Artificial Intelligence_Lecture_1. .pptx

1. Artificial Intelligence
Lecture # 1
Sobia Shafiq

2. Course Information
Marks Distribution:
• Internals – 25% (Assignments, Quizzes, Presentation, Project)
• Mid Term Exam – 25%
• Final Exam – 50%

3. Textbook, Course Outline

4. Natural Intelligence (NI)
• NI is about how Humans or Animals brain functions.
• The ability to solve the problems
• Consider the following sequence …
• 1,3,7,13,__
• What is the next number ?
• Intelligence is to reason in a logical way to reach a
conclusion

5. Artificial Intelligence VS. Human Intelligence

6. 6

7. Artificial Intelligence VS. Human Intelligence

8. Artificial Intelligence VS. Human Intelligence

10. What is artificial intelligence?
Q. What is artificial intelligence?
A. It is the science and engineering of making intelligent machines, especially intelligent computer
programs. It is related to the similar task of using computers to understand human or other intelligence,
but AI does not have to confine itself to methods that are biologically observable.
Q. Yes, but what is intelligence?
A. Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees
of intelligence occur in people, many animals and some machines.

11. AI in Practice

12. AI in Practice

13. Artificial Intelligence Defined: Four Types Of Approaches
• Thinking humanly: mimicking thought based on the human mind.
• Thinking rationally: mimicking thought based on logical reasoning.
• Acting humanly: acting in a manner that mimics human behavior.
• Acting rationally: acting in a manner that is meant to achieve a
particular goal.

14. Components of Artificial Intelligence
1. Learning
2. Reasoning
3. Problem-solving
4. Perception
5. Language-understanding

15. Artificial Intelligence
• To understand the idea behind AI, you should think about what distinguishes human intelligence
from that of other creatures –
• our ability to learn from experiences
• apply these lessons to new situations.
• Human beings can do this because of advanced brain power
• Artificial intelligence (AI) is the ability of machines to replicate or enhance human intellect, such
as reasoning and learning from experience. Artificial intelligence has been used in computer
programs for years, but it is now applied to many other products and services.
• Today’s computers don’t match the human biological neural network – not even close. But they
have one significant advantage over us: their ability to analyze vast amounts of data and
experiences much faster than humans could ever hope.

16. Artificial Intelligence, Machine Learning, Deep Learning and Data Science

18. Goals of Artificial Intelligence
• It helps you reduce the amount of time needed to perform specific tasks.
• Making it easier for humans to interact with machines.
• Facilitating human-computer interaction in a way that is more natural and
efficient.
• Improving the accuracy and speed of medical diagnoses.
• Helping people learn new information more quickly.
• Enhancing communication between humans and machines.

19. Different fields under AI
Machine Learning:
Machine learning is the art of studying algorithms that learn from examples and experiences. Machine learning is
based on the idea that some patterns in the data were identified and used for future predictions. The difference
from hardcoding rules is that the machine learns to find such rules.
Deep Learning:
Deep learning is a sub-field of machine learning. Deep learning does not mean the machine learns more in-depth
knowledge; it uses different layers to learn from the data. The depth of the model is represented by the number of
layers in the model. For instance, the GoogleLeNet model for image recognition counts 22 layers.
Natural Language Processing:
Natural language processing means developing methods that help us communicate with machines using natural
human languages like English.
Computer Vision:
Computer vision works by allowing computers to see, recognize, and process images, the same way as human
vision does, and then it provides an appropriate output. Computer vision is closely related to AI. Here, the
computer must understand what it sees, and then analyze it, accordingly.

20. Types of Artificial Intelligence

21. Type-I
• Narrow AI:
Sometimes referred to as “weak AI,” this kind of AI operates within a limited context
and is a simulation of human intelligence. Narrow AI is often focused on performing a
single task extremely well and while these machines may seem intelligent, they are
operating under far more constraints and limitations than even the most basic human
intelligence. (eg Voice assistance: Alexa)
• Artificial general intelligence (AGI):
AGI, sometimes referred to as “strong AI,” is the kind of AI we see in movies — like the
robots. The Next Generation. AGI is a machine with general intelligence and, much like a
human being, it can apply that intelligence to solve any problem. (eg An AGI-powered
self-driving car encounters an unexpected traffic jam on its usual route)
• Superintelligence:
Super intelligent AI will not only be able to replicate the complex emotion and
intelligence of human beings, but surpass it in every way. This could mean making
judgments and decisions on its own, or even forming its own ideology. Still a theoretical
stage of AI

22. Type-II
• The four A.I. types are
1. Reactive Machines
2. Limited Memory
3. Theory of Mind
4. Self Aware

23. Type-II
• Reactive Machines
• Reactive Machines perform basic operations. This level of A.I. is the simplest. These types
react to some input with some output. There is no learning that occurs. This is the first stage to
any A.I. system. A machine learning that takes a human face as input and outputs a box
around the face to identify it as a face is a simple, reactive machine. The model stores no
inputs, it performs no learning.
• Limited Memory
• Limited memory types refer to an A.I.’s ability to store previous data and/or predictions, using
that data to make better predictions. With Limited Memory, machine learning architecture
becomes a little more complex. Every machine learning model requires limited memory to be
created, but the model can get deployed as a reactive machine type.

24. Type-II
• Theory of Mind
• We have yet to reach Theory of Mind artificial intelligence types. These are only in their
beginning phases and can be seen in things like self-driving cars. In this type of A.I., A.I.
begins to interact with the thoughts and emotions of humans.
• Self-Aware
• Finally, in some distant future, perhaps A.I. achieves its highest state. It becomes self-aware.
This kind of A.I. exists only in story, and, as stories often do, instills both immense amounts
of hope and fear into audiences. A self-aware intelligence beyond the human has an
independent intelligence, and likely, people will have to negotiate terms with the entity it
created. What happens, good or bad, is anyone’s guess.

26. Application of Artificial Intelligence

28. Intelligence
• Turing Test: A human communicates with a computer via a
teletype. If the human can’t tell he is talking to a computer or
another human, it passes.
• Natural language processing
• knowledge representation
• automated reasoning
• machine learning

29. Future of Artificial Intelligence
• When you look around you, you will notice that Artificial Intelligence has impacted almost every
industry and it will continue to do so in the future. It has emerged as one of the most exciting and
advanced technologies of our time. Robotics, Big Data, IoT, etc. are all fueled by AI.
• There are companies around the world conducting extensive research on Machine Learning and
AI. At the current growth rate, it is going to be a driving force for a very long time in the future as
well.
• AI helps computers generate huge amounts of data and use it to make decisions and discoveries in
a fraction of the time that it would have taken a human to. It has already had a lot of impact on our
world. If used responsibly, It can end up massively benefiting human society in the future.

30. Assignment 01
• What is the scientific method hypothesis behind AI?
• Future of AI, friend or foe
• What is the impact and role of AI on/in information sciences
• How can AI be used in information sciences research
• Will AI ever exceed NI?