Search Constraints

Number of results to display per page
Results for: Artificial Intelligence Remove constraint Artificial Intelligence

Search Results

  • e-book 
    Writing Instruction Tips For Automated Essay Graders: How To Design an Essay for a Non-human Reader

    Writing Instruction Tips For Automated Essay Graders: How To Design an Essay for a Non-human Reader

    As schools, as well as the workplace, become more automated, and remote or distance learning/working becomes the “new normal,” understanding and leveraging artificial intelligence will become a critical skill.

    Keywords:
    Report writing Grading marking (Students) -- Computer programs Textbooks
    Resource Type:
    e-book
     
  • Presentation 
    Workshop on Semantic Business Process Management - Semantic business process validation

    Workshop on Semantic Business Process Management - Semantic business process validation

    This video was recorded at 5th Annual European Semantic Web Conference (ESWC), Tenerife 2008. The degree of automation in the management of the business process space of single enterprises and whole value chains is still unsatisfying. A key source of problems are representational heterogeneities between the various perspectives and the various stages in the life-cycles of business processes. Typical examples are incompatible representations of the managerial vs. the IT perspective, or the gap between normative modeling for compliance purposes and process execution log data. As early as in the 1990s, researchers have evaluated the potential of using ontologies for improving business process management in the context of the TOVE project; however, the impact of that work remained beyond initial expectations. Since 2005, there is now a renewed and growing interest in exploiting ontologies, of varying expressivity and focus, for advancing the state of the art in business process management, in particular in ERP-centric IT landscapes. The term "Semantic Business Process Management" has been suggested for the described branch of research in an early 2005 paper, which is now frequently cited as the first description of the overall vision. A flagship activity in the field is the European research project "SUPER", with more than a dozen premier industrial and academic partners, among them SAP, IDS Scheer, and IBM. In the past two years, substantial advancement has been made in investigating the theoretical and practical branches of this vision. However, the interdisciplinary nature of the topic requires a tight collaboration of researcher from multiple fields of, namely the BPM, SOA, Semantic Web, Semantic Web services, and Economics communities. There is a clear need for an annual event at which those communities meet, debate, challenge each others approaches, and eventually align their research efforts. Due to the strong involvement of Semantic Web researchers in the field, ESWC is the ideal target venue for this event. In this workshop, we want to bring together experts from the relevant communities and help reach agreement on a roadmap for SBPM research. We aim at bundling experiences and prototypes from the successful application of Semantic Web technology to BPM in various industries, like automotive, engineering, chemical and pharmaceutical, and services domains. The particular focus is on deriving reusable best-practices from such experiences, and to yield convincing showcases of semantic technology.

    Subjects:
    Management and Computing
    Keywords:
    Industrial management Workflow -- Management
    Resource Type:
    Presentation
     
    OER
  • e-book 
    The Crystal Ball Instruction Manual Volume One: Introduction to Data Science

    The Crystal Ball Instruction Manual Volume One: Introduction to Data Science

    A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.

    Subjects:
    Computing
    Keywords:
    Data mining Computer science Artificial intelligence Textbooks
    Resource Type:
    e-book
     
  • Video 
    The Basics of AI for Business

    The Basics of AI for Business

    On the TED@BCG stage, AI pathfinder Philipp Gerbert dispels the myth of AI as a complex and mysterious tool for business. In reality, he says, even those of us outside Silicon Valley can have an intimate understanding of AI and put it to work today. Gerbert walks us through the ABC's of AI and what it can mean for your organization.

    Keywords:
    Business enterprises -- Technological innovations Artificial intelligence
    Resource Type:
    Video
     
  • Video 
    Technology That Knows What You're Feeling

    Technology That Knows What You're Feeling

    What happens when technology knows more about us than we do? Poppy Crum studies how we express emotions -- and she suggests the end of the poker face is near, as new tech makes it easy to see the signals that give away how we're feeling. In a talk and demo, she shows how "empathetic technology" can read physical signals like body temperature and the chemical composition of our breath to inform on our emotional state. For better or for worse. "If we recognize the power of becoming technological empaths, we get this opportunity where technology can help us bridge the emotional and cognitive divide," Crum says.

