This document provides an overview of artificial intelligence (AI) presented by Alia Hamwi. It defines AI and intelligence, describes major AI fields like machine learning, computer vision, natural language processing, and robotics. It discusses when machine learning is useful and challenges of AI, including being in the stage of narrow AI currently. Ethics concerns around fairness, accountability, transparency, privacy and reliability are also mentioned. The presentation introduces AI and its applications at a high level in under 3 sentences.

1. Teens In AI Damascus
Artificial
Intelligence
(AI)
Presented by Alia Hamwi

2. Hello!
I’m Alia
AI Engineer – Data Scientist – Python Developer

3. AI Definition
a computing concept that helps a
machine think and solve complex problems
as we humans (emulate) do with our intelligence.

4. Intelligence Definition
Reasoning
Learning
Problem Solving
Perception

5. Intelligence Definition
There is many definition but the main one is the
“Ability to learn”

6. AI fields
Machine Learning
Predictive analysis, Deep Learning
Computer Vision
Images, Videos
Natural Language Processing
Text, Speech
Robotics

7. AI fields
Machine Learning
Predictive analysis, Deep Learning
Computer Vision
Images, Videos
Natural Language Processing
Text, Speech
Robotics

8. Machine Learning
“Machine Learning: Field of study that gives
computers the ability to learn without being
explicitly programmed.” -Arthur Samuel (1959)

9. ML vs Programming

10. When we use ML
ML is used when:
• Humans can’t explain their expertise (speech
recognition)
• Models are based on huge amounts of data
(genomics)
Learning isn’t always useful:
• There is no need to “learn” to calculate payroll

11. When we use ML
ML is used when:
• Humans can’t explain their expertise (speech
recognition)
• Models are based on huge amounts of data
(genomics)
Learning isn’t always useful:
• There is no need to “learn” to calculate payroll

12. AI fields
Machine Learning
Predictive analysis, Deep Learning
Computer Vision
Images, Videos
Natural Language Processing
Text, Speech
Robotics

13. Computer Vision
The science of allowing computers to see.
relies on pattern recognition and deep learning to
recognize what’s in a picture or video.
When machines can process, analyze, and
understand images,
they can capture images or videos in real-time and
interpret their surroundings.
Ex: Face Recognition (Apple ID)

14. AI fields
Machine Learning
Predictive analysis, Deep Learning
Computer Vision
Images, Videos
Natural Language Processing
Text, Speech
Robotics

15. Natural Language
Processing
the ability of computers to analyze,
understand, and generate human language,
including speech.
Ex: Siri

16. AI fields
Machine Learning
Predictive analysis, Deep Learning
Computer Vision
Images, Videos
Natural Language Processing
Text, Speech
Robotics

17. Robotics
A field of engineering focused on the design and
manufacturing of robots.
Ex: Self-driving cars

18. Challenges:
Do we need AI ?
- Platform for recipes.
- Platform for share disease information.
- Music stream app like (sound cloud).

19. Stages of AI
Stage 1
Narrow AI
Stage 2
General AI
Stage 3
Super AI

20. In which stage we are?

21. In which stage we are?

22. AI Ethics
Fairness, Accountability, Transparency, privacy ,
Reliability

23. Some Challenges
- Bias in AI
- Moral Dilemma
- privacy

24. Thank You