These slides provides brief overview about Artificial Intelligence and its applications.

1. Artificial Intelligence
& Robotics Session.

2. WHAT IS AI?
It is the machine’s ability to keep improving its
performance without humans having to explain
exactly how to accomplish all the tasks it’s given.

3. The term artificial intelligence was coined in 1955 by John
McCarthy, a math professor at Dartmouth who organized the
seminal conference on the topic the following year. Ever since,
perhaps in part because of its evocative name, the field has
given rise to more than its share of fantastic claims and
promises.
John McCarthy

4. To supplement natural intelligence for e.g. we
are building intelligence in an object so that it
can do what we want it to do, as for example--
robots, thus reducing
human labour and reducing human mistakes
Why do we need AI?

5. From SIRI to self-driving cars, artificial intelligence (AI) is
progressing rapidly AI can encompass anything from
Google’s search algorithms to IBM’s Watson to
autonomous weapons.

6. Artificial
Neural
Networks
Machine
Learning
Computer
Vision
Natural
Language
Processing
Robotics
Artificial Intelligence Branches

7. Artificial neural networks are
composed of interconnecting artificial
neurons (programming constructs that
mimic the properties of biological
neurons).
Machine learning is a
scientific discipline
concerned with the design
and development of
algorithms that allow
machines to mimic human
intelligence.
NLP or Speech
Recognition is where an
AI system can
be controlled and
respond to verbal
commands
Examples-
• Speech-driven word
processors
• Military weapon control
• Mobile assistants(SIRI, OK
Google)
• Customer query lines

8. Machine Learning is…
Machine learning is about predicting the future based on the
past.
Everybody learns from experiences. EVERYBODY. The
question is CAN WE MAKE COMPUTERS LEARN FROM
EXPERIENCES??

10. Difference between machine Learning and
AI!!

11. Uses labeled data Uses Unlabeled data
Machine Learning Types
Other Types: Reinforcement Learning, Recommender Systems.

12. Example: Arranging Into Group

13. Apple Cherries
Grapes Banana

14. By using Supervised Learning
No. SIZE COLOR SHAPE FRUIT NAME
1 Big Red Rounded shape with depression at the top Apple
2 Small Red Heart-shaped to nearly globular Cherries
3 Big Green Long curving cylinder Banana
4 Small Green Round to oval,Bunch shape Cylindrical Grapes

15. By using Unsupervised Learning
You know NOTHING about the fruits. So where to start?
Step 1:
● RED COLOR GROUP: Apple & Cherries.
● GREEN COLOR GROUP: Banana & Grapes.
Step 2:
● RED COLOR AND BIG SIZE: Apple.
● RED COLOR AND SMALL SIZE: Cherries.
● GREEN COLOR AND BIG SIZE: Banana.
● GREEN COLOR AND SMALL SIZE: Grapes.

16. Example: Google Photos

17. Housing price
prediction.
Breast cancer
prediction.

18. Artificial Neural Networks

19. Example: SIRI!

20. It is a field that includes
methods for acquiring,
processing, analyzing and
understanding images
It duplicates the ability of
human vision by electronically
perceiving and understanding
images.
Some Applications of CV
• Face Detection
• Traffic Monitoring
• Login without password
• Target recognition
• Optical Character recognition
• Interpretation o higher resolution satellite images
• 3D shape reconstruction
• Object recognition
• Medical Imaging
• Interactive gaming
What is Computer Vision?

21. You should choose
Raspberry Pi If:
Your project is complex
and networking is
involved.
Your project is more like a
software application, like
a VPN server or
Webserver
Raspberry Pi is a fully
functioned computer,
a system-on-chip
(SoC) device, which
runs on a Linux
operating system
specially designed for
it, named Rasbian.
Like a computer, It has
memory, processor,
USB ports, audio
output, graphic driver
for HDMI output and
as it runs on Linux,
most of the linux
software applications
can be installed on it.
Arduino is a microcontroller,
which is not as much powerful
as Raspberry Pi, and can be
considered as a one
component on computer
system. But it is a great
hardware for electronics
projects.
It doesn’t need any OS and
software applications to run,
we just need to write few lines
of code to make it use.
You should choose Arduino if:
You are from electronics background or if you are a beginner
and really want to learn about electronics and its components.
Your project is simple, especially networking is not involved.

22. APPLICATION OF AI
ML systems are often excellent learners. They can
achieve superhuman performance in a wide range of
activities, including detecting fraud and diagnosing
disease.

23. Let’s start by exploring what AI is already doing and how
quickly it is improving.
• Voice recognition- millions of people are now using it —
think Siri, Alexa, and Google Assistant.
• Speech recognition is now about three times as fast, on
average, as typing on a cell phone. The error rate, once
8.5%, has dropped to 4.9%.

24. • Image recognition- You may have noticed that Facebook
and other apps now recognize many of your friends’ faces
in posted photos and prompt you to tag them with their
names.
• Image recognition is even replacing ID cards at corporate
headquarters.

25. • Machines have already beaten the finest (human) players
of poker and Go
• Dozens of companies are using ML to decide which trades
to execute on Wall Street, and more and more credit
decisions are made with its help.
• Amazon employs ML to optimize inventory and improve
product recommendations to customers.

26. • Aptonomy and Sanbot, makers respectively of drones and
robots, are using improved vision systems to automate
much of the work of security guards.
• The software company Affectiva, among others, is using
them to recognize emotions such as joy, surprise, and
anger in focus groups.
• Enlitic is one of several deep-learning startups that use
them to scan medical images to help diagnose cancer.

27. APPLICATION OF AI-
WHAT YOU CAN THINK OF AND EVEN WHAT YOU CAN’T!!!

28. Thankyou!!