SPEAKER：Dr. Jonnie Penn
(Associate Teaching Professor of AI Ethics and Society at the University of Cambridge; Faculty Affiliate at the Berkman Klein Center at Harvard University)

TOPIC：
Climate Instability and the Future of AI: Force Majeure, Open Source Hardware, and a Decomputerisation Movement

DATE：113年12月13日(五)上午10點10分至12點
　　
PLACE：台達館 108教室

Abstract:
The semiconductor industry has a global market cap of 6.7 trillion dollars. The software industry has a market cap of 11.9 trillion. I argue that the compounding and global-in-scale political, economic, and social implications of runaway climate instability have not yet been priced into this cumulative ±18 trillion dollar valuation, nor accounted for in popular commentary about an inevitable ‘AI future.’ Rather than omit fires, floods, droughts, famines, and their resulting human and ecological implications from speculations about AI’s future, I attempt to account for their impact on the incentives driving technical research in the coming decades. With reference to history, I outline three speculative trends: A) increased overlap between the political economy of the tech and energy sectors, opening room for a decomputerisation movement, B) a push towards AI-based edge computing and C) the emergence of open source hardware towards the semiconductor industry’s ‘Raspberry Pi’ moment.

Join us via Zoom: https://mit.zoom.us/j/99257231404?pwd=z1Lyehp1EE812N68UIWcqI8LcA4fRn.1

Speaker's bio:
Dr. Jenq-Neng Hwang received the BS and MS degrees, both in electrical engineering from the National Taiwan University, Taipei, Taiwan, in 1981 and 1983 separately. He then received his Ph.D. degree from the University of Southern California. In the summer of 1989, Dr. Hwang joined the Department of Electrical and Computer Engineering (ECE) of the University of Washington in Seattle, where he has been promoted to Full Professor since 1999. He served as the Associate Chair for Research from 2003 to 2005, and from 2011-2015. He also served as the Associate Chair for Global Affairs from 2015-2020. He is currently the International Programs Lead in the ECE Department. He is the founder and co-director of the Information Processing Lab., which has won several AI City Challenges awards in the past years. He has written more than 400 journal, conference papers and book chapters in the areas of machine learning, multimedia signal processing, computer vision, and multimedia system integration and networking (my Google citation), including an authored textbook on "Multimedia Networking: from Theory to Practice," published by Cambridge University Press. Dr. Hwang has close working relationship with the industry on artificial intelligence and machine learning.

Dr. Hwang received the 1995 IEEE Signal Processing Society's Best Journal Paper Award. He is a founding member of Multimedia Signal Processing Technical Committee of IEEE Signal Processing Society and was the Society's representative to IEEE Neural Network Council from 1996 to 2000. He is currently a member of Multimedia Technical Committee (MMTC) of IEEE Communication Society and also a member of Multimedia Signal Processing Technical Committee (MMSP TC) of IEEE Signal Processing Society. He served as associate editors for IEEE T-SP, T-NN and T-CSVT, T-IP and Signal Processing Magazine(SPM). He served as the General Co-Chair of 2021 and 2022 IEEE World AI IoT Congress, Seattle, WA. He also served as the Program Co-Chair of IEEE ICME 2016 and was the Program Co-Chairs of ICASSP 1998 and ISCAS 2009. Dr. Hwang is a fellow of IEEE since 2001.

主講人：洪淳琦 副教授
題　目：人工智慧發展與智慧財產權法制韌性
The Development of Artificial Intelligence and the Resilience of Intellectual Property Law
時 間：113年11月29日(五)上午10點10分至12點
地　點：台達館108教室
演講摘要：
人工智慧(AI)發展的討論中，總有一種很常見的論述，認為現行的智慧財產權法，不足以應付AI發展。是否真的如此？本演講初步分析AI發展上會遇到的幾個重要智慧財產權議題，包含著作權、專利法、營業秘密法上的常見問題，並鼓勵大家一起思考智慧財產法制的韌性。

Abstract
In discussions about AI development, a common narrative suggests that existing intellectual property laws are insufficient to address the challenges posed by AI. But is this truly the case? This lecture offers a preliminary analysis of key intellectual property issues emerging from AI advancements, focusing on common challenges in copyright, patent law, and trade secret law. It also encourages participants to reflect on the resilience of intellectual property frameworks.

