Friday, December 13, 2024

12/13/24: Using AI to write books & informational websites, etc.

  Machine Learning Study Group

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

Agenda & Minutes  (142nd meeting, Dec. 13, 2024

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

Agenda and minutes
  • Announcements, updates, questions, presentations, etc.
    1. DB has found some masters students interested in the project below starting next semester for their masters degree project requirement. An important qualification for the student is to be able to attend these meetings weekly to update us on progress and get suggestions from all of us! 
      • Project description: Suppose a generative AI like ChatGPT or Claude.ai was used to write a book about a simply stated task, like "how to scramble an egg," "how to plant and care for a persimmon tree," "how to check and change the oil in your car," or any other question like that. Just ask the AI to provide a step by step guide, then ask it to expand on each step with substeps, then ask it to expand on each substep, continuing until you reached 100,000 words or whatever impressive target one might have.
        • LG: "How to bake a cake." Has some thoughts on the hallucination issue that AB mentioned.
        • ET: Gardening (veggies, herbs in particular). Specifically, growing vegetables from seeds. 
        • DD: Better to write about something you know something about.
        • YP: Prompt engineering would require looping, giving feedback, maybe agents would be useful. Youtube videos are available by subject matter experts. So you can familiarize with a topic that way.
        • MM: We could show examples of prompting using agents.
        • JK is focusing on prompt eng. with agents (but is not here today).
      • If anyone else has a project they would like to help supervise, let me know!
    2. JK submitted a video to AAAI 2024: video (https://drive.google.com/file/d/1KJNQQU7IfSywljADxkGHMZuDkchbIc38/view?usp=sharing); call for videos (https://aaai.org/about-aaai/aaai-awards/aaai-educational-ai-videos). See also complex prompts, etc. (https://drive.google.com/drive/u/0/folders/1uuG4P7puw8w2Cm_S5opis2t0_NF6gBCZ).
    3. NM: Updates/problems/questions on the process of turning the thesis into a publishable document using AI to help, while not having it look like it was AI generated and, more importantly, not having it overly AI generated to the extent that truth is compromised, while still using AI as an assistant as much as possible.
The meeting ended here.
    1. Here is a tool the library is providing. Some people here thought it would be a good idea to try it live during a meeting, so we can do that.

      Library trial of AI-driven product Primo Research Assistant

      The library is testing use of Primo Research Assistant, a generative AI-powered feature of Primo, the library's search tool. Primo Research Assistant takes natural-language queries and chooses academic resources from the library search to produce a brief answer summary and list of relevant resources. This video provides further detail about how the Assistant works.
      You can access Primo Research Assistant directly here, or, if you click "Search" below the search box on the library home page, you will see blue buttons for Research Assistant on the top navigation bar and far right of the Primo page that opens. You will be prompted to log in using your UALR credentials in order to use the Research Assistant.
       
    2. 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 when available, every now and then but not every week.
    3. Anything else anyone would like to bring up?
  • Here are the latest on readings and viewings
    • Next we will continue to work through chapter 5: https://www.youtube.com/watch?v=wjZofJX0v4M. We got up 15:50 awhile ago but it was indeed awhile ago so we started from the beginning and went to 15:50 again. Next time we do this video, we will go on from there. (When sharing the screen, we need to click the option to optimize for sharing a video.)
    • We can work through chapter 6: https://www.youtube.com/watch?v=eMlx5fFNoYc.
    • We can work through chapter 7: https://www.youtube.com/watch?v=9-Jl0dxWQs8
    • Computer scientists win Nobel prize in physics! Https://www.nobelprize.org/uploads/2024/10/popular-physicsprize2024-2.pdf got a evaluation of 5.0 for a detailed reading.
    • We can evaluate https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10718663 for reading & discussion.
    • Chapter 6 recommends material by Andrej Karpathy, https://www.youtube.com/@AndrejKarpathy/videos for learning more.
    • 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). 6/7/24: vote was 4 3/7. We read the abstract. We could start it any time. We could even spend some time on this and some time on something else in the same meeting. 

Transcript:

ML discussion group  
Fri, Dec 13, 2024

7:23 - D. B.
All right. So anyway, if you're new here, we call this the Machine Learning study group or maybe machine learning discussion group. And it's every Friday at four. We're going to even meet next Friday, although the following Friday, probably not. And we talk about machine learning and artificial intelligence. So just to kind of announce or describe agenda item number one. So there's a number of students in our master's program, information science master's program, who would like to do a project of the following type. So they're gonna, you know, the idea is to use the generative AI, like ChatGPT, Cloud.AI, you know, Google Gemini, some other, whatever, okay? Or maybe a book with pictures, they could use a picture generating AI. But anyway, the intent is to write a book about some, you know, with some simple title or simply stated task, like how to scramble an egg, how to cook an egg, how to plant, care for your persimmon tree, how to check and change the oil in your car, how to read the dipstick for the oil in your car. That's not as easy as it sounds for some cars. Any other question like that? And it's just sort of an experimental idea of just what would be the experience of using an AI to a full length book about it, or an equivalent task, not write a book, but create a informational website that's equivalent in content to a book, okay? Since a lot of people check websites instead of reading books nowadays. Ultimately, I would like to see a book like that self-published on Amazon or a website put up for people to, for the world to, make use of and we'll see how that goes as part of the project. And it's basically a prompt engineering problem because you can't just tell the AI to write the book. You've got to step it through and provide some structure to the task and get it to do it. Okay, that's the question. How do you get it to do it? And I think it'll be really interesting to see how a number of different students, what their experiences are in doing that. And And I think other people here would like to see how that goes and provide suggestions and advice along the way. So really, the only real requirement for the students is that you be attending these meetings.

10:20 - A. B.
Because otherwise, we don't know what you're doing. Like how will the, is it on the student then to kind of validate the quality of the output, like, you know, along the way, or is it just to, like, I guess, so what if they, you know, we, you pick a topic and they, you know, you start compiling these different, you know, they're prompting and compiling these different outputs, like, is it on them as the onus on them to then kind of validate the, you know, is the information correct before bringing it back into the folder? Is that part of what we're measuring or just curious? Well, yeah.

11:01 - D. B.
I mean, one of the problems with using AI-generated text is that the AIs, when they don't know something, they'll make it up and it'll sound pretty convincing. That is a problem to which I do not have a solution, but I'm glad you raised it. And it's going to have to be addressed somehow, maybe not successfully, but it's a question that has to, you know, that will hover over the project.

11:28 - Unidentified Speaker
How about that? Yeah.

11:29 - A. B.
Is the AI, you know, how do you tell?

11:32 - D. B.
Because, you know, normally, you know, maybe, you know, many times you don't know the answer. So you're, yeah, so that is a question. And I'm glad you raised it. And we'll have to have to make that part of the project somehow. Or maybe not, we'll just come up with a book that sounds plausible, but has mistakes. Some real books have that too. I don't know, does anyone else have any thoughts on that? Okay, so let's see who the students are here. We'd like to welcome E. T.

12:16 - M. M.
Oh, okay.

12:17 - D. B.
I thought there were like four different, there were like four or five people, but only two people are here, which might make the project a little more manageable. So anyway, thanks for showing up and you're already among the few and the proud and you were the ones to show up. One of the, the question that I sort of sent you early on was to come up with some, some title or question or something that would be the subject of your of your book or website. And I'm going to turn it over to you folks and let you tell us what you came up with.

13:01 - L. G.
It's okay, I'll go first. Sure. With the idea of how to bake a cake, because it seems fairly simple, but it does have quite a few steps. And areas where you could, you know, get the ads, maybe do something different, right? And to Mr. Berry's question, I thought that one of the things we would be studying in the process are the hallucinations. So, you know, it's a part of the book, but it's also something that you can document and you can get some understanding about, or you could either try to do some prompt engineering around it and say, hey, I ran the question x these number of ways. And so, still get a hallucinogenic answer to it.

13:45 - D. B.
So I thought it was that kind of part of the project it could be addressed. Absolutely, yeah.

13:55 - Unidentified Speaker
I was thinking gardening.

13:58 - E. T.
I mean gardening is my hobby and I sort of have some of the knowledge on gardening. So simply gardening, growing vegetables or mostly vegetables or herbs seems easy, especially if you go get your plants, seedlings from the store. It's fairly easier compared to growing from seeds. But I was thinking growing. From seeds. Okay.

