Friday, October 3, 2025

10/3/25: Discussions

Artificial Intelligence Study Group

Welcome! We meet from 4:00-4:45 p.m. Central Time on Fridays. 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

Agenda, Minutes & Status (181st meeting, Oct. 3, 2025)

Table of Contents
* Agenda and minutes
* Appendix: Transcript (when available)

Agenda and Minutes
  • Announcements
    • Today: 
      • EG: will tell us about prompt configuration next time on ChatGPT for a few minutes or whatever it takes.
      • LG (book project): has schedule conflict.
      • GE will demo locally hosted LLMs and Ollama on Oct. 17.
    • On 9/8/2025, Blackboard said: 
      • "This release introduces improvements in instructional design and assessment grading: 
        • AI-Powered Feedback Summaries: Instructors can use the new Summarize option when grading assessments to generate AI-driven overall feedback based on the graded rubric, with options to edit, accept, reject, or regenerate."
    • Dept. of Psychological Science is sponsoring a monthly colloquium which will often feature something AI-related, starting Oct. 17, 12-1 p.m. First meeting: FRIDAY, OCTOBER 17, 12-1 pm, feel free to brownbag it*. Where: Stabler Hall 502
    • Some time? MM may lead us in one of the short NVIDIA courses to us (see list at https://nvdam.widen.net/s/brxsxxtskb/dli-learning-j)
    • Teaching with AI meetings (organized by ES), biweekly, Mondays, 4 p.m., starting 9/29/25, at https://ualr-edu.zoom.us/j/83928282737.
  • Updates
    • LG. Book writing project update.
      • 9/18/25: has defined various Gemini agents or apps and is experimenting with them.
      • Topic of book will likely be: personal investing.
      • Committee: DB, MM, RS
      • Need to keep a log of activities and results, to become the final report. 
    • DD. Research
    • course updates?  
  • Other 
    • Possible activity: Invite paper authors to host a study session on the abstract and first several paragraphs of a paper they published or plan to submit.
    • Any questions you'd like to bring up for discussion, just let me know.
    • Anyone read an article recently they can tell us about next time?
    • Any other updates or announcements?
  • Readings/viewings for discussion. Here is the latest on future readings and viewings. Let me know of anything you'd like to have us evaluate for a fuller reading, viewing or discussion.
    • Evaluated
    • 7/25/25: eval was 4.5 (over 4 people). https://transformer-circuits.pub/2025/attribution-graphs/biology.html.
    • Evaluation was 4.4 (6 people) on 8/8/25: https://transformer-circuits.pub/2025/attribution-graphs/biology.html#dives-refusals
    • 8/22/25: eval. was 4.0 (4 people): Https://www.nobelprize.org/uploads/2024/10/popular-physicsprize2024-2.pdf. 
    • https://arxiv.org/pdf/2001.08361. 5/30/25: eval was 4.0. 7/25/25: vote was 2.5.
    • Evaluation was 3.87 on 8/8/25 (6 people voted): https://venturebeat.com/ai/anthropic-flips-the-script-on-ai-in-education-claude-learning-mode-makes-students-do-the-thinking
    • Evaluation was 3.75 by 6 people on 8/8/25 for: Use the same process as above but on another article.
    • (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
      • Prompt engineering course. 
      • Also at Syllabus page: https://apps.cognitiveclass.ai/learning/course/course-v1:IBMSkillsNetwork+AI0117EN+v1/home. 
      • Registration page: https://apps.cognitiveclass.ai/learning/course/course-v1:IBMSkillsNetwork+AI0117EN+v1/home
      • Requires registering. DD volunteered to register if it is free, so we can check it out briefly and decide if to do the course in detail.
    • Evaluation was 3.5 by 6 people on 8/8/25: Put the following into an AI and interact - ask it to summarize, etc.
      • Towards Monosemanticity: Decomposing Language Models With Dictionary Learning  (https://transformer-circuits.pub/2023/monosemantic-features/index.html); Bricken, T., et al., 2023. Transformer Circuits Thread.
    • We can evaluate https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10718663 for reading & discussion. 7/25/25: vote was 3.25 over 4 people.
    • Not yet evaluated
    • Neural Networks, Deep Learning: The basics of neural networks, and the math behind how they learn, https://www.3blue1brown.com/topics/neural-networks. (We would need to pick a specific one later.)
      • We checked the first one briefly. 8/22/25: eval was 3.625 (from 4 people) for a full viewing.
      • Let's evaluate a few more of them.
    • LangChain free tutorial, https://www.youtube.com/@LangChain/videos. (The evaluation question is, do we investigate this any further?)
    • Chapter 6 recommends material by Andrej Karpathy, https://www.youtube.com/@AndrejKarpathy/videos for learning more. What is the evaluation question? "Someone should check into these and suggest something more specific"?
    • Chapter 6 recommends material by Chris Olah, https://www.youtube.com/results?search_query=chris+olah
    • Chapter 6 recommended https://www.youtube.com/c/VCubingX for relevant material, in particular https://www.youtube.com/watch?v=1il-s4mgNdI
    • Chapter 6 recommended Art of the Problem, in particular https://www.youtube.com/watch?v=OFS90-FX6pg
    • LLMs and the singularity: https://philpapers.org/go.pl?id=ISHLLM&u=https%3A%2F%2Fphilpapers.org%2Farchive%2FISHLLM.pdf (summarized at: https://poe.com/s/WuYyhuciNwlFuSR0SVEt). (Old eval from 6/7/24 was 4 3/7.)
    • Back burner "when possible" items:
        • TE is in the informal campus faculty AI discussion group. 
        • SL: "I've been asked to lead the DCSTEM College AI Ad Hoc Committee. ... We’ll discuss AI’s role in our curriculum, how to integrate AI literacy into courses, and strategies for guiding students on responsible AI use."
        • Anyone read an article recently they can tell us about?
        • The campus has assigned a group to participate in the AAC&U AI Institute's activity "AI Pedagogy in the Curriculum." IU is on it and may be able to provide updates now and then. 
        • Here are projects that MS students can sign up for. If anyone has an idea for an MS project where the student reports to us for a few minutes each week for discussion and feedback - a student might potentially be recruited! Let me know.
          • JH suggests a project in which AI is used to help students adjust their resumes to match key terms in job descriptions, to help their resumes bubble to the top when the many resumes are screened early in the hiring process.
          • JC suggested: social media are using AI to decide what to present to us, the notorious "algorithms." Suggestion: a social media cockpit from which users can say what sorts of things they want. Screen scrape the user's feeds from social media outputs to find the right stuff. Project could be adapted to either tech-savvy CS or application-oriented IS or IQ students.
          • VW had some specific AI-related topics that need books about them.  
          • DD suggests having a student do something related to Mark Windsor's presentation. He might like to be involved, but this would not be absolutely necessary.
            • markwindsorr@atlas-research.io writes on 7/14/2025: Our research PDF processing and text-to-notebook workflows are now in beta and ready for you to try,
              • You can now: 
                • - Upload research papers (PDF) or paste in an arXiv link and get executable notebooks
                • - Generate notebook workflows from text prompts
                • - Run everything directly in our shared Jupyter environment
                • This is an early beta, so expect some rough edges - but we're excited to get your feedback on what's working and what needs improvement.
                • Log In Here: https://atlas-research.io


        



Friday, September 26, 2025

9/26/25: AI and Employment (IS)

Artificial Intelligence Study Group

Welcome! We meet from 4:00-4:45 p.m. Central Time on Fridays. 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

Agenda, Minutes & Status (180th meeting, Sept. 26, 2025)

