All Sessions：

Large Language Models (LLMs) have been a major focus in the tech world for nearly two years, sparking debates over whether they are overhyped or genuinely transformative. In this talk, I will explore how CyCraft Technology has harnessed LLMs across various cybersecurity domains, focusing on three critical aspects: - The Good: Discover how LLM-empowered products significantly enhance the efficiency of security experts, reducing incident response times and revolutionizing threat management. - The Bad: Uncover the domain-specific challenges we encounter when integrating LLMs into cybersecurity, including issues of scalability, accuracy, and adaptation to rapidly evolving threats. - The Ugly: Examine the fundamental security vulnerabilities inherent in LLMs, highlighting the risks they pose and the potential for exploitation by malicious actors. Join us for an insightful journey into the practical applications, challenges, and pitfalls of deploying LLMs in the cybersecurity landscape.

By leveraging digital transformation and AI-driven insights, and incorporating international trends and regulations, AI technology drives growth in businesses and investment market value, meeting the demands of niche missions and talent needs. As domestic industries in Taiwan face the advent of the AI era, the need for digital transformation has accelerated. Meanwhile, organisations are tackling the challenges of merging computational power on the production side with AI resources on the application side. Through case studies in smart logistics and retail services within the context of Industry 5.0, Deloitte demonstrates how AI can optimise logistics and enhance consumer experiences, while also interweaving sustainable development and circular power systems to establish a one-stop ecosystem. Furthermore, this ecosystem fosters the integration of hardware and software, process management, and talent empowerment, paving the way for a brand new, win-win business model. 透過數位轉型與 AI 驅動的洞察，整合國際趨勢與規範，帶動技術與投資市值增長，滿足特定任務與人才需求。國內產業面對 AI 的時代的來臨，加速了數位轉型的需求。面對生產端算力與應用端 AI 資源整合的挑戰。Deloitte 透過工業 5.0 的智慧物流和零售服務案例，說明使用 AI 來最佳化物流與增加消費者體驗，同時結合永續發展及循環電力系統，建立一站式生態圈，實現軟硬體整合、流程管理與人才賦能，開創共贏的新商業模式。

Mr. Peter Hu, CIO of FET, will explore the challenges and opportunities of AI adoption in enterprise, such as lack of scenarios, monetization difficulties, ambiguous investment decisions, and insufficient .Peter Hu effective data. He will discuss how FET enhances productivity, fosters innovation, drives data-driven decisions, manages net-zero targets, and ensures digital resilience and security. This session will also cover how these capabilities align with FET's technological, organizational, cultural, and financial transformation strategies.

This research focuses on the challenges faced by Small and Medium Enterprises (SMEs) manufacturers in adopting AI technologies. Despite their successful decades-long operations, SMEs are seeking ways to leverage AI for enhancing product value and manufacturing efficiency. However, the lack of resources and collaborative development talent in AI technology presents a significant barrier. To address these challenges, the study proposes a shared AI software platform where SMEs can utilize AI from design to operation, collaborate with each other, share resources through open-source, and add proprietary features for their businesses. Specifically, the research aims to establish a lathe machining quality and tool damage diagnostic system using AI models. This system is expected to predict machining errors and tool damage, ensuring quality control without extensive manual inspection, reducing inspection costs, and increasing tool lifespan. The goal is to cater to the current machining demands of small batches with quick changeovers, overcoming the lack of versatility in existing technologies.

We will share our view of recent LLM development from different aspects, like open-source vs. proprietary, use vs. training, application and product, and etc. We will also share several applications with scenario in industries based on our experience.

For individual users, as the leader in high-performance Gaming PCs, MSI is integrating AI technology into its innovations, such as a self-developed small language model preloaded in MSI AI PCs. This model supports offline generative AI capabilities, addressing user needs for data privacy protection and real-time responsiveness.

In this session, we will explore how an open platform for enterprise ready AI can address the fragmentation challenges of generative AI (GenAI) technology. While open-source projects have accelerated AI innovation, they have also led to the dispersion of technologies and tools, creating barriers for enterprises to adopt GenAI. Developers face numerous options and struggle with integration. To tackle this issue, we need a robust open-source collaboration framework to build and evaluate composable GenAI solutions. This framework will provide a systematic approach to grading and assessing GenAI based on performance, reliability, scalability, and flexibility, ensuring its suitability for enterprise needs. Additionally, this collaborative model will help address current challenges in retrieval-augmented generation (RAG) technology and provide an innovative platform for developers to unlock the full potential of GenAI. 在此次演講中，我們將探討企業級 AI 的開放平台如何應對生成式人工智慧（GenAI）技術的碎片化挑戰。開源專案推動了 AI 的迅速創新，但也導致了技術和工具的分散，對企業採用 GenAI 形成障礙。開發人員面臨眾多選擇，難以整合。為解決這一問題，我們需要一個強大的開源協作框架，以建構和評估可組合的 GenAI 解決方案。這個框架將根據性能、可信度、可擴展性和彈性對 GenAI 進行分級和評估，確保其適合企業需求。同時，這種合作模式將有助於解決目前 RAG（檢索增強生成）技術的挑戰，並為開發人員提供創新平台，發揮 GenAI 的最大潛力。

Starting from the four major cycles of IT development, this outline explains how the era of AI marks the fifth cycle, referred to as the "Age of It," and explores its profound impact. Addressing the specific needs of Taiwanese businesses, Dr. Tsai will introduce a strategic framework of "Five Dimensions of AI Application" to help enterprises find optimal solutions in improving productivity, integrating digital platforms, connecting with the AI ecosystem, implementing AI models, and addressing AI ethics. In the end, Dr. Tsai will share tangible "low-hanging fruits" for businesses applying AI.

