2/13/26: DR on the reviewing process

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 added to the invite list - or removed 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 (194^th meeting, Feb. 13, 2026)

Agenda and Minutes

• Announcements
• DR will explain a paper and seek input on reviewing it
•  Plans
• DR defense is Wednesday, rm. 219, 10:30 A.M.
• 2/27/2026: Guest speaker (Ashley B.) and demo: AI in Wolfram|Alpha Pro.
• Next meeting: "What is the latest, latest important news in AI?" This was requested as a session topic! 
• "Go Fourth Fridays" series:

                        Ever wonder how our local businesses use AI day-to-day? 

        Friday, Feb 27 at Noon for free pizza and real-world AI insights you can apply immediately.
        What You'll Learn:
        Josh Jones from Chick-fil-A will demo how he creates and manages
        AI agents to manage operations at one of Little Rock's busiest locations (Markham & Chenal)
        Marla Johnson shares what LR business leaders told her they wish they knew about AI—from prompting basics to building custom agents
The Details: 📅 Friday, February 27 🕛 Noon - 1:30 PM 📍 Reynolds First Floor Atrium, UA Little Rock
Schedule:
    Noon - 12:30: Lunch & networking (FREE PIZZA! 🍕)
    12:30 - 1:30: Presentations & open mic for YOUR ideas
Who Should Attend: Whether you're a business owner curious about AI, a student exploring careers, or just want to understand what all the AI hype means for Little Rock—this is for you.
   Save Your Spot: 👉 https://forms.gle/YabL14LkwZJzbi5f9   
Community members, students, and faculty all welcome. Bring your questions! Bring a friend!

• • Did anyone go?

    ---

    Th Feb. 12, 12-1pm. 

    UA Little Rock/Google Future AI Series

     "AI on Campus: A High Level Overview of
    Google's Tools for Research &
    Operations"

    Dear Campus Community,

  • I know many of you are curious about Generative Artificial Intelligence (Gen AI) and would like to know more. To help fill that knowledge gap, Google has partnered with us to do a series of monthly webinars. These webinars will start with the basics but will progress as the year goes on to include demonstrations of use cases, real-time workshopping of problems, and much more. 

    
    

    The first of these webinars will be Thursday, February 12, 2026 from 12-1 p.m. (webinar link). They will then continue on the 2nd Thursday of each month. Please think about attending these webinars to learn more about what AI can do as well as what its limitations are. I look forward to seeing you there. 

    Brian Berry, PhD | Vice Provost of Research and Dean of the Graduate School 

    AI Council Chair

• Other plans
• Read a couple paragraphs and decide if we should read it in detail: LLMs Are Randomized Algorithms (https://share.google/sLYorUX7Mz4KQBxxH)
• DR website/book(s)
• Site: https://www.thecenterforethicalai.com.
• We read the first page of chapter 1 in his ebook Ethical AI Integration.
• Check a couple minutes of https://www.youtube.com/watch?v=RNF0FvRjGZk to see if we should view it in detail.
• What if we read from papers authored by people in this group? Then an author would be present to help everyone understand it.
• AB has a paper under revision.
• DR has a paper just published.
• Similarly: Invite paper authors at UALR or anywhere to host a reading session on the abstract and various paragraphs of a paper they published or plan to submit. 

• Other 
• Any discussion questions you'd like to hear input on? 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. 
• Not evaluated yet
• https://youtu.be/UclrVWafRAI?si=7y_OAvKlr8kM9lbc (VK)
• https://youtu.be/BFU1OCkhBwo?si=KnHNuedfNaTkZzwp (VK)
• https://youtu.be/x4ZY25OU4Ys?si=K1xp4uA14vBdCgOI (VK)
• https://arxiv.org/abs/2511.21622
• 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.
• 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.)

•  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
• (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
• 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.
• Back burner "when possible" items:
• 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."
• Any 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.
• Please suggest a project!  

2/6/26: BB Socratic questioning tool, etc.

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 added to the invite list - or removed 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 (193^rd meeting, Feb. 6, 2026)

Agenda and Minutes

• Announcements
• Blackboard's Socratic questioning tool. Let's try it out. Do blackboard.ualr.edu > a specific course > Content tab > Course content > + > create > AI conversation > Socratic Questioning >
• Socratic questioning with general purpose AI chatbots
• We could use DD's recent conference paper to test it.
• Multi-question modification; guiding the questioner
• Future items
• Next week: DR will explain a paper and seek input on reviewing it
• DR defense is in two weeks
• 2/27/2026: Guest speaker (Ashley B.) and demo: AI in Wolfram|Alpha Pro.
• "What is the latest, latest important news in AI?" This was requested as a session topic! 
• "Go Fourth Fridays" series:

                        Ever wonder how our local businesses use AI day-to-day? 

