Hong Kong Machine Learning Season 6 Episode 2
22.03.2024 - Hong Kong Machine Learning - ~3 Minutes
When?
- Friday, March 22, 2024 from 6:30 PM to 9:30 PM (Hong Kong Time)
Where?
- This HKML Meetup is hosted at Amazon AWS, Tower 535, 535 Jaffe Road, Causeway Bay, Hong Kong.
Thanks to Vahid Asghari (HKML) and Amy Wong (Amazon AWS) for helping making this event a success!
The page of the event on Meetup: HKML S6E2
The page of the event by Amazon AWS
Programme:
Talk 1: Leveraging generative AI to identify potential anomalies before they escalate into critical issues
Speaker: Jason Li is a data scientist, specialising in predictive maintenance and vibration analysis. With a background in machine learning and deep learning, Jason has developed advanced models to support these projects. Jason holds a degree and master’s from the Chinese University of Hong Kong (CUHK), where they honed their skills and expertise in data science and engineering.
Talk 2: Pie & AI: Hong Kong - Prompt engineering + LangChain
Speaker: Cyrus Wong is Senior Lecturer of Hong Kong Institute of Information Technology (HKIIT) at Lee Wai Lee. He is AWS Hero since 2016 and actively promotes the use of AWS in different media and events. His projects have received four Hong Kong ICT Awards in 2014, 2015, 2016, 2020 and all winning projects are running solely on AWS using Data Science and Machine Learning services. Cyrus also helps to deliver the full-time course “Higher Diploma in Cloud and Data Centre Administration”, which is the first tertiary course in Asia dedicated to providing Cloud Technology training. The course is committed to providing AWS Academy training to Hong Kong students and Cyrus is the world first AWS Academy Accredited Trainer. He incorporates AI/ML into his daily curriculum and often writes about projects.
Talk 3: Benchmarking Interactive Large Language Models: Advances and Challenges
Abstract: The emergence of interactive large language models (LLMs) has marked a significant milestone in technology, seamlessly integrating into the daily lives of users with remarkable performance and rapid evolution. Initially, the capabilities and limitations of LLMs were ambiguous to both the public and the academic community. This presentation will introduce a pioneering evaluation framework that conducted a comprehensive technical assessment of LLMs, focusing on their multi-task and reasoning abilities. It will also overview current benchmarking trends and the latest advancements in LLMs, emphasizing the importance of user comprehension of these benchmarks. Additionally, the talk will discuss ongoing challenges within the domain of LLMs, highlighting critical areas for user awareness and engagement.
Speaker: Yejin Bang is a Ph.D. Candidate at the Center for AI Research (CAiRE) at The Hong Kong University of Science and Technology (HKUST), specializing in Natural Language Processing (NLP) and Responsible AI. Her research encompasses Large Language Model (LLM) Evaluation, Human Value Alignment, and AI Safety. She has made notable contributions, including projects on multitask, multilingual, and multimodal ChatGPT evaluations, framing bias reduction through neutral multi-news summarization, and few-shot fact-checking. Yejin’s work has been recognized at key conferences such as EMNLP, NAACL, AACL, and AAAI, with a strong focus on safety, bias, and ethics in AI. Significantly, her work was selected for the Top 100 AI Contributions of 2022-2023 by BenchCouncil. Yejin earned her Bachelor’s degree in Computer Science.
Talk 4: Introduction & Demo of Amazon Bedrock
Speaker: Haowen Huang, a senior developer advocate at AWS based in Hong Kong, brings over 20 years of experience in cloud computing, internet, and telecommunications industries. His research focuses on Generative AI, Large Language Models (LLMs), machine learning, and data science.