Table of Contents
* Agenda and minutes
* Appendix: Transcript (when available)

Agenda and Minutes
  • Announcements
    • Today: IS informally presents experiences with AI employment and related items.
    • Dept. of Psychological Science is sponsoring a monthly colloquium which will often feature something AI-related, starting Oct. 17, 12-1 p.m.: 
      • Formats include:
        • presentation+conversation; brainstorming a research idea; test-driving a presentation; getting feedback on data
      • Feel free to bring food or drink please be mindful of others about making noise (wrapping/chewing) and food smells...
      • First meeting: FRIDAY, OCTOBER 17, 12-1 pm, feel free to brownbag it*.
        Where: Stabler Hall 502
    • Next time 
      • LG update on book project.
      • DD will step us through the IBM free prompt course.
    • Some time: MM may lead us in one of the short NVIDIA courses to us (see list at https://nvdam.widen.net/s/brxsxxtskb/dli-learning-j).
    • Th Dec. 11 4:30: Students in YP's AI course will present their projects.
    • Teaching with AI meetings (organized by ES), biweekly, Mondays, 4 p.m., starting 9/29/25, at https://ualr-edu.zoom.us/j/83928282737.
  • Today's activities
    • LG. Book writing project update.
      • 9/18/25: has defined various Gemini agents or apps and is experimenting with them.
      • Topic of book will likely be: personal investing.
      • Committee: DB, MM, RS
      • Need to keep a log of activities and results, to become the final report. 
    •  DD. Described the free prompt course from IBM. Zero-shot prompting, one-shot, few-shot, chain-of-thought (CoT) prompts, tree-of-thought (ToT) prompts, ...
      • Course is at https://apps.cognitiveclass.ai/learning/course/course-v1:IBMSkillsNetwork+AI0117EN+v1/home.
      • Would people like to do this course as an activity during meetings of this group? 
    • Possible activity: Invite paper authors to host a study session on the abstract and first several paragraphs of a paper they published or plan to submit.
    • course updates?  
  • Other 
    • Any questions you'd like to bring up for discussion, just let me know.
      • On 9/8/2025, Blackboard said: 
        • "This release introduces improvements in instructional design and assessment grading: 
        • AI-Powered Feedback Summaries: Instructors can use the new Summarize option when grading assessments to generate AI-driven overall feedback based on the graded rubric, with options to edit, accept, reject, or regenerate."
    • Anyone read an article recently they can tell us about next time?
    • Any other updates or announcements?
  • Readings/viewings for discussion. Here is the latest on future readings and viewings. Let me know of anything you'd like to have us evaluate for a fuller reading, viewing or discussion.
    • Evaluated
    • 7/25/25: eval was 4.5 (over 4 people). https://transformer-circuits.pub/2025/attribution-graphs/biology.html.
    • Evaluation was 4.4 (6 people) on 8/8/25: https://transformer-circuits.pub/2025/attribution-graphs/biology.html#dives-refusals
    • 8/22/25: eval. was 4.0 (4 people): Https://www.nobelprize.org/uploads/2024/10/popular-physicsprize2024-2.pdf. 
    • https://arxiv.org/pdf/2001.08361. 5/30/25: eval was 4.0. 7/25/25: vote was 2.5.
    • Evaluation was 3.87 on 8/8/25 (6 people voted): https://venturebeat.com/ai/anthropic-flips-the-script-on-ai-in-education-claude-learning-mode-makes-students-do-the-thinking
    • Evaluation was 3.75 by 6 people on 8/8/25 for: Use the same process as above but on another article.
    • (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
      • Prompt engineering course. 
      • Also at Syllabus page: https://apps.cognitiveclass.ai/learning/course/course-v1:IBMSkillsNetwork+AI0117EN+v1/home. 
      • Registration page: https://apps.cognitiveclass.ai/learning/course/course-v1:IBMSkillsNetwork+AI0117EN+v1/home
      • Requires registering. DD volunteered to register if it is free, so we can check it out briefly and decide if to do the course in detail.
    • Evaluation was 3.5 by 6 people on 8/8/25: Put the following into an AI and interact - ask it to summarize, etc.
      • Towards Monosemanticity: Decomposing Language Models With Dictionary Learning  (https://transformer-circuits.pub/2023/monosemantic-features/index.html); Bricken, T., et al., 2023. Transformer Circuits Thread.
    • We can evaluate https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10718663 for reading & discussion. 7/25/25: vote was 3.25 over 4 people.
    • Not yet evaluated
    • Neural Networks, Deep Learning: The basics of neural networks, and the math behind how they learn, https://www.3blue1brown.com/topics/neural-networks. (We would need to pick a specific one later.)
      • We checked the first one briefly. 8/22/25: eval was 3.625 (from 4 people) for a full viewing.
      • Let's evaluate a few more of them.
    • LangChain free tutorial, https://www.youtube.com/@LangChain/videos. (The evaluation question is, do we investigate this any further?)

    • Chapter 6 recommends material by Andrej Karpathy, https://www.youtube.com/@AndrejKarpathy/videos for learning more. What is the evaluation question? "Someone should check into these and suggest something more specific"?
    • Chapter 6 recommends material by Chris Olah, https://www.youtube.com/results?search_query=chris+olah
    • Chapter 6 recommended https://www.youtube.com/c/VCubingX for relevant material, in particular https://www.youtube.com/watch?v=1il-s4mgNdI
    • Chapter 6 recommended Art of the Problem, in particular https://www.youtube.com/watch?v=OFS90-FX6pg
    • LLMs and the singularity: https://philpapers.org/go.pl?id=ISHLLM&u=https%3A%2F%2Fphilpapers.org%2Farchive%2FISHLLM.pdf (summarized at: https://poe.com/s/WuYyhuciNwlFuSR0SVEt). (Old eval from 6/7/24 was 4 3/7.)
    • Back burner "when possible" items:
        • TE is in the informal campus faculty AI discussion group. 
        • SL: "I've been asked to lead the DCSTEM College AI Ad Hoc Committee. ... We’ll discuss AI’s role in our curriculum, how to integrate AI literacy into courses, and strategies for guiding students on responsible AI use."
        • Anyone read an article recently they can tell us about?
        • The campus has assigned a group to participate in the AAC&U AI Institute's activity "AI Pedagogy in the Curriculum." IU is on it and may be able to provide updates now and then. 
        • Here are projects that MS students can sign up for. If anyone has an idea for an MS project where the student reports to us for a few minutes each week for discussion and feedback - a student might potentially be recruited! Let me know.
          • JH suggests a project in which AI is used to help students adjust their resumes to match key terms in job descriptions, to help their resumes bubble to the top when the many resumes are screened early in the hiring process.
          • JC suggested: social media are using AI to decide what to present to us, the notorious "algorithms." Suggestion: a social media cockpit from which users can say what sorts of things they want. Screen scrape the user's feeds from social media outputs to find the right stuff. Project could be adapted to either tech-savvy CS or application-oriented IS or IQ students.
          • VW had some specific AI-related topics that need books about them.  
          • DD suggests having a student do something related to Mark Windsor's presentation. He might like to be involved, but this would not be absolutely necessary.
            • markwindsorr@atlas-research.io writes on 7/14/2025: Our research PDF processing and text-to-notebook workflows are now in beta and ready for you to try,
              • You can now: 
                • - Upload research papers (PDF) or paste in an arXiv link and get executable notebooks
                • - Generate notebook workflows from text prompts
                • - Run everything directly in our shared Jupyter environment
                • This is an early beta, so expect some rough edges - but we're excited to get your feedback on what's working and what needs improvement.
                • Log In Here: https://atlas-research.io