14:34 - D. B.
It has some steps and especially some for certain vegetables. Yes, you know, the little, the virtually nothing I know about growing plants from seeds is, you know, a lot of times you have to stratify and scarify, all these things, you have to do the seeds to make them grow. And then sometimes they don't grow. I don't know. It's just, I think that would be a book that I would find useful and interesting to read.

15:08 - E. T.
OK.

15:08 - D. B.
Those both sound really interesting to me. And I hope that we'll all learn a lot by seeing how the process goes and where it works, where it doesn't work, where hopefully people have some ideas to get things going again when you get stuck, if you get stuck. Yeah. All right. And are you okay with meeting all next semester and maybe the semester after that, assuming you're doing a two-semester project on these Fridays at four? Because that's kind of part of the plan.

15:46 - A. B.
I was just curious on what the strategy would be to get, because 100,000 words is a lot of words, right? Right. Yeah.

15:57 - D. B.
Well, you know, a hundred. Yeah. I think that would be a pretty long book, but you know, if it's 70,000, that's, that's book length too.

16:05 - A. B.
Right. Well, but I guess, is it like, would the strategy be something to the effect of, I don't know, like you kind of identify like the larger steps, whatever the process is you pick. And then like, then, you know, as you get those, like keep asking, like, so, you know, the, whatever, you know, get your flower and then like, you know, kind of continually prompt and ask it to elaborate, elaborate on like one of that, you know, get you on the first step and then, and then, you know, go on to the second step. And so for like, I'm just trying to think through how to logistically do that. Right. Cause if you just ask it to, how do you make a cake, it's going to give you like a, probably a pat answer out of, you know, that's going to be at a certain length.

16:50 - D. B.
Right.

16:50 - A. B.
So then how do you, How do you continually get it to draw that out longer and longer, I guess, is the question.

16:59 - D. D.
That's prompt engineering, isn't it?

17:01 - L. G.
I did try something just before volunteering to do this project, because it's kind of outside of what I thought. So let's say, for example, it said, hey, to make a cake, we need to turn on the oven to 375. And then I asked it, how would I turn on in the oven to 375.

17:22 - A. B.
And they need to give you a whole nother list. And my favorite one I tried was like, the second step was like, you would need to grease a pan. And I'm like, how do I grease a pan?

17:34 - L. G.
So the whole process, like you can use butter and you can do this. And I just kept trying to bring it down.

17:41 - A. B.
Or, you know, or if you say, or you could ask a question, like, is there something I could add to this step?

17:48 - L. G.
Like, Is it possible to use, you know, large degrees of paying for your cake? And then it'll give you some more information that you could then add. So I'm just kind of playing around with it from that kind of sequential thing, but I thought eventually you would need to say, okay, you have this, can you make it a paragraph? You know, instead of being a list.

18:07 - Multiple Speakers
That makes a lot of sense. Yeah. Well, and I get what you're saying.

18:11 - A. B.
I was just like, I wasn't, I was thinking that more around where you prompt it one prompt and you get an output then you know like what's the you'd have to do something like you have to ask more specific questions about each like granular step right to draw it out of this what I was trying to get to you know make sense yeah that does sound like a really good strategy that he's got one of the things that

18:35 - D. D.
like if I was going to undertake this project I would definitely write about something that I could already do And that way I could verify its response. So I would be, it would be like me taking, I would take, I'm going to write this book and I'm going to get ChatGPT to help me so I can write it faster. That's the way I would approach the problem.

19:00 - Multiple Speakers
And then I already know what I want.

19:03 - D. D.
And then I would just have the AI write it for me.

19:08 - Y. P.
is saying 100% whether it is machine learning or generative AI feedback loop. Somebody did mention isn't that prompt engineering and part of prompt engineering is better prompts and that's where you know the agents and automated agents are going where the agents know what to ask better automatically and then they continuously do that until, but that feedback loop and feedback loop is only possible when you know the subject matter that you are doing things or prompting about very well. I concur with that. And that's why, you know, I was talking to somebody who's researching And that's what I was trying to say that when you're building an agent, what you are building agent on perhaps is more important because that's how your agents will actually do the right agency, if I can say that. But I agree with what D. was saying. I just wanted to concur on that. J. is kind of the agents guy.

20:24 - D. B.
He's really getting, he's not here today, but he was really getting to this whole agents idea. But I have to admit that I'm a little in the dark about it.

20:39 - M. M.
This is extremely good approach. Like we show some examples of multi-agents and how they can do different tasks, subtasks. And this is how we can approach creating a good book.

20:56 - Y. P.
And in second week or third week of January, my team will demonstrate agents in the area of product development. And in fact, we will have a couple of people on from UL are joining that project from January as well. If things go well, we are kind of interviewing or assessing them. And we will demonstrate some concepts of agents. It's still not at the autonomous stage, that is phase two of the project, but we'll demonstrate some agents in the product development area. And concepts of the way, whether prompt engineering or feedback loop, everybody was saying, sorry, this is my car. Be big, I'm safe. But what I was was that we will try to demonstrate some aspects of it and coming to D.'s and I don't know who was saying about prompt engineering on that having that subject matter being an expert in something that you are building things on or if you are an engineer then having somebody who is an expert with you perhaps will help you to do that.

22:16 - D. B.
Well you know just getting back to the nuts and bolts of these master's projects, it's good to have, you need three people on your committee, three faculty members or similar to, you know, in the role of faculty members. And, you know, it's good to pick someone with some expertise in the area that you're doing your project, whether it's technical expertise or some other expertise. So like, you know, I don't know if there's any faculty members around that are avid, bakers or gardeners but if there were you know that or maybe someone in another department that that you know of that would be a good person to have on your committee um yeah that's right um well um e. or um uh l. do you have any Any other questions you want to ask us about or anything like that? Any other concerns?

23:23 - E. T.
I actually have some questions about how we're going to, I mean, what are the requirements? What is the expectation every week during the meeting? What do I need to get prepared? Yeah, I mean, this is a kind of a general purpose discussion group.

23:40 - Multiple Speakers
We cover a lot of different things, talk a lot about a lot different things at different times.

23:47 - D. B.
So this is not going to take over the meetings entirely, but I'd like to see some sort of a one minute progress update that we can either absorb or comment on or something. In other words, it's not going to be a big time sink for each meeting, but I'd like to see some progress. Of course, if you miss a meeting or you don't have for a week or something, of course you know everybody knows that's that's fine but you know you should be making progress all along steady progress throughout the two semesters

24:26 - E. T.
and and therefore have something brief to tell us about each time yes are you know are you taking a two semester sequence um actually that's that was the only So I need to complete my graduate project to be able to graduate. So I have one course left in my graduate project. I talked to Dr. Pierce at the beginning of the fall semester, and she was like, maybe register for one credit graduate project, and then this spring term, you would register for the two credits so it would add up to three credits and it would fulfill your graduate project requirement. However, the thing is the course I registered along with the one credit graduate project for the fall semester was intense and unfortunately I was not able to do anything toward my graduate project.

25:35 - D. B.
Which is why you're here this project.

25:38 - E. T.
Okay yeah well let me let me just say you know these kinds some some of the sort of advising issues we can discuss um you know outside the meeting but the important you know if if you're going to graduate

25:50 - D. B.
next semester you've got to you got to do the whole six credits or whatever is left to finish the project if you're going to graduate in two more semesters or include the summer then you should do it across across

26:03 - E. T.
two semesters. I see. That's my guideline. Yeah.

26:06 - D. B.
Better to do it across two semesters. But if you're graduating in a hurry, you got to do the whole thing at once.

26:14 - E. T.
So this is for two semesters, spring and summer. Am I right?

26:19 - D. B.
Well, if you're planning on graduating at the end of next summer, then you would do it over spring and summer.

26:27 - E. T.
If you want to graduate in to do the whole thing next semester. OK. Would it be possible to do it during the spring term?

26:37 - D. B.
If that's, yeah, that's something we should really discuss. It's kind of an advising issue. You send me an email, and we'll discuss it.

26:47 - Multiple Speakers
I will.

26:48 - E. T.
Thanks so much.

26:49 - D. B.
L., how about you? What's your situation?

26:52 - L. G.
Oh, OK. So I don't know if more or less complicated than hers. I have three hours remaining of the requirements. I have three hours left for the final project, but the first part of my, I guess we'll talk about the rest later, but the question I had was, I'm open to other questions, but just like, I believe it was Mr., I don't know which person said it, I felt like I wanted something that I would know kind of what, you know, when you get down the path, what the correct answer was. Right. But I am open to other topics if there's some that you guys think may be better topics. I do. I've played around with agents a little bit. And so I'm curious to see what they would do with that. But I think maybe I try to try it out a little bit over the next week to see how that would work.

