CEO, ASUS Cloud and TWSC
Topic:
Democratizing LLM to Empower Generative AI Innovations
Abstract:
Generative AI is sparking a revolutionary shift in how humanity harnesses information technology, triggering a wave of innovation. Its applications are diversifying across various sectors, promising new opportunities. Generative AI is a knowledge-based technology, and currently, many countries are actively crafting legislation to regulate the risks associated with its development and use.
To manage these risks, we rely on democratizing LLM AI technology, open-source models, and data governance, especially in critical areas like healthcare. Taiwan boasts a solid industrial foundation for promoting democratizing AI, with strengths in computing power, semiconductor manufacturing, systems, and IT services. With government support, Taiwan aims to emerge as a leader in both Generative AI and Trusted AI.
Biography:
Peter Wu is a highly accomplished executive with a diverse range of experiences and achievements in the technology industry. He currently holds two prominent positions, serving as the CEO of ASUS Cloud of Taiwan Web Service Corporation.
In addition to his current roles, Peter Wu is actively involved in various organizations and committees. He serves as a committee member of the Biotechnology and Pharmaceutical Industries Promotion Office under the Ministry of Economic Affairs. Peter Wu is also holds the position of Director at Information Service Industry Association of R.O.C., Supervisor at the Cloud Computing & IoT Association in Taiwan and serves as the Deputy Director of the Policy and Legal Committee and President of Taipei Computer Association AI Alliance. Through these roles, he helps drive policy discussions and promote the growth of cloud computing in Taiwan.
Recognized for his expertise and insights, Peter Wu was appointed as a member of the Advisory Committee on Bio Taiwan Committee by the Executive Yuan in 2017 and 2019. In this capacity, he provided valuable guidance and advice on the strategic direction of the biotechnology industry in Taiwan.
With a wealth of experience and a passion for technology and innovation, Peter Wu is a highly respected leader in the industry. His contributions to the advancement of cloud computing, smart healthcare, and the software industry have been instrumental in driving growth and shaping the future of Taiwan’s technology landscape.
CDO, Inventec Inc.
Topic:
Reliable AI for Manufacturing: Challenges in Data Curation, Continual Learning, and Agile Production.
Abstract:
Lights-out manufacturing refers to a production process requiring little human intervention. This promise of higher production efficiency also brings significant investment and poses multifaceted challenges for AI and robotics technologies. Data curation emerges as the primary obstacle, as the ability to collect, label, and evolve the datasets can significantly vary across various sites and parties. We also find it challenging to share data across parties because of the multiple stakeholders involved. Continual learning becomes critical as we encounter scope and concept changes during model deployment. Scaling out also challenges model reliability under domain transfer. Agility has become a key differentiator under dynamic production settings. The production facilities must react and adapt to new tasks for smaller production batches with greater versatility. As researchers and practitioners with firsthand experiences, we hope this talk can shed some light on these respective challenges and realize that we are still just a few steps away from foundation models in reliable AI manufacturing.
Biography:
Wei-Chao Chen is the Chief Digital Officer at Inventec Corporation and the Chairman at Skywatch Inc. Dr. Chen is also a Visiting Professor at the National Taiwan University. His research interests include graphics hardware, computational photography, augmented reality, and computer vision. Dr. Chen was the Chief AI Advisor at Inventec (2018-2020), a senior research scientist in Nokia Research Center at Palo Alto (2007-2009), and a 3D Graphics Architect in NVIDIA (2002-2006). Dr. Chen received his MS in Electrical Engineering from National Taiwan University (1996) and Ph.D. in Computer Science from the University of North Carolina at Chapel Hill (2002).
Head of AI & Data Engineering Division, MediaTek Inc
Topic:
Boost Productivity & Innovation : MediaTek DaVinci GenAI Platform
Abstract:
MediaTek DaVinci, based on MediaTek’s Generative AI Service Framework (GAISF), was initially developed as a data-secure, productivity-enhancing generative AI tool for the MediaTek group’s internal use. It has been widely used by various departments, and has evolved into a generative AI service platform that can be imported by external enterprises, and a rich set of ecosystem.
