Tag: AI

  • A Little Brainstorming with an AI

    I was asked to do some a little thinking and brainstorming recently. Rather than send some emails or get on a call, I decided to ask my local AI a few things. This talks about the responses and reactions from my local DeepSeek AI..

    This is part of a series of experiments with AI systems.

    Requests for Feedback

    I’m a part a research group that is trying to learn how to work better with others inside or outside of an organization. As a part of this, I was asked for some questions we might use to survey people on how they work as a baseline.

    I was a little stumped on where to start. I had some ideas, but everything sounds to vague or too specific and I felt as though I couldn’t find a good place to start. So, I decided to ask my AI.

    I have a DeepSeek model running in a container, so I opened my browser and asked this question: What are some questions I can ask employees to understand if they collaborate well with others?

    The response was interesting. DeepSeek tries to give you some insight into how it approaches the problem. The initial responses showed a little stream-of-consciousness that reminded me of someone thinking out loud. Here’s the first part:

    Okay, so I need to figure out how to determine what questions to ask when employees work together. I’m not really sure where to start, but maybe I should break it down step by step.

    First, I think about why we’re asking these questions. If it’s to understand collaboration, then we want to know if the team is working well together, communicating effectively, or if there are areas they’re struggling with. So, what kinds of questions would help us assess that?

    I remember reading somewhere about gathering feedback from employees. Maybe those are good ones because they can show how each person feels about the group’s work. But how exactly do I phrase that? Like, “How have you felt about the team’s performance so far?” or something along those lines.

    Then there’s communication style. If an employee doesn’t contribute much in the moment, maybe asking them to describe what went on before they spoke would help identify if their approach is effective or not. It sounds a bit direct, but it might reveal issues like being quiet when someone speaks up later.

    Collaboration skills are another area. I think it’s important that employees know how to work with others, so asking specific questions about group processes and roles could be useful. Maybe something like, “What do we use for planning meetings?” or, “How often do you give feedback within a week?”

    From there it had more explanation and then it said “consider the following structured approach:” and it gave me a set of bullets, which you can see some of in the image below.

    2025-02_0298

    This wasn’t quite what I was looking for, but it did get me thinking and helped me send a list of possible questions to the group to consider. This was as helpful as if I’d have called someone, but way quicker and I didn’t interrupt anyone else.

    I was genuinely pleased by the way this went.

    A Recommendation Letter

    I had an author ask me for a recommendation letter. This has happened in the past and I’ve written a few of them, but I always struggle to get one written that sounds professional and not like I’m a clown of a DBA/Editor who wears Hawaiian shirts to professional events.

    Again, I decided to ask DeepSeek to outline one, giving it the title of an article. It had a few suggestions and then gave me a draft. My prompt was: draft a reference letter for XXX YYY for the article: ipsem lorum ipse lore.

    First I got the thinking, making sure I was considering the aspects of the article, should I point out some technical things in my recommendation. It also thinks about including the impact of the article as well. Next, I got a draft with some “insert name” and “insert date” places.

    I then added another prompt noting this was for SQL Server Central, which is a respected and long-lived (24 years now) publication well read in the industry. DeepSeek then adjusted its thinking, noting that we want to include info about SSC, how we review articles, etc.  This was the end of the thinking, which I really liked. It’s the type of thing a human might say to let me know what they’re going to do:

    2025-02_0299

    The draft letter is still a little off, with too much praise for me. This is a good article, but it’s not amazing. In any case, this gave me a decent first draft I could edit and then send off to the author.

    It’s not that I couldn’t have done this, but this draft saved me some time and allowed me to clarify my own thinking about what I actually wanted to write.

    I think this is slightly better or worse than if I’d asked a human to help give me a draft. Some people might have given me a slightly better draft, some worse, but I’d still be adjusting the tone and editing the content. I know because I’ve used humans for this exact task before.

