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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:
- Mechanical Engineering and Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Robotics Human-robot interaction
- Resource Type:
- Video
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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