Intelligent Technology Management (2025 SPRING)

This course is an elective course particularly designed for NCHU EMBA students. Students are expected to attend all lectures and complete all courseworks including bonus assignments and course project. Attendance will not be accounted for the final score but absence without proper reason will be.

Professor John Sum is a strict person, sometimes a monster. His expectation on the behavior and the performance of a student is stringent. It is simply because John Sum has been teaching in the area of intellient technology for more than three decades. Materials in his mind are abundant. Only some of them are extracted and complied as teaching materials.

Prerequisites

1. Students should have elementary level of English and have no problem in reading English materials.
2. Skillful in the use of word processing software, such as Word and Latex, for report writing and presentation.
3. Skillful in searching information over the Internet.
4. Knowledge in one of the following subjects: Principles of Computing, Computer Literacy, Introduction to Information Systems, Introduction to Computer Science, Introduction to Information Technologies or other related subjects. (To refresh the concepts in 'Introduction to Computer Science', here is a link to the course 'Introduction to Computer Science' which was delivered by me in the 2022 Fall term for the BBA students in our management school.)
5. Able to complete a coursework report as compared with a jorunal publication.

Course Outline

1. Introduction to Intelligent Technology.
   • Notes (20250219) [JS]
     • Fact (Axiom): We are all intelligent. Living organisms are all intelligent.
     • Meaning of intelligence: Intelligence in AI and intelligence in CIA.
     • Intelligence vs smart: Smart material, smart home and smart city.
     • Question: What is the difference between intelligence and smart?
     • Question: How do you justify your intelligence?
     • Question: How do you justify the intelligence of an AI system?
     • Question: What does multimodal mean?
     • Question: What does human-in-a-loop mean?
   • Piaget Theory of Cognitive Development.
     • Assimilation (interactive): An action to the environment.
     • Accomodation (passive): Make change of my mind based on the reponses (resp. observations) from the environment.
     • Could be a reference model for the cognitive level of an AI system.
     • Question: In accordance with Piaget's cognitive theory, which cognitive stage should be appropriately described the contemporary AI systems? (JS: Senori-Motor intelligence stage to pre-operational stage.)
     • Question: Have you achieved the formal operational stage? (JS: Not everyone.)
   • Turing test: A test to justify if a machine is intelligent.
     • Question: Can AlphaGO pass the Turing test?
     • Question: Can ChatGPT pass the Turing test?
     • Reverse Turing test: A test to justfy if a human is intelligent.
   • Key AI model advancements for the present applications.
     • AlexNet (2012): Object recognition and auto-driving.
       • Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton (2012), ImageNet Classification with Deep Convolutional Neural Networks, Advances in Neural Information Processing Systems 25.
     • Generative Adversarial Network (2014): Image generation.
       • Goodfellow, I. et al. (2014). Generative adversarial networks. arXiv preprint, arXiv:1406.2661.
       • Goodfellow, I. et al. (2020). Generative adversarial networks. Communications of the ACM, 63(11), 139-144.
       • Radford, A., Metz, L., & Chintala, S. (2015). Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint, arXiv:1511.06434.
     • Transformer (2017): Natural language processing (NLP) and large language model (LLM).
       • Vaswani, A. (2017). Attention is all you need. Advances in Neural Information Processing Systems.
       • Generative pre-trained transformer (GPT).
       • Open AI (2023). GPT-4 Technical Report.
     • OpenAI o1 (2024): A language model capturing problem solving procedure.
   • Supporting technologies.
     • Communication technology (4G, 5G, 6G and so on).
     • Internet technology.
     • Graphical processing unit (GPU), central processing unit (CPU).
     • XPU: Specialized designed processing unit like neural processing unit (NPU), intelligent processing unit (IPU), tensor processing unit (TPU) and data processing unit (DPU).
     • Smartphone: iPhone and Android phone.
     • Computer: Notebook computer (presonal use), desktop computer (personal use), workstation (profesional use), server (powerful machine).
     • Cloud and edge (not yet).
     • Human-Computer interface (HCI) and brain-computer interface (BCI).
       • Text-Command -> GUI-Command -> Voice-Command -> (Voice + Hand Gesture)-Command -> (Voice + Hand Gesture + Brain Signal)-Command.
       • Text-Output -> Graphical Output -> (Graphical + Voice)-Output -> ???
   • Tools with AI systems embedded: Amazon Alexa, Apple Siri, Google Gemini, Google Search, Google Translate, Microsoft Bing, Microsoft Copilot.
   • Notes.
     • Some (so called) AI tools for the manufacturing sector are not intelligent. Will explain this in the later lectures.
     • The results generated by those AI tools might include incomplete, non-logical and even erroneous information.
     • A recent fact! It is from an email received on September 28, 2024, from PLOS. Some reviewers used LLM to review a journal paper and submit a LLM generated review report to the editor. As you might know, a journal editor's decision on accpetance or rejection a paper largely relies on the comments received. Therefore, the LLM generated comments can influence the editor's decision. In other words, LLM plays a part in justifying the quality of a research paper.
     • Question: If Google Gemini or ChatGPT is used to determine the PASS/FAIL grade for your report, will you accept that?
     • Open Problem: (1) If a user is knowledgeable in AI and good in presentation, why the user has to use an LLM to generate a survey report? (2)If a user has no any knowledge on AI, how the user is able to validate the quality of the contents in the LLM generated survey report?
2. Introducing Generative AI.
   • English large language model (LLM): OpenAI ChatGPT, Google Bard/Gemini, Microsoft Copilot.
   • Chinese LLMs: Baidu Ernie, Tencent Hunyuan, BAAI WuDao.
   • Many LLMs have been developing in many countries for their mother languages, such as Japanese and Vietnamese.
   • Offline LLM models (Edge AI): LLM services without Internet connection.
   • Wikipedia, Factor analysis: A generative model for statistical analysis in social science research.
   • Reasoning models (towarads agentic AI): ChatGPT o1, ChatGPT o3, DeepSeek R1.