主講人：丁川康教授 (Professor Chuan-Kang Ting)
SPEAKER
題　目：Exploring Human Ethics through AI
TOPIC
時 間：113年11月08日(五)上午10點至12點
DATE　　
地　點：台達館108教室
PLACE
Abstract:
This talk presents our research on exploring human ethics using AI techniques. First, we established a website to collect data on human ethical decisions across a range of scenarios. Then, we developed evolutionary algorithms to model commonsense morality. Our approaches aim to deepen understanding of ethical decision-making processes and the potential for AI to assist in modeling human ethics.

Short Bio
Chuan-Kang Ting
Professor
Department of Computer Science
National Tsing Hua University, Taiwan
Chuan-Kang Ting received the Dr. rer. nat. degree in Computer Science from Paderborn University, Germany. He is currently a Professor of Department of Computer Science, National Tsing Hua University, Taiwan. His research interests include evolutionary computation, computational intelligence, artificial intelligence, machine learning, and their applications in intelligent systems, smart manufacturing, data mining, music and art.
Dr. Ting is the Editor-in-Chief of IEEE Computational Intelligence Magazine (IF 10.3) and Memetic Computing (IF 3.3), and an Associate Editor of IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION. He served as the IEEE Computational Intelligence Society (CIS) Newsletter Editor, the IEEE CIS Webmaster, the Chair of IEEE CIS Chapters Committee, and the Chair of IEEE CIS Creative Intelligence Task Force. Dr. Ting has been involved in organization of many international conferences, symposiums, workshops, and special sessions. He was the Special Session Chair of IEEE WCCI 2016, WCCI 2018, and CEC 2019, the Chair of IEEE Symposium on Computational Intelligence for Creativity and Affective Computing 2013, the Program Chair of TAAI (2012, 2015, 2019), and the Organizing Chair of AI Forum (2012, 2023). He is the President of Taiwanese Association for Artificial Intelligence.

主講人：林昕璇教授 (成功大學政治學系)
SPEAKER
題　目：AI自主性武器系統之國際規範秩序-以國際人道法為中心
TOPIC
時 間：113年9月27日(五)上午10點至12點
DATE　　
地　點： 清華大學台達館108教室
PLACE

Abstract:
This presentation explores the international regulatory framework governing AI autonomous weapon systems, focusing on the principles of international humanitarian law (IHL). It examines the ethical, legal, and strategic challenges posed by the deployment of AI in military operations, including autonomous decision-making in weapons systems and their implications for human oversight. Through a review of historical examples and recent developments, the study highlights the tension between technological advancements in autonomous weaponry and the need for regulatory measures to ensure compliance with international law. The presentation further discusses the role of major international actors, such as the United States and China, in shaping the global governance of AI in military contexts.

主講人：唐鳳 Audrey Tang (前數位發展部部長)
SPEAKER
題　目：人工智慧時代下的民主 Democracy in the Age of AI
TOPIC
時 間：113年10月11日(五)上午10點至12點
DATE　　
地　點：台積館 1F 孫運璿演講廳
PLACE
Abstract:
因應現代科技發展與人工智慧浪潮，使用這些便利、高效率的技術提升工作與生活的同時，無法忽略其對於倫理、社會和法律層面的影響。當科技進步而保護規範或道德標準停滯不前時，該如何避免侵害、建立更具責任的人工智慧環境，更是現代新興技術發展不可或缺的核心價值。人工智慧的倫理現今變得由為重要，不只是私人企業連政府也逐漸開始使用並透過人工智慧運作協助其工作的進行。然而人工智慧的使用卻衍伸出了倫理和權利上的議題，包含隱私、安全、公平、平等、問責性、人權及民主 等問題。
為確保課程的內容更具備落地性，本課程將在10/11(五) 10:00am-12:00pm盛邀數位政策專家唐鳳至清大演講。透過其專業、實踐的經驗和同學們分享人工智慧 時代對於民主的影響為何態樣。究竟人工智慧的使用是會促進民主的蓬勃發展，還是成為另一種隱性的阻礙，甚至現有的民主呢？
In light of the rapid advancements in modern technology and the surge of artificial intelligence, it is essential to recognize the impact these convenient and efficient technologies have on ethics, society, and legal frameworks. As technology progresses, yet protective re gulations and moral standards lag behind, addressing how to prevent violations and establish a more responsible AI environment has become a critical value in the development of emerging technologies.
Artificial intelligence ethics are increasingly signifi cant today. Not only are private enterprises adopting AI, but governments are also integrating these technologies into their operations. However, the use of AI raises important ethical and rights related issues, including privacy, security, fairness, equal ity, accountability, human rights, and democracy.
To delve into these pressing issues, we are excited to announce a special lecture by renowned digital policy expert Audrey Tang, taking place on October 11 (Friday) at National Tsing Hua University. With her extensive expertise and practical experience, Tang will explore the impact of the artificial intelligence era on democracy, offering insights into whether AI will enhance democratic development or pose new challenges to existing democratic systems.