        

Friday, September 19, 2025

9/19/25: DD discusses IBM's free short prompting course

Artificial Intelligence Study Group

Welcome! We meet from 4:00-4:45 p.m. Central Time on Fridays. 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

Agenda, Minutes & Status (179th meeting, Sept. 19, 2025)

Table of Contents
* Agenda and minutes
* Appendix: Transcript (when available)

Agenda and Minutes
  • Announcements
    • Today: 
      • LG update on book project.
      • DD will step us through the IBM free prompt course.
    • Next time: MM will invite a former student to describe AI employment, and if not, will provide one of the short NVIDIA courses to us (see list at 
      https://nvdam.widen.net/s/brxsxxtskb/dli-learning-j).
    • Th Dec. 11 4:30: Students in YP's AI course will present their projects.
    • Teaching with AI meetings (organized by ES), biweekly, Mondays, 4 p.m., starting 9/29/25, at https://ualr-edu.zoom.us/j/83928282737.
  • Today's activities
    • LG. Book writing project update.
      • 9/18/25: has defined various Gemini agents or apps and is experimenting with them.
      • Topic of book will likely be: personal investing.
      • Committee: DB, MM, RS
      • Need to keep a log of activities and results, to become the final report. 
    •  DD. Described the free prompt course from IBM. Zero-shot prompting, one-shot, few-shot, chain-of-thought (CoT) prompts, tree-of-thought (ToT) prompts, ...
      • Course is at https://apps.cognitiveclass.ai/learning/course/course-v1:IBMSkillsNetwork+AI0117EN+v1/home.
      • Would people like to do this course as an activity during meetings of this group? 
    • Possible activity: Invite paper authors to host a study session on the abstract and first several paragraphs of a paper they published or plan to submit.
    • course updates?  
  • Other 
    • Any questions you'd like to bring up for discussion, just let me know.
      • On 9/8/2025, Blackboard said: 
        • "This release introduces improvements in instructional design and assessment grading: 
        • AI-Powered Feedback Summaries: Instructors can use the new Summarize option when grading assessments to generate AI-driven overall feedback based on the graded rubric, with options to edit, accept, reject, or regenerate."
    • Anyone read an article recently they can tell us about next time?
    • Any other updates or announcements?
  • Readings/viewings for discussion. Here is the latest on future readings and viewings. Let me know of anything you'd like to have us evaluate for a fuller reading, viewing or discussion.
    • Evaluated
    • 7/25/25: eval was 4.5 (over 4 people). https://transformer-circuits.pub/2025/attribution-graphs/biology.html.
    • Evaluation was 4.4 (6 people) on 8/8/25: https://transformer-circuits.pub/2025/attribution-graphs/biology.html#dives-refusals
    • 8/22/25: eval. was 4.0 (4 people): Https://www.nobelprize.org/uploads/2024/10/popular-physicsprize2024-2.pdf. 
    • https://arxiv.org/pdf/2001.08361. 5/30/25: eval was 4.0. 7/25/25: vote was 2.5.
    • Evaluation was 3.87 on 8/8/25 (6 people voted): https://venturebeat.com/ai/anthropic-flips-the-script-on-ai-in-education-claude-learning-mode-makes-students-do-the-thinking
    • Evaluation was 3.75 by 6 people on 8/8/25 for: Use the same process as above but on another article.
    • (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
      • Prompt engineering course. 
      • Also at Syllabus page: https://apps.cognitiveclass.ai/learning/course/course-v1:IBMSkillsNetwork+AI0117EN+v1/home. 
      • Registration page: https://apps.cognitiveclass.ai/learning/course/course-v1:IBMSkillsNetwork+AI0117EN+v1/home
      • Requires registering. DD volunteered to register if it is free, so we can check it out briefly and decide if to do the course in detail.
    • Evaluation was 3.5 by 6 people on 8/8/25: Put the following into an AI and interact - ask it to summarize, etc.
      • Towards Monosemanticity: Decomposing Language Models With Dictionary Learning  (https://transformer-circuits.pub/2023/monosemantic-features/index.html); Bricken, T., et al., 2023. Transformer Circuits Thread.
    • We can evaluate https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10718663 for reading & discussion. 7/25/25: vote was 3.25 over 4 people.
    • Not yet evaluated
    • Neural Networks, Deep Learning: The basics of neural networks, and the math behind how they learn, https://www.3blue1brown.com/topics/neural-networks. (We would need to pick a specific one later.)
      • We checked the first one briefly. 8/22/25: eval was 3.625 (from 4 people) for a full viewing.
      • Let's evaluate a few more of them.
    • LangChain free tutorial, https://www.youtube.com/@LangChain/videos. (The evaluation question is, do we investigate this any further?)

    • Chapter 6 recommends material by Andrej Karpathy, https://www.youtube.com/@AndrejKarpathy/videos for learning more. What is the evaluation question? "Someone should check into these and suggest something more specific"?
    • Chapter 6 recommends material by Chris Olah, https://www.youtube.com/results?search_query=chris+olah
    • Chapter 6 recommended https://www.youtube.com/c/VCubingX for relevant material, in particular https://www.youtube.com/watch?v=1il-s4mgNdI
    • Chapter 6 recommended Art of the Problem, in particular https://www.youtube.com/watch?v=OFS90-FX6pg
    • LLMs and the singularity: https://philpapers.org/go.pl?id=ISHLLM&u=https%3A%2F%2Fphilpapers.org%2Farchive%2FISHLLM.pdf (summarized at: https://poe.com/s/WuYyhuciNwlFuSR0SVEt). (Old eval from 6/7/24 was 4 3/7.)
    • Back burner "when possible" items:
        • TE is in the informal campus faculty AI discussion group. 
        • SL: "I've been asked to lead the DCSTEM College AI Ad Hoc Committee. ... We’ll discuss AI’s role in our curriculum, how to integrate AI literacy into courses, and strategies for guiding students on responsible AI use."
        • Anyone read an article recently they can tell us about?
        • The campus has assigned a group to participate in the AAC&U AI Institute's activity "AI Pedagogy in the Curriculum." IU is on it and may be able to provide updates now and then. 
        • Here are projects that MS students can sign up for. If anyone has an idea for an MS project where the student reports to us for a few minutes each week for discussion and feedback - a student might potentially be recruited! Let me know.
          • JH suggests a project in which AI is used to help students adjust their resumes to match key terms in job descriptions, to help their resumes bubble to the top when the many resumes are screened early in the hiring process.
          • JC suggested: social media are using AI to decide what to present to us, the notorious "algorithms." Suggestion: a social media cockpit from which users can say what sorts of things they want. Screen scrape the user's feeds from social media outputs to find the right stuff. Project could be adapted to either tech-savvy CS or application-oriented IS or IQ students.
          • VW had some specific AI-related topics that need books about them.  
          • DD suggests having a student do something related to Mark Windsor's presentation. He might like to be involved, but this would not be absolutely necessary.
            • markwindsorr@atlas-research.io writes on 7/14/2025: Our research PDF processing and text-to-notebook workflows are now in beta and ready for you to try,
              • You can now: 
                • - Upload research papers (PDF) or paste in an arXiv link and get executable notebooks
                • - Generate notebook workflows from text prompts
                • - Run everything directly in our shared Jupyter environment
                • This is an early beta, so expect some rough edges - but we're excited to get your feedback on what's working and what needs improvement.
                • Log In Here: https://atlas-research.io

      Appendix: Transcript
        

      Artificial Intelligence Study Group  
      Fri, Sep 19, 2025

      0:13 - M. M.  
      D. B., hello. You probably should admit some of the people. I sent the Zoom link for some of my students, but I don't know if they are coming.

