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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
- Subjects:
- Social Work and Human Services and Computing
- Keywords:
- Older people -- Care Natural language generation (Computer science) Artificial intelligence Technological innovations
- Resource Type:
- Video
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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:
- Philosophy and Computing
- Keywords:
- Artificial intelligence -- Philosophy Great Britain Artificial intelligence -- Moral ethical aspects
- Resource Type:
- Video
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Others
OER4AI features a collection of public resources on AI, with categorization of different AI topics. With this OER portal, teachers can use its teaching materials, while students can access it and attempt its exercises. We aim at:
• Providing materials for students to gain hands-on experience;
• Collecting the public resources on AI;
• Giving teachers access to this website through PolyU OER Portal.
- Subjects:
- Computing
- Keywords:
- Machine learning Machine learning -- Study teaching Artificial intelligence Artificial intelligence -- Study teaching
- Resource Type:
- Others
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Video
PAIR distinguished lecture series: an overview of high performance computing and future requirements
In this talk, we examine how high performance computing has changed over the last ten years and look toward the future in terms of trends. These changes have had and will continue to impact our numerical scientific software significantly. A new generation of software libraries and algorithms are needed for the effective and reliable use of (wide area) dynamic, distributed, and parallel environments. Some of the software and algorithm challenges have already been encountered, such as the management of communication and memory hierarchies through a combination of compile-time and run-time techniques, but the increased scale of computation, depth of memory hierarchies, range of latencies, and increased run-time environment variability will make these problems much harder.
Event date: 6/12/2023
Speaker: Prof. Jack Dongarra
Hosted by: PolyU Academy for Interdisciplinary Research
- Subjects:
- Computing
- Keywords:
- High performance computing
- Resource Type:
- Video
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Others
Audacity is an easy-to-use, multi-track audio editor and recorder for Windows, macOS, GNU/Linux and other operating systems. Audacity is free, open source software
- Subjects:
- Computing
- Keywords:
- Audacity (Computer file) Digital audio editors
- Resource Type:
- Others
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Others
Python can be easy to pick up whether you're a first time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way writing programs with Python!
- Subjects:
- Computing
- Keywords:
- Computer programming Python (Computer program language) Information visualization Computer science
- Resource Type:
- Others
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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:
- COMP3011 Design and Analysis of Algorithms, COMP1001 Problem Solving Methodology in Information Technology, COMP4434 Artificial Intelligence, and COMP2011 Data Structures
- Subjects:
- Human-Computer Interaction and Computing
- Keywords:
- Computer programming Computer science Python (Computer program language) Artificial intelligence
- Resource Type:
- Courseware
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Others
Symbol Table is an important data structure created and maintained by the compiler in order to keep track of semantics of variables i.e. it stores information about the scope and binding information about names, information about instances of various entities such as variable and function names, classes, objects, etc.
- Course related:
- COMP3438 System Programming
- Subjects:
- Computing
- Keywords:
- Compilers (Computer programs)
- Resource Type:
- Others
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Others
本站由清华大学信息化技术中心支持创办，由清华大学 TUNA 协会运行维护。 清华大学 TUNA 协会，全名清华大学学生网络与开源软件协会，是由清华大学热爱网络技术和开源软件的极客组成的学生技术社团。
- Subjects:
- Computing
- Keywords:
- Open source software Computer software -- Development
- Resource Type:
- Others
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Others
Learn to code, design, and more—all on your own time
- Subjects:
- Computing
- Keywords:
- Coding theory Mobile apps Computer programming
- Resource Type:
- Others
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Video
In this series we learn how to make an RPG from scratch using the Unity engine.
- Course related:
- COMP4122 Game Design and Development
- Subjects:
- Computing
- Keywords:
- Computer games -- Programming Unity (Electronic resource) Computer games -- Design
- Resource Type:
- Video
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Others
In these comprehensive video courses, created by Santiago Basulto, you will learn the whole process of data analysis. You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn, Additionally, we've included a thorough Jupyter Notebook course, and a quick Python reference to refresh your programming skills.