【報名連結 Registration link 】
https://forms.gle/Gv2YUtit2utzxRFNA

相關網址:https://cvgip2024.csie.ndhu.edu.tw/news/best-paper/

主講人：Prof. Jing-Ming Guo
1.Distinguished Professor, National Taiwan University of Science and Technology
2.Chief Technology Officer, Industrial Technology Research Institute
題　目：Development Trends and Considerations for Practical Applications of Generative AI
時 間：113年05月24日(五)下午1點20分至3點
地 點：台達館104教室

Title of speech
This presentation explores the latest trends in Generative AI, focusing on key topics such as the evolution of GPT, domain-specific optimization in large language models (LLMs), micro-sizing LLMs, and the deployment of Generative AI in Industrial Technology Research Institute (ITRI) and its potential expansion to Taiwan enterprises. The talk delves into the advancements in GPT models, highlights the significance of expert-level optimization techniques in enhancing LLM performance, and discusses strategies for scaling down large models. Moreover, it showcases the current efforts by ITRI in implementing Generative AI and outlines the future prospects of adopting this technology within Taiwan's business landscape.
Biography
Prof. Guo is currently a full Professor with the Department of Electrical Engineering, and Director of Advanced Intelligent Image and Vision Technology Research Center. He was Vice Dean of the College of Electrical Engineering and Computer Science, and Director of the Innovative Business Incubation Center, Office of Research and Development. His research interests include Big data signal processing, artificial intelligence, digital image/video processing, computer vision. Dr. Guo is a Senior Member of the IEEE and Fellow of the IET.
Dr. Guo is Chapter Chair of IEEE Signal Processing Society, Taipei Section, Board of Governor member of Asia Pacific Signal and Information Processing Association, and Chair of IET Taipei Local Network. He was General Chair of many international conferences, e.g., APSIPA 2023, IEEE Life Science Workshop 2020, ISPACS 2019, IEEE ICCE-Berlin 2019, IWAIT 2018, and IEEE ICCE-TW 2015. He was Technical Program Chair of many international conferences as well, e.g., IEEE ICIP 2023, IWAIT 2022, IEEE ICCE-TW 2014, IEEE ISCE 2013, and ISPACS 2012. He is/was Associate Editor of the IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technologies, IEEE Transactions on Multimedia, IEEE Signal Processing Letters, Information Sciences, Signal Processing, and Journal of Information Science and Engineering.

主講人：謝君偉教授（陽明交通大學）
題　目：Pre-trained Models與LLM結合測試
時 間：113年05月21日(二)上午10點10分至12點
地　點：台達館102教室

Abstract:
Large Language Models (LLMs) have demonstrated incredible potential in generating text that resembles human writing, as shown in numerous studies. Despite their impressive abilities, training them from scratch is not easy. Recently, model reuse has become a key technique, allowing developers to utilize pre-trained models, ranging from small ones to large language models, to improve the performance and efficiency of their machine learning systems. This presentation will explore how to establish connections between the widely adopted practice of model reuse across different domains and covers various stages of leveraging Pre-Trained Models (PTMs), including data preparation, architecture design, model training, and model inference. In addition to providing a comprehensive overview of typical methods for model reuse, we'll address the important issue of how to retrain a model using cost-effective GPUs like Nvidia 4090. We'll also discuss solutions and results based on Phison’s aiDAPTIV platform.

主講人：李承緒 副總 (訊連科技)
題　目：電腦視覺在業界的開發實務與應用
時 間：113年05月17日(五)下午1點20分至3點　
地　點：台達館104教室

Abstract:
近幾年來AI與AR技術突飛猛進，許多技術已經應用在日常生活上了，尤其是生成式AI更是帶來新技術的大躍進及應用的大爆發，因此也造就了許多商機。
訊連科技與玩美移動兩家軟體服務公司，分別投入了許多相關的研究與開發，本次演講將以技術與應用的層面介紹這兩家公司在AI與AR的研究開發成果。

Speaker：
李承緒，於1996年台大資訊工程系碩士畢業，目前於訊連科技擔任研發部資深副總，帶領超過兩百位工程師研發AI在多媒體及電腦視覺的技術與應用。