      0:32 - D. B.  
      OK. Yeah, well, I mean, there's no real gate keeping. The link, they can join in.

      0:42 - M. M.  
      I think so. Maybe. He just asked me right now, so this is fine. And I can invite more people from AI and machine learning class if I. S. S. wants to give a talk next week if you're thinking it's okay. Yeah, because he can share experience what the students can learn right now to get a better job. And I will invite AI machine learning students. Yeah, that's good. Why the student is not coming? I just give them. Oh, Link. Oh, maybe. Well, I was telling my daughter about it.

      1:29 - D. B.  
      Oh, he's here.

      1:30 - Unidentified Speaker  
      A lot of people in class, just because someone's taking a class doesn't mean they're so interested in the topic that they want to do it as an extracurricular activity, too.

      1:46 - D. B.  
      Some students are interested, some are more interested, some are less. Us. Okay. All right. Well, it's a graduate student in my AI class.

      1:58 - M. M.  
      We have several that are very interested, so we have to invite them. Yes. Oh, definitely. Yeah.

      2:08 - Unidentified Speaker  
      Welcome.

      2:09 - D. B.  
      I'm very pleased to be here.

      2:14 - M. M.  
      Thank you. We have a few people today because assembly meeting and the faculties are over there so. Oh, okay. Yeah, they say that we're doing excellent job here in this university. The enrollment and tuitions and everything is looking good. That's good. Yeah, well I'm glad enrollment is up a bit.

      2:40 - D. B.  
      I know our graduate student enrollment in our programs is not doing too well because it's you know, number of foreign students is going down.

      2:52 - M. M.  
      Yeah, but the general is going up.

      2:55 - D. B.  
      Overall, it's going up.

      2:57 - M. M.  
      Overall, overall, yeah, everything is up. D. supposed to talk, you mentioned yesterday, but where is, not D., D., D.

      3:06 - D.  
      D., D.'s here, can you hear me?

      3:09 - Unidentified Speaker  
      D., ah, D. is here, yeah, yeah, yeah.

      3:13 - E. G.  
      Hey, D. He is serious. Hello, A.

      3:17 - D. B.  
      All right, well, here's what we got. So we're going to start with L. Give us an update on his book project. And then D. can step us through some prompts that he learned. And that's basically the program for today. Yeah, it's great. So L., why don't you go ahead and give us an update? I know we've been a couple of weeks, a few weeks where we didn't do it. So I'm glad we have a chance to do it today.

      3:52 - L. G.  
      Is there a way that I can share my screen? It won't be that much more exciting than your screen, but

      4:01 - D. B.  
      Yes. I'm looking for it.

      4:03 - L. G.  
      I haven't used. I see it right now.

      4:07 - D. B.  
      I see it. Perfect.

      4:12 - L. G.  
      Is it working? Yes, sir. I'm sharing it. I'm going to share the screen.

      4:17 - D. B.  
      I won't now. OK, sorry about that. So I haven't used it.

      4:21 - L. G.  
      Oh, man, this is really hard with it. All right, so basically, I wanted to go through kind of with you some stuff. I don't have it as organized as I would like, I'll make this a little bit bigger. So I started off trying to say, OK, we're going to do this research. But we're gonna use agents to do it. So I set out, I first talked with you guys, and of course, I talked to AI, and then chat GPT came up with some general concepts of what it thought we could do. And I was like, okay, so we had determined we were going to try to build it in Gemini, the command line interface, which I get to that very shortly. And Here was the initial setup, kind of thinking. You would have a number of agents, like a project manager agent, a research agent, a writer agent, an editor agent, and a refinement agent. Now, during testing, other agents came up. A marketing agent was suggested by one AI, said, hey, maybe we should let the, go out and do research and have an agent do that and tell us what to write about, right? So I kind of defined that kind of like marketability and audience size. I tried to come up with some metrics that could work there. And then, yeah, Jim and I was like, no, we need an outline agent because of the size of the book. I told it a minimum of 30,000 words, which is roughly what a book size would be. Now, this is when all the fun started. So I got everything loaded up. One second. I want to share some. I want to share some screenshots with you and I emailed him to myself so that I could bring him up. Alright. They may be out of order. If you can't see it, let me know.

      6:20 - D. B.  
      OK, I can see it.

      6:21 - L. G.  
      So we got everything in there and I said, hey, I had set up this whole thing where we're going to use VS code and Python to do some stuff and then. I came up with the idea why don't I just ask Gemini to do it and See what it did. Okay. Now I've spent like three hours doing But I'm gonna try to go through a couple of iterations of what it did so at first Sorry that the thing is so light I basically gave it a basic prompt and I've already recorded it But I asked it to create an agent and a user interface that finds the best topics, right? And basically I gave it a prompt to create this marketing agent. I gave it some criteria like we wanted to get on the New York Times bestseller list, like something that could be there, right? And so it went through a process. It was like, okay, it wanted to create an app, which wasn't what I expected at first, okay? But it went through the process, it created an app. Now, this app, the initial app, because it wasn't the full project idea, I named it like marketing research app, so it turned to Mr. Agent, but it's really funny. But you would put in, what I gave the criteria was, you would put in a subject and kind of a writing style, right? Now, that was just to get it off the top and it would generate would be five subtopics, like you put investing, it would generate subtopics. I'm gonna try to see if I have another picture. And then it would give two possible book titles in the topic, right? So then I thought, you know what? We're thinking too small. We got that to work, but we got it to work with basic, like a basic OpenAI key. I don't know why it wanted to use OpenAI, but it was like a small flash in Python. I got a lot of screenshots of it, but it worked somewhat. So, I was like, okay, I'm gonna try to see if I can find the other screenshot real quick. I don't see it off the jump. Yeah, oh, that's no, that's where the problems came in. So, then, I was like, we're thinking too small and I tried a larger, a larger Yeah, a larger prompt. So this time I kind of outlined the size of the book, what some of the agents would be, what they would do, how they would work, right? And I don't want, and basically, so I wanted a marketing research agent bot, definitely wasn't there. Then I wanted what I was calling a, one user, Mr. Agent will pass top. So they would, okay, let me go through it. This was set up, I wanted to make sure it was working, that the agent would pass the topics, three subtopics to a user. So they could pick the best one or ask them to redo it. And then create, we would get a research bot, a research agent that would be like a research and writing agent. And it would provide us an initial outline of the chapter outline and then the user could approve that. And then we'll move on to writing the first chapter and then send it to like an editing bot, so forth. Okay. This was a basic idea I gave it, but I did tell it, hey, let me know if you have questions. And boy, that was like very interesting. So let me see if I can find that one here. It's questions. Is this the one with this questions? No. That's the one with my questions. That's the one. I apologize that they're a little out of order. But, oh, just a brief knowledge. Because I didn't want to give it full access to my system, I'm kind of newbie at Mac systems and what I have at home to use. Basically, this is how it would work. You put in something, and then it would ask me for permissions to do those things. So obviously, I could say allow all things, but I'm kind of paranoid. And do that. So I kind of could go step by step, whatever it would do. I found this to be quite fascinating. I wanted to find its question, because I feel like those were, OK, that's when we got to the API key. I apologize. It's a little out of order. Can I ask a question?

      11:07 - Unidentified Speaker  
      So you developed some agents to assist in the book writing process. Yeah.

