3/1/24: Discuss a potential research direction

Machine Learning Study Group

Welcome! We meet from 4:00-4:40 p.m. Central Time. Anyone can join. Feel free to attend any or all sessions, or ask to be removed from the invite list as we have no wish to send unneeded emails of which we all certainly get too many.

 Contacts: jdberleant@ualr.edu and mgmilanova@ualr.edu

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Agenda & Minutes

103rd meeting, Mar. 1, 2024

• Updates, announcements, questions, etc.?
• Discussion about ED's proposed research direction.
• Next time we do this I will take notes to put in the minutes for future reference. Also this would be a good use of read.ai.
  

The meeting ended here.

 

• Readings: We are reading
  
• Sparks of Artificial General Intelligence: Early experiments with GPT-4 (https://arxiv.org/abs/2303.12712).
• We will start with "Throughout the paper we emphasize limitations"
• Here is a Youtube video about the article: https://www.youtube.com/watch?v=qbIk7-JPB2c (found by IE)
• Here is a video about Geoff Hinton: https://www.youtube.com/watch?v=qrvK_KuIeJk
• We have read chapter 1 part 4: https://huggingface.co/learn/nlp-course/chapter1/4 up to "Note that the first attention layer in a decoder block pays attention to" and we can start from there.
• Suggested viewings/readings on LAMs (Large Action Models) we could evaluate:
  
• https://www.youtube.com/watch?v=22wlLy7hKP4&t=91s&ab_channel=rabbit
• https://www.youtube.com/watch?v=UOZqFMxRpWE&ab_channel=ExitsMedia
• https://www.youtube.com/watch?v=Rqh6fhcAqpw&ab_channel=ColdFusion
• https://www.youtube.com/watch?v=uJnhh7YSr5Q&ab_channel=TheAIGRID
• https://medium.com/version-1/the-rise-of-large-action-models-lams-how-ai-can-understand-and-execute-hum

• Nvidia training materials
• We could go through some of these. MM has a license for free course/resource access. See https://www.nvidia.com/en-us/training/online/.

2/23/24: Continue reading "Sparks of Artificial General Intelligence ..."

 

Machine Learning Study Group

Welcome! We meet from 4:00-4:40 p.m. CT. Anyone can join. Feel free to attend any or all sessions, or ask to be removed from the invite list as we have no wish to send unneeded emails of which we all certainly get too many.

 Contacts: jdberleant@ualr.edu and mgmilanova@ualr.edu

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Agenda & Minutes

102nd meeting, Feb. 23, 2024

• Updates, announcements, questions, etc.?
• Readings: 
• We viewed and discussed a video about Geoff Hinton: https://www.youtube.com/watch?v=qrvK_KuIeJk
• Sparks of Artificial General Intelligence: Early experiments with GPT-4 (https://arxiv.org/abs/2303.12712).
• We are up to "Throughout the paper we emphasize limitations"
• Here is a Youtube video about the article: https://www.youtube.com/watch?v=qbIk7-JPB2c (found by IE)
• We have read chapter 1 part 4: https://huggingface.co/learn/nlp-course/chapter1/4 up to "Note that the first attention layer in a decoder block pays attention to" and we can start from there.
• Suggested viewings/readings on LAMs (Large Action Models) we could evaluate:
  
• https://www.youtube.com/watch?v=22wlLy7hKP4&t=91s&ab_channel=rabbit
• https://www.youtube.com/watch?v=UOZqFMxRpWE&ab_channel=ExitsMedia
• https://www.youtube.com/watch?v=Rqh6fhcAqpw&ab_channel=ColdFusion
• https://www.youtube.com/watch?v=uJnhh7YSr5Q&ab_channel=TheAIGRID
• https://medium.com/version-1/the-rise-of-large-action-models-lams-how-ai-can-understand-and-execute-hum

• Nvidia training materials
• We could go through some of these. MM has a license for free course/resource access. See https://www.nvidia.com/en-us/training/online/.

2/16/24: Reading of "Sparks of Artificial General Intelligence ..."

Machine Learning Study Group

Welcome! We meet from 4:00-4:40 p.m. CT. Anyone can join. Feel free to attend any or all sessions, or ask to be removed from the invite list as we have no wish to send unneeded emails of which we all certainly get too many.