- Course related:
- AMA1600 Fundamentals of AI and Data Analytics and AMA1751 Linear Algebra
- Subjects:
- Mathematics and Statistics and Computing
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Others
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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
- Keywords:
- Machine learning Artificial intelligence
- Resource Type:
- MOOC
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Others
This project was started in 2007 as a Google Summer of Code project by David Cournapeau. Later that year, Matthieu Brucher started work on this project as part of his thesis. In 2010 Fabian Pedregosa, Gael Varoquaux, Alexandre Gramfort and Vincent Michel of INRIA took leadership of the project and made the first public release, February the 1st 2010. Since then, several releases have appeared following a ~ 3-month cycle, and a thriving international community has been leading the development.
- Course related:
- EIE6207 Theoretical Fundamental and Engineering Approaches for Intelligent Signal and Information Processing
- Subjects:
- Computing
- Keywords:
- Machine learning Python (Computer program language)
- Resource Type:
- Others
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Others
All resources and notes from the Complete Web Developer in 2022: Zero to Mastery course
- Course related:
- COMP3421 Web Application Design and Development, LGT3109 Introduction to Coding for Business with Python, COMP3211 Software Engineering, and COMP1001 Problem Solving Methodology in Information Technology
- Subjects:
- Computing
- Keywords:
- Web sites -- Design Web site development
- Resource Type:
- Others
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Others
Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access GPUs at no cost to you and a huge repository of community published data & code. Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 50,000 public datasets and 400,000 public notebooks to conquer any analysis in no time.
- Subjects:
- Computing
- Keywords:
- Machine learning Artificial intelligence Big data
- Resource Type:
- Others
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Others
菜鸟教程的 Slogan 为：学的不仅是技术，更是梦想！我们相信：再牛逼的梦想也抵不住傻逼似的坚持！我们坚持一件事情，并不是因为这样做了会有效果，而是坚信，这样做是对的。本站域名为 runoob.com, runoob 为 Running Noob 的缩写，意为：奔跑的菜鸟。本站包括了HTML、CSS、Javascript、PHP、C、Python等各种基础编程教程。同时本站中也提供了大量的在线实例，通过实例，您可以更好地学习如何建站。本站致力于推广各种编程语言技术，所有资源是完全免费的，并且会根据当前互联网的变化实时更新本站内容。
- Subjects:
- Computing
- Keywords:
- Programming languages (Electronic computers) Computer programming
- Resource Type:
- Others
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Video
This channel walks you through the entire process of learning to code in Python; all the way from basics to advanced machine learning and deep learning. The primary emphasis will be on image processing and other relevant functionality. Why did I create this channel? To help you (students and researchers) gain a new skill and succeed in your respective fields.
You may think coding is hard and that it's not your cup of tea, but Python made it easy to code even advanced algorithms. In addition, coding will make you self sufficient, it will teach you how to think, it improves your collaborative skills and it can take your career to new heights. Therefore, if you want to stay ahead of your peers and relevant in your field, overcome your fears and start coding!
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Video
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Video
Machine learning can deliver unprecedented performance. Its application domain has expanded into safety-critical cyber-physical systems such as UAVs and self-driver cars. However, the safety assurance of vehicular control has two conditions: 1) an analytical model of system behaviors such as provable stability, and 2) the software safety certification process (e.g., DO 178C) requires that the software be simple enough so that software safety can be validated by a combination of model checking and near exhaustive testing. Although ML software, as is, does not meet these two safety requirements, the real-time physics model supervised ML architecture holds the promise to 1) meet the two safety requirements and 2) enable ML software to safely improve control performance and safely learn from its experience in real-time. This talk will review the structure of the proposed architecture and some methods to embed physics into ML-enabled CPS control.
Event Date: 12/05/2022
Speaker: Prof. Lui Sha (University of Illinois Urbana-Champaign)
Hosted by: Graduate School
- Subjects:
- Aeronautical and Aviation Engineering and Computing
- Keywords:
- Machine learning Vehicles Remotely piloted Computer software -- Reliability Drone aircraft
- Resource Type:
- Video
-
Video
An online lecture on the topic of "Computer Software Challenges for Aerospace Missions".This lecture of “Science World: Exploring Space to Benefit Mankind” Education Programme in the 2021/22 school year for secondary students, which aims to cultivate the interest of local youth in space science and elevate their enthusiasm for participating in the development of space technology.
- Subjects:
- Aeronautical and Aviation Engineering and Computing
- Keywords:
- Aeronautics -- Data processing Computer programming
- Resource Type:
- Video