    This was interesting to me to play with an LLM and look for help. On balance, this didn’t take long and I think I did get some help from an AI. It didn’t do my work, but it helped.

  • Unreliable Narrators

    I listened to an interview with Grady Booch. If you’ve never heard of him, he has been a software engineer for a long time, developed UML, and worked at IBM and a number of other places. He has devoted his life to improving software engineering. He even told Bill Gates he didn’t want to be the Chief Software Architect at Microsoft.

    At one point he had a less than flattering description of AI LLMs. Politely, they are unreliable narrators. Less politely, he feels that they allow us to build at a global scale, unreliable BS generators. This is because the LLMs that are stochastic parrots, which can produce some coherent results. Primarily they allow us to navigate a very large lake in space, i.e. the Internet. I think that’s true. I have found AIs to be pretty good search engines. Not perfect, but good.

    Mr. Booch notes that LLMs, while interesting, are a shadow or a whisper of what humans can do. He’s critical of those who think AI is going to compete with humans. Here are limitations on what the tech can do, and Mr. Booch thinks that the approaches people are taking, architecturally, are wrong. As part of his work, he studies more of how humans work and think as a way of trying to build better software architecture.

    Caveat, he does think we can build more intelligent systems, but it’s not with Gen AI/LLM architectures.

    I tend to agree with him and do think that the LLMs are unreliable. They appear to be intelligent, but they are more predictive engines in many ways. They can be very helpful in many ways, but they aren’t necessarily replacing smart humans. They might help smart humans replace some other humans, but they are likely to be better assistants than replacements.

    It’s a great interview and worth listening to. There’s a walk-through where Mr. Booch touched on computing as well as a very positive outlook on the future of his career and the things that he is working on. It’s long, (1.5 hours), but a fun listen. Give it a go and let me know what you think.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.

  • AIs Struggle with Family

    This post looks at a logic problem asked to an AI, and which is struggles at finding an answer. This is based on an article noting this question stumps most AIs. The article is at: https://futurism.com/logic-question-stumps-ai

    This is part of a series of experiments with AI systems.

    The Setup

    I loaded a Deepseek model to compare with my Mistral model. I did this with the following commands:

    docker run ollama
    docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
    docker exec -it ollama ollama pull deepseek-r1:1.5b
    docker exec -d ollama ollama run deepseek-r1:1.5b
    docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v ollama-webui:/app/backend/data --name ollama-webui --restart always ghcr.io/ollama-webui/ollama-webui:main

    From there, I had a website.

    The Logic Problem

    In the article, we ask a question.  I asked: >Alice has [5] brothers and she also has [3] sisters. How many sisters does Alice’s brother have?

    The response was interesting, using the Deepseek-r1:1.5b model. Here it is, with the entire response in Italics.

    First, determine the total number of children in the family by adding Alice’s brothers (5) to her sisters (3). This gives a total of 8 children.

    Next, since Alice is one of those 8 children and she has 5 brothers, subtracting Alice from the total gives the number of brothers as 4. However, this calculation leads to a discrepancy because it doesn’t align with the original information provided.

    Recognizing that there might be an error in the initial assumption, consider that Alice has 3 sisters, meaning there are at least 4 girls (including herself). Adding her 5 brothers results in 9 children, which still does not match the given numbers.

    Finally, re-evaluating the problem, it’s clear that without additional context or information, determining the exact number of sisters a brother has is not possible with the provided details.

    Solution:

    Let’s break down the problem step by step.

    1. Total Number of Children in the Family:

      Alice has:

      • 5 brothers

      • 3 sisters

      Since Alice herself is one child, the total number of children is:

      [
      \text{Total children} = \text{Number of brothers} + \text{Number of sisters} + 1 = 5 + 3 + 1 = 9
      ]

    2. Number of Brothers:

      Alice has 5 brothers in her family.