 Contacts: jdberleant@ualr.edu and mgmilanova@ualr.edu

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Agenda & Minutes

101st meeting, Feb. 16, 2024

 

• Updates, announcements, questions, etc.?
• Readings: We are reading
  
• Sparks of Artificial General Intelligence: Early experiments with GPT-4 (https://arxiv.org/abs/2303.12712).
• We continued where it says "However, impressive outputs are not enough to convince us that". Next time start with "Throughout the paper we emphasize limitations"
• Here is a Youtube video about the article: https://www.youtube.com/watch?v=qbIk7-JPB2c (found by IE)
  
• We have read chapter 1 part 4: https://huggingface.co/learn/nlp-course/chapter1/4 up to "Note that the first attention layer in a decoder block pays attention to" and we can start from there.
• Suggested viewings/readings on LAMs (Large Action Models) we could evaluate:
  
• https://www.youtube.com/watch?v=22wlLy7hKP4&t=91s&ab_channel=rabbit
• https://www.youtube.com/watch?v=UOZqFMxRpWE&ab_channel=ExitsMedia
• https://www.youtube.com/watch?v=Rqh6fhcAqpw&ab_channel=ColdFusion
• https://www.youtube.com/watch?v=uJnhh7YSr5Q&ab_channel=TheAIGRID
• https://medium.com/version-1/the-rise-of-large-action-models-lams-how-ai-can-understand-and-execute-hum

• Nvidia training materials
• We could go through some of these. MM has a license for free course/resource access. See https://www.nvidia.com/en-us/training/online/.

2/9/24: NVIDIA training (MM)

Machine Learning Study Group

Welcome! We meet from 4:00-4:45 p.m. CT. Anyone can join. Feel free to attend any or all sessions, or ask to be removed from the invite list as we have no wish to send unneeded emails of which we all certainly get too many.

 Contacts: jdberleant@ualr.edu and mgmilanova@ualr.edu

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Agenda & Minutes

100th(!) Meeting, Feb. 9, 2024

 🎉🎉

• Updates, announcements, questions, etc.?

• MM writes: "Some students asked me to share the link and the [access] code. Using the code, any course will be $0.00. I think I need to show next time how we can use the code. [...] There are many resources (https://www.nvidia.com/en-us/training/online/)."

  • Today MM will explain more about this.
  
  
• Suggested viewings/readings on LAMs (Large Action Models) we could evaluate:
  
• https://www.youtube.com/watch?v=22wlLy7hKP4&t=91s&ab_channel=rabbit
• https://www.youtube.com/watch?v=UOZqFMxRpWE&ab_channel=ExitsMedia
• https://www.youtube.com/watch?v=Rqh6fhcAqpw&ab_channel=ColdFusion
• https://www.youtube.com/watch?v=uJnhh7YSr5Q&ab_channel=TheAIGRID
• https://medium.com/version-1/the-rise-of-large-action-models-lams-how-ai-can-understand-and-execute-hum

• Readings: We are reading
  
• Sparks of Artificial General Intelligence: Early experiments with GPT-4 (https://arxiv.org/abs/2303.12712).
• We can continue where it says "However, impressive outputs are not enough to convince us that"
• We earlier read chapter 1 part 4: https://huggingface.co/learn/nlp-course/chapter1/4 up to "Note that the first attention layer in a decoder block pays attention to" and we can start from there.
  
• Last time
  
• DA  - brainstorming about topics. IK suggests checking https://github.com/meagmohit/EEG-Datasets. Maybe it is time to do a literature search and find similar works and what they are achieving and what the open problems are.

 

 

2/2/24: Readings (from HuggingFace)

Machine Learning Study Group

Welcome! We meet from 4:00-4:45 p.m. CT. Anyone can join. Feel free to attend any or all sessions, or ask to be removed from the invite list as we have no wish to send unneeded emails of which we all certainly get too many.

 Contacts: jdberleant@ualr.edu and mgmilanova@ualr.edu

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Agenda & Minutes

99th Meeting, Feb. 2, 2024

• Updates, announcements, questions, etc.?
• Readings: We are reading
  
• Sparks of Artificial General Intelligence: Early experiments with GPT-4 (https://arxiv.org/abs/2303.12712).
• We can continue where it says "However, impressive outputs are not enough to convince us that"
• We earlier read chapter 1 part 4: https://huggingface.co/learn/nlp-course/chapter1/4 up to "Note that the first attention layer in a decoder block pays attention to" and we can start from there next time.
  
• Last time
  
• DA  - brainstorming about topics. IK suggests checking https://github.com/meagmohit/EEG-Datasets. Maybe it is time to do a literature search and find similar works and what they are achieving and what the open problems are