⏱️ 09/28 (Sat.) 13:00-13:30 at R0 - International Conference Hall
大型語言模型(LLM)的快速發展為各行各業帶來了重大機遇,但其成功部署需奠基於任務設計、資料集創建與評測這三大核心工作。基於我在 TAIDE 第一、二期計畫中的經驗,本次演講將深入探討在推動 LLM 落地過程中所面臨的挑戰,如如何確保資料品質和提升模型的可擴展性,並分享我們如何克服這些挑戰的具體方法。這些工作對於確保 LLM 能夠在不同領域實現擴展和應用至關重要。透過健全的資料集建設、有效的任務設計與嚴謹的評測,台灣正逐步邁向成為全球 AI Foundry 的目標,推動創新與技術領導力。本次討論也將闡明這些關鍵步驟如何為各行業及社會帶來深遠影響。
The rapid development of Large Language Models (LLMs) offers significant opportunities across industries, but their deployment relies on a strong foundation in task design, dataset creation, and evaluation. Based on key insights from the first and second phases of the TAIDE project, this talk will highlight the specific challenges we faced, such as ensuring data quality and scalability, and how we addressed them. These foundational efforts are crucial for scaling LLMs and ensuring practical applications in various sectors. By focusing on building robust datasets, designing impactful tasks, and establishing rigorous evaluation frameworks, Taiwan is well-positioned to accelerate its journey towards becoming a global AI Foundry, driving forward both innovation and leadership. This talk will also explore how these critical steps create far-reaching benefits, not only for industries but also for society as a whole.
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Dr. Richard Tzong-Han Tsai is an expert in model training for the TAIDE project under Taiwan's National Science and Technology Council. He currently serves as the President of the Taiwanese Association for Digital Humanities and the Vice President of the Taiwanese Association for Artificial Intelligence. He is also a Research Fellow at Academia Sinica’s Research Center for Humanities and Social Sciences, a Professor in the Department of Computer Science at National Central University, and an adjunct professor at National Taiwan University’s Graduate Institute of Linguistics. His areas of expertise include natural language processing, artificial intelligence, and digital humanities, with a track record of publishing several papers annually at top-tier international conferences, including ACL, EMNLP, and COLING.
Dr. Tsai holds a Bachelor's to Ph.D. degree in Computer Science from National Taiwan University. He was awarded the Google Research Award in 2023 and 2024 and has led his teams to victory in the BioCreative competition organized by the National Institutes of Health (NIH) in 2021, as well as the BioASQ international biomedical question-answering competition from 2020 to 2023, hosted by multiple global research institutions. Additionally, he has been honored with the Outstanding Research Award at National Central University in 2020, 2021, and 2023.
Beyond his academic contributions, Dr. Tsai is the author of popular science books on AI for young students, including "AI Lessons for Middle Schoolers" and "AI Lessons for Elementary Students," both of which have become bestsellers and received multiple educational awards and recommendations, including the 12th Wu Ta-You Science Popularization Award for Youth Science Education, the Taipei Public Library's Monthly Book Selection, and the 2023 Hong Kong Education City's Teacher Recommendation Award. Due to his contributions to the development of generative AI (Gen AI) in Taiwan, Dr. Tsai was selected by CommonWealth Magazine as one of the AI 20 in 2024.
蔡宗翰教授是台灣國家科學技術委員會 TAIDE 專案的模型訓練組專家,現任台灣數位人文學會理事長與台灣人工智慧學會副理事長。蔡教授同時擔任中央研究院人文社會科學研究中心研究員、中央大學資訊工程系教授,以及台灣大學語言學研究所合聘教授。他的專長包括自然語言處理、人工智慧與數位人文,在這些領域中每年都有多篇頂尖國際會議論文發表,包括 ACL、EMNLP 和 COLING。
蔡教授擁有台灣大學資訊工程學士至博士學位,並於 2023 年及 2024 年連續獲得 Google Research Award。他帶領的團隊曾在 2021 年獲得由美國國立衛生研究院(NIH)主辦的 BioCreative 競賽冠軍,並於 2020 至 2023 年間連續獲得由多國科研機構主辦的 BioASQ 國際生醫問答系統競賽冠軍。此外,他在 2020、2021 及 2023 年榮獲中央大學研究傑出獎。
除了學術研究外,蔡教授還是多本科普書籍的作者,包括「寫給中學生看的 AI 課」及「寫給小學生看的 AI 課」,這些書籍不僅在博客來暢銷,還榮獲第十二屆吳大猷科學普及著作獎青少年科普特別推薦獎、臺北市立圖書館「每月一書」、2023 年香港教育城中學教師推薦好讀獎等多項教育獎項及推薦。由於蔡教授對台灣生成式人工智慧(Gen AI)發展的貢獻,他被天下雜誌選為 2024 年的 AI 20 之一。
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