27:49 - D. B.
I'm going to leave it up to you. I mean, I kind of agree that, you know, if you write about, if you do this about some topic that you know something about, you're gonna be able to catch the hallucinations better. But if you don't, you know, I'm just, you know, again, this is exploratory.

28:10 - L. G.
I'm just curious what's gonna happen, you know?

28:13 - Y. P.
And I'm a big fan of, I'm a big fan of students doing what's interesting to them.

28:19 - D. B.
So if you're really, on writing a book about something you don't know anything about, I would say go for it and let's just see what happens. Yeah. Okay. Any other comments on, yeah, go ahead.

28:37 - Y. P.
The one idea that I have that we are using is sometimes, I'm going to give an example. So for example, we are using Next.js as a framework, which we had never used, very difficult to find subject matter experts. So it's very difficult when you don't have subject matter experts, which I spoke about that knowing something that you are putting agents on is helpful. So what I would, or we did was, which is a trick, is in those cases, you can use YouTube videos, top YouTube videos, which you can, I would say, so for example, if somebody is doing, scrambled eggs or something like that, or gardening, you find the top 10 chefs or whoever who have been scrambled eggs, their videos, take a summary of that, YouTube videos, use Gemini to do that, or there are other tools to create a description. And you can use third parties or third party sources as your subject matter expert also. Just an idea that we use because we didn't have a subject matter expert. Or we had to build our subject matter expertise in Next.js, which is a new framework. But that's another idea that we used third party reliable sources, like for example, for scrambled eggs, it is reliable top chefs, right? If they have scrambled egg recipe, then you can depend on those recipes because they are the top chefs in the world. I just wanted to give idea that sometimes you may be asked to do something where you are not the subject matter experts but you can use these sources as if you have heard about RAC and create that environmental layer on top of it which becomes like a learning module and you can use that as your virtual subject matter expert. Just sharing an idea if somebody has to choose a topic they're not able to find something or somebody who is a subject matter expert.

31:22 - Unidentified Speaker
Thank you. Thank you.

31:25 - D. B.
Any other comments? Well, J is not here. I keep wanting to show this video that he submitted to the AAAI conference. I'd rather he sort of thought it'd be better if he's here, but I guess I could show it when he's not here. And the video stands on its own and it's pretty interesting video. So let me do that. And we can always ask him questions about it if he comes back some other time or whatever. Anyway, so he submitted this This is one of the major academic artificial intelligence conferences. It's been going on for 40 years or more. Anyway, this year, apparently, they have a video track where they're soliciting AI-generated videos, or I don't know what kind of videos exactly, but videos intended for a public audience. And J submitted one. Let's take a look. I'm gonna bring it up here and I may have to, actually, I need probably to unshare my screen and then optimize for video or something. Let me try that. I'm gonna optimize for a video clip. Reshare. Okay, I am sharing, am I not?

33:00 - D. D.
I do not see a video. There is no video.

33:04 - D. B.
Okay, but you see my page, right?

33:06 - Multiple Speakers
Yeah, I see your page.

33:08 - D. B.
Yes, you are currently sharing your page. All right, I'm gonna go to the video. Okay, do you see the purple? We do. Okay, I'm just gonna go ahead and play it, you know. This is from J. J submitted it. He made it. I'm going to go ahead with it.

33:27 - Unidentified Speaker
A lot of people view generative AI as a threat to creativity, that it's going to replace artists. But I think it's going to have the opposite effect. It's going to make us more successful than ever. Artists who learn prompt engineering, which is just the technical term for communicating with AI, can build a team of mentors and collaborators. For example, if you use a prompt like, you are an expert grant writer for independent painters, based on my work, please walk me through the process of filling out this application. You can put that prompt into chat GPT, and because you've told it that it's an expert grant writer, it's gonna be able to act as that expert. Same thing if you say, you're a publicist for photographers, please help me plan my social media strategy. This kind of mentorship used to only be available to the top tier of creators. Now everyone can have a world-class art coach.

34:34 - Y. P.
Generative AI is also multimodal, meaning that it can produce text, images, audio, and video.

34:41 - Unidentified Speaker
So it can complement your work as a collaborator. Let's say you're a musician. You are really passionate producing your music, but now you can team up with AI to generate album art, create music videos, and produce writing that complements your work in a way that you couldn't do before. So AI isn't going to replace what we do best, it's going to amplify it. No matter what your style, medium, income, location is, you now have the opportunity to reach audiences that you wouldn't have otherwise and have a greater shot at producing art successfully full-time. So I guess what I'm saying is, it's not gonna replace us, it's gonna empower us. Oops, trying to catch that.

35:36 - D. B.
Yeah, because it says what methods you used.

35:41 - R. S.
Some of those I haven't heard before.

35:45 - D. B.
Yeah.

35:46 - R. S.
Cling AI, Suno AI, and 11 labs. OK. But I mean, match between the text and images.

35:57 - M. M.
There is no exactly kind of link between the text and images, but otherwise the text is wonderful. The images. OK.

36:13 - D. B.
Images are kind of random. I mean, they're kind of fun, but they're not...

36:19 - M. M.
Not related to the text.

36:22 - D. B.
Yeah, there's a loose connection, I guess.

36:25 - M. M.
Yeah. Well, that is good. I can see V is here and V has a very good design experience. Maybe one moment he will share with us now or later, V?

36:39 - V. W.
I was just enjoying seeing... I enjoyed seeing J's video for the second time because it has an impressionistic quality that I didn't appreciate the first time. I had been in a similar situation where I was trying to give life to some disparate ideas using and when you use runway, you can take an image that's on task for what you're trying to do, and then you can give it a prompt and you get a three or four second video out of it. And then you string those together like a storyboard and you've got content. So I thought it was very creative. You know, J is a science fiction writer, among other things, and I could see that influence in his artwork. So, yeah, this week I signed up for the two hundred dollar a month chat GPT pro, and it is truly the road to perdition because I found it so engaging. And it was like having a superpower king for a day or something like that. And so I just I just chose a task that I thought would be interesting. And I kept making progress I didn't expect to make. And it was really fun and very, very exciting. And it wore me completely out.

37:52 - D. B.
I'm still recovering from it, so. Well, if it wore you out, that means you weren't just sort of lazily letting AI do the work. You were sort of more truly part of an active part of the larger Yeah, it's like having a brainstorm that won't stop.

38:11 - V. W.
It's because whatever you can come up with, it amplifies it. And then the the relationship, as J points out, is. It's it's incredible because you're able to do all these things you always wanted to do that you thought might take a year, you can do them in seconds or moments or, you know, minutes or hours. And it's a very intoxicating adrenalizing type of activity and like what E said you know the AI is changing us and I'm not completely sure. I think it's something we're gonna have to learn to manage.

38:52 - D. B.
So Dr.

38:53 - Y. P.
W., can you share something about what was so different between the $20 and $200 if you with some example or something. Now you've got me excited to sign up for 200 and try something. Right.

39:09 - V. W.
I totally recommend that you do that because you can, well, I was told that you could back out of it if you wanted to, but I shouldn't advertise that as being true because I don't know for a fact that it's true. I just heard or read a report about it and it said so. So, you know, this is a do it your own risk kind of activity, But I would recommend that you work in an area that you're very familiar with so that you can judge the quality. And also, you can take these giant steps. Whereas before in programming, we design top down, but then we implement bottom up a line of code at a time. And I just wasn't used to developing 100 lines of high quality code. Over 100 lines of high quality code an hour is just a thrilling experience. Because it's such a the right it's a right question so it I think it lights up your whole brain and yeah I still I'm still coping with what happened I remember it being very exciting just the whole it was

40:16 - Y. P.
so exciting I continued doing it for 12 hours and so you know I'm not sure that's completely a good idea yeah and most likely that will happen to me too if you are that excited but I'm I'm curious I'm I'm going to use it now I may have some feedback about this my personal because I was like this paid one basic one is helping me so much how much great it would be but it seemed like there is a lot of value I'm trying to see what that value is I kept running I kept running against limits early on when trying to program with it.

