Tag: AI

  • AI Sings the Blues

    Quite a few of you aren’t thrilled or enamored by GenAI (Generative Artificial Intelligence) with things like ChatGPT or CoPilot. Some of you love it or find it fascinating. My guess is many of you are like me and you’re not quite sure how useful this is with a healthy dose of skepticism.

    No matter how you feel, I find this piece on AI Blues fascinating to read. It talks about some of the problems with AI and how people are becoming less tolerant of the small errors that AIs make. I think people might be upset with some of the issues, but I also think these are types of things we might see in a colleague as well, and we might tolerate them for much longer than we think.

    The thing in the piece that really caught my eye is that training models to make less errors might make them less creative. I don’t think they are very creative, but I do think part of the idea is that they might do something better than we could do, at least for those of us working in a space where we’re a beginner to intermediate (or advanced beginner). In many cases, we’d expect better output from a model.

    The note about training not being often or in-depth enough as well is interesting. Perhaps some of the models ought to be trained separately, with some having a more specific focus, like learning Python and producing very few errors, or learning Python to produce interesting solutions to large scale problems even if there are some errors in the code.

    I could see similarly more tightly trained models for other areas, such as marketing email or legal issues. Maybe we need a lot of different models tailored for different jobs. Of course, if companies are struggling to generate revenue on AI already (and I think they are), then can they afford to train and retrain specific models focused for smaller audiences?

    Maybe, and maybe Moore’s law will help bail out some AI experiments, but I’m not sure. For now, I continue to experiment, and I think skilled tech people ought to do the same. I don’t think it will replace us, but I do think it can be a useful tool in many ways to help us become more productive.

    Steve Jones

  • Expanding Northwind with Prompt+

    I was trying to do a little testing of our subsetter and needed a larger database. So I decided to ask Prompt + to help me with a little AI assist. This post looks at what happened.

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

    Getting More Data

    I had a Northwind_FullRestore from my experiments with Alex Yate’s quick PoC tool. I selected that database and asked for a little code. I asked the AI to give me 1000 more rows of data in the Customers table. I got this code.

    -- This script inserts 1000 rows data entry into the dbo.Customers table
    WITH numbers
    AS ( SELECT TOP (1000)
                 ROW_NUMBER () OVER (ORDER BY
                                       (SELECT NULL)) AS num
          FROM sys.all_objects)
    --INSERT INTO dbo.Customers
    --  (CustomerID, CompanyName, ContactName, ContactTitle, Address, City, Region, PostalCode, Country, Phone, Fax)
    SELECT
       'CUST' + RIGHT('0000' + CAST (num AS nchar(4)), 5)