Dozens of companies from high-tech, financial, telecom, legal, manufacturing, sales, service, system integration, and cloud services industries, as well as educational institutions and start-ups, have already joined the MediaTek Davinci ecosystem.
MediaTek Davinci provides a highly integrated and scalable open platform that allows developers to create customized generative AI extension plug-ins and assistants for various industries, while enterprises can make good use of the platform’s rich tools to improve productivity and competitiveness in a data-secure environment.
Biography:
Jason Yeh is the head of AIDE (AI & Data Engineering) at MediaTek. AIDE’s mission is to empower BU/FU to adopt AI to boost productivity.
He has 27 years of experience in semiconductor IT, big data and AI. Prior to joining MediaTek, he worked for TSMC. He received his MBA degree in Management Information System from National Chengchi University, Taiwan.
Department Head (Machine Intellection), A*STAR
https://personal.ntu.edu.sg/xlli/
Topic:
Unveiling Tomorrow: AI and Data Science for Industrial Transformation
Abstract:
This presentation explores the transformative potential of AI and data science across key industries, including manufacturing, aerospace, and semiconductors. In manufacturing and aerospace, AI-driven time series analytics emerge as a game-changer, enabling predictive maintenance and condition monitoring. Witness how these advancements optimize operations, minimize downtime, and elevate productivity. In the semiconductor industry, AI proves indispensable in optimizing Design of Experiments (DOE) and detecting defects in 3D structures. Uncover how these applications ensure the highest standards of product quality and reliability, driving innovation and competitiveness. Join us on a journey to uncover how AI and data science are reshaping industries, driving innovation, and paving the way for real-world transformation.
Biography:
Xiaoli is currently a department head (Machine Intellection department, consisting of 100+ AI and data scientists, which is the largest AI and data science group in Singapore) and a principal scientist at the Institute for Infocomm Research, A*STAR, Singapore. He also holds adjunct professor position at Nanyang Technological University (He was holding adjunct position at National University of Singapore for 6 years). He is an IEEE Fellow and Fellow of Asia-Pacific Artificial Intelligence Association (AAIA). Xiaoli is also serving as KPMG-I2R joint lab co-director. He has been a member of Information Technology Standards Committee (ITSC) from ESG Singapore and Infocomm Media Development Authority (IMDA) since 2020. Moreover, he serves as a health innovation expert panel member for the Ministry of Health (MOH), expert panel member for Minstry of Education (MOE), as well as an AI advisor for the Smart Nation and Digital Government Office (SNDGO), Prime Minister s Office, highlighting his extensive involvement in key Government and industry initiatives.
The Machine Intellection department has established itself as a leader in the industry, with a proven track record of successful collaborations with various partners, including SIA, KPMG, Lam Research, GLOBALFOUNDRIES, DBS, Singtel, Mclaren, AIA, Standard Chartered Bank, NEC, and NCS. Moreover, the department has also achieved remarkable success on the international stage, having won prestigious competitions such as the IJCAI Competition (Stage 1), which is considered the top AI Conference in the world, in 2015, and KDD Cup (Part of First Place Winning Team), which is the best data mining competition in the world, in the same year. Additionally, the department also emerged victorious in the GE Flight Quest Challenge in 2013, further solidifying its reputation as a world-class research team.
CTO, Delta Electronics, Inc.
Topic:
Harnessing AI for Competitive Advantage
Abstract:
Leveraging Artificial Intelligence (AI) and data analytics is crucial for maintaining a competitive edge in today’s dynamic business environment. In this session, Dr. Tei-Wei Kuo, CTO of Delta Electronics Inc., will showcase the transformative role of AI and data management across industries. Dr. Kuo will highlight how AI enhances product innovation, optimizes manufacturing processes, and improves supply chain efficiencies. The presentation will focus on a case study of AI-powered manufacturing in collaboration with Nvidia, demonstrating the use of Digital Twin technologies and Synthetic Data. This case study will provide a glimpse into effectively integrating AI into business strategies.
Biography:
Dr. Tei-Wei Kuo is Chief Technology Officer of Delta Electronics, Inc. and Chair of the Company’s Strategy and Technology Council. Before joining Delta, Dr. Kuo was a Distinguished Professor of Department of Computer Science and Information Engineering at National Taiwan University and served as a senior research advisor role to Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), United Arab Emirates.