      11:11 - L. G.  
      You could write any book about anything using those three.

      11:14 - D. B.  
      Well, that's what I was going to...

      11:16 - Unidentified Speaker  
      Okay, so basically, that was the point that I was making to you, was when I started out saying I was going to build the agents to write a specific book, I believe AI thought that was stupid and thought I should make an application that could do it.

      11:30 - L. G.  
      So that's kind of... I don't know if we're okay with that or not okay with that. I don't know if it's something I can complete in six weeks, but I think... I think I can, a basic version of it at least, but I'm trying to find the one. Anyway, when I asked it about the questions and unfortunately, all right, I can't switch back because I'm currently not at my home computer. What it asked me was things like, you know, the first set was kind of like, well, are you, how would they share information? How do I want the agent to share information right so you could put in an app state or I could put it in a static file and I prefer to file I thought for a log so I could have a log so we could look back at what they were sharing right and we could record it ask if I wanted to add a couple of agents one of them being the outline agent the other one being something like a like a task agent of some sort which wasn't odd I just said a but I haven't really seen how that works yet. And then it asked me questions about whether the user wanted to view each chapter before it went to editing. A lot of different things like that, which I found very fascinating that it was kind of planning it out. Now in the end, we ran into some problems. So it did create something and it was like, well, it's going to be a book writer. I'm going to tell you what it said. We're going to make this book right at Apple. OK, we're making it. But what happened was it got the first part right. But at that point, it kind of went through a loop. And I think some of the coding is bad. So I think it's two things probably. It preferred Flask for some reason. And I'm just not as familiar with Flask as a development tool. So I think I need to play around with the tools to see if I can one that works for me that I know more about development in. But I don't know. It's been very fascinating. I don't want to get sidetracked with it, but I think I do like the idea that, yeah, I could end up writing any kind of book, but it would be interesting to see if it could work. So I wanted to take another week or two to see if I could get it actually working a little bit more.

      13:56 - D. B.  
      Well, my suggestion as a member of your committee would be to keep a record of what you're doing so that because your report is not going to be the book itself or the book will be an appendix, but the report will be the process that you developed and the lessons that you learned and the log of what you tried.

      14:20 - M. M.  
      Yes, ma'am. Yes, I agree with D. B. I have two of my students, A. and A., they are very good with agents creating content. Uh-huh. So I need to make a meeting with them, you know. OK. Did you meet some of them?

      14:39 - L. G.  
      No, probably. No, ma'am, I've never met them. OK.

      14:44 - M. M.  
      We can meet online. Yeah. So if time works for you and they will be happy to help you. What kind of software tool For agents genetic you're using you mentioned this time.

      15:00 - L. G.  
      I was I was testing and using a Gemini collect command-line interface so yeah, so it's like Yeah, but I also I also did some preliminary tests in lane Chain, which worked okay with me.

      15:15 - Unidentified Speaker  
      Lane chain is fine, but there is a lane graph That's what it ended up having to use lane They're using this and they're very happy. I told you this crew AI, but they're not happy from crew AI. So just send me message when you're available. A. is almost every day here. Tuesday, Thursday for sure is here.

      15:44 - L. G.  
      So yeah. So we will be happy to help.

      15:47 - M. M.  
      Awesome. Thank you so much, doctor.

      15:50 - L. G.  
      No problem. Well, that's pretty interesting.

      15:53 - D. B.  
      I'm looking forward to seeing where it goes.

      15:58 - M. M.  
      Very good.

      15:59 - D. B.  
      It's very good. OK. Well, thanks to L. Anyone else have any comments for L. before we move on to D.'s prompt information?

      16:12 - Y.’s iPhone  
      I have a question. When you're building the agents, are there utilities or components that are helping you to put the guardrails, reduce hallucination, like what is it making it? I mean, many times yesterday in my course we had a discussion, people have different definitions of agents. So what are you doing special using this technology to make it really an agent but not an extension of normal proms and prompt engineering, like what are the things that you're doing extra, such as putting security, guardrails, risk, reduce hallucination around this? Or if you have not done, what are you planning to do?

      17:00 - L. G.  
      Oh yeah, so that's a great question. I don't know what I'm planning to do yet. So I haven't done anything to, because my goal was to first measure the amount of loosers and then come up with the guardrail plan. But what I've tried to do is kind of take a more of a, I think of a more of agent just because I'm letting it do what it wants, but I haven't set the guardrails up for it yet.

      17:32 - D. B.  
      Okay. All right. Well, thank you L. and D. Why don't you go ahead? All right, so I want to share more than that.

      17:47 - D.  
      Let me see how I'm going to do this. So can you guys see that?

      17:57 - Unidentified Speaker  
      Yes. Yes.

      17:59 - D. B.  
      You see my drive?

      18:02 - D.  
      Yep. OK. So basically I was, I volunteered to take a look at a prompt engineering class by IBM. And what I volunteered for actually was to look into it and see what was offered in the course. And Dr. M. told me that I needed to go ahead and knock it out. So I went ahead and knocked it out. And now I'm just gonna kind of give you a report of what was in the course. This is my certificate. There might be a way for me to roll that over. But it did not take me long. Maybe an hour or two, maybe three. I didn't really time it because it was a prompt engineering class and it was really fun. So it wasn't like I was being counting it. I finished it, I was surprised. I actually enjoyed the course. They had a nice setup with different models to choose from, and the interface was good. So I have a question. Yes, go ahead.

      19:17 - D. B.  
      What if we decided at some point to do that course, run through the course as a group, and everybody gets the certificate at the same time at the end of the course as a set of meetings of this group, three or four meetings.

      19:39 - D.  
      I think it might take longer in that framework, but then it might take weeks and weeks to do it, but it could work if everybody wanted to do it and come into the class and sign up, but as soon as everybody as soon as everybody was done, the first night, they'll probably just go ahead and finish it.

      20:05 - M. M.  
      But for NVIDIA, I offer many times we can do NVIDIA courses, whatever you want from NVIDIA.

      20:11 - D.  
      Well, this is not, this is, this would be like a lower quality. Excuse me, I've been sick all week.

      20:19 - M. M.  
      Oh yeah, you told me. You say that this is, yeah.

      20:24 - D.  
      It's been, it's been really challenging. It's not NVIDIA quality. Okay, so this is a much lower quality course. It's a good course. I'm not trying to say anything bad, but this is not Udemy quality. This is not NVIDIA quality course. This is kind of a lower quality.

      20:54 - M. M.  
      I think as long as you're with us, I think we could do that. I think you have, you're supposed to have an instructor if you're going to be having a bunch of people but yeah yeah so I I offer this the Y. can also help me to decide what kind of courses will be interesting or done or for all of you uh what kind of courses are interesting for you and we can do it so I mean I'm happy to go and my class is teaching from engineering and Mac models.

      21:53 - Y.’s iPhone  
      We're using NVIDIA content for it.

      21:56 - Unidentified Speaker  
      Yeah.

      21:56 - M. M.  
      Yeah, NVIDIA's got quality content.

      21:59 - D.  
      And they've got all the money too. So that's one that they can really sink some resources into it. So what I did was I kind of went through the course and I just downloaded certain parts of it and try to, and try to get some documents together. And then I pass the documents to an AI to try to generate a report. I got two reports. One of them was absolutely terrible. This is the terrible one. And it's got maybe some prompts in here from the courses. It was in a terrible order. But then this one right here, actually, you know, named it and gave me a decent report. And then I cut and paste and made this document. So what what they're what they started with this kind of, you know, how English is now they're claiming it's a programming language. I disagree. It's a prompting language. It's not a programming language. But that, you know, that's kind of their entry point. And then they they go into this defining what prompt engineering is. And they go back to stuff that I think most of us already heard of

      23:29 - Unidentified Speaker  
      What is prompting? Well, there's the zero shot prompt.

