1. Artificial intelligence (AI)

2. What is ‘ AI ‘ ?
Cars that drive themselves •2005: DARPA grand challenge •2011: Google self-driving cars

3. natural language: The Turing Test http://www. pandorabots
natural language: The Turing Test A.L.I.C.E. talking to ELIZA (circa 2005)

4. natural language: machine translation

5. natural language: question answering

6. game: chess

7. WWW: web search •Ranking is everything smart people in Google, Yahoo
WWW: web search •Ranking is everything smart people in Google, Yahoo!, MSN, etc. e.g. Peter Norvig •A whole Search Engine Optimizer (SEO) industry Promote your webpage’s rank in search engines Some bad reputations (spam the search engines)

8. WWW: driving directions

9. robotics

10. إذن ..ما هو الذكاء الاصطناعي ..!
يهدف علم الذكاء الاصطناعي إلى فهم طبيعة الذكاء الإنساني عن طريق عمل برامج للحاسب الآلي قادرة على محاكاة السلوك الإنساني. وتعني قدرة برنامج الحاسب على حل مسألة ما أو اتخاذ قرار في موقف....

11. يهتم علم الذكاء الاصطناعي بالعمليات المعرفية التي يستخدمها الإنسان في تأدية الأعمال التي نعدها ذكية. وتختلف هذه الأعمال اختلافا بينا في طبيعتها , فقد تكون فهم نص لغوي منطوق أو مكتوب أو لعب الشطرنج أو حل لغز أو مسألة رياضية أو كتابة قصيدة شعرية أو القيام بتشخيص طبي أو الاستدلال على طريق للانتقال من مكان إلى آخر. ويبدأ الباحث في علم الذكاء الاصطناعي عمله أولا باختيار أحد الأنشطة المتفق على أنها ذكية ثم يضع بعض الفروض عما يستخدمه الإنسان لدى قيامه بهذا النشاط من معلومات واستدلالات .. ثم يدخل هذه في برنامج للحاسب الآلي ثم يقوم بملاحظة سلوك هذا البرنامج. ....

12. History of AI
The human aspiration to create intelligent machines has appeared in myth and literature for thousands of years, from stories .
After thousands of years of fantasy, the appearance of the digital computer, with its native, human-like ability to process symbols, made it seem that the myth of the man-made intelligence would
finally become reality.
  Origins The early history of artificial intelligence, from Greek myth through the work of Alan Turing in the 1950s. 
 After 1950 The challenges of creating artificial intelligence in the age of the digital computer.

13. Problems
The general problem of simulating (or creating) intelligence has been broken down into a number of specific sub-problems. These consist of particular traits or capabilities that researchers would like an intelligent system to display. The traits described below have received the most attention :

14. Deduction, reasoning, problem solving الاستدلال,المنطق,حل المشكلات
Knowledge representation تمثيل المعرفة
Planning التخطيط
Learning التعلم
Natural language processing معالجة اللغات الطبيعية
Motion and manipulation الحركة والتعامل
Perception الإدراك
Main articles: Machine perception, Computer vision, and Speech recognition
Social intelligence الذكاء الاجتماعي

15. List of programming languages
IPL[1] was the first language developed for artificial intelligence.
Lisp[2] is a practical mathematical notation for computer programs based on lambda calculus.
Prolog[3][4] is a declarative language where programs are expressed in terms of relations, and execution occurs by running queries over these relations. Prolog is particularly useful for symbolic reasoning, database and language parsing applications. Prolog is widely used in AI today.
STRIPS is a language for expressing automated planning problem instances.
Planner is a hybrid between procedural and logical languages.
AI applications are also often written in standard languages like C++ and languages designed for mathematics, such as MATLAB and Lush.

16. What is the Applications of artificial intelligence ?...
now
What is the Applications of artificial intelligence ?...

17. Hybrid intelligent system Intelligent agent Intelligent control
Typical problems to which AI methods are applied
Pattern recognition
Optical character recognition
Handwriting recognition
Speech recognition
Face recognition
Artificial Creativity
Computer vision, Virtual reality and Image processing
Diagnosis (artificial intelligence)
Game theory and Strategic planning
Game artificial intelligence and Computer game bot
Natural language processing, Translation and Chatterbots
Nonlinear control and Robotics
Other fields in which AI methods are implemented
Artificial life
Automated reasoning
Automation
Biologically inspired computing
Concept mining
Data mining
Knowledge representation
Semantic Web
spam filtering
Robotics
Behavior-based robotics
Cognitive
Cybernetics
Developmental robotics
Epigenetic robotics
Evolutionary robotics
Hybrid intelligent system
Intelligent agent
Intelligent control
Litigation

18. What have we learned TODAY ?

19. There’s no magic in AI. It’s all about optimization, statistics, logic, and algorithms.