    Subjects:
    Technology, Electronic and Information Engineering, and Mechnical Engineering
    Keywords:
    Emotion recognition Artificial intelligence
    Resource Type:
    Video
     
  • Video 
    Student Voices on Chat GPT: Learners’ Views on Generative AI Tools

    Student Voices on Chat GPT: Learners’ Views on Generative AI Tools

    In this ‘Student Voices’ session, students share their views on, and experiences with, emerging Generative AI tools, including ChatGPT. The session will provide a conversation opportunity between teachers and students in this rapidly changing area, and a valuable chance to hear the learner's perspective.
    Event Date: 23/3/2023
    Facilitator(s): Dr Julia Chen (EDC), Mr Anthony Ho (EDC)
    Honourable moderator for Q&A session: Prof David Shum, Dean of FHSS
    EDC Coordinator: Darren Harbutt

    Subjects:
    Lesson Design
    Keywords:
    Artificial intelligence College teaching Artificial intelligence -- Educational applications
    Resource Type:
    Video
     
  • Courseware 
    Stanford Engineering Everywhere

    Stanford Engineering Everywhere

    Stanford Engineering Everywhere (SEE) expands the Stanford experience to students and educators online and at no charge. A computer and an Internet connection are all you need. The SEE course portfolio includes one of Stanford's most popular sequences: the three-course Introduction to Computer Science, taken by the majority of Stanford’s undergraduates, as well as more advanced courses in artificial intelligence and electrical engineering.

    Course related:
    EE1D01 Electrical Science for Everyone
    Subjects:
    Electronic and Information Engineering, Biomedical Engineering, Mechanical Engineering, and Computing
    Keywords:
    Engineering Computer science
    Resource Type:
    Courseware
     
  • Video 
    Search: Games, Minimax, and Alpha-Beta

    Search: Games, Minimax, and Alpha-Beta

    In this lecture, we consider strategies for adversarial games such as chess. We discuss the minimax algorithm, and how alpha-beta pruning improves its efficiency. We then examine progressive deepening, which ensures that some answer is always available.

    Course related:
    COMP4431 Artificial Intelligence
    Subjects:
    Computing and Mathematics and Statistics
    Keywords:
    Artificial intelligence
    Resource Type:
    Video
     
  • Presentation 
    Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process

    Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process

    This video was recorded at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Athens 2011. Hierarchical modeling and reasoning are fundamental in machine intelligence, and for this the two-parameter Poisson-Dirichlet Process (PDP) plays an important role. The most popular MCMC sampling algorithm for the hierarchical PDP and hierarchical Dirichlet Process is to conduct an incremental sampling based on the Chinese restaurant metaphor, which originates from the Chinese restaurant process (CRP). In this paper, with the same metaphor, we propose a new table representation for the hierarchical PDPs by introducing an auxiliary latent variable, called table indicator, to record which customer takes responsibility for starting a new table. In this way, the new representation allows full exchangeability that is an essential condition for a correct Gibbs sampling algorithm. Based on this representation, we develop a block Gibbs sampling algorithm, which can jointly sample the data item and its table contribution. We test this out on the hierarchical Dirichlet process variant of latent Dirichlet allocation (HDP-LDA) developed by Teh, Jordan, Beal and Blei. Experiment results show that the proposed algorithm outperforms their "posterior sampling by direct assignment" algorithm in both out-of-sample perplexity and convergence speed. The representation can be used with many other hierarchical PDP models.

    Subjects:
    Computing
    Keywords:
    Machine learning Artificial intelligence
    Resource Type:
    Presentation
     
    OER
  • Video 
    Robot Alice: The Science behind an Application that Stole the Hearts Worldwide

    Robot Alice: The Science behind an Application that Stole the Hearts Worldwide

    An online lecture on the topic of "Robot Alice: The Science behind an Application that Stole the Hearts Worldwide".This lecture is suitable for secondary school and university students as well as the general public.

    Subjects:
    Social Design
    Keywords:
    Robotics Robots -- Design construction
    Resource Type:
    Video
     
  • e-book 
    Responsible Innovation: Ethics, Safety and Technology

    Responsible Innovation: Ethics, Safety and Technology

    This textbook is based on the MOOC Responsible Innovation offered by the TU Delft. It provides a framework to reflect on the ethics and risks of new technologies. How can we make sure that innovations do justice to social and ethical values? How can we minimize (unknown)risks?The book explains: The concept and importance of responsible innovation for society Key ethical concepts and considerations to analyse the risks of new technologies Different types of innovation (e.g. radical, niche, incremental, frugal) Roadmap for Responsible Innovation by Industry The concept of Value Sensitive Design (VSD) It includes a link to all the web lectures as well as case studies ranging from care robots and nuclear energy to Artificial Intelligence and self-driving vehicles.

