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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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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
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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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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Video
Here's a paradox: as companies try to streamline their businesses by using artificial intelligence to make critical decisions, they may inadvertently make themselves less efficient. Business technologist Sylvain Duranton advocates for a "Human plus AI" approach -- using AI systems alongside humans, not instead of them -- and shares the specific formula companies can adopt to successfully employ AI while keeping humans in the loop.
- Keywords:
- Business enterprises -- Technological innovations Artificial intelligence
- Resource Type:
- Video
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Video
In 20 episodes, Jabril will teach you about Artificial Intelligence and Machine Learning! This course is based on a university-level curriculum. By the end of the course, you will be able to: * Define, differentiate, and provide examples of Artificial Intelligence and three types of Machine Learning: supervised, unsupervised, and reinforcement * Understand how different AI and ML approaches can be combined to create compelling applications such as natural language processing, robotics, recommender systems, and web search * Implement several types of AI to classify images, generate text from examples, play video games, and recommend content based on past preferences * Understand the causes of algorithmic bias and audit datasets for several of these causes
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Human-Computer Interaction Machine learning
- Resource Type:
- Video
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MOOC
In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini project. This course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence
- Resource Type:
- MOOC