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Video
The seminar began with a warm welcome by Prof. ZHANG Weixiong, Associate Director of PAIR, followed by a brief introduction of the speaker by Prof. ZHANG Chengqi, Chair Professor of Artificial Intelligence. Prof. Liu kick-started his presentation by outlining the key milestones in the evolution of robotics, and pointed out that human-centred intelligent robots should be able to co-exist, cooperate and collaborate with humans. He stated that robotics is a truly interdisciplinary field that combines engineering, science and humanities. Next, through a series of case studies, Prof. Liu examined how intelligent robots have been designed to work alongside humans in various applications, including civil infrastructure maintenance, construction, and manufacturing. He then discussed the dynamics of collaboration between humans and robots, and examined issues such as trust, computational modelling, physical and cognitive workload, brain-robot interface and human-centred design. By reflecting on the lessons learnt from these case studies, Prof. Liu highlighted both successes and challenges. At the end of his presentation, Prof. Liu emphasised that human-robot teaming is an interdisciplinary field. He also pointed out some areas for further development in the field, highlighting the many opportunities in robotics.
Event date: 10/10/2024
Speaker: Prof. LIU Dikai
Hosted by: PolyU Academy for Interdisciplinary Research
- Subjects:
- Computing, Data Science and Artificial Intelligence and Mechanical Engineering
- Keywords:
- Human-robot interaction Artificial intelligence Robotics
- Resource Type:
- Video
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Video
The seminar commenced with a welcome speech and speaker introduction by Prof. CHEN Qingyan, Director of the PolyU Academy for Interdisciplinary Research (PAIR). In his presentation, Prof. Cao stated that urban environment engineering seeks to apply system engineering to solve complex urban problems. He highlighted that interdisciplinary research that combines scientific and mathematical approaches is crucial for understanding the mechanisms and laws concerning the complex interactions between humans and the ecological environment. Prof. Cao emphasised that the modelling of urban pollution involves a mix of techniques, including remote sensing, big data, computational simulation, the Internet of Things, artificial intelligence, digital twins, etc. He gave various project examples to explain how different techniques can be used for scientific monitoring, fast prediction, assessment and regulation of urban pollution. To conclude, Prof. Cao pointed out that advancements in urban environment modelling and intelligent control can build the scientific foundation for sustainable urban development.
Event date: 22/05/2024
Speaker: Prof. CAO Shi-Jie
Hosted by: PolyU Academy for Interdisciplinary Research
- Subjects:
- Environmental Engineering
- Keywords:
- Urban ecology (Sociology) Urbanization -- Environmental aspects Urban pollution
- Resource Type:
- Video
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PDF Video Website
Creativity is important in nearly every facet of life. Advances in neuro-science, computing and psychology, along with developments in other domains and cross-disciplinary areas have resulted in ever increasing understanding of creativity. This module will explore some advanced approaches to creativity such as the use of analogy and metaphor, various thinking styles and the role of artificial intelligence. A framework called the creativity diamond is used to guide the selection of approach to creativity relevant to your project or activity.
- Keywords:
- Creative ability Analogy Creative thinking Metaphor Artificial intelligence
- Resource Type:
- PDF, Video, and Website
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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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Video
This talk will survey the intersection of artificial intelligence (AI), ethics, and the Humanities in the UK. It integrates insights from bibliometric analyses, interviews with various stakeholders, and reviews of existing research infrastructure and policies. The talk examines the current state of AI ethics research in the UK, identifying the contributions of the Arts and Humanities, the obstacles researchers face, and the potential impacts of their work. It also considers the international research environment and strategic investments made by other countries in AI and ethics, drawing comparisons with the UK's approach. Opportunities and threats are identified within the context of academia, public perception, and commerce, including the impacts of AI on diverse populations and industries. The talk will conclude by considering how the situation in the UK may compare with that in Hong Kong.
Event date: 30/04/2024
Speaker: Prof. Tony MCENERY (Lancaster University and Shanghai International Studies University)
Hosted by: Faculty of Humanities
- Subjects:
- Computing, Data Science and Artificial Intelligence and Philosophy
- Keywords:
- Artificial intelligence -- Moral ethical aspects Artificial intelligence -- Philosophy Great Britain
- Resource Type:
- Video
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Video
People have been grappling with the question of artificial creativity -- alongside the question of artificial intelligence -- for over 170 years. For instance, could we program machines to create high quality original music? And if we do, is it the machine or the programmer that exhibits creativity? Gil Weinberg investigates this creative conundrum.
- Keywords:
- Creative ability Artificial intelligence
- Resource Type:
- Video
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Video
In this lecture, Prof. Sifakis will discuss the relevance of existing criteria for comparing human and machine intelligence and show some notable analogies and differences between scientific knowledge and that produced by neural networks. Emphasising that autonomy is an important step towards Artificial General Intelligence (AGI), he will present a characterisation of autonomous systems, and showing key differences with mental systems equipped with common sense knowledge and reasoning, and advocate challenging work directions, including the development of a new foundation for systems engineering and scientific knowledge, and the joint exploration of physical and mental phenomena that embody human intelligence.
Event date: 3/3/2023
Speaker: Prof. Joseph Sifakis
Hosted by: PolyU Academy for Interdisciplinary Research
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence
- Resource Type:
- Video
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Video
EDC is organising a series of Sharing Sessions that present departmental project deliverables and innovations in Technology Enhanced Learning, promoting sustainable and impactful practices that resonate across PolyU and beyond, and funded by PolyU’s Quality Incentive Scheme on Online Teaching, Stage I. This session proudly presents three departments:
AP: Artificial Intelligence by Dr Dennis Leung
CBS: Large-class e-learning applications: Japanese teaching and L2L activities by Dr Jack Chun
ELC: Effective class teaching with apps by Mr Adam Forrester
Event Date: 14/12/2022
Facilitator(s): Mark, Kai Pan
- Subjects:
- Good Practices
- Keywords:
- Internet in education Motivation in education Educational technology College teaching Web-based instruction
- Resource Type:
- Video
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Courseware
This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
- Course related:
- COMP1001 Problem Solving Methodology in Information Technology, COMP3011 Design and Analysis of Algorithms, COMP2011 Data Structures, and COMP4434 Artificial Intelligence
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Computer programming Computer science Artificial intelligence Python (Computer program language)
- Resource Type:
- Courseware
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MOOC
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.
- Course related:
- AAE5103 Artificial Intelligence in Aviation Industry
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
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