        Friday, Feb 27 at Noon for free pizza and real-world AI insights you can apply immediately.
        What You'll Learn:
        Josh Jones from Chick-fil-A will demo how he creates and manages
        AI agents to manage operations at one of Little Rock's busiest locations (Markham & Chenal)
        Marla Johnson shares what LR business leaders told her they wish they knew about AI—from prompting basics to building custom agents
The Details: 📅 Friday, February 27 🕛 Noon - 1:30 PM 📍 Reynolds First Floor Atrium, UA Little Rock
Schedule:
    Noon - 12:30: Lunch & networking (FREE PIZZA! 🍕)
    12:30 - 1:30: Presentations & open mic for YOUR ideas
Who Should Attend: Whether you're a business owner curious about AI, a student exploring careers, or just want to understand what all the AI hype means for Little Rock—this is for you.
   Save Your Spot: 👉 https://forms.gle/YabL14LkwZJzbi5f9   
Community members, students, and faculty all welcome. Bring your questions! Bring a friend!

• • Th Feb. 12, 12-1pm. 

    UA Little Rock/Google Future AI Series

     "AI on Campus: A High Level Overview of
    Google's Tools for Research &
    Operations"

    Dear Campus Community,

  • I know many of you are curious about Generative Artificial Intelligence (Gen AI) and would like to know more. To help fill that knowledge gap, Google has partnered with us to do a series of monthly webinars. These webinars will start with the basics but will progress as the year goes on to include demonstrations of use cases, real-time workshopping of problems, and much more. 

    
    

    The first of these webinars will be Thursday, February 12, 2026 from 12-1 p.m. (webinar link). They will then continue on the 2nd Thursday of each month. Please think about attending these webinars to learn more about what AI can do as well as what its limitations are. I look forward to seeing you there. 

    Brian Berry, PhD | Vice Provost of Research and Dean of the Graduate School 

    AI Council Chair

• Other plans
• Read a couple paragraphs and decide if we should read it in detail: LLMs Are Randomized Algorithms (https://share.google/sLYorUX7Mz4KQBxxH)
• DR website/book(s)
• Site: https://www.thecenterforethicalai.com.
• We read the first page of chapter 1 in his ebook Ethical AI Integration.
• Check a couple minutes of https://www.youtube.com/watch?v=RNF0FvRjGZk to see if we should view it in detail.
• What if we read from papers authored by people in this group? Then an author would be present to help everyone understand it.
• AB has a paper under revision.
• DR has a paper just published.
• Similarly: Invite paper authors at UALR or anywhere to host a reading session on the abstract and various paragraphs of a paper they published or plan to submit. 

• Other 
• Any discussion questions you'd like to hear input on? 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. 
• Not evaluated yet
• https://youtu.be/UclrVWafRAI?si=7y_OAvKlr8kM9lbc (VK)
• https://youtu.be/BFU1OCkhBwo?si=KnHNuedfNaTkZzwp (VK)
• https://youtu.be/x4ZY25OU4Ys?si=K1xp4uA14vBdCgOI (VK)
• https://arxiv.org/abs/2511.21622
• 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.
• 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.)

•  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
• (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
• 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.
• Back burner "when possible" items:
• 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."
• Any 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.
• Please suggest a project!  

1/30/26: DD paper reading

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 (192^nd meeting, Jan. 30, 2026)

Agenda and Minutes

• Announcements
• We could look at Blackboard's Socratic questioning tool some time (next time?). Yes, let's try it out. Do blackboard.ualr.edu > a specific course > Content tab > Course content > + > create > AI conversation > Socratic Questioning >
• Today: readings from DD's recent conference paper. We read and discussed the title and abstract.

 The meeting ended here. 

• Future plans
• Read a couple paragraphs and decide if we should read it in detail: LLMs Are Randomized Algorithms (https://share.google/sLYorUX7Mz4KQBxxH)
• DR website/book(s)
• Site: https://www.thecenterforethicalai.com.
• We read the first page of chapter 1 in his ebook Ethical AI Integration.
• Check a couple minutes of https://www.youtube.com/watch?v=RNF0FvRjGZk to see if we should view it in detail.
• What if we read from papers authored by people in this group? Then an author would be present to help everyone understand it.
• AB has a paper under revision.
• DR has a paper just published.
• Similarly: Invite paper authors at UALR or anywhere to host a reading session on the abstract and various paragraphs of a paper they published or plan to submit. 

• Updates
• DD. Research status?
• Anyone else?  
• Other 
• Any discussion questions you'd like to hear input on? 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. 
• Not evaluated yet
• https://youtu.be/UclrVWafRAI?si=7y_OAvKlr8kM9lbc (VK)
• https://youtu.be/BFU1OCkhBwo?si=KnHNuedfNaTkZzwp (VK)
• https://youtu.be/x4ZY25OU4Ys?si=K1xp4uA14vBdCgOI (VK)
• https://arxiv.org/abs/2511.21622
• 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.
• 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.)

•  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
• (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
• 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.
• Back burner "when possible" items:
• 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."
• Any 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.
• Please suggest a project!  

