store memories or past experiences for future.
-Focus on current scenarios and react. E.g. Deep Blue. (IBM)
Limited Memory:-
-These machines can use stored data for a limited time period only.
-Examples: Self Driving Cars. It can store recent speed of nearby cars, the distance etc. for
short period.
Theory of Mind and Self-Awareness :-
Self-awareness & Interact Socially like humans are the features.
Hypothetical Concept it means it based on possible ideas
8. Machine
Learning
Machine Learning is the Branch of Artificial
Intelligence, which provides the machine to learn and
work automatically. Machine are installed with the
specific Algorithms once installed no further
programing in these machines is required because with
this technology machine will work and improves
accuracy automatically through experience like
humans. Human intervention is very less
L E A R N I N G
M A C H I N E
10. Supervised ML
• Past experience
are applied to new
work for better
result
Unsupervised ML
• Output predicted
on given data
only. Test data or
real data is used
and identify
similarities
between data and
gives output
Reinforcement ML
• Possible trial and
error identifies
and helps
machines.
MACHINE LEARNING MODEL
INPUT DATA
(APPLES)
EXPLANATION
MODEL
PREDICTION
(ITS AN APPLE)
11. Deep Learning solves more complex data. It has Hugh
data both structure and unstructured than machine
learning
Deep learning is an AI function that mimics (to copy
somebody’s behavior) the workings of the human brain
in processing data for use in detecting objects,
recognizing speech, translating languages, and making
decisions.
Deep learning AI is able to learn without human
supervision.
Deep learning, a form of machine learning, can be used
to help detect fraud or money laundering, among other
functions.
L E A R N I N G
D E E P
12. BlockChain is basically related with crypto-currency. Crypto-
currencies are the form of digital or virtual currency.
Blockchain creates blocks of similar crypto-currencies.
During transaction this technology encrypt the details with
code words and remit it to the person with protected &
secured network.
Main features:-
1. Open data base
2. Continuous work even if other computer fails to operate
3. Public distributed ledger
4. Protected with strong & complex algorithms which
protects system from hackers.
TEC H N OLOGY
B L O C K C H A I N
13. Big data is the largely unstructured data which is generating
world wide.
To analysis the data and make it from unstructured to
structured big data technology is used.
BDT is generally a software that is design to analysis the ever
increasing exponential data to have some utility.
Globally distributed Data.
TEC H N OLOGY
B I G D A T A
*SOFTWARE USED IN BDT :- Hadoop, Hunk, RainStar
MongoDB (Now came under Apache)
When to browse something the same will be
displayed again and again when you use social
media
14. A u g m e n t e d
r e a l i ty ( AR )
*Digital elements to a live view often by using the
camera on a Smartphone.
*Digital object placed on the real environment.
*You bring digital world to real world.
*Detection and measure distance of object and work
accordingly.
*Eg. Google AR Core., Snap chat lenses and the game
Pokémon Go. , Asian Paints
15. V i r t u a l
Reality (VR)
•Virtual Reality (VR) is the use of computer
technology to create a simulated environment.
*Implies a complete immersion experience that
shuts out the physical world
*Need VR glasses to see Digital World
*You have to go to 3D world from real World.
16. ROBOTICS
*Robotics is an interdisciplinary field that integrates
computer science and engineering.
*Robotics involves design, construction, operation, and
use of robots.
*The goal of robotics is to design machines that can
help and assist humans.
*Robotics develops machines that can substitute for
humans and replicate human actions