41:00 - V. W.
You have to kind of babysit it. You have to figure out how you're going to talk to it so it doesn't forget what you're talking about. And that is to some degree been released. What I found out by sort of hard, the school of hard knocks was that it cannot deliver back to you in one gulp the complete rehash of what you've just talked about. So I was able to go to 20 shots, just getting a monolithic response. But then at 20 shots, we had to break the project up into eight chunks because it couldn't deliver all the content that had been accumulated because it was even past the 200 a month buffer length. But what was nice that I didn't realize before is that it had retained state information that it had simply forgotten before. So it's like you have access to a larger persistent state of consciousness, but you still have to get that back out in bite-sized chunks. It's a little bit like a person who's in a coma and you say blink once for yes and twice for no or something, except the chunk size is much bigger than a blink, but there's still this, there's still a

42:15 - Multiple Speakers
bottleneck on communication that it can't, you know, it can't completely flush out everything you've done every time. Does it have capability to build agents, automated agents or anything like that?

42:26 - Y. P.
No, actually.

42:27 - V. W.
Well, the right answer is I don't know, because I had to build it took me an hour to build the prompt for what I wanted. I gave it a loose description of what I wanted that had all the facets I thought were important. But then I said, please interview me. In each of these areas of graphical user interface and geometry and all the user interface subtleties that make a program usable with low user friction. And then it spent about an hour asking me questions that I answered as completely as I could. And then it created an eight point multi-page summary of what we were going to embark on. And then and only then did we embark on the first step of the eight step steps to try to get a version running one chunk at a time, which we did. Got it. Thank you.

43:24 - D. B.
So I'm wondering, you know, $200 a month sounds like a lot, so I'm glad they offered you a free two weeks or whatever. But, you know, if you're using it for your job, like you're something or, you know, professionally, it doesn't take that much an improvement in productivity to make it worthwhile. I mean, when you think about, like, take a professor, for example, $200 to me sounds like a lot to be spending on something for fun. But, you know, if it could save, you know, if it saved me several hours a month in time preparing classes or something like that, you know, it'd be worthwhile.

44:09 - V. W.
For example, a professional video editor will cost you $400 an hour to sit with them and put together content that's important to you. Or if you want to rent an airplane, it's going to be $120 an hour for the airplane and 50 for the gas. And so that's per hour. And so here we have something for 200 a month. So I asked myself if I work 12 hours a day for 30 days, it only works out to like a couple of dollars an hour. And so since it's like having a heavy machine tool in your shop, you have to pay for having this heavy machine tool there. But if you're always using this giant lathe to make stuff, then it sort of becomes absorbed into the cost of doing business. And this is like, it's so on the center line of exactly what it is we're doing in knowledge engineering and understanding what these tools are capable of, and acting as extensions of ourselves that it's, it's the only thing I'm

45:09 - Unidentified Speaker
missing is more hours in the day to consume it and, or use it. It's a lot of fun.

45:18 - V. W.
Yeah.

45:19 - D. B.
Or if you're, if you're a programmer, if it makes you 10% more productive, 15% more productive, it was probably a boost your professional career.

45:34 - V. W.
or it's more like 10 times more productive, which makes it a little bit addictive because remember you're used to struggling to get, well, you know, they say at JPL, the average programmer built four lines of code a day. And I thought, well, that's silly. Most people I know can do a hundred lines of code a day, but then it was like, well, you can now do a hundred lines of code in an hour. So you're eight to 10 times more productive. So that's allowing you to cover ground that you couldn't cover before intellectually because it's all in front of you.

46:05 - R. S.
Are you using artificial intelligence to generate 100 lines of code an hour? Yes.

46:13 - V. W.
But you have to guide those 100. I mean, you totally have to steer it.

46:20 - D. B.
But here's the thing I was thinking about.

46:24 - V. W.
It was like being able to have a magic wand And instead of saying how I wanted something done, I could say what I wanted done and the how you get for free. So it's like being a manager who can take a magic wand and simply illuminate tasks that you want done and then poof, they exist. And now what are you gonna do? And there were a couple of points where I had to do off task activities to complete the main thread. Like I had to build an airfoil database. And so I said, I don't really feel like doing an Air Force database. So give me a bash script that'll create a directory and populate it with these data files for these airfoils. And so I said, oh, okay, I'll do that. It built me the bash script. I ran the bash script and now I have the thing. It was like, kabam that we, I mean, I could have done it manually, but it would just took all that heavy lifting out of the equation and just allowed me to have the thing I needed right now. And I wondered like, it's like being a man, a total manager instead of just a grunt who's shaving off one piece of code at a time, like you're whittling or something.

47:39 - D. B.
Another question I have is, so J is into this idea of telling the AI, maybe you are too, V, telling the AI, you are an expert in gardening, tell me how to garden, as opposed to just prompt, like, just tell me how to garden. Does telling the AI you are a world-class expert make it do better?

48:05 - V. W.
Well, to me, the task factored a little bit differently. It was like saying, I want a hundred rows of corn now. Like it says, poof, you have a hundred rows of corn, now what? It's like, you already have the garden. That you can conceive of, you are just a few moments away from possessing. So that's an odd sort of superpower to have, and you have to actually learn how to use the superpower. So I spent a lot of time having it ask me to construct things. Then we ran into a weird misunderstanding about a couple hours in, and neither one of us knew where the misunderstanding was. And when we finally found it, it was extremely illuminating and got rid of a bug. And it had to do with the conversion from SI to imperial units, display calculations and internal calculations. And we had to make policies like internally, we always use SI units, but the user can see imperial units if they want, but those are not the internal versions. And we had to make these policies. So we jointly created policies that would simplify the code and make the chance for errors go away. And so then the error went away and it was a very kind of collaboration like you have at a meeting where a project is run behind, people are in trouble, they don't know exactly why things aren't going well, mythical man month, Fred Brooks and all that. And then you just have this deep discussion, knock down, drag out, fight to get at what is the problem here. And then when it's solved, it's incredibly like uplifting. So I got into one of those kinds of troubles. So, and then I got it. But the nice thing was, is instead of being in that trouble, you get into trouble, you recognize the trouble, maybe you've over-constrained the problem description, and that over-constraint is showing up later as having made something you thought was easy impossible, because there's a built-in contradiction in these conflicting goals that you've specified, but you haven't realized that embedded in your goals is this conflict, and then in the process of doing it, you understand the presence of this conflict, you resolve You create a policy to resolve the conflict and that process can usually take weeks or months and often are accompanied with tears and budget overruns and difficulties. And to be able to get through that in moments instead of months is very empowering. It's just, yeah, I was joking with my hand radio friends. This is the road to partition because it's so uplifting and empowering.

50:37 - D. B.
All right, well, we're kind of running out of time. Mentioned something that I'd like to spend a few more minutes on like next week. So N. is here and he's like to turn his master's thesis into a publishable article. And the idea that I sort of propose is to use AI to do it as much as possible, but not have it look like it was AI generated. Because otherwise, you know, publishers aren't gonna like it potentially. But more importantly, you don't want to have it so overly AI generated that its truth is compromised, but yet you want to use AI as much as possible. So that was the sort of task I posed for N., and I think I'd like him to address it next week for a few moments, although we're kind of out of time for this week.

51:31 - V. W.
That's a great task.

51:32 - N. M.
In a short but quick explanation, I did all the work I had all the research. I can explain things in my own way, but a lot of people fail to understand how I'm explaining it. So I put all the research into ChatGPT, point by point, and say, rewrite. Here's my work. Rewrite this to make it more comprehensive. Right. And having it not let...

52:00 - V. W.
I have to often discipline the AI not to take away my voice. And it can use previous interactions that it's had with you. It can use the personal profile that you can build with chat GPT to make sure that it's staying on voice. And often, especially when you use a lesser AI like Grammarly, it'll try to rewrite some words or phrases of emphasis that are not you, and you have to not let it do that. But also AI and the large can do that. And you can almost start reading it when it gets too flowery or too descriptive or too complete, It lacks that human feeling, and people will kind of tune out of it because they can feel it's automated.

52:42 - Multiple Speakers
It's automated. It's generated. It's whatever.

52:45 - D. D.
Exactly. Exactly. Yeah. I mean, I think that my approach would be to try to get the model to teach me how to write better and then write better.

52:59 - Multiple Speakers
That's how I would approach this. I wouldn't have the AI write a single word that I used. Well, that's not true. That's a little over.

53:08 - D. D.
I wouldn't want it writing complete sentences on its own. I think you've identified the crucial thing of chunk size.