Dr. Kuo is recognized as a pioneer in non-volatile memory software and systems. His research results were technically transferred to many storage and IC-design companies, such as Acer, Macronix, Genesys Logic. His team is also one of the first few in proposing the concept of unified memory (i.e., an integrated design of the main memory and storage) to conquer the data moving latency inside computers and is a leading team in in-memory computing research. He is a Fellow of ACM, IEEE, and US National Academy of Inventors and is General Co-Chair of CPS-IoT Week 2024 and General (Co-)Chair of Embedded Systems Week 2024/2025.
CTO, Quanta Computer
Topic:
Revolutionizing Healthcare: Enhanced Patient Outcomes through AI-Driven Data Optimization
Abstract:
In the swiftly evolving realm of healthcare, the integration of AI technologies is catalyzing a transformative shift towards precision medicine and improved patient care. At the heart of this revolution is the strategic optimization of the data journey, a critical endeavor that promises to elevate the patient experience by delivering accurate medical outcomes and enriching interactions at every care touchpoint. This journey, spanning both outpatient and inpatient services, grows increasingly intricate with the integration of advanced computational models such as Large Language Models (LLMs) and Large Multimodal Models (LMMs). These innovations bring to the fore the necessity of incorporating comprehensive dialogues between patients and healthcare providers into the conventional data ecosystem, comprising Electronic Medical Records (EMR) and medical IoT sensor data.
Addressing these integration challenges transcends the capabilities of isolated systems or devices. This presentation proposes a pioneering solution: a versatile platform architecture built upon Quanta QOCA. Characterized by its simplicity, security, scalability, and adaptability, this framework is designed to navigate the complexities of modern healthcare data management. By enabling seamless access to smart healthcare services for individuals of all ages, regardless of their location, we are not just streamlining healthcare delivery but redefining it. This initiative is poised to leverage the full potential of AI in precision health, significantly enhancing patient outcomes and transforming the healthcare landscape for all stakeholders. Through this visionary approach, we aim to usher in a new era of digital health, marked by unparalleled efficiency and accessibility.
Biography:
Dr. Ted Chang is a highly accomplished Chief Technology Officer, Vice President and General Manager of Quanta Computer, which is the world’s largest computer ODM and laptop computer maker. He has more than 20 years of experience in leading global corporations and has been instrumental in driving corporate technology strategy and global research partnership. In addition, Dr. Chang is responsible for overseeing the Quanta Research Institute (QRI) for advanced research and BU12, a business unit dedicated to integration of AI, IoT and cloud computing as a platform solution for smart transformation of Heathcare, Medicine and Agriculture etc.
Dr. Chang has been appointed as representatives of Taiwan for APEC Business Advisory Council (ABAC) since 2019. Academically, Dr. Chang holds various guest professorships in the EECS colleges of National Taiwan University (NTU), National Cheng-Kung University (NCKU), Asia University (AU) and the AI college of National Yang-Ming Chao-Tung University (NYCU). He serves as a member of the board for several educational and research foundations, including the Epoch Foundation, Spring Foundation, Quanta Culture and Education Foundation (QCEF), Quanta Medicine Technology Foundation (QMTF), Chinese Medical Advancement Foundation, and Ming Dao Culture and Education Foundation etc.
Among many honors, Dr. Chang received Japan Good Design Best 100 award in 2022, five REDDOT Design Awards on Smart Medicine (2021 and 2022), and IF Design Award on Smart Agriculture in 2021. He was also awarded distinguished alumni awards from both NCKU and Chia-Yi High School in 2021. He led the Quanta-NCTU Joint AI Center to win the CES Innovation Award and WITSA in 2020 Award. He was the chief advisor to the Taiwan Pavilion “Swingphony” at London Design Biennale 2020. Dr. Chang is a prolific inventor with over 250 patents granted globally by Dec. 2023. His invention in 2001, “A Network Object Delivery System for Personal Computing Device,” defined the “Application Module Store.” Dr. Chang joined Quanta in 2000, promoted as VP in 2009 and promoted as the first CTO in Quanta history in 2010. Since 2004, Dr. Chang has led the strategic research collaboration on future computing with MIT Computer Science and Artificial Lab (CSAIL) to support the transformation of Quanta. The partnership started with TParty project on Human Centric Computing, Qmulus Project on Cloud Computing and now on AIM project with focus on AI medicine and computational health. Dr. Chang’s past projects, One Laptop Per Child (OLPC) and the QRI research model, were published as business cases by Harvard Business School.
