NCHU Course Outline
Course Name (中) 智慧科技(7652)
(Eng.) Intelligent Technologies
Offering Dept Executive Master Program in Intelligent Technology Management
Course Type Elective Credits 3 Teacher SUM, PUI-FAIJOHN
Department Executive Master Program in Intelligent Technology Management(W)Graduate Language 中/英文 Semester 2024-FALL
Course Description This course intends to introduce the core concepts and ideas of intelligent technologies. Student will have to understand the evolution of technologies and then the intelligent technologies. Besides, technological applications of intelligent technologies will be presented. The working principles of some commercial products which integrate multiple intelligent technologies will be elucidated.

Medium of instruction: Chinese (lecturing; assignments and reports) and English (teaching materials).

Use of ChatGPT: It is allowed. Student needs to declare in each assignment and the project report how did you use the ChatGPT. Furthermore, student has to ensure that (1) no content generated by the ChatGPT is incorrect; (2) the content is logical. Professor John Sum will definitely read all your assignments and the project report. You will be requested to clarify if there is any content not true or not logical.
Prerequisites
self-directed learning in the course N
Relevance of Course Objectives and Core Learning Outcomes(%) Teaching and Assessment Methods for Course Objectives
Course Objectives Competency Indicators Ratio(%) Teaching Methods Assessment Methods
Course Objectives
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1. To introduce the evolution & impacts of intelligent technologies.
2. To introduce some of the latest technologies in artificial intelligence and machine learning.
3. To introduce potential applications of intelligent technologies.
topic Discussion/Production
Exercises
Discussion
Lecturing
Written Presentation
Oral Presentation
Course Content and Homework/Schedule/Tests Schedule
Week Course Content
Week 1 Chapter 1: Introduction to Intelligent Technology

1.1 Course outline and assessment.
1.2 Intelligence: Human/Animal intelligence vs artificial intelligence.
1.3 Intelligent technology and AI/ML.
Week 2 Chapter 1: Introduction to Intelligent Technology

1.4 Exemplar intelligent technologies, systems and services.
1.5 Five foundational types of intelligent technology.
1.6 Intelligent infrastructure.
1.7 Issues in intelligent technology.
Week 3 Chapter 2: History of AI

2.1 Evolution of technology.
2.2 Evolution of AI.
Week 4 Chapter 3: First Foundational Type of iTech

3.1 National language processing (NLP)
3.2 Voice assistant: Alexa, Google Assistant and Siri.
3.3 Machine translator: Google Translate.
3.4 ChatBot: Google Bard and OpenAI ChatGPT.
3.5 Epilog:
-- 3.5.1 Text-to-text (document summarization, paraphrasing)
-- 3.5.2 Voice-to-text.
Week 5 Chapter 4: Second Foundational Type of iTech

4.1 Image processing: Pattern/Object recognition.
4.2 Character recognition.
-- 4.2.1 Optical character recognition.
-- 4.2.2 Car plate recognition.
4.3 Object recognition.
-- 4.3.1 Image/Photo tagging for untagged image/photo.
-- 4.3.2 Image/Photo captioning for uncaptioned image/photo.
-- 4.3.3 ImageNet challenge (Boosting the rise of AI research in 2010).
4.4 Multiple-Image processing.
-- 4.4.1 Object and motion detection.
-- 4.4.2 Auto-driving.
-- 4.4.3 Autonomous system.
4.5 Epilog: Image-to-text and video-to-text.
Week 6 Chapter 5: Third Foundational Type of iTech

5.1 Robotic.
5.2 Industrial robot.
-- 5.2.1 Manufacturing automation.
-- 5.2.2 Working a some danger zones.
5.3 Humanoid robot for mimicking human body movement.
5.4 Military robot.
5.5 Exploring outer-space.
5.6 Epilog:
-- 5.6.1 Can a robot decide who is enemy?
-- 5.6.2 Can a robot kill the enemy?
Week 7 Chapter 6: Forth Foundational Type of iTech

6.1 Game playing.
6.2 IBM Deep Blue.
6.3 Alpha Go.
6.4 Poker game.
6.5 Epilog
-- 6.5.1 Would an AI player bluff?
-- 6.5.2 Are they intelligent?
Week 8 Chapter 7: Fifth Foundational Type of iTech

7.1 Nature inspired optimization algorithms.
7.2 Industrial applications.
-- 7.2.1 Production cost reduction.
-- 7.2.2 Production process scheduling.
-- 7.2.3 Logistics.
-- 7.2.4 Workflow management.
7.3 Key ideas.
-- 7.3.1 Simulation annealing.
-- 7.3.2 Genetic algorithm and evolutionary computing.
-- 7.3.3 Big data analytic.
7.4 Epilog: Are they really intelligent?
Week 9 Project progress report.
Week 10 Chapter 8: Key Concepts in Intelligent Technology