1/23/26: Welcome back! DR leads discussion on his website and activities

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 (191^st meeting, Jan. 23, 2026)

Agenda and Minutes

• Announcements

• Welcome back!
• Today 
• DR discussed his activities and website:
• Site: https://www.thecenterforethicalai.com.
• We read the first page of chapter 1 in his ebook Ethical AI Integration.
• Next time: readings from DD's recent conference paper.
• Future plans
• Read a couple paragraphs and decide if we should read it in detail: LLMs Are Randomized Algorithms (https://share.google/sLYorUX7Mz4KQBxxH)
• Check a couple minutes of https://www.youtube.com/watch?v=RNF0FvRjGZk to see if we should view it in detail.
• What if we read from papers authored by people in this group? Then an author would be present to help everyone understand it.
• AB has a paper under revision.
• DR has a paper just published.
• Similarly: Invite paper authors at UALR or anywhere to host a reading session on the abstract and various paragraphs of a paper they published or plan to submit. 

• Updates
• DD. Research status?
• Anyone else?  
• Other 
• Any discussion questions you'd like to hear input on? 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. 
• Not evaluated yet
• https://youtu.be/UclrVWafRAI?si=7y_OAvKlr8kM9lbc (VK)
• https://youtu.be/BFU1OCkhBwo?si=KnHNuedfNaTkZzwp (VK)
• https://youtu.be/x4ZY25OU4Ys?si=K1xp4uA14vBdCgOI (VK)
• https://arxiv.org/abs/2511.21622
• 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.
• 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.)

•  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
• (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
• 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.
• Back burner "when possible" items:
• 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."
• Any 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.
• Please suggest a project!  

12/12/25: LG defense (AI book project)

 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 (190^th meeting, Dec. 12, 2025)

Agenda and Minutes

• Announcements

• Today. LG defense (book project). 

The meeting ends here. 

• Hopefully later Dec. or Jan.:  DR part 2, to be scheduled. Website: www.dalerutherfordai.com
• Read a couple paragraphs and decide if we should read it in detail: LLMs Are Randomized Algorithms (https://share.google/sLYorUX7Mz4KQBxxH)
• Check a couple minutes of https://www.youtube.com/watch?v=RNF0FvRjGZk to see if we should view it in detail. 

• Updates
• LG. Book writing project update.
• Need to submit a proposal document (it can focus on the current status of the project and what is left to do, and it can be mostly reusable in the final report).
• Topic of book is: personal investing.
• Committee: DB, MM, RS
• Need to keep a log of activities and results, to become the final report. 
• DD. Research
• 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. 
• Not evaluated yet
• https://arxiv.org/abs/2511.21622 
• 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.
• 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.)
•  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
• (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
• 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.
• Back burner "when possible" items:
• 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?
• 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.
  
    

12/5/25: NVIDIA learning opportunities (MM)

 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 (189^th meeting, Dec. 5, 2025)

Agenda and Minutes

• Announcements

• Today. MM discussion of NVIDIA materials.
• Resources:
• NIMs models 
• https://developer.nvidia.com/nim?sortBy=developer_learning_library%2Fsort%2Ffeatured_in.nim%3Adesc%2Ctitle%3Aasc
• https://www.youtube.com/watch?v=NaT5Eo97_I0&t=23s
• https://www.youtube.com/watch?v=087spL8hMvM
• https://developer.nvidia.com/blog/develop-specialized-ai-agents-with-new-nvidia-nemotron-vision-rag-and-guardrail-models/?ncid=so-yout-580975
• https://www.youtube.com/watch?v=vE80SLk-4PM&t=717s 
• Self-paced courses
• https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-23+V1
• LLaVA: Large Language Vision Assistant
• https://llava-vl.github.io/

 The meeting ended here.

• Dec. 12. LG defense (book project). 
• Hopefully later Dec. or Jan.:  DR part 2, to be scheduled. Website: www.dalerutherfordai.com
• Read a couple paragraphs and decide if we should read it in detail: LLMs Are Randomized Algorithms (https://share.google/sLYorUX7Mz4KQBxxH)
• Check a couple minutes of https://www.youtube.com/watch?v=RNF0FvRjGZk to see if we should view it in detail. 

• Updates
• LG. Book writing project update.
• Need to submit a proposal document (it can focus on the current status of the project and what is left to do, and it can be mostly reusable in the final report).
• Topic of book is: personal investing.
• Committee: DB, MM, RS
• Need to keep a log of activities and results, to become the final report. 
• DD. Research
• 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. 
• Not evaluated yet
• https://arxiv.org/abs/2511.21622 
• 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.
• 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.)
•  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
• (Eval 8/29/25 was 3.75 over 5 people.) Https://docs.google.com/document/d/1NeNmKlAmJdf50ST7plw4mvgeeS7UJuYLyEQMz8slCA0/edit?tab=t.0#heading=h.hnzmulgvk3qx.  
• 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.
• Back burner "when possible" items:
• 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?
• 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.