AMD not only has the broadest AI product portfolio but also leads in silicon design and packaging technologies. AMD pioneers chiplet modular design and 3.5D packaging in AI Accelerator. Together with Open and Proven software/hardware stack, AMD aims to advance the AI development with the ecosystem through deep collaboration.

The emergence of generative artificial intelligence (AI) at the end of 2022 marked a significant evolution, as these technologies increasingly integrate into daily human activities. The scale of generative models has been expanding annually at an exponential rate, with architecture advancements evolving from single-model frameworks to complex multi-expert systems. As industries across the board incorporate generative AI into their operational processes, concerns regarding information security and controllability have come to the forefront. However, the high deployment costs associated with generative AI technologies pose a significant barrier to widespread adoption. In response, Phison has introduced the aiDAPTIV+ initiative, a revolutionary approach that leverages NAND Flash to expand High Bandwidth Memory (HBM), thereby substantially reducing costs.

Abstract: This presentation delves into the forefront of medical artificial intelligence, particularly focusing on the role of agentic Large Language Models (LLMs) in transforming healthcare. These advanced models exhibit agency by autonomously generating realistic and contextually appropriate medical data and interventions, marking a shift from theoretical exploration to tangible, real-world applications. This evolution emphasizes the need for a unified, interdisciplinary approach. The session starts with an analysis of how agentic LLMs have been seamlessly integrated into existing healthcare frameworks, notably enhancing the accuracy and efficiency of disease prognosis and diagnosis. Specific case studies, such as the use of these models in diagnosing acute ischemic stroke, highlight how agentic LLMs are instrumental in critical health domains. Acute ischemic stroke, a leading cause of disability and mortality worldwide, requires rapid and accurate diagnosis to initiate timely intervention, which can significantly reduce long-term disabilities and improve outcomes. This illustrates the crucial role of agentic LLMs in improving diagnostic accuracy and refining medical decision-making processes. The objective of this presentation is to provide a rigorous academic perspective on the potential and current applications of agentic LLMs in healthcare. It aims to foster a comprehensive understanding of their impact on the future trajectory and developmental prospects of medical AI.

Taichung Veterans General Hospital (TCVGH) has been recognized as the only hospital in Taiwan to be listed in Newsweek's top 300 World's Best Smart Hospitals in 2023 (Ranking #254) and 2024 (Ranking #246). By the survey of Healthcare Information Management System Society (HIMSS) of United States, Taichung Veterans General Hospital (TCVGH) is the Second Highest Global Ranking of DHI (Digital Healthcare Indicator) Score in 2024. TCVGH was also the first National Medical Center in Taiwan to achieve HIMSS EMRAM Stage 6 and 7 validations in 2023, it takes only 8 months, also created the fastest record in Taiwan. In the National Recognition of Taiwan, Taichung Veterans General Hospital (TCVGH) is the first hospital in Taiwan to Achieve 3 Times of Smart Hospital Award (2015, 2019 and 2023). Taichung Veterans General Hospital (TCVGH) also deployed hospital information system to 12 Regional Branch Veterans Hospitals around Taiwan. In this session, we will introduce Digital Strategy, Hospital Information System, and some innovations of Smart Hospital."

Jubo is a leading SaaS provider for nursing information systems. Its solutions have been successfully implemented in over 1,200 long-term care facilities across Taiwan, Canada, and the United States. Dr. Kang, the founder of Jubo, will introduce four key AI technologies embedded in Jubo’s solution, each designed to support and enhance the work of nursing professionals. The first AI focuses on detecting abnormalities in vital signs, ensuring timely interventions. The second AI is dedicated to wound detection, aiding in accurate and early diagnosis. The third AI automatically summarizes nursing records between shifts, streamlining communication and reducing errors. The fourth AI aims to reduce the time nurses spend on family communication, allowing them to focus more on patient care. In his presentation, Dr. Kang will share insights from both an academic and commercial perspective. He will discuss his experiences in integrating AI into nursing practice and the impact of these technologies on the healthcare industry.

Ministry of Education's AI English Speaking Inspirational Game Ministry of the Interior's Big Data AI Code Generation Ministry of the Environment AI Air Pollution Tracing Ministry of Agriculture AI Legislative Inquiry and Response Ministry of Digital Affairs Government Plan AI-Assisted Review Practical Experiences in Developing Government AI

MediaTek Research is dedicated to the research and development of LLMs, with a particular focus on Traditional Chinese. In March 2023, we open-sourced the first LLMs for Traditional Chinese. In October 2023, we released the first comprehensive benchmark for Traditional Chinese LLMs. At the beginning of 2024, we open-sourced new Traditional Chinese LLMs, including Breeze-7B and BreeXe-8x7B. Breeze outperforms other models of the 7B-level in Chinese, while BreeXe performs on par with GPT-3.5 in both English and Traditional Chinese. MediaTek Research will continue to advance technology and support the Taiwan community through open-sourcing. In this talk, I will share with you Breeze 2.0, our new model featuring API capabilities and other development-oriented enhancements.