8.1 AI model.
-- 8.1.1 Just a mathematical model with lot of parameters.
-- 8.1.2 Capturing the complicated regular patterns from a dataset.
8.2 Evolution.
-- 8.2.1 Simple (classical) models.
-- 8.2.2 Complex (contemporary) models.
-- 8.2.3 Model made up of multiple (thousands of) complex models.
Week 11 Chapter 8: Key Concepts in Intelligent Technology

8.3 Learning (i.e. model building) from a set of data.
8.4 Epilog
-- 8.4.1 Data collection.
-- 8.4.2 Representation of non-numeric data.
-- 8.4.3 Human-in-a-loop learning.
-- 8.4.4 Model bias and data poisoning.
-- 8.4.5 Technological support: Internet and cloud.
Week 12 Chapter 9: Research & Development in iTech

9.1 Intelligent infrastructure.
9.2 Foundation models: Academic and industry.
9.3 AI as a service: Industry.
9.4 Intelligent infrastructure: Industry.
9.5 Intelligent services: Industry.
9.6 Epilog
-- 9.6.1 Increasingly demand on the use of cloud XPU (i.e. GPU, TPU and IPU).
-- 9.6.2 AI at the edge: Use of AI without connecting to the Internet?
Week 13 Chapter 10: XYZ-To-Text and Text-To-XYZ

10.1 XYZ-To-Text.
-- 10.1.1 Everything observable instance in the nature could be converted to text.
-- 10.1.2 All observable instances are encoded and collected for training an AI model.
-- 10.1.3 XYZ = Measurement data, text, photo, voice or video.
-- 10.1.4 Internet-of-Thing == Internet-of-Text.
10.2 Text-To-XYZ.
-- 10.2.1 Text to text: Story writing.
-- 10.2.2 Text to speech.
-- 10.2.3 Text to image.
-- 10.2.4 Text to video.
10.3 Epilog
-- 10.5.1 Fake news.
-- 10.5.2 Fake images.
-- 10.5.3 Fake videos.
-- 10.5.4 Knowledge generation?
Week 14 Chapter 11: Personal Applications of iTech

11.1 Examples.
-- 11.1.1 Topic survey (informal survey).
-- 11.1.2 Document preparation (spelling check and correction, grammar check, paraphrasing).
-- 11.1.3 Search keywords recommendation (Google search engine and Bing).
-- 11.1.4 Document translation (Goolge Translate).
-- 11.1.5 Image/Photo editing.
-- 11.1.6 Voice command to PC/Phone.
-- 11.1.7 Driving, parking and route recommendation.
-- 11.1.8 Product recommendation.
11.2 Effective use of iTech.
-- 11.2.1 A user should be able to complete the task even if no iTech has been used.
-- 11.2.2 A user should be able to determine in which step which iTech is helpful.
-- 11.2.3 A user should be able to justify if the result is making sense.
-- 11.2.4 A user should be able to identify the limitation of the use of an iTech.
-- 11.2.5 A user should use an iTech as an assistant role but should not survive on the iTech.
Week 15 Chapter 12: Business & Industrial Applications of iTech

12.1 Administration.
12.2 Marketing.
12.3 Customer support.
12.4 Manufacturing.
12.5 Logistics.
Week 16 Chapter 13: Societal Issues of AI

13.1 AI safety: About 99.99% recognition rate.
13.3 AI ethic: Ethical use of AI systems. Something AI can do but we cannot let it do.
13.3 AI bias: All about the training dataset and the AI models.
13.4 Augmented reality 2.0: Reals and fakes mix-up.
13.5 Job replacement
-- 13.5.1 Operational (administrative and technical) staff?
-- 13.5.2 Middle/Top management staff?
13.6 Roles of human workers in the AI era: From using AI to serving AI?
-- 13.6.1 Robotic systems maintenance.
-- 13.6.2 Cloud systems maintenance.
-- 13.6.3 Data labeling/tagging.
-- 13.6.4 System testing and user experience testing.
Week 17 Project final report (Session I)
Week 18 Project final report (Session II)
Evaluation
Attendance (Discussions + Class Exercises): 30%
Assignments: 20%
Project: 50%
Textbook & other References
Nil
Teaching Aids & Teacher's Website
1. Lecture notes on the broad (Handwritten by John Sum).
2. Handouts distributed during lectures.
3. Images from Google.
4. Videos from YouTube (mainly documentaries, speeches, lectures and seminars).
5. Articles from magazines.
6. Papers from journals and conferences.
7. Technical reports from research labs.
8. Writings from your assignments, class exercises, discussions.
9. Group project reports
Office Hours
By appointment!
Sustainable Development Goals, SDGs
01.No Poverty   04.Quality Education   08.Decent Work and Economic Growth   09.Industry, Innovation and Infrastructure   17.Partnerships for the Goalsinclude experience courses:N
Please respect the intellectual property rights and use the materials legally.Please repsect gender equality.
Update Date, year/month/day:None Printed Date, year/month/day:2024 / 10 / 13
The second-hand book website:http://www.myub.com.tw/