CTO, Appier
Topic:
Double Down on MarTech Impact with Strategic GenAI Deployment
Abstract:
The emergence of GenAI has swiftly changed the digital marketing landscape. Within just a year, LLMs have shifted from a novel concept to an essential tool in the business sector, compelling enterprises to deploy GenAI applications strategically and in a targeted way. This session will showcase how innovative GenAI technology is reshaping the MarTech ecosystem through advertising, hyper-personalization, and real-time data analysis. Welcome to a journey where innovation meets impact!
Biography:
Dr. Ming-Yu “Robert” Chen served as Appier Chief Technology Officer. He received his Ph.D. in Computer Science from Carnegie Mellon University. Dr. Chen has over 20 years of experience driving technology strategy, leading large-scale organizations, building scalable platforms for global deployment, and conducting AI technology research. At Appier, he leads product development and technology across all product lines, directs R&D for CrossX and ESS solutions and formulates strategies from high-value customer acquisitions, retargeting to customer retention and engagement, accelerating transaction process and insight generation. His leadership in applying advanced decision-making and generative AI technologies is instrumental in enhancing Appier’s solutions and efficiently optimizing ROI for Appier’s customers. Dr. Chen joined Appier from Compass, where he built the first modern enterprise real estate end-to-end platform and led a global engineering team of over 300 scientists and engineers. Before Compass, he established the industry’s first cloud-based housing valuation system in Zillow and a large-scale news recommendation system in Microsoft with machine learning technology, improving users’ personalized experience.
Principal Research Staff Member, IBM Thomas J. Watson Research Center
https://sites.google.com/site/pinyuchenpage/home
Topic:
Exploring Safety Risks in Large Language Models and Generative AI
Abstract:
Large language models (LLMs) and Generative AI (GenAI) are at the forefront of current AI research and technology. With their rapidly increasing popularity and availability, challenges and concerns about their misuse and safety risks are becoming more prominent than ever. In this talk, I will provide new tools and insights to explore the safety and robustness risks associated with state-of-the-art LLMs and GenAI models. In particular, I will cover (i) safety risks in fine-tuning LLMs, (ii) LLM jailbreak mitigation, (iii) prompt engineering for safety debugging, and (iv) robust detection of AI-generated text from LLMs.
Biography:
Dr. Pin-Yu Chen is a principal research scientist at IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA. He is also the chief scientist of RPI-IBM AI Research Collaborationand PI of ongoingMIT-IBM Watson AI Lab projects. Dr. Chen received his Ph.D. in electrical engineering and computer science from the University of Michigan, Ann Arbor, USA, in 2016. Dr. Chen’s recent research focuses on adversarial machine learning of neural networks for robustness and safety. His long-term research vision is to build trustworthy machine learning systems. He received theIJCAI Computers and Thought Awardin 2023. He is a co-author of the book “Adversarial Robustness for Machine Learning”. At IBM Research, he received several research accomplishment awards, including IBM Master Inventor, IBM Corporate Technical Award, and IBM Pat Goldberg Memorial Best Paper. His research contributes to IBM open-source libraries including Adversarial Robustness Toolbox (ART 360) and AI Explainability 360 (AIX 360). He has published more than 50 papers related to trustworthy machine learning at major AI and machine learning conferences, given tutorials at NeurIPS’22, AAAI(’22,’23,’24), IJCAI’21, CVPR(’20,’21,’23), ECCV’20, ICASSP(’20,’22,’23,’24), KDD’19, and Big Data’18, and organized several workshops for adversarial machine learning. He is currently on the editorial board of Transactions on Machine Learning Research and serves as an Area Chair or Senior Program Committee member for NeurIPS, ICML, AAAI, IJCAI, and PAKDD. He received the IEEE GLOBECOM 2010 GOLD Best Paper Award and UAI 2022 Best Paper Runner-Up Award.
