Applied ML: LLMs and Knowledge Graphs
When: Friday, May 24th
Time: 18:00-21:00
Where: Akkodis, 3F
Welcome to TAI's first Applied ML and AI (AMA) Talk!
AMAs will focus on the technical side of applied machine learning (selecting the right algorithms, training models, model evaluations, etc.).
In other words: the practical implementation of machine learning techniques to solve real-world problems.
Topic
This first AMA will feature three 30-minute talks, and one 20-minute talk, with some Q&A and networking afterward. In this session, we'll be exploring LLMs and Knowledge Graphs.
Akkodis Introduction - Takuhiro Maeda, Executive Director.
Speaker 1 - Mohamed Haggag - "LLMs Without Jargon."
Speaker 2 - Marko Simic - "RAGs and Knowledge Graphs."
Speaker 3 - Kyle Liu - "Semantic Search Consideration at Mercari."
Speaker 4 - Chan-jun Park - "The Ecosystem of LLMs from a Real-World Perspective."
TAI fosters a vibrant and cohesive AI ecosystem in Tokyo by hosting an array of technical and accessible meetups focused on Artificial Intelligence (AI) and Machine Learning (ML). By hosting gatherings in both English and Japanese, we bridge communities, facilitate knowledge exchange, and nurture innovation, ensuring Tokyo emerges as a formidable force in the global AI landscape.
Organizers
Kaitlan Melone: General Manager at the AI Industry Foundation, and co-organizer of the recent TAIS Conference 2024, Kaitlan is currently working on building a referral and knowledge sharing network in the AI industry.
Colin Rowat: Colin is a research scientist in Rakuten's Institute of Technology. Previously, he has worked at quant finance company G-Research, the University of Birmingham, including as a Fellow of the Turing Institute. He has founded a fintech, and helped develop the world's cheapest BCI.