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Video
The PolyU Academy for Interdisciplinary Research (PAIR) of The Hong Kong Polytechnic University (PolyU) today hosted its inaugural Public Forum for Research and Innovation. Titled “DeepSeek and Beyond”, the keynote speech was delivered by Prof. YANG Hongxia, Associate Dean (Global Engagement) of the PolyU Faculty of Computer and Mathematical Sciences and Professor of the Department of Computing, who highlighted the latest developments in artificial intelligence (AI). The event attracted over a thousand participants, including faculty members, students, alumni, and leaders from the innovation and technology sector, as well as academics and the public. Additionally, over 390,000 viewers tuned in through the live streaming platforms.
The Forum began with a welcoming speech delivered by Prof. CHEN Qingyan, Director of PAIR and Chair Professor of Building Thermal Science of the PolyU Department of Building Environment and Energy Engineering. This was followed by Prof. ZHANG Chenqi, Chair Professor of Artificial Intelligence of the PolyU Department of Data Science and Artificial Intelligence, and Director of the PolyU Shenzhen Research Institute introducing the speaker.
Prof. Zhang said, “The development of large models is at the core of competition in the AI wave. DeepSeek has demonstrated that high-performance AI models can be achieved using fewer and less advanced graphics processing units (GPUs), demonstrating that cutting-edge AI technology can be realised through the optimisation of algorithms.”
The large AI model developed by the mainland Chinese startup DeepSeek has garnered wide acclaim around the world for its low-cost, high-performance, and open-source framework, disrupting the traditional “computing power-first” logic of AI model training. At the Forum, Prof. Yang highlighted the potential of generative AI (GenAI), adding that it presents abundant opportunities for various sectors, including healthcare, finance, manufacturing, retail, media and fashion, and for applications in medical imaging analysis, fraud detection, predictive maintenance, retail inventory management, content creation, and design and marketing.
Prof. Yang also recounted the evolution of AI and shared her professional milestones with the audience, notably the development of the M6 large model, which trained a 10-trillion-parameters model using just 512 GPUs. Prof. Yang further elaborated on how her GenAI project, Co-GenAI, improves the accessibility of AI technology while minimising dependence on large-scale centralised computing resources, thereby transforming the trajectory of AI progress. This ground-breaking effort has positioned Hong Kong and the Mainland at the forefront of global advancement in GenAI.
Moderated by Prof. Zhang Chenqi, a panel discussion was also held, featuring esteemed panellists Prof. Yang Hongxia and Prof. LI Qing, Head and Chair Professor of Data Science of the PolyU Department of Computing, and Co-Director of the Research Centre for Digital Transformation of Tourism. The scholars discussed the opportunities and challenges that advancements in AI present for higher education and research. They also engaged in fruitful discussion with participants during the question-and-answer session. The topics included the application of AI in industry, the regulation of information, its impact on the employment environment and economic development, and the integration of AI technologies.
PolyU is committed to advancing AI education and research. In January 2025, the University established the Faculty of Computer and Mathematical Sciences with a vision to lead global advancements in digital transformation and AI through distinguished education, research, and knowledge transfer.
Event date: 11/03/2025
Speaker: Prof. YANG Hongxia
Hosted by: PolyU Academy for Interdisciplinary Research
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Video
Prof. Alex MIHAILIDIS, Associate Vice President of International Partnerships at the University of Toronto delivered the 19th PAIR Distinguished Lecture titled “The Future of Elder Care: Integrating Large Language Models” on 26 April 2024. The lecture attracted about 100 participants to join in person and captivated an online viewing audience of over 14,100 from different countries and regions to watch the live broadcast on multiple social media platforms, including Bilibili, WeChat, Weibo, YouTube, etc.
The lecture commenced with a welcome speech and speaker introduction by Prof. ZHENG Yongping, Director of the Research Institute for Smart Ageing (RISA), followed by an engaging presentation by Prof. Mihailidis. The content materials used in Prof. Mihailidis’s presentation were generated by ChatGPT, while he added the narrative.
