6/9/23: End 3-week cycle with week 2 of Huggingface

 

 Machine Learning Study Group

Welcome! We start at 4:00 (or as soon as the weekly seminar is over and people have logged in). Zoom automatically ends the meeting after 40 minutes. New members are always welcome and anyone can join. You may attend any or all sessions. Also feel free to ask to be removed from the invite list at any time, as we have no wish to send unneeded emails which we all certainly get too many of.

 

Agenda & Minutes

 

• Welcome to the 66th meeting, June 9, 2023.
• Status updates/news/inputs/comments
• Student and project updates?
• Any other updates/news/inputs or comments?

• We are finishing a 3-week cycle of: background reading one week, Huggingface prep/discuss the next week, and lab exercise the following week, then repeating the cycle. No one is really needed to "lead," we think/hope.
  
• For the Huggingface lab session this week (week 3 of the 3-week cycle), we reviewed https://huggingface.co/learn/nlp-course/chapter0/1?fw=tf using Colab. Then, we started on chapter 1, https://huggingface.co/learn/nlp-course/chapter1/1?fw=tf, and got through the initial video. We can start at that point next time we work on this (which will be in two weeks, at week 2 in the next 3-week cycle).
  
• Our last general reading (for week 1 of the 3-week cycle) was from https://openai.com/research/gpt-4 about GPT-4. We got up to the section "Predictable scaling." We will proceed from there next time we get to this article, which will be next week (which will be week 1 of the next 3-week cycle).
  
• Here are some other things we could choose to read from in the future.
  
• At some point we can discuss and vote on other sources. See the list on the page of sources. Also Youtube is full of videos about neural nets, transformers, etc.
• MC suggested: Sparks of Artificial General Intelligence: Early experiments with GPT-4 (https://arxiv.org/abs/2303.12712). We read the abstract to decide whether to read the article. The group's evaluation was 3 6/7 out of 5 to read it.

• Readings/videos/demos we have finished. 
• 2/17/23; "Deep Learning for AI" by Bengio, LeCun and Hinton, the Turing Award Lecture paper for 2018, published in CACM, 2021, https://dl.acm.org/doi/pdf/10.1145/3448250.
  
• ChatGPT Is a Tipping Point for AI (Harvard Business Review). Finished 1/27/23.
• 12/16/22: We demoed ChatGPT.
• 11/4/22: We viewed and discussed a transformers video: https://www.youtube.com/watch?v=TQQlZhbC5ps first. This seemed to be one of the better videos of the many out there.
• Transformers From Scratch," https://e2eml.school/transformers.html. Finished on 10/28/22.
• The Narrated Transformer Language Model, Jay Alammar, https://www.youtube.com/watch?v=-QH8fRhqFHM, finished 7/22/22.
• https://www.youtube.com/watch?v=F1X4fHzF4mQ. Finished 8/26/22.
  
• We also finished other things from before this list of finished sources was created to keep a record of them.