53:15 - V. W.
If you write a whole big paper and then you feed it to AI and say, now make a decent paper out of this, the chunk size is so big that you're going to get you overwritten with it. But if you hand it smaller crafted chunks and say, these to reflect very specific lexical and semantic goals that I have. Let's just get that piece tightened up. Then when you make those a brick at a time, accumulate, you get something that reflects your own creativity and not just the AI slop.

53:47 - N. M.
Yes, that's exactly what I did. I didn't feed it the whole paper. If I was talking about the flaws of the H-index, let's say, because that's what my paper was about, I would give it one point. I'd give it the information that I collected, the research I've done about one point of the falls. I'd say, rewrite this and make it more comprehensive. Then I would deal with the next one and the next one and the next one.

54:15 - V. W.
I wouldn't give it the whole thing because I knew it would eventually merge something or make it into a format that I would not like, It'll tear stuff up.

54:26 - Unidentified Speaker
Exactly.

54:26 - N. M.
Exactly. Well, thanks, everybody.

54:28 - D. B.
And I guess we'll go ahead and meet next week. But the following week is going to be kind of whatever. We'll see. But we're going to meet next week. And we'll go from there.

54:43 - V. W.
Awesome.

54:43 - D. B.
So everybody, have a good weekend. And we'll see you back soon.

54:48 - Multiple Speakers
Great meeting, guys.

54:49 - N. M.
Thanks. Thank you. Bye, everyone.


Friday, December 6, 2024

12/6/24: TE research prospectus discussion, etc.

Machine Learning Study Group

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

Agenda & Minutes  (141st meeting, Dec. 6, 2024

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

Agenda and minutes
  • Announcements, updates, questions, presentations, etc.
    1. Grad student applies, is rejected due to AI-generated statement of purpose (AA):
    2.  TE gave an informal walkthrough of his research prospectus.
    3.  Hackathon:              Join us to innovate in LLM Agents technology across 5 dynamic tracks, welcoming both innovative agent applications and research projects on new technologies:
      • Applications: Build cutting-edge LLM agents
      • Benchmarks: Create innovative AI agent evaluation benchmarks
      • Fundamentals: Strengthen core agent capabilities
      • Safety: Address critical safety challenges in AI
      • Decentralized & Multi-Agents: Push the boundaries of multi-agent systems


      Incentives and Prizes:

      • Prize Pool: Over $200,000 in prizes & resources, including $100,000 in credits for top AI platforms and an additional $100,000 in credits, cash and merchandise.
      • Special Raffle: Participate in the hackathon for a chance to win travel grants to the LLM Agents Summit at Berkeley in the Summer 2025, which includes up to $1,000 in travel stipends, and priority summit registration.
      • Exposure Opportunity: Winners will have the chance to showcase their projects at the LLM Agents Summit.

      Distinguished Panel of Judges

      This hackathon represents a remarkable opportunity to push the limits of what is possible with LLM Agents technology, connect with a vibrant community, and potentially win big.

       

      How to Join
      To join the hackathon, please visit our hackathon registration page. You will find the submission requirements on the website as well. Don’t miss your chance to make an impact in the AI community!

      We eagerly await your innovative contributions and are excited to see how you will drive the future of LLM Agents technology.

      Best,
      LLM Agents MOOC Hackathon

      Join the LLM Agents MOOC Hackathon: $200K+ Prizes/Resources Sponsored by OpenAI, Google AI, AMD, Intel and More

      Dear developers and researchers,

      We are thrilled to extend an invitation to the LLM Agents MOOC Hackathon, hosted by Berkeley RDI in collaboration with our LLM Agents MOOC. This exciting event, sponsored by leading organizations including OpenAI, Google AI, AMD, Intel, and others, is designed to challenge, inspire, and showcase the capabilities of developers and researchers in the exciting field of LLM Agents. We are excited to share that over 2,200 developers have signed up for the Hackathon. The hackathon is currently underway and will accept final project submissions until December 17, in conjunction with our LLM Agents MOOC. The MOOC has ~14K registered learners & ~7K Discord members, with 35K+ views for the 1st lecture to date! 






    4. NM has a problem: how to convert a masters thesis, made with liberal help from AI, into a shorter publishable paper, using AI to help but which will not be flagged by AI detection tools like gptzero.com, etc.
    5. We're looking for masters student(s) to work on AI with Hexanika. Stay tuned.
The meeting ended here.
    1. JK submitted a video to AAAI 2024: video (https://drive.google.com/file/d/1KJNQQU7IfSywljADxkGHMZuDkchbIc38/view?usp=sharing); call for videos (https://aaai.org/about-aaai/aaai-awards/aaai-educational-ai-videos). See also complex prompts, etc. (https://drive.google.com/drive/u/0/folders/1uuG4P7puw8w2Cm_S5opis2t0_NF6gBCZ).
    2. Here is a tool the library is providing. Some people here thought it would be a good idea to try it live during a meeting, so we can do that.

      Library trial of AI-driven product Primo Research Assistant

      The library is testing use of Primo Research Assistant, a generative AI-powered feature of Primo, the library's search tool. Primo Research Assistant takes natural-language queries and chooses academic resources from the library search to produce a brief answer summary and list of relevant resources. This video provides further detail about how the Assistant works.
      You can access Primo Research Assistant directly here, or, if you click "Search" below the search box on the library home page, you will see blue buttons for Research Assistant on the top navigation bar and far right of the Primo page that opens. You will be prompted to log in using your UALR credentials in order to use the Research Assistant.
       
    3. DB plans to try to find a masters student to do the project below starting next semester. An important qualification for the student is to be able to attend these meetings weekly to update us on progress and get suggestions from all of us! 
      • Project description: Suppose a generative AI like ChatGPT or Claude.ai was used to write a book about a simply stated task, like "how to scramble an egg," "how to plant and care for a persimmon tree," "how to check and change the oil in your car," or any other question like that. Just ask the AI to provide a step by step guide, then ask it to expand on each step with substeps, then ask it to expand on each substep, continuing until you reached 100,000 words or whatever impressive target one might have.
      • Anyone else have a project they would like to help supervise, let me know!
    4. 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 when available, every now and then but not every week.
    5. Anything else anyone would like to bring up?
  • Here are the latest on readings and viewings
    • Next we will continue to work through chapter 5: https://www.youtube.com/watch?v=wjZofJX0v4M. We got up 15:50 awhile ago but it was indeed awhile ago so we started from the beginning and went to 15:50 again. Next time we do this video, we will go on from there. (When sharing the screen, we need to click the option to optimize for sharing a video.)
    • We can work through chapter 6: https://www.youtube.com/watch?v=eMlx5fFNoYc.
    • We can work through chapter 7: https://www.youtube.com/watch?v=9-Jl0dxWQs8
    • Computer scientists win Nobel prize in physics! Https://www.nobelprize.org/uploads/2024/10/popular-physicsprize2024-2.pdf got a evaluation of 5.0 for a detailed reading.
    • We can evaluate https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10718663 for reading & discussion.
    • Chapter 6 recommends material by Andrej Karpathy, https://www.youtube.com/@AndrejKarpathy/videos for learning more.
    • 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). 6/7/24: vote was 4 3/7. We read the abstract. We could start it any time. We could even spend some time on this and some time on something else in the same meeting. 

Transcript:

ML discussion group  
Fri, Dec 6, 2024

1:36 - Unidentified Speaker
All right.

1:37 - D. B.
I'm going to share my screen.

2:19 - D. B.
Okay, so although we're sort of classes are over and we're at the end of the semester, there's actually a lot of stuff that sort of ended up on the on the list of things to potentially get to today. We're not going to get to them all. So if we don't get to it today. We'll get to it next time. Here's one. Someone sent me this note from a grad school. So a grad student applied to grad school, and the AI generated their statement of purpose. And the grad school checked, did an AI, generative AI check on their statements of purpose and rejected the applicant. I'll let you, let's see if I can, Let's go to this. Here's the letter.

3:24 - Unidentified Speaker
So the fourth paragraph there.

3:36 - A. B.
Yeah. Your personal statement was AI generated.

3:39 - D. B.
Therefore, we aren't going to accept you.

3:42 - A. B.
Well, someone a few meetings ago, I think, can't remember what department they were with, but we asked that question about AI checkers and whatnot. And I think the consensus is that they're just not accurate enough to actually do that to a degree that you would want catch plagiarism or do this sort of stuff. So it's interesting that people are taking a more aggressive stance, I guess, than admissions.