    3. Number of Sisters Alice’s Brother Has:

      Since the total number of children is 9 and there are 5 brothers, we can determine the number of sisters each brother has by subtracting the number of brothers from the total number of children:

      [
      \text{Sisters per brother} = \frac{\text{Total children}}{\text{Number of brothers}} = \frac{9}{5}
      ]

      However, this division does not result in a whole number, which suggests that the problem might be interpreted differently.

    4. Alternative Interpretation:

      Considering that Alice has 3 sisters, it implies there are at least:

      • 1 (Alice) + 3 = 4 girls

      Including her own siblings, if each brother has an equal number of sisters, we can find the exact number by dividing the total number of children among all siblings:

      [
      \text{Sisters per brother} = \frac{\text{Total children}}{\text{Number of brothers} + 1} = \frac{9}{5 + 1} = \frac{9}{6} = 1.5
      ]

      This result still doesn’t make sense in the context of having whole sisters.

    5. Conclusion:

      Given the information provided, it’s not possible to determine an exact number of sisters that each brother has because:

      • The total number of children is fixed at 9.

      • Each brother has a different number of sisters based on their position in the family tree.

      Therefore, with the current details, there isn’t enough information to definitively state how many sisters Alice’s brother has.

    \boxed{\text{Cannot determine}}

    That’s interesting, but is this a Deepseek problem? Let’s try another.

    Mistral

    Mistral is the first model I played with locally. Let’s ask it the question. This response was shorter, so I’ll add it as an image:

    2025-01_0090

    It seems the AIs don’t quite understand family, and they’re making simple mistakes in putting things together. I could see humans making this mistake, but they’d catch it quickly if someone pointed something out.

    Let’s try one more thing.

    What’s a Family?

    I then ran this prompt: In a family, if I say Alice has 2 brothers and 1 sister, how many children are in the family?

    Easy, isn’t it? If I have 3 siblings, whether brothers or sisters, then there are 4 kids. How does the AI do?

    2025-01_0094

    I suppose Alice could be male (Alice Cooper), but even in that case, the AI seems to struggle to separate out Alice from the counts. For some reason, even listing the siblings out it counts 5 rather than 4. I guess 2+2=5 (for extremely confused AIs).

    Conclusion

    This isn’t to imply the AIs aren’t useful or helpful, but rather they aren’t intelligent in a human sense, or even logical in a human sense. They are very well trained search engines that can put things together in a way that we can’t easily program. They can predict the way to approach problems with mimicry of how humans think.

    However, they don’t have common sense. They are just working with patterns that are very complex, but aren’t intelligent.

    They are useful and can help you solve problems, however, they do make mistakes. Knowing something about the problem you’re asking them to solve is important. These are tools to help us, not tools that replace us.

  • The Local OLLAMA Gui

    I ran a small ollama model in a container and have been doing some experiments. One of the things I wanted to do was get a GUI so I wasn’t always running docker to connect (with –it) or writing code to interact.

    I saw a post somewhere that there is a webgui, so I decided to try it. This post shows the quick setup process.

    This is part of a series of experiments with AI systems.

    Run the Container

    The command I used was this one:

    docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v ollama-webui:/app/backend/data --name ollama-webui --restart always ghcr.io/ollama-webui/ollama-webui:main

    This downloaded and ran the container, which I forgot about until I saw it running in my Docker list.

    Connecting and Getting Going

    The command above runs on port 3000, so I went to port 3000 on my local host and saw this:

    2025-01_0162

    I clicked signup and added info, which isn’t really checked.

    2025-01_0163

    The first account is set at the admin and I see this screen:

    2025-01_0164

    I need to select a model to query, and when I click the drop down, I see the two I downloaded as part of my ollama container setup.

    2025-01_0165

    I picked mistral and started asking questions. I started with clicking the prompt on the screen, and I saw:

    2025-01_0166

    If you play with different models, give this a try as an easy way to run an AI on your local machine and see how well it can help you with anything you do.

    Note, be wary, and make sure you read the disclaimer at the bottom (circled by me)

    2025-01_0154