      23:33 - D.  
      This is the prompt that we do when we just want to get some surface information now, right? So we put in that one little prompt that says, tell me about this or tell me what this word means in the context of software engineering or something like that. So then there's, you know, this one shot, few shot where we give some kind of an example of what we want. And so, and also I think it's fair to say that, you know, giving it a format is really important. Really, you know, I think that's kind of introducing this idea when we start telling the model that, you know, this is how we want your response. And this is the context of the prompt. You know, this is why I'm asking, you know, the AI knows what's going on. It can kind of tailor its response. But I think that's kind of handled in these, let's say, naive prompting strategies. Or the zero shot, one shot, few shot prompting, right? And then it talks about this chain of thought prompting, okay? And then you go through and you do some tests, you run some tests and they demonstrate how that, you know, if you ask a AI to do something that's just kind of a zero shot prompt and say, okay, so this guy walks in the room with a ball, and he puts the ball in a cup, and then he goes over and he turns the cup upside down, he sits it down on the desk, then he walks in that, then he picks it up and goes into another room, and then he goes to the garden or something. And then he, you know, then he pours the cup, or tilts the cup or something. Well, the AI makes a mistake about where the ball is. It gets lost in the weeds and can't really, You can't really. Can't really figure out where. The cup would have fallen out of the ball. And so it it goes, you know, into this. You know you have this kind of a chain of thought problem where you you know you. I might be on the wrong one. That's not the chain of thought. That's a different. Sorry about that guys. Table that example for a second. This is the menu problem where you tell AI to get me the best calories and the most meals on this menu. And so the idea is the AI should go to the menu. It should find the cheapest meal. And it should order it as many times as it can so that you can get the most bang for your buck. But the AI doesn't really do that. It goes and says, okay, you can order this item, this item, this item, this item. And so what they're saying with this chain of thought is that you give the AI an example of the problem and the reasoning, you know, which if you just kinda, you just kinda, you know, summarize this, this is just really, you know, telling the AI what you really want. And they're calling that a chain of thought. And then there's the zero shot chain of thought where you just, to how you tell it to go step by step, give it some instructions, just trying to coerce the AI into giving it instructions to where it pays closer attention to its output, instead of just letting the AI just run off the rails to get a fast response. And here's the chain of thought with the deep x you give, obviously you give it more information, right? Of what you want and how you want it framed. Now the tree of thought, this is where you give it multiple lines of angles to look at the problem. Now, I practiced this one. It said, if you look here, it says simulate three experts who answer in turn, sharing one step of their thinking at a time. So this turns into a step-by-step process, right? And so the experts all work with each other, step-by-step through the problem.

      28:45 - D.  
      I found that if you tell the AI to put together a committee or a group of these experts and tell it to give you a thorough response and allow each expert to give input onto whatever you want for answer, I got like an 18 page response from, what was it? C., yeah, I got like an 18 page response page response from the AI that covered almost every single detail of the query that I had. I thought that this variations of this tree of thought, it is an excellent prompting mechanism. I tried seven first because I thought, well, they were doing this three group, I would do seven and It was ridiculous. I finally just shut it down. It was coming up with so much stuff. I mean, it was, so I decided three was probably the best way, you know, if you actually want to Read what he produces so that, so it, it proves a valid point that how you prompt and how you structure your prompts and what kind of system you're telling it to go through will seemingly exponentially change how the AI responds to you and what level of information that you get if you want like if you want a lot of details use a use a tree of thought it from different angles.

      30:40 - Unidentified Speaker  
      Let a committee decide it actually Yes, please.

      30:43 - E. G.  
      It sounds like you're breaking up into one of the things that I do with prompts.

      30:52 - Unidentified Speaker  
      You're giving it the first context as a so you're telling it how you want it to operate as you're giving it the context of the problem.

      31:04 - E. G.  
      I you're giving it the definitions, basically the constraints. It's almost like a rules engine. I gave it a rules engine, but then I form a committee so that it can make these alter egos.

      31:19 - Unidentified Speaker  
      And that's the follow up piece.

      31:21 - E. G.  
      Now, these are some of the pieces that are newer is I ask it to validate. Well, I don't use the term committee with multiple committees, validate the answer as a whatever. I want you to validate the answer and ensure that all of the assumptions and output is accurate and identify, and this is a big one, and identify where you've made changes and why did you make those changes. That gives me more insight to the thinking within the machine itself, then it'd be a black box of me putting stuff in, and then trying to understand the stuff coming out. Because as I asked for its interpretation of why it changed, not just the what, but the why, that gives me more insight.

      32:21 - D.  
      Yeah. And so what I found is that the AI will actually report to me, the committee members, how much experience have, what their names are. It just does all this on its own. But I say, OK, I want a social studies teacher. I want this type of teacher. I want a historian. I want a researcher. And then I want an administrator to oversee. But it's really powerful. It really is. Control on the output. This right here, this is giving the AI levels of how you see. I guess you need something like a system prompt to do this. But you're telling the AI, OK, I'm going to give you this scale, verbosity. I say zero, don't chat with me at all. You just give me A to B. I say I want this, you give me that precisely. And then as you go up and in your control mechanism, the AI is designed. So this is almost like overriding the creativity control. You know that we talked about what's at the top, the top score. Remember we talked about that maybe a few weeks ago and the, what's the other one that we call the temperature, right? We had those two and we did experiment and found out that, you know, if you turn the top down, even if you had the creativity all the way up, that it changed and it was kind of, it was interesting. Well, this is kind of a, a play on those controls, except for you're defining these levels and what the AI does. It doesn't matter what your temperature's at. I'm assuming it's somewhere in the mid-range, like a default or more or less a default setting. But imagine testing something like this, where you could turn the temperature all the way down and then tell it to give you produce an extremely detailed and elaborate explanation, you know, imagine what you would get. And so I haven't really tested this except for what was provided in the course, you know, cause in the course you got, you got a access to a little, you know, sandbox where you could prompt AI and, and put the prompts in and choose different models and stuff. But it was, it was interesting. So, You can see that like zero concise, five being super chatty, and then you can give it levels and whatever you prompt, you just tell it what the V equals do you wanna, I think the examples they gave it like a standard of two, like if I don't choose, choose to kind of a mid-level, just like temperature or something, or some setting inside the AI. And then there's this Nova system. This system, it's kind of, I don't know, I guess for me, it wasn't really intuitive. So you're basically, you're having a It's almost like what I was talking about earlier, administrator. You have these two, the DCE and the CAE. And these people, they're not people obviously, but these personas have certain jobs like the DCE facilitates the conversation, summarizes progress and keeps discussions on track within your within your prompt, right? And then you have this CAE examines proposed solutions for flaws, challenges, assumptions, and ensures ideas are robust and safe. And they prompt it and say, you know, why is the sky blue? And then if you implemented the verbosity and you set it to really high, you could get a lot of information as to why the sky is blue about every snippet of every scientific paper that was ever written about it. Or you can say, just tell me this, and it says, oh, it's the light. It's the light reflecting, and that's why it's blue. And so this is just a way, I think, to have like what I was doing, and I just put an administrator, but this is more of a technical, a couple of technical administrators to control your committee or your, here I think they're calling it an expert assembly. So it's, anyways, I thought these were, you know, thought these were kind of refreshing little angles. And the way they described it in the course was that, you know, that, you know, we have all these prompting methods and sometimes you're working with a model and you prompt it, you know, this way. And you get a really good response, but then you use this other way and you don't get a good response, but a different model has different, you know, has different ways that it responds to the these queries and that really the people that are out there, like for instance, E. G. and B. who are just coming up with ways to prompt the model, thinking of new ideas. They're the ones that's making all the progress in the prompting areas. I noticed that in their sandbox, the models that they had selected and the models that I had tested, I didn't really use their models. Because if you just use their models, you just get the prompt that they're showing you on the left-hand side, let's say. Here's what we did and this is what we got and you can try it and get the exact same thing. I thought, well, that doesn't sound very fun. I changed the models and realized that Their responses was only from that model. Other models don't do that. Some of them are really good at the zero shot or your more basic prompts, and some of them are really bad at it. It's a really good course for I enjoyed it. Does anybody have any questions? Yeah, all right.

