Tag: AI

  • 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

  • The Era of Cloned Humans

    AI-technologies are evolving at an alarming rate. The ability of LLMs to produce drafts, review work, even write some code continues to improve to the point where junior level workers are in danger of having less opportunity than in the past.

    Perhaps even more alarming is the ability of AI technologies to mimic what they find in the real world, which can include voices. As with any technology created to make the world better, criminals will find a way to use it for nefarious purposes. This article notes that the FBI has warned families to have a secret word or phrase, as criminals are using AI to clone the voice of a family member asking for financial help.

    Can you imagine getting a call from your spouse, parents, or children, saying that they’re in trouble and need some money right away? With AI tech, the voice could even respond to your questions, mimic anxiety or distress, cry, or who knows what.

    Last year Microsoft announced a text to speech technology that can closely simulate a person’s voice with just 3 seconds of audio. I’m sure that capability has improved in a year and soon we may not be able to trust the voices we hear. We certainly can’t trust the photographs we see, something that we enjoy when we see artists photoshop images for fun, but when we look at an image  in the news, we want it to be real, but we can’t trust that an organization hasn’t manipulated a photo. When anyone could simulate another’s voice, things can go wrong quickly.

    I assume the ability to fake video in real time is coming soon. With enough hardware and some imagery, I would guess AI models will be able to hold a Facetime-type call as a human, fooling most people that might not know the person extremely well. At some point, since all our images and video are digital anyway, I assume that without some security measure, the tech could likely fool almost everyone.

    Even as I write this I doubt how well the quality is, but I’m sure that it will continue to improve to the point where we might be loathe to trust remote interactions. This has the potential to be a security nightmare for some people, and I worry about the scams and losses criminals will inflict upon the unsuspecting.

    This is one type of technology whose negatives will far outweigh the positives.

    Steve Jones

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

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