Description
The recent advancements in large language models (LLMs) have significantly enhanced their capabilities, leading to a paradigm shift in how AI can be integrated into our society. This is particularly evident in the case of ChatGPT, including the latest iteration, GPT-4. It is intriguing how the straightforward approach of Transformer models trained on massive datasets has achieved such remarkable progress, which should pique our interest on both conceptual and technical levels.
This mini-workshop aims to provide tutorial-style talks introducing the technology behind GPT-4 and discussing its implications for society. The technical talks are tailored for researchers in the field of AI.
The workshop was held as follows:
Day 1 – June 30th
Day 2 – July 3rd
(*This video includes 4 talks for Day1.)
Time: 2:30 p.m. – 4:10 p.m. (JST)
00:00:07 Speaker: Matthias Weissenbacher
Title: Opening Remarks: Transformers and the Power of GPT4
00:25:32 Speaker: Noriki Nishida
Title: Introductory Talk: Standard supervision vs. context learning in NLP
01:04:03 Speaker: Benjamin Heinzerling
Title: Why can LMs learn in-context? An overview of current theories
01:34:31 Speaker: Koiti Hasida
Title: Future R&D directions of generative AI & social impacts
Presentation Document PDF(1.88MB)
