AIn't What It Used to Be

Friday, July 21, 2023

7/28/23: TE defense

Machine Learning Study Group

Welcome! We start at 4:00, and go for 40 minutes. New members are always welcome and anyone can join. You may attend any or all sessions. 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 73rd meeting, July 28, 2023.
MSIS defense (TE)

Title: A Customer Service Chatbot Using Python and Machine Learning
Abstract: The report shows that with the most recent advancements in artificial intelligence and natural language processing using generative-pretrained transformers, we can develop robust AI applications to assist customer service departments with question answer systems. This paper takes look at some of the related work that has been done in the question answer task using OpenAIs APIs. This report also examines how I was able to create an AI question answer application using my own documents that generated correct answers to my questions about those documents. I used two different approaches to create the question answer system. One was to use just the OpenAI APIs. The other was to use the LangChain framework and libraries. Both applications did answer my questions correctly. LangChain used less code with a higher learning curve. OpenAI APIs used more code with more detailed answer results.
Congratulations! It's a pass.

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.

6/30/23: We finished https://openai.com/research/gpt-4 about GPT-4!
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.

Monday, July 17, 2023

7/21/23: BERT Presentation and Discussion

Machine Learning Study Group

Agenda & Minutes

Welcome to the 72nd meeting, July 21, 2023.
BERT. Discussion led by DD.

The meeting ended here.

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.

6/30/23: We finished https://openai.com/research/gpt-4 about GPT-4!
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.

Wednesday, July 12, 2023

7/14/23: Guest speaker!

Machine Learning Study Group

Welcome! We start at 4:00, and 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 71st meeting, July 14, 2023.
Guest speaker with Q & A. It's informal, and sometimes basic questions are the most illuminating, so go ahead and ask whatever questions you might have!

The meeting adjourned here.

-----

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.

6/30/23: We finished https://openai.com/research/gpt-4 about GPT-4!
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.

Friday, July 7, 2023

7/7/23: Hugging Face lab (ending a 3-week quasi-cycle)

Machine Learning Study Group

Welcome! We start at 4:00. 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 70th meeting, July 7, 2023.
Status updates/news/inputs/comments

Student and project updates?
Schedule of activities:

Today: Hugging Face (week 3 of the 3-week quasi-cycle)
Following week (7/14): part of 3-week rotation -- week 1 of 3, readings
Week after that (7/21): EG informally presents a draft paper for our information, comments and suggestions
Week after that (7/28): back to the 3-week rotation -- week 2 of 3, Hugging Face

Any other updates/news/inputs or comments?

Status of the threads of activity:

To continue with the Huggingface lab program, last time we worked on chapter 1, part 3, https://huggingface.co/learn/nlp-course/chapter1/3?fw=tf. After the first paragraph we went to the collab link where we worked on that, starting to experiment with the code window
from transformers import pipeline

generator = pipeline("text-generation", model="distilgpt2")
generator(
"In this course, we will teach you how to",
max_length=30,
num_return_sequences=2,
)
Next time we can experiment a bit more and then go on from there.

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.

6/30/23: We finished https://openai.com/research/gpt-4 about GPT-4!
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.

Friday, June 30, 2023

6/30/23: Student presentation, etc.

Machine Learning Study Group

Agenda & Minutes

Welcome to the 69th meeting, June 30, 2023.
Status updates/news/inputs/comments

Student and project updates?
Schedule of activities:

Today: SR presentation; finish a reading
Next week (7/7): Hugging Face #2 (week 3 of the 3-week quasi-cycle)
Following week (7/14): part of 3-week rotation -- week 1 of 3, readings
Week after that (7/21): EG informally presents a draft paper for our information, comments and suggestions
Week after that (7/28): back to the 3-week rotation -- week 2 of 3, Hugging Face

Any other updates/news/inputs or comments?

SR will present his work today (then back to week 3 of the 3-week cycle next week)
Status of the threads of activity:

To continue with the Huggingface lab program, last time we worked on chapter 1, https://huggingface.co/learn/nlp-course/chapter1/1?fw=tf, finished that page, clicked "next" to go to https://huggingface.co/learn/nlp-course/chapter1/2?fw=tf and read that, then "next" again to go to part 3, https://huggingface.co/learn/nlp-course/chapter1/3?fw=tf, read the first paragraph and went to the collab link where we worked through that through the code window
classifier(
["I've been waiting for a HuggingFace course my whole life.", "I hate this so much!"]
)
Next time we work on this we could start right after that.

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.

6/30/23: We finished https://openai.com/research/gpt-4 about GPT-4!
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.

Friday, June 23, 2023

6/23/23: Hugging Face again

Machine Learning Study Group

Agenda & Minutes

Welcome to the 68th meeting, June 23, 2023.
Status updates/news/inputs/comments

Student and project updates?

SR can present his own work next week

Any other updates/news/inputs or comments?

Today is week 2 of a new 3-week cycle of: background reading one week, Huggingface prep/discuss the next week, and lab exercise in the 3rd week. No one is really needed to "lead," we think/hope.

Our last background reading session (last week, 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 proceeded from there today and got up to the section "API."
To continue with the Huggingface lab program, last time we worked on this (2 weeks ago), 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. Today, we finished that page, clicked "next" to go to https://huggingface.co/learn/nlp-course/chapter1/2?fw=tf and read that, then "next" again to go to part 3, https://huggingface.co/learn/nlp-course/chapter1/3?fw=tf, read the first paragraph and went to the collab link where we worked through that through the code window
classifier(
["I've been waiting for a HuggingFace course my whole life.", "I hate this so much!"]
)
Next time we work on this we could start right after that.

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.

Friday, June 16, 2023

6/16/23: Background reading

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 67th meeting, June 16, 2023.
Status updates/news/inputs/comments

Student and project updates?
Any other updates/news/inputs or comments?

We are starting week 1 of a new 3-week cycle of: background reading one week, Huggingface prep/discuss the next week, and lab exercise in the 3rd week. No one is really needed to "lead," we think/hope.

Our last background reading session (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 proceeded from there today and got up to the section "API."
Last week 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).

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.