由於雲端已累積個人、企業乃至國家產出的大數據(Big Data)，善用殺手級應用(Killer application)工具，界接人工智慧(Artificial intelligence)模型，則可推動更經濟效益
、普惠易用及無所不在的運用範疇。
本課程首先介紹遷移式學習(Transfer Learning)、強化學習及貝爾曼方程式(Bellman Equation)、GAN生成對抗網路及自注意力(Self-attention)機制，分別應用在:辨識物
件擴充至其他物件、機器人走迷宮、概念生成實際文本、設計圖暨影像及OpenAI Sora的架構，俾令學生對現今關鍵人工智慧里程碑有初步了解。
其次，應用場域來到金融財富管理，含括其他產業，例如:流行音樂、醫學癌症研究、生物基因定序、電動汽車及智慧生成程式設計等。最後，因應半導體製程已經細分至
2奈米以下，傳統做法已不可行，為克服人工智慧未來發展瓶頸，導讀量子電腦與量子計算（Quantum Computing）基礎知識，從未來看現在，提升學生未來職場勝率。
本課程綜整人工智慧的數學基礎與實作場景，讓同學在動手操作的樂趣中享受人工智慧應用之方便與效益，從而引發強烈研究動機與啟發，並研讀國內外SCI/SSCI/EI人
工智慧相關應用文章，有助於後續論文內涵之發展完成。
《 課程簡介 -- English 》
Since the cloud has accumulated big data (Big Data) generated by individuals, enterprises and even countries, making good use of killer application (Killer application) tools and connecting with artificial intelligence (Artificial intelligence) models can promote more economic benefits, inclusiveness and ease of use. Usable and ubiquitous application areas.
This course first introduces transfer learning, reinforcement learning and Bellman Equation, GAN generative adversarial network and self-attention mechanism, which are respectively used in: extending the recognition of objects to other objects, The robot walks through the maze, concept generation actually produces text, design drawings and images, and the architecture of OpenAI Sora, giving students a preliminary understanding of today's key artificial intelligence milestones.
Secondly, the application field comes to financial wealth management, including other industries, such as: pop music, medical cancer research, biological gene sequencing, electric vehicles and intelligent generative programming, etc. Finally, as the semiconductor manufacturing process has been subdivided to below 2 nanometers, traditional methods are no longer feasible. In order to overcome the bottleneck of the future development of artificial intelligence, this article introduces the basic knowledge of quantum computers and quantum computing (Quantum Computing), looks at the future from the present, and improves students' future workplace. winning percentage.
This course comprehensively integrates the mathematical foundation and practical scenarios of artificial intelligence, allowing students to enjoy the convenience and benefits of artificial intelligence applications in the fun of hands-on operation, thus triggering strong research motivation and inspiration, and studying domestic and foreign SCI/SSCI/EI artificial intelligence Relevant application articles will help to develop and complete the connotation of subsequent papers.
|