      39:57 - Unidentified Speaker  
      I'll start off. I have a question.

      40:00 - D. B.  
      I wonder if this concept of different styles of prompts could be adapted to teaching students where your homework question is sort of tells them, it's like you're prompting an AI, but then they have to give an answer. So they have to think in a certain way. It's not a bad idea.

      40:21 - D.  
      Yes, very good idea.

      40:24 - M. M.  
      I'm sorry. I just wonder how the course is organized. Do they have a video like NVIDIA and PowerPoint presentation and hands-on or is just hands-on? What is the structure?

      40:43 - D.  
      Can you see my Google? Thing here for the school? Yes, yes.

      40:53 - M. M.  
      Okay, good. So what do you do? Just the Jupyter notebook, how do you graphical user interface to enter the prompt or how the course is organized? Now, let me see if I can get the course. And in the meantime, I sent you the a link to courses that NVIDIA offers and I can deliver or my students or the help of my team, we can deliver all of these that are self-paced or self-learning courses. I can show you the content.

      41:36 - E. G.  
      Actually, I would love that because it forces you into a regimen. Right now, I've got so much going on, I'd like to actually carve out time where we actually sit down and do that.

      41:55 - D.  
      And I do that for these meetings.

      41:59 - M. M.  
      So I'm happy to do this very quickly, or my students, somebody to.

      42:06 - D. B.  
      So F., if you were going to deliver a course like that, would everybody in the group be doing the same exercise at the same time, or will we be watching the instructor doing it?

      42:20 - M. M.  
      They will do in the same time. Yes. I think that Y. experimented this approach.

      42:27 - Unidentified Speaker  
      Y.

      42:27 - Y.’s iPhone  
      Yeah, it worked fine. So then what we'll do is we'll send a link, then there will be kind of exercises, which will be a combination of videos, PowerPoint, and Obviously, we can do all that during our free time. And then what we will do together is if anybody has any problem in understanding the assignment, we'll solve those and do the assessment together. So what we'll do is this.

      42:59 - D. B.  
      I can guarantee you that the great majority of people will not do homework.

      43:05 - Y.’s iPhone  
      So then we can do 15 minutes, 30 minutes each week, and then say, we'll do it in a month or two months. So there are two ways of doing about it.

      43:19 - D. B.  
      Like do piecemeal.

      43:21 - Y.’s iPhone  
      Like if there are eight, eight assessments, we'll quickly do one assessment, 15 minutes every week, and then finish it off. It's up to you.

      43:31 - Unidentified Speaker  
      Or, or we say, give a link and say, okay, two weeks, we'll finish.

      43:35 - Y.’s iPhone  
      There are different ways of doing about it.

      43:38 - M. M.  
      Plus, they're different size, you know, the length of the... Yeah, so I can select something that is short Y., that is for one hour.

      43:50 - Y.’s iPhone  
      Yeah, we can...

      43:51 - D. B.  
      We spent, you know, weeks upon weeks viewing these videos together, so something that takes a few weeks is okay.

      43:58 - Unidentified Speaker  
      Yeah, but we can select shorter versions.

      44:02 - M. M.  
      Can everybody see the link and actually let me know.

      44:08 - E. G.  
      I've already opened it, yes. By the way, Dr. B., I don't know if people won't do the homework because I know as soon as they got One Brown, Three Blue, I went through all of those videos in a week because they were just that interesting. And I see one here on Accelerated Computing Training for Fundamentals of Accelerated Computing with CUDA and Python. That would be an awesome one.

      44:43 - M. M.  
      I have a guy, I have a guy, my ex-PhD, R., I don't know if you met him, but he's instructor teaching this course. So we can ask him to I mean, I'm not familiar with this course to teach you, but I know who can help. Yeah. Unfortunately, even I can't do that.

      45:13 - Y.’s iPhone  
      But what my focus on NVIDIA has been rag models, prompt engineering, and then I'm doing agents. We have not started, but those are the three areas that particularly I'm focused on. There are introductory classes like gen AI introduction. And so that is assumed that, you know, we all perhaps know here, but when it comes to prompt engineering, RAG or agents, I'm happy to help also. And obviously Dr. M. has a whole crew who could support us.

      45:47 - M. M.  
      Me and Y. and our team, generative AI, whatever you want, images or RAG or PROMPT, all of these courses, but I'm not okay, E., but I have a guy for CUDA.

      46:02 - E. G.  
      I have a guy.

      46:04 - Y.’s iPhone  
      I have a guy for CUDA and Python.

      46:07 - E. G.  
      That is really very good. No, the thing is, with me, and why I love the One Brown, Three Blue, is what you've identified are interfaces to the LLMs. Once you understand how they're built, what the foundations are, all of those pieces come natural how to interact with it, because then at that point, you're not, you're not having people tell you how to interact with it, you're able to make those abstractions, those connections yourself. Because now at that point, you're not restricted by what they've told you, you have a whole another death and breath because you understand the foundational pieces.

      46:58 - Y.’s iPhone  
      And that's where I want to get to. Once you know how a person thinks, you know how to communicate.

      47:09 - Unidentified Speaker  
      Exactly.

      47:10 - M. M.  
      So, yeah, like we say, we can start from generative AI courses. We can select is short in the beginning and going further, yeah, Y.? Sounds good.

      47:24 - E. G.  
      I'm happy to help.

      47:26 - Y.’s iPhone  
      D., what was the architecture, what was the infrastructure behind this? Do you know what, what are they using when you did actually work on property engineering for this course?

      47:42 - D.  
      Are you talking to me?

      47:44 - Y.’s iPhone  
      Yes, sir. Okay.

      47:46 - D.  
      So you're asking me how the course is laid out? No.

      47:51 - Y.’s iPhone  
      So I'm assuming you must have built some prompts and then build automation around prompts. And then you might have had built some structure, architecture, design. What was it on the back end on which you were doing all these exercises or practice? It's this right here.

      48:16 - D.  
      If you're talking about the engineering course, this was just they had a lab set up. So every every assignment. So you have this like little one minute Read like Dr. M. was asking, you know how the class was laid out. So you have these little one minute late one minute reading things.

      48:39 - Unidentified Speaker  
      And then you and then you have a lab or something.

      48:42 - D.  
      And then, you know, then you get into here and it just it tells you okay so you Read about the chain of thought in the prompt and then it says you can you know just copy this over here and bring it over here to this chat engine and you pick your model and then you start your chat and so I use their prompts during the course I use their prompts and I only think really changed was the model on these lessons. And then they had these short little quizzes where you basically said, do you remember what we just told you?

      49:30 - E. G.  
      And so it was really quick.

