Artificial Intelligence Algorithms Presentations

1. ARTIFICIAL
INTELLIGENCE
ALGORITHM
FOR-IAN V. SANDOVAL

2. Learning Objectives
➢ Differentiate Artificial Intelligence with Machine
Learning
➢ Determine the types of machine learning
➢ Identify the problems solved using Artificial
Intelligence Algorithms
➢ Classify Artificial Intelligence Algorithms

3. ARTIFICIAL INTELLIGENCE

4. ARTIFICIAL INTELLIGENCE
➢ Artificial Intelligence
is the science of
getting machines to
think and make
decisions like human
beings do.
➢ theory and
development of
computer systems

5. ARTIFICIAL INTELLIGENCE
➢ human intelligence
➢ visual perception
➢ speech
recognition
➢ decision-making
➢ translation
between
languages

6. ARTIFICIAL INTELLIGENCE
➢ Accomplished by
studying how human
brain:
➢ thinks
➢ learns
➢ decide
➢ work

7. ARTIFICIAL INTELLIGENCE
➢ Deep Learning ➢ Natural Language
Processing

8. AREAS OF AI CAN BE APPLIED

9. IMPORTANCE OF AI
➢ AI automates Repetitive Learning and discovery
through data.
➢ AI adds intelligence to existing products.
➢ AI adapts through progressive learning
algorithms to let the data do the programming.
➢ AI analyzes more and deeper data using neural
networks that have many hidden layers.
➢ AI achieves incredible accuracy through deep
neural networks

10. APPLICATIONS OF AI
➢ AI in Health Care

11. APPLICATIONS OF AI
➢ AI in Business

12. APPLICATIONS OF AI
➢ AI in Education

13. APPLICATIONS OF AI
➢ AI in Agriculture

14. APPLICATIONS OF AI
➢ AI in Media and Entertainment

15. APPLICATIONS OF AI
➢ AI in Autonomous Vehicle

16. APPLICATIONS OF AI
➢ AI for Robotics

17. APPLICATIONS OF AI
➢ Cyborg Technologies

18. DOMAINS OF AI
➢ Neural Networks
➢ Neural Networks
are a class of
models within the
general machine
learning literature

19. DOMAINS OF AI
➢ Robotics
➢ a branch of AI,
which is composed
of different
branches and
application of
robots

20. DOMAINS OF AI
➢ Expert System
➢ a computer system
that emulates the
decision-making
ability of a human
expert

21. DOMAINS OF AI
➢ Fuzzy Logic Systems
➢ an approach to
computing based on
“degrees of truth”
rather than the usual
“true or false” (1 or 0)
Boolean logic on
which the modern
computer is based

22. DOMAINS OF AI
➢ Natural Language Processing
➢ Machine translation
➢ Named Entity
Recognition
➢ Sentiment Analysis,
➢ Speech
Recognition
➢ Topic
Segmentation

23. AI Technologies
➢ Natural Language Generation

24. AI Technologies
➢ Speech Recognition

25. AI Technologies
➢ Face Recognition and Automatic Tagging

26. AI Technologies
➢ Virtual Agents / Virtual Assistant

27. AI Technologies
➢ Machine Learning

28. AI Technologies
➢ Deep Learning Platforms

29. AI Technologies
➢ Biometrics

30. AI Technologies
➢ Robotic Process Automation

31. AI Technologies
➢ Text Analytics and NLP

32. CLASSIFICATION OF AI
➢ AI system that is designed and trained for a
specific type of task.
➢ Also known as Narrow AI
➢ Weak AI

33. CLASSIFICATION OF AI
➢ Strong AI
➢ AI system with generalized human cognitive
abilities so that when presented with an
unfamiliar task, it has enough intelligence to find
a solution.
➢ Also know Artificial General Intelligence

34. TYPES OF AI
Type 1. Reactive Machines
➢ Deep Blue
➢ it has no memory and cannot use past
experiences to inform future ones.
➢ it has no memory and cannot use past
experiences to inform future ones.

35. TYPES OF AI
Type 2. Limited Memory
➢ AI systems can use past experiences to inform
future decisions.
➢ Most of the decision-making functions in the
autonomous vehicles have been designed

36. TYPES OF AI
Type 3. Limited Theory
➢ understanding that the other have in their own
beliefs and intentions that impact the decisions
they make.
➢ At present this kind of artificial intelligence does
not exist.

37. TYPES OF AI
Type 4. Self-awareness
➢ AI systems have a sense of self, have
consciousness.
➢ Machines with self-awareness understand their
current state and can use the information to infer
what others are feeling.
➢ This type of AI does not yet exist.