In his presentation, Prof. Mihailidis first played several videos created by artificial intelligence (AI) to introduce what LLM is, how it can support elderly care services, some drawbacks of using LLM, and its future development. He supplemented that LLMs are advanced AI systems capable of understanding and generating human-like texts, as well as visual outputs and models that can respond to or interact with users. Next, Prof. Mihailidis outlined the specific benefits of using LLMs in elderly care, including the support tools and resources they offer to caregivers. He then delved into the ethical considerations and challenges in LLM design, such as privacy concerns, the risk of over-dependence on technology, and the barriers to technology adoption by older adults and their caregivers. To conclude, Prof. Mihailidis emphasised the role of empathetic and emotionally-intuitive AI in enhancing the quality of life for the elderly and supporting the caregiving ecosystem.
Following the presentation was a lively and insightful question-and-answer session moderated by Ir Prof. Zheng. The audience had a fruitful discussion with Prof. Mihailidis. A souvenir was presented by Prof. CHEN Qingyan, Director of PAIR, to thank Prof. Mihailidis for his excellent presentation and support to PAIR.
Event date: 26/04/2024
Speaker: Prof. Alex MIHAILIDIS (University of Toronto)
Hosted by: PolyU Academy for Interdisciplinary Research
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MOOC
Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.
This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand.
Accordingly, in this course, you will learn:
- The major steps involved in tackling a data science problem.
- The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.
- How data scientists think!
- Course related:
- LGT6202: Stochastic Models and Decision under Uncertainty, LGT6802 Guided Study in Logistics II, LGT6803: Guided Study in Logistics III, and LGT6801 Guided Study in Logistics I
- Subjects:
- Business Information Technology and Computing, Data Science and Artificial Intelligence
- Keywords:
- Data mining Problem solving Electronic data processing
- Resource Type:
- MOOC
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Others
Agent based modeling focuses on the individual active components of a system. This is in contrast to both the more abstract system dynamics approach, and the process-focused discrete event method. With agent based modeling, active entities, known as agents, must be identified and their behavior defined. They may be people, households, vehicles, equipment, products, or companies, whatever is relevant to the system. Connections between them are established, environmental variables set, and simulations run. The global dynamics of the system then emerge from the interactions of the many individual behaviors. AnyLogic combines professional discrete event, system dynamics, and agent based modeling in one platform for efficient, no compromise results. In our white paper, Multimethod Simulation Modeling for Business Applications, we investigate these three main simulation modeling approaches and construct a multimethod model example to illustrate the advantages of multimethod simulation modeling. Read the white paper and see why hybrid models are always a better choice!
- Course related:
- CE631 Simulation and IT Applications in Construction
- Subjects:
- Computing, Data Science and Artificial Intelligence and Business Information Technology
- Keywords:
- Multiagent systems Computer simulation System analysis -- Data processing
- Resource Type:
- Others
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e-book
Business Mathematics was written to meet the needs of a twenty-first century student. It takes a systematic approach to helping students learn how to think and centers on a structured process termed the PUPP Model (Plan, Understand, Perform, and Present). This process is found throughout the text and in every guided example to help students develop a step-by-step problem-solving approach. This textbook simplifies and integrates annuity types and variable calculations, utilizes relevant algebraic symbols, and is integrated with the Texas Instruments BAII+ calculator. It also contains structured exercises, annotated and detailed formulas, and relevant personal and professional applications in discussion, guided examples, case studies, and even homework questions.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Textbooks Business mathematics
- Resource Type:
- e-book
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e-book
This second edition of Database Design book covers the concepts used in database systems and the database design process. Topics include: The history of databases Characteristics and benefits of databases Data models Data modelling Classification of database management systems Integrity rules and constraints Functional dependencies Normalization Database development process New to this edition are more examples, highlighted and defined key terms, both throughout and at the end of each chapter, and end-of-chapter review exercises. Two new chapters have been added on SQL, along with appendices that include a data model example, sample ERD exercises and SQL lab with solutions.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Database design Textbooks
- Resource Type:
- e-book
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e-book