     • vinayakh, How Reasoning Models are transforming Logical AI thinking, Feb 04, 2025.
   • TechEmergent (2023), 60 best generative AI companies and startups in 2023.
   • Midjourney: A text-to-image generator.
     • Question: What is(are) the possible application(s) of text-to-image generation?
   • OpenAI GPT-4o, from Wikipedia. From text-to-text -> voice-to-voice. A report.
   • OpenAI o1, from Wikipedia. Reasoning + Text generation.
     • Question: Are you smarter than OpenAI o1?
     • Question: Could you be smarter than the future OpenAI o1 in the future?
     • Question: What does 'O' stand for? Orion?
   • Interface: text/voice/image/video <=> text/voice/image/video.
   • Training dataset (i.e huge dataset) preparation (equi. collection of sea-size data).
   • Latent Space, The 2025 AI engineer reading list, Dec 28, 2024.
3. Evolution of Technology (2023 version). [JS]
   • Stages.
     • Industrial revolution.
     • Automation and electrification.
     • Information technologies.
     • Intelligent technologies.
   • Benefit and threads.
   • Supplementary: Processor Achitectures.
     • AMD Zen architecture. First released: 2017. (Wikipedia).
     • ARM Holding. ARM architecture (equi. advanced RISC machine or Acorn RISC machine). (Wikipedia).
     • Intel, Introduction to Intel® Architecture, Feburary 9, 2024.
     • Nvidia processor architectures.
     • x86 Ecosystem Advisory Group (Oct 15, 2024).
   • Question: What technologies have been developed to let you enjoy the services provided by your smartphone? Note that, many of them are not intelligent but disruptive.
   • Question: Telecommunication technology is one group of them. Telecom technology, 4G or 5G, refers to a collection of technologies supporting voice and data services. Could you name a few of these technologies?
4. Technologies for Information/Intelligent Infrastructue.
   • Telecommucation technology.
     • Telegraph (resp. telephone) is for data (resp. voice) communication.
     • Wired versus wireless.
     • Today telecom network: Data and voice communication network.
     • List of wireless tech generations.
     • Brief on telecommunication technology (20231127). [JS]
   • Internet: Data communication network.
   • Satellite constellation. Satellite internet constellation.
   • Global Internet usage report, Janurary 2023 edition.
   • Cloud services: supported by a network of computers and the Internet.
   • IEEE The spirit of innovation (on communication).
   • Intelligent infrastructure = Information infrastructure + AI services.
   • Web 1.0 => Web 2.0 => Web 3.0 (Information infrastructure + AI services + Blockchains).
5. Intelligent Products and Services. [JS]
   • Key technologies; Working principles; My daily live and daily work. Go beyond.
   • OpenAI AI Pin; Amazon Echo; Google Home.
   • The business of intelligent services.
   • Metaverse: Second Life; Decentraland.
     • Market forecast by Statista;
     • Market size and growth (2023) by Influencer Marketing Hub.
   • Question: How does a tech firm make profit from an intelligent technology?
6. Essentials of Intelligent Technology. [JS]
   • Technologies for language understanding.
   • Technologies for image recognition.
   • Core AI/ML technologies.
   • Federated learning (Collabrative/Decentralized/Distributed learning).
     • Speed-up learning.
     • Data privacy protection.
     • AI model specified.
7. Intelligent Services Development. [JS]
   • Intelligent technology development (hard) = AI model development = Foundation model development.
     • Theoretical analysis.
     • Empirical analysis.
     • Software/Hardware implementation.
     • Hardware design, i.e. processor design.
   • Intelligent service development for fun.
   • Intelligent service development for profit = Application system development.
8. Intelligent Technology for Manufacturing.
   • Manufacturing execution systems (beware of the terminology).
     • History of the MESA models, from Manufacturing Enterprise Solutions Association (MESA) International.
     • Manufacturing execution systems, from SAP.
     • Manufacturing execution systems, from Autodesk.
     • Production and plant optimization, from Siemens.
   • Digitial twin.
     • What is digital twin? from Autodesk.
     • Azure Digital Twins demo|Creating replicas of real-world environments.
     • Ericsson's 5G Digital Twin Simulation.
   • Don't Expect Too Much.
     • BMW Factory - Integration of A.I. in the Production Line.
     • Artificial Intelligence in the Automotive Industry, from Glorious insight.
     • AI and manufacturing, from IESE Business School.
   • AI + Digital Twin.
     • With digital twin, a light-off factory can now be visualized and controlled (remotely) from its digital twin.
     • With AI, the light-off factory could be made to be an autonomous system.
     • Predicting and visualizing the coming behavior of a system.
     • Note: A digital twin can simply be a bunch of data showing the current status of a system.
   • AI algorithms for solving optimization problems are not really intelligence.
   • Questions.
     • What intelligent technologies have been applied?
     • How does AI help in solving the optimization problems in manufacturing?
     • How does AI help in new product design?
   • AI in Manufacturing: China Experiences. (3+ hours)
   • Practical AI use cases for manufacturing, by Siemen and Maya HTT (54 minutes).
9. Advanced Topics on Intelligent Technology.
   • Perceptron and Human Cognition: Frank Rosenblatt Perspectives. [JS]
   • Linking Mind and Brain: Steve Grossberg SEP Lifetime Achievement Award Lecture (2015).
     • Grossberg, S. (2019). A half century of progress toward a unified neural theory of mind and brain with applications to autonomous adaptive agents and mental disorders. Artificial Intelligence in the Age of Neural Networks and Brain Computing, 31-51.
     • Grossberg, S. (2021). Toward autonomous adaptive intelligence: Building upon neural models of how brains make minds. IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol.51(1), 51-75.
   • AI safety, Job replacement, Legal issues, AI Bias
     • Oscar Schwartz, Untold history of AI: Algorithmic bias was born in 1980s, IEEE Specturm, April 15, 2019.
     • Amazon scraps secret artificial intelligence recuriting engine that showed biases against women.
   • Fake AI: The Mechanical Turk, a chess master hidding inside the machine.
   • Fake video.
     • Barack Obama speech.
     • It's Getting Harder to Spot a Deep Fake Video.
   • Three laws of robotics, by Issaac Asimov in 1942.
   • Taiwan Computing Cloud (TWCC); Taiwan Web Service (TWS).
   • John Sum, Benefits and threads of intelligent technology, unpublished manuscript, November 2021. [JS]