    Subjects:
    Philosophy
    Keywords:
    Risk management Technological innovations -- Moral ethical aspects Textbooks
    Resource Type:
    e-book
     
  • Video 
    Redesigning Assessments in the Age of Generative AI

    Redesigning Assessments in the Age of Generative AI

    Join colleagues from the Department of Computing (COMP) and the English Language Centre (ELC) as they share their insights, experiences, challenges and plans on redesigning assessments in response to the emergence of generative AI. In this webinar, participants will learn how PolyU staff are adapting their assessment strategies to incorporate AI-generated content, while still maintaining academic integrity and ensuring student learning outcomes are met. This session will provide valuable perspectives for educators who are interested in leveraging AI in their own teaching and assessment practices.
    Event Date: 30/5/2023
    Facilitator(s): Richard Lui (COMP), Adam Forrester (ELC), Mitesh Patel (EDC)

    Subjects:
    Student Engagement, Assessment & Feedback, Lesson Design, and Good Practices
    Keywords:
    Artificial intelligence Computer-assisted instruction Education -- Effect of technological innovations on Educational technology
    Resource Type:
    Video
     
  • Video 
    Quality Incentive Scheme on Online Teaching: Sharing Sessions AP, CBS and ELC

    Quality Incentive Scheme on Online Teaching: Sharing Sessions AP, CBS and ELC

    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
     
  • Others 
    Papers With Code: The latest in machine learning

    Papers With Code: The latest in machine learning

    The mission of Papers With Code is to create a free and open resource with Machine Learning papers, code and evaluation tables.We believe this is best done together with the community and powered by automation.

    Course related:
    COMP5121 Data Mining and Data Warehousing Applications, COMP5212 Software Design and Architecture, COMP5123 Intelligent Information Systems, COMP5222 Software Testing and Quality Assurance, and COMP5131 Introduction to Information Systems
    Subjects:
    Computing
    Keywords:
    Machine learning Artificial intelligence
    Resource Type:
    Others
     
  • Video 
    PAIR distinguished lecture series : the future of elder care : integrating large language models

    PAIR distinguished lecture series : the future of elder care : integrating large language models

    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
     
  • Video 
    PAIR distinguished lecture series : artificial intelligence and autonomous systems

    PAIR distinguished lecture series : artificial intelligence and autonomous systems

    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:
    Human-Computer Interaction
    Keywords:
    Artificial intelligence
    Resource Type:
    Video
     
  • Presentation 
    Media Stream

    Media Stream

    This video was recorded at COIN / PlanetData Winter School on Knowledge Technologies for Complex Business Environments, Ljubljana 2011. Organized by COIN FP7 Integrated Project and PlanetData FP7 Network of Excellence, the school seeks to bring together students, scholars and researchers from industry in order to foster collaboration and interoperability with innovative services and project large-scale data management in business environments. The main topics of the winter school are: Interoperability and collaboration models and solutions, Enterprise interoperability and collaboration services, Innovative knowledge and semantically powered technologies, Knowledge process and context modelling, Pro-active knowledge tools, Large scale analytics and reasoning tools, Business cases and real case studies. Detailed information can be found here.

    Subjects:
    Management and Computing
    Keywords:
    Data mining Real-time data processing
    Resource Type:
    Presentation
     
    OER
  • Others 
    Mars Pineapple Hotel | GreatCase100

    Mars Pineapple Hotel | GreatCase100

    The Mars Pineapple Hotel is an innovative marketing project that utilizes generative AI technology to create videos and images based on specified requirements. The hotel targets astronauts, scientists, and individuals interested in future technology and space travel. Its unique selling points include a pineapple-inspired design, emphasizing technological innovation, and personalized experiences such as stargazing through grid skylights and experiencing lunar craters in space capsule rooms. However, there are challenges in terms of the unstable quality of AI-generated content and the inability of AI to understand human emotions and create individualized experiences. Feedback and improvements are needed to enhance the marketing outcome and address these challenges.

    Subjects:
    Marketing and Hotel, Travel and Tourism
    Keywords:
    Hotels -- Marketing Artificial intelligence Hospitality industry -- Marketing
    Resource Type:
    Others
     
  • MOOC 
    Machine Learning Specialization

    Machine Learning Specialization

    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
     
  • MOOC 
    Machine Learning

    Machine Learning

    Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

    Course related:
    EIE6207 Theoretical Fundamental and Engineering Approaches for Intelligent Signal and. Information Processing and COMP4434 Big Data Analytics
    Subjects:
    Computing
    Keywords:
    Artificial intelligence Machine learning
    Resource Type:
    MOOC