4:12 - D. B.
Yeah, you know, I don't know if it's the people that that these systems don't work. I think it's that there's a proof problem. You know, they may work, but you can't use it as proof, you know?

4:25 - A. B.
Right. Well, it seems like they are here at least.

4:29 - D. B.
That's interesting. Yeah. I use Grammarly.

4:32 - E. G.
all the time because I'm trying to get a large amount of information out. And a lot of times I'm used to presenting it very succinctly, but I'd like other people to absorb it. So I ask it to go in, correct the sentence structure and things like that. Does that, would that preclude me? You know, I don't know.

4:58 - D. B.
I mean, you're, you're right. It yourself and then, or maybe you're rough, rough drafting it, and then you're asking it to kind of polish, polish it. You know, you could try one of these checkers, like one of them is called GPT-0. If you just do a web search on GPT-0, it's, it's free, right? You can, you can paste stuff in it and you can see if, if Grammarly will be, will flag, it'll flag that.

5:22 - A. B.
I'd be curious to know, I mean, if you try it.

5:25 - D. B.
Because, you know, I think it's just perfectly natural to write something yourself and then, you know, even a rough draft, even some rough, you know, some notes or something, and then ask an AI to kind of put it into a nicer expository, you know, format, which you can then edit. Is that bad? You know?

5:47 - T. E.
So that's an interesting point. And the course that we just finished up with Dr. P. for I don't remember the name of it, but it's basically we went through the process of writing a research proposal for our dissertation. And her stance on it was she didn't mind us using these tools just to make note of it in the references that we did.

6:16 - D. B.
Yeah. So what course was this?

6:19 - T. E.
It's the course that I actually used to do the proposal. That you asked me about. It was information quality. Let me see if I can find it real quick. Information quality theory? Possibly. Okay. Go ahead.

6:39 - E. G.
I just put an email that I wrote and I ran it through it and it says 97% AI generated. And I wrote, Yeah, 90% of this email.

6:56 - A. B.
But you wrote all of it, right? I wrote nine 90% of the email.

7:02 - E. G.
He wrote 3% of it.

7:05 - Multiple Speakers
Yeah.

7:05 - T. E.
According to this, I only wrote 3% of it.

7:10 - E. G.
I'm just teasing.

7:11 - T. E.
Yeah, I don't know.

7:13 - D. B.
I kind of noticed in using chat and using gbt zero that that I didn't try the numbers it came up with. If I had a paragraph, if I had a chunk of text that I wrote most of it, but a couple of sentences were in fact fully AI generated, it would flag it as AI generated.

7:36 - A. B.
So if you took an output from chat GPT, and then let's say you took that output and then you asked Claude or another one to randomly change some of the words here or there for synonymous words, would that then fly under the radar of these tools?

7:55 - E. G.
Actually, V. showed me a tool that is able to go in and rewrite stuff so it's not picked up by AI generators. V., do you remember that tool?

8:11 - T. E.
No, I don't.

8:13 - V. W.
And I'm curious about that because, Last week, I did a presentation where I pitted the AIs against each other. I thought the results were dubious. I presented them, and now I'm going back over them with a fine-tooth comb. It's been a real difficult process to establish what the truth is. I asked four different AIs how much they cost to develop, how many training tokens were used, and what kind of user input context length is allowed. And they were all over the place. So I actually did a mathematical investigation of just how all over the place they were. And it's, it's, I would say was a little when I got really rigorous with it. It's like the AI is picked up on that. And they they snap to but yeah, I'm one that you mentioned was stealth GPT.

9:09 - Multiple Speakers
But I had found another one undetectable.ai.

9:12 - V. W.
I don't have enough experience with those to really say except for the fact that I find it interesting that you'd write 90% of an email and it would say 97%. So it says it makes me not trusted at all. Because the figures that I was asking it to generate last week, were not accurate. And now I'm doing a fine tooth comb analysis of just how inaccurate For example, Claude Artifacts was publishing that it could program in all these languages when in fact it's specialized for HTML, CSS, and JavaScript. So that's not OK. And I've got to be able to quantify just how true or untrue a statement is. So I'm off on the thing of that, hey, we're using AI so frequently in our work. And also, grammarly, we'll try to rewrite content that I have written and it will use things that are out of voice for me. And so I'll have to reject them saying, you know, I appreciate you changing that word. But for example, I frequently use the phrase with respect to as a comparative statement for comparing and contrasting two ideas. And Grammarly tries to remove the with respect to and use some more flowery language that's not what I meant. And so I have to say, I don't suggestion. So it's like I've kind of gone through a period of like, this wholehearted embrace of anything that I could do to now I'm starting to get pissed off that it's trying to take my my true intention and voice away and I'm trying to claw back my identity.

10:57 - E. G.
I'm thinking of it from a different perspective. We work with a day in day out. What if It's generative language is now become infused in our. Yeah. Is it changing our vernacular?

11:13 - V. W.
Is it changing the way?

11:15 - E. G.
Is it changing us?

11:17 - V. W.
Well, if it changes the way we communicate, it is changing us.

11:23 - Unidentified Speaker
Therefore.

11:24 - E. G.
It is taking over. Oh, yeah. Being assimilated.

11:28 - V. W.
Talk about assimilated. There was an announcement two days ago that, OpenAI has agreed to use its products as war tools for the Pentagon. And I was really disheartened by that because we have all these 439 scary moments in this seminar of which war has come up as one of them. And they were talking about drone swarms for the Pentagon and things like that. And I'm thinking, we've already got mass death in the Middle East right now. We don't need any more of it. It's AI facilitated. And so, yeah, it's terrible. I was really concerned about that. And that made me double down on my factual check. For example, if I'm gonna hire an AI employee that happens to be a programmer, I'm gonna want it to give me some references. And so one of the things I'm gonna do is I'm gonna ask its peers, and its peers are other LLMs that might be possibly employed instead of the one that's the candidate. And so I'm using this kind of would I trust this line of reasoning I'm engaging into to somebody who just came in off the street, who may have been programmed by any nation state with any set of motives, and would I trust this thing to do that job for me? And so this making an AI do it, ask questions about who built you, how much did you cost, how smart are you, and how smart are you gonna let me be with what, because of your input token length. Be the smartest AI ever, but if you limit my input to you, then I cannot take full advantage of you. So I'm treating AIs now as, you know, in potential employees. And now they have to be, give me their references, show me their background, show me how they were trained, show me what they were trained on. And this all came out and I'll wrap it up after this is six out of 10 of the references that I had chat a one mini generate for me. Were specious. And it wasn't till I went and visited every one of them and counted them up and reviewed their content. It's like, you're just spinning a big yarn here.

13:41 - E. G.
Well, I got a question. And this, this can be a topic. But V. brings up a very valid point, you're going to be using AI as an employee. But Are you paying them?

13:56 - A. B.
Oh yeah. Oh yeah. I'm paying them.

13:58 - V. W.
Um, and in chat G open AI wants me to pay them 200 a month, which is a little above my ceiling for a monthly fees. I, you know, I've got all these $20 subscriptions that are killing me. And so I was supposed to go to two, 10 times that I don't know.

14:14 - E. G.
Cause I'm only paying a chat GPT, 20 bucks a month.

14:18 - V. W.
Yeah, but there's an open AI just released a $200 a month version for professionals and researchers and academics. Well, that's pretty much everybody's sitting here.

14:26 - Multiple Speakers
Well, no academic is gonna pay $200 a month unless they're getting a million dollar grant or something like that. Or maybe for the whole lab.

14:35 - V. W.
It seems more than the cable TV bill used to be, so.

14:39 - D. B.
All right, well anyway, that's pretty interesting. Here's the second item on our agenda.

14:44 - Multiple Speakers
So, T. E. is a student in our department and he'd like to give us an informal walkthrough of a positive possible research project, and I told him it was very informal and that we were friendly, so please be informal and friendly. Welcome to the group, T.

15:03 - D. B.
And I'll turn it over to you.

15:06 - T. E.
Well, and the opening topic is a great segue into this research, and there was a few weeks ago, there was some discussion very similar to this, and Dr. B. kicked around an idea of using chat GPT and the Socratic method in teaching in education. So, that's kind of what, you know, I talked to him after that. He's actually my research advisor as well for my dissertation. And so, I talked to him after that meeting. And he was kind enough to say, you know, I told him I was interested in that topic if, you know, I didn't want to step on anybody that was already doing the work, you know, or whatever. And he said, no, take it and develop it and see what you can come up with. So, like I said, for this information theory class, we had to write a proposal for a dissertation as our final assignment, and so I with that and I don't know how you guys want to do that if you want to just walk through it or just give I can give you the high the high points real quick I don't want to take up too much time but basically I think I think Dr.