Squeak is a modern open-source development environment for the classic Smalltalk-80 programming language. Despite being the first purely object-oriented language and environment, Smalltalk is in many ways still far ahead of its successors in promoting a vision of an environment where everything is an object, and anything can change at run-time. Squeak by Example, intended for both students and developers, will guide you gently through the Squeak language and environment by means of a series of examples and exercises. The book helps you get started with A Quick Tour of Squeak and guides you through A First Application. The Smalltalk language is introduced in three chapters on Syntax in a Nutshell, Understanding Message Syntax and The Smalltalk Object Model. Development with Squeak is covered in The Squeak Programming Environment and SUnit. Several of the key classes are presented in chapters on Basic Classes, Collections, Streams and Morphic. The first edition of the book concludes with chapters on Classes and Metaclasses and Frequently Asked Questions.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Textbooks Smalltalk-80 (Computer program language) Squeak Multimedia systems
- Resource Type:
- e-book
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e-book
Think Bayes is an introduction to Bayesian statistics using computational methods. The premise of this book, and the other books in the Think X series, is that if you know how to program, you can use that skill to learn other topics. Most books on Bayesian statistics use mathematical notation and present ideas in terms of mathematical concepts like calculus. This book uses Python code instead of math, and discrete approximations instead of continuous mathematics. As a result, what would be an integral in a math book becomes a summation, and most operations on probability distributions are simple loops. I think this presentation is easier to understand, at least for people with programming skills. It is also more general, because when we make modeling decisions, we can choose the most appropriate model without worrying too much about whether the model lends itself to conventional analysis. Also, it provides a smooth development path from simple examples to real-world problems.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Mathematics and Statistics
- Keywords:
- Python (Computer program language) Textbooks Bayesian statistical decision theory
- Resource Type:
- e-book
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e-book
We set out to design an introductory course governed by four themes: Give students a good idea of what a career in MIS looks like by doing MIS. Enhance the professionalism of deliverables by teaching design and usability concepts. Promote creativity by assigning projects that demand it. Teach students about cloud computing by having them do cloud computing. Students in an introductory Management Information Systems (MIS) course often ask what a career in MIS looks like. Lacking a clear vision, they make their own assumptions. Often they assume the career involves programming with little human interaction. That MIS is a technical field could not be further from the truth. MIS job descriptions typically require candidates to be able to collaborate, communicate, analyze needs and gather requirements. They also list the need for excellent written and communication skills. In other words, MIS workers are constantly interacting with other people both inside and outside the organization. They are coming up with creative solutions to business problems. This course is designed to help students get a feel for what a career in MIS would be like. Our students report that they learn more about information systems from their internships than from their IS courses. Consequently, we designed a course that looks very much like an internship—an introduction to the field followed by a substantial project. Chapter 1 begins by introducing the information systems landscape. Here we discuss all the usual suspects: the information systems triangle, the systems development life cycle, transaction systems (ERP, SCM, CRM), collaboration systems, and business intelligence systems. Other aspects of the landscape such as usability, outsourcing, database concepts and so forth are introduced throughout chapter in Chapter 2 where they fit in naturally with the flow of the project. Chapter 2 is the substantial project which runs over a number of chapters. Over the course of the semester, students plan, build, and develop a proposal for an iPhone application. They develop a very realistic mockup. They also build a website to help market and support the app. Students are engaged because the project is fun and feels real. However, they are simultaneously learning business concepts and MIS skills. Prior to the existence of this course, we were only able to give such an interesting project at the senior level. Now, even as freshmen, students have a real experience of MIS in operation. A by product of creating an engaging course is increased enrollment in the MIS major. Even students who have never heard of MIS become excited about the major and either switch majors or add it as a double major or minor. Many other books have students study tools and then do a case. By contrast, most of this book is a case. Much like the real world, we introduce tools when needed, and only to the extent needed, to get at each part of the case.
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Others
GitHub is a development platform inspired by the way you work. From open source to business, you can host and review code, manage projects, and build software alongside 50 million developers. GitHub brings teams together to work through problems, move ideas forward, and learn from each other along the way. You can write better code, manage your chaos, and find the right tools in GitHub.
- Course related:
- EIE6811 Guided Study in Electronic and Information Engineering I/II/III and EE4006A Individual Project
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Computer software -- Development Software engineering Git (Computer file)
- Resource Type:
- Others
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