Project (Individual or Group)

Case Study

1. Describe what are the usages of the tool? The content should be based on your personal experience.
2. Describe the problem(s) you have encountered when you are using the tool. You need to ensure that the problem(s) is(are) due to your incapability.
3. Describe how you overcome the problem(s).
4. What technologies (including both AI and non-AI) have been applied in the tool?
5. (*) Explain why the problem(s) exists (exist).

Topic Survey

Others

Submissions

1. Submit a written progress report and your presentation slides before Week 9 and give an oral presentation of the written report on Week 9.
2. Submit a final report and your presesntation slides before Week 18 and give an oral presentation of the final report on Week 18.

• Progress report.
  • Email heading: EMBA2025_ITM_Progress_Report_5111027804
  • Filename (written report): EMBA2025_ITM_Progress_Report_5111027804.docx
  • Filename (slides): EMBA2025_ITM_Progress_Report_Slides_5111027804.pptx
• Final report.
  • Email heading: EMBA2025_ITM_Final_Report_5111027804
  • Filename (written report): EMBA2025_ITM_Final_Report_5111027804.docx
  • Filename (slides): EMBA2025_ITM_Final_Report_Slides_5111027804.pptx

Project Assessment

Overall Assessment

• Progess report [40]; Final report [60]; Bonus Assignment [20].
• Total = min{100, PR + FR + A}.

Supplementary Notes/ Lecture Diaries

• 20250307 lecture diary.

Bonus Assignments (Individual)

Use of AI Tools

AI tools, like ChatGPT, Google Gemini and DeepSeek, have to be used with extrememly careful. Some AI tools might give incomplete information in response to certain questions. Moreover, Google Bard does not provide any reference for the content generated. Students have to be aware of these drawbacks.

ChatGPT, Google Gemini, DeepSeek and other AI text generators are very good in paraphrasing. Using these tools to paraphrase your assignments and project reports are highly encouraged.

You are allowed to use AI tools, like ChatGPT, Google Gemini and DeepSeek, for your assignments and project report. In the first step, you have to complete your assignment or the project report based upon your own writing. In the second step, you could use those AI tools to paraphrase the contents of your assignments and reports.

WARNING: For any part of the content (respectively, any word) you have put in an assignment or report, I will ask for your reason and explanation why this part of content (respectively, the specific word) has to be added. If you fail to do so, your assignment (respectively, group project) score will be zero. Nevertheless, your assignment (respectively, group project) score will be zero if you fail to give the source for any part of the content you have added in your assignment (respectively, group project).