      49:33 - D.  
      It didn't take that long. I mean, the time that you spend on it is how much do you want to spend in here playing with it? But what I was talking about, though, when I built my prompts on different subjects that I was working on, I used some of these ideas, just altered them just to see what kind of results I would get in a real world thing when I actually had a real problem I was trying to solve. And, you know, and I found that, you know, some of these prompting strategies, what are there? There's like four prompting strategies that are really, you know, kind of maybe relatively new or above the very naive strategies. And I know that, you know, a couple of them were, you know, were actually really good ideas. And, you know, having somebody administer like the, the DCA and the CEA or whatever that was. Having, you know, I didn't go to that route to have two controllers, but I did put an administrator over my committees that I formed to help keep them on track and to filter things. And I found out, I mean, it's amazing that And understand this isn't agents. This is, these are just little, you know, it's like making a little imaginary friends.

      51:19 - Unidentified Speaker  
      You know, they're not really, it's the same model. He's just making little alter egos.

      51:26 - D.  
      He's got like a, you know, multi personality disorder going on, but in an ordered structured way. And it's, making the AI spend more time on the details and track its logic better. And so when you tell the AI to do these types of things, you're basically telling the AI to, you're not giving it this little short, take all the time you need. That's yesterday's naive prompting. You make the AI take all the time that it needs.

      52:05 - Y.’s iPhone  
      Got it.

      52:06 - Unidentified Speaker  
      And that's similar to earlier question. Did it allow you to set any data restrictions? I don't. I spare no expense.

      52:19 - D.  
      Yeah, I don't set data restrictions.

      52:22 - Y.’s iPhone  
      All right.

      52:23 - D. B.  
      Does anybody have anyone who hasn't had a chance to ask a question have any questions? If not, then. And then anybody else, if you have any more questions, go for it.

      52:39 - E. G.  
      Well, I would like to point out that the sky really isn't blue. It's actually purple.

      52:47 - D.  
      It's blue.

      52:48 - E. G.  
      You're just colorblind, E. Everybody knows that. No, I don't know. I don't know what color the sky is.

      52:55 - D.  
      Imagine if I was told something was red my whole life, but when I say red, I release all the way everybody else is brown.

      53:04 - Unidentified Speaker  
      We would never know the difference.

      53:06 - D.  
      We would both be calling it red, but it would look red to you and brown to me. I just called it red because that's what I learned it was. We don't even know if we all see the same colors.

      53:19 - D. B.  
      All right.

      53:20 - D.  
      Look at the PM I sent you. All right.

      53:22 - D. B.  
      Well, thanks, everybody.

      53:23 - D.  
      I'm going to stop sharing now.

      53:26 - D. B.  
      Pretty interesting meeting, and we'll have Hopefully another interesting meeting next time. I'm not sure what we, oh, F., you may have a student give us a presentation.

      53:36 - M. M.  
      Yeah, if he agrees to make a presentation.

      53:39 - D. B.  
      If not, we will start with course, okay?

      53:43 - Unidentified Speaker  
      Short course. F., I got a question for you.

      53:46 - D.  
      There's only one link?

      53:48 - Unidentified Speaker  
      I only got one link.

      53:50 - E. G.  
      Yeah, but it opens up into everything.

      53:53 - Unidentified Speaker  
      It scrolls down.

      53:54 - M. M.  
      It's PowerPoint, you go down, or you click on the particular topic and- Oh, I see.

      54:00 - D.  
      Can you see it? I thought you sent me something, E.

      54:06 - Unidentified Speaker  
      No, it's a private message.

      54:09 - D.  
      Oh, okay. I can't see.

      54:10 - Y.’s iPhone  
      So one thing for people on the call, next Thursday between 4.30 to 7.30, if anybody wants to know, so my team or my students are doing rag model and We are not doing agents but prompt engineering and we did all the basics of generative AI. If you all want to get any help and if you want to do the course, just reach out to me directly and we are doing in-person help. So if you find any difficulty in moving ahead, for example, in the rag model, there's a process of creating files and it's not in the instructions and everybody was But I'm more than happy to help you, particularly on any of these topics, on what you see. And you're welcome to come between 430 to 730, room 218 on Thursday.

      55:10 - D.  
      430, 730, where is this at?

      55:14 - Y.’s iPhone  
      Room 218, EIT building.

      55:17 - D.  
      280. 218.

      55:19 - M. M.  
      Yeah, that's just a little outside my driving zone.

      55:24 - Unidentified Speaker  
      Are you in Georgia?

      55:26 - E. G.  
      Is that what you said?

      55:29 - M. M.  
      No, I'm in Bangor, Maine.

      55:32 - Unidentified Speaker  
      Maine?

      55:33 - Unidentified Speaker  
      Yeah.

      55:33 - Y.’s iPhone  
      Great White North.

      55:36 - E. G.  
      So you go straight, take right. Yeah. Go south until it gets too hot.

      55:44 - Unidentified Speaker  
      You might want to leave now.

      55:51 - M. M.  
      I can share the screen and you can see the courses, but I, like I say, you have them, okay? So, yeah, your question, E., is about this accelerating?

      56:04 - E. G.  
      Well, what I'm thinking of is, have you ever thought of hosting these, actually making these courses at UALR? Just a course on going through a specific path? To a destination, because there's all of these paths that you can go.

      56:22 - Unidentified Speaker  
      That's what college is.

      56:24 - M. M.  
      This is correct, but I don't know if they will allow me to do.

      56:31 - Y.’s iPhone  
      Indirectly, I'm doing that. I'll tell you, but we could not do it officially. So I have a whole course, but we are putting only three out of the 14 sessions on this, where we are building like a And obviously, there are layers of building that. So we did that, and I'm happy to speak to you about it. But formally, we can't do, but I embedded three of my lectures around getting this certification. So all my students have three certificates in addition to obviously finishing the course. So we are doing that in a certain way.

      57:12 - Unidentified Speaker  
      doing it tangentially, yes. Yes.

      57:14 - D.  
      There was other, there's other courses that are like solely wrapped around online courses that you actually, you pay to be in the course and then you pay to take another course inside of that course. And it's, you know, cause I signed up for one of them. Uh, so I think that it, I think, I don't think it's like a breach of protocol or anything like that. You know, if you were teaching something and you had some people run through NVIDIA or something, I think that's, I think that's allowed, but I don't know.

      57:51 - M. M.  
      Yeah, but there is STC, data science training. Actually, we create a program for data science, but it's not implemented yet. But it's a good point. Like Y. mentioned, he integrate the courses in his syllabus.

      58:07 - D. B.  
      Well, F., if you want to teach one of these in this group, just let me know. I can schedule it.

      58:17 - M. M.  
      Oh, definitely. Definitely. Just teach them all.

      58:20 - Unidentified Speaker  
      Well, I'd like to get the professional AI certification out of this. I run Rapids.

      58:28 - M. M.  
      I love Rapids. Do you want to teach Rapids here? No, it's for but not for everybody, probably.

      58:39 - E. G.  
      Yeah, I've been called unique before, but not in those terms. Yeah, yeah, me too. I feel your pain.

      58:50 - M. M.  
      Personality disorders, something where I was like, get upset, obsessed on some particular way.

      58:59 - D.  
      And that's the way I write all my codes. And then all of a sudden I have this epiphany that that was crazy.

      59:08 - E. G.  
      Why did I do that?

      59:10 - D. B.  
      All right, folks. Well, thanks for joining in.

      59:14 - Unidentified Speaker  
      And see you next time.

      59:17 - D.  
      All right. Thanks, guys. Thank you, guys.