16:34 - D. B.
B. sent it to everyone I don't think I did okay but you can share your screen if you like and just kind of use it or or just go through a list of...

16:48 - T. E.
Yeah, so basically, we're trying, this research, I'll just read you the introduction. This research proposes an innovative approach to education by combining the Socratic method with artificial intelligence to create a dynamic learning tool. AI-driven Socratic questioning, it's aimed to comprehension and engagement with students across various educational settings, you know, whether it be... Do you all know what Socratic questioning is?

17:23 - D. B.
Yes, questions that lead into critical thinking, where the teacher at that point really doesn't present or lecture.

17:32 - E. G.
What they do is ask questions and let the organic nature of the questions generate more questions and conclusions by the students.

17:43 - T. E.
Yeah, that's correct. And apparently it's very popular in law schools as a teaching method and it's based on Socrates, the philosopher, is kind of where it all started. And so what we're looking at doing is use the, and I think Dr. B. kind of showed us what he was doing, some of the he was kind of playing around with the idea and he kind of showed us the transcript of that that day on the call but some of the things we're going to look at is um the questions I have right now is what extent can ai an ai model replicate the socratic method and emulate human-led questioning in educational context and how effective is AI-driven Socratic questioning and enhancing critical thinking and comprehension skills compared to traditional teaching methods? And thirdly, what are the subjective experiences of students interacting with an AI tutor that uses a Socratic method? Now, having not gone through this process before, but from what I understand, those questions may change a little bit depending on where the research leads us down the road.

19:07 - A. B.
So, in that though, and I'm not a definite expert here, but it seems like you'd have to really like you'd have to do true like IRB because you'd have to have like human subjects, I think. That is, yep, I'm sorry, I didn't mean to cut you off.

19:22 - T. E.
No, you're good.

19:23 - A. B.
Yeah, you're right about that and I was talking to Dr.

19:27 - T. E.
P. about that and she sent me a link. I haven't read it yet. But because it's an education setting, if I'm not mistaken, somebody have to help me out here. Maybe it's not quite as rigorous. I'll have to go and check out the link that she sent me. But that conversation, because when I started my dissertation, I did take the ethics course and all that.

19:59 - A. B.
Yeah, the CBT stuff.

20:00 - T. E.
And they talked about the IRB and I was kind of hesitant, you know, I was trying to, my, you know, my initial research ideas were trying to steer away from having to go through all of that. And Dr. B. kind of said, you know, it is a process, but it's not as bad, you know, it's something that we felt like we could get through.

20:23 - D. B.
So, so I could use, like, if you if you came up with a method for doing this, you know, using an AI to be the tutor, using syncretic questioning, I could use it in my classes. And I'm willing to do that without IRB approval. Now, if we take data from the classes and try to analyze how well it worked, then I don't know.

20:47 - T. E.
We might need IRB approval. Okay. And that's probably the link she sent me to. But from based on the research I've already done I feel like the the more complicated part is going to be coming up with a way to analyze you know we'll have to come up with a set of some kind of assessment for whoever for the students that go through the Socratic method and the ones that don't go through it and compare the results because we want to know, you know, did it and this may be cross-disciplinary where we may have to probably have to get tap someone from education or psychology to help come up with the assessments.

21:44 - Multiple Speakers
If you've taken anything from Professor S. This seems right in his wheelhouse. So I don't know if he's even still teaching, but he's one of the best intellects I think we have in our education department.

21:57 - V.W.
And that's one item. And the other item is J. K is an excellent prompt writer. And I would really be interested in the multi-agent aspect of the Socratic method, because in that method, you're kind of putting the AI in the driver's seat of composing the questions that it thinks are going to lead you to the most enriching exchange between the student and the machine. And since you're doing that, it reeks of multi-agent as soon as you start saying the word assessment, you're asking the AI to change hats from, here's what I did with the student versus here's how I want to analyze what I did. Well, that's at least a two-hat multi-agent process. And J. K has a conspicuous talent for prompt writing from the multi-agent point of view because of his background in character development for writing science fiction and so forth. So he's really good at it. And, you know, we all want to do like, oh, completely own our work. But having the right consultants to our work can really take us up to the next level of achievement. And so I would really like to see you talk with J. K and Professor S. How do you spell S.?

23:12 - D. B.
S-U-T-T-E-R.

23:13 - Multiple Speakers
And J. K was the last name?

23:16 - V. W.
Yeah, J. K. He's usually here and I really am sad he's not here today because he would have been just chomping at the bits to have an exchange with you.

23:28 - T. E.
Okay.

23:29 - D. B.
You know, another possibility is Dr. P. She's actually typically pretty interested in these kinds of, you know, teaching oriented survey type projects. So she actually supervises a number of PhD students who do surveys, not of students, but of people in industry and things like that.

23:49 - T. E.
So she'd be another good person. That's good, because it was her class, and I turned this in for my project, my final project. So if I get a good grade on it, maybe that'll be a promising thing.

24:09 - Y. iPhone
I'm not an expert in this subject matter, but if you need any help from engineering standpoint, I can ask some of my people to help you out. So if you need any help on the engineering side, maybe around 100 to 200 hours of time, I'm ready to offer that help to you.

24:32 - T. E.
Oh, thank you so much. Okay.

24:38 - D. B.
All right.

24:40 - T. E.
So, that's kind of the high-level overview. I ended up doing for the literature review, I ended up breaking it down by, where'd it go?

25:05 - T. E.
We ended up having 20 reviews and for some reason I can't find it on here. There it is. Yeah, 20 different sources that we looked at effectiveness. There's some research that's been done in effectiveness in educational settings, personalized learning and adaptability. Driven and critical thinking support. There's been some research done in that. That I reviewed. Development of AI systems for Socratic dialogue. And so that brought up an interesting point. Apparently, there's some software out there. And one of them is called AutoTutor, which I didn't really dig too much into it. But there was a study done by G. back in 1999 that talked about this AutoTutor. And I don't really know that there would be any need to develop something outside of CHAT-GBT. I'm thinking maybe CHAT-GBT would, in its form today, would be able to do what we're needing to do for the research.

26:24 - V. W.
I would say you would want more than one LLM so that you could compare their responses and get some contrast. And for those, Claude Sonnet would be good because of its, you know, it's really a good LLM. And also, E. introduced us to the Facebook LLM, which has now been supercharged. The Lama is now up to Lama 3, 405 billion token model. So, you know, those, those, if you go through something like Poe.com, you can write a prompt and then you can, uh, shovel the, your prompt from LLM to LLM and get really fast turnaround on a compare and contrast of what they're saying to kind of get, to find out if there is among the LLMs, uh, an expert consensus or more importantly, a contradiction.

27:18 - T. E.
Yep. So you mentioned chat GBT and what was the other one?

27:23 - V. W.
Uh, Claude sonnet. Well, the most important thing I probably mentioned was the fact that Poe.com lets you have access to multiple bots of very high quality, including the Gemini advanced engine. And that's Poe.com. It's 20 bucks a month.

27:41 - T. E.
It's the same price as a chat GPT subscription before last week.

27:46 - V. W.
And so you can just go from LLM to LLM very quickly and then The Llama 3, 405 billion token model. And then of course, chat GPT has now gone from 1.0 preview to 1.0. And to get at the 1.0, you have to use the chat GPT site because POE doesn't give you direct access to that model, but it does give you the access to the chat GPT 4.0 level of models, but who wants to use yesterday's model? So, yeah. Okay. Good, good information.

28:17 - T. E.
I got, I made note of that so I can look into those. So that's kind of, again, this high level. Some of the other things that I think are important would be getting feedback from the students to see how they felt about the process using artificial intelligence. If they felt like it was too slow, you know, in responding, or if they felt like, you know, it was a natural conversation or, you know, I don't know. Again, I would have to probably speak with someone from the psychology department or education department on how to come up with those assessments and evaluations.

29:10 - V. W.
You could ask an AI.

29:12 - T. E.
And we're back to E.'s seg.

29:15 - E. G.
It's called key think times because your key think time at that point is your gap in digesting the information, formulating a response. Now, just like AI, it's going to be based on the back end computing power. Somebody with a much more powerful brain will be able to come off with a more detailed, deeper answer and understanding than one who is, say, running on a Visa card. Not Visa, V-E-S-A, which is an old, old video card.

30:08 - T. E.
Oh, okay, okay. B-E-S-A, okay, yeah, yeah.

30:11 - E. G.
But what I had done previously is I had actually taken the output from one model, ran it through the same model again, and asked it to identify whether or not you were hallucinating. This is actually some of the stuff D. and I had postulated. But it was able to identify to say, I know this information. I surmise this information. Uh, I extrapolated this information and I asked for information.

30:44 - V. W.
It's sort of like asking a crazy person if they were making something up when they talked to you in the last conversation. And I've, I think one has to have a lot of skepticism. I really liked that going to psychology. You're, Your topic is so timely, even it's on trend. It's got so much potential for harnessing the educational connection to use of LLMs by students who want to improve their own understanding of things. So it sounds super interesting to me. I would really be curious to follow this work.

31:22 - T. E.
And I think it hopefully it could lead into like answer some of the questions that we had at the beginning of this call where like this administration that rejected this student's use, rejected their application because they detected AI usage.

31:40 - V. W.
It's like asking the crazy person, you know, did they forge this? Yeah, they forge everything.

31:48 - T. E.
Get out of here. So maybe, you know, rather than just rejecting anything, maybe we should, and I think this was an idea that we kicked around last time I was on this call, come up with ways to embrace AI and use it in teaching and learning, as opposed to just saying, hey, you used AI, so we're going to kick you out and fail you. And that's not where things are going.

32:18 - Multiple Speakers
Yeah. Yeah.

32:18 - T. E.
And I believe there was a conference that someone on the last call had attended. And this was the topic of that conference as well. I think it may have been someone from UCA or possibly, I don't remember what her name was, but that's kind of where this research is going and we'll see what happens. This is Y. and I agree. I concur with that.

32:47 - Y. iPhone
And one of the ways I like to give back to society is in the form of education. That's why I would like to help or contribute in any ways if you need help. And what I can help primarily is on the engineering side, on the back end side, because the front end topic is not my expertise. So happy to help you out in any ways possible.

33:18 - T. E.
Yeah, I appreciate that.

33:19 - D. B.
That's great. Well, with that, I'm going to come back to this hackathon announcement, but let's segue into, where are we? Oh, okay, yeah, so Y., I had a chat with Y. earlier today, and so we're looking for master's students to work on AI with his company, Hexanica, so just mentioned that. Y., I don't know if you wanna just say a few words about it, or at any rate, there'll be something to say certainly next semester. Sure, so I can give brief background.

33:58 - Y. iPhone
The main topics that we mentioned, and which is actually a follow-up of what we spoke on the previous couple of calls, is around use of generative AI in code development. So if you all remember, Dr. W. had presented a chart of various GPT models versus coding standards. And I had also mentioned that we'll present something, but it appears that most likely it will be in the first or second week of January when we meet. I'm sorry, I'll try to do before the year end, but my team feels more comfortable presenting it later. But anyways, There are two areas that we identified. One is how to use generative AI right from conceptualization, which Dr. W. had as text to code, then code to code, meaning unit testing, integration testing, right up to user testing and production. So in the development world, we call CICD pipeline, my team has already tested few things which we will present we have created standards documentation which we are signing off literally later this week or over the weekend and starting on implementing that next week and and the students that we are talking about with essentially be trained on those guidelines documentation and etc and they will start using generative and guide that is the guide in version one, but there will be two sets of team, D. and I mentioned. One is people who can contribute to engineering and a team of students who may not be core engineers, but they can follow the standards and see whether whatever we have built is working properly or not. So that is one set of things. And the second set of work would be using generative AI for website or content, D. had a plan of look, but around that topic, like how we can use generative AI to automate that function. So I've sent maybe a one pager to D. earlier, but if you all want to know how it is going to work, when we present what we have done, we can present also what we'll do with students then is

36:43 - D. B.
that enough or do you want me to say anything more or do you want to add or remove anything what I said oh that's good unless anyone has any questions anyone have any questions about this so yeah so I'm gonna be looking for master's students who have projects to do and and we'll want to work on this okay I had a very productive exchange on how we do double blind testing We're really wrestling with this problem of how

37:13 - V. W.
do we evaluate a piece of code that an AI has generated when the person who was prompting the AI had their own prejudices or biases about what the code should do or look like or what it would be good at. And so we talked about the possibility of creating like two experiments we kind of go off and don't inform each other except for some ground rules of what we might like to see. And then we come back and we ask, how well did the various LLMs do at meeting our program specification? And this goes right into the work of D. D., who we don't want to, we want to embrace that however it fits in. And so this idea of coding to a specification and then judging how accurately the specification was met came up when I did the side-by-side comparison of the performance of all the LLMs on all the different languages, which in fact turned out to be not complete fiction, but enough of a fiction that it needs to be studied in a little more rigorous detail.

38:28 - D. B.
Okay. Yeah.

38:28 - Y. iPhone
And to that point, the presentation would be around our assessment on a few of the models that Dr. W. had on that chart. And only one vertical for now, which is around front-end. I think there was a section of HTML, CSS, and JavaScript. Having said that, when we present, we'll also mention why we chose Next.js versus JavaScript. There could be some amendments. But we will present our assessment on one vertical and three models. And later on, we are also going to do on Python. But that's what we'll present.

39:17 - Unidentified Speaker
I'll try in maybe two weeks. But if you're not going to meet over Christmas break, then maybe it will be in January.

39:27 - D. B.
I haven't really thought about when not to meet. When to meet. We'll certainly meet next week. And, you know, I don't know if Christmas is on a Friday or something, I probably wouldn't meet. But other than that, you know, as long as there's participation and so on, people want to meet, we can keep meeting.

39:47 - Multiple Speakers
This is what we do. Yeah. I mean, this is not really a UALR sanctioned activity. It's just us, right? Okay.

39:55 - Y. iPhone
So I just wanted to mention, I got notice of this hackathon invitation.

40:00 - D. B.
Yeah. So if you're interested in hackathons, you might want to check out this today's minutes and read about this hackathon invitation. Build cutting edge LLM agents. $200,000 in prizes, distinguished panel of judges from like UC Berkeley and Google DeepMind and OpenAI and everything. I sent this to J.

40:28 - V. W.
as well as the CS mailing list. And when I read through it, it just gave me a sense, this is something he could walk in there and just show some of the work he's already done in learning tools and just, you know, maybe grab a prize or two.

40:44 - D. B.
Well, I hope he does. I hope he does too. Let us know what happened. Anyway, he can join by clicking this link. And so can you. Anybody. So yeah, any other comments on this? Let's see, submissions closed December 17th, another 11 days. Thank you. Okay, what else? J. sent, he sent around, I guess, I don't know if you all got the email that he sent with his submittal to the AAAI's track on videos or something. And if he was here, I'd show the video. It's like a two minute video. He did this, it's pretty good, but I wanna wait for him to actually be in a meeting to do that. So we'll probably do that next time. I have a student, he just got his master's, just completed his master's thesis. He used AI liberally to make, to help write the thesis. And we'd like to turn that thesis into a shorter publishable paper using AI to help shrink it, which AIs can do pretty nicely. But the hard part is we don't want, we wanna come up with a good paper that can be published, but won't be flagged by AI detection tools.

42:15 - E. G.
So- That's what we're talking about, beginning of this meeting.

42:20 - Unidentified Speaker
Yeah.

42:20 - Multiple Speakers
Lather, rinse, repeat.

42:21 - D. B.
Just put it through the AI detector till it says you wrote it.

42:27 - Multiple Speakers
Yeah. So yeah. Or one of these AI tool, these tools that purport to turn a AI generated text into make it non-detectable.

42:37 - Unidentified Speaker
Um, yeah. Anyway, I wish he was here. We could, uh, um, Dig into that. So anyway, I told him, just start working on it and we'll see how to come up with the workflow that'll make that happen. Okay, well, let's see. Anything else anyone would like to bring up? There's a couple other things which take more than a minute.

43:16 - D. B.
We'll talk about them next week, probably. Hearing nothing, I guess we can go ahead and adjourn and meet again next week.

43:27 - V. W.
Thanks for the meeting. Yeah, awesome. Thanks. Take care.

43:32 - D. B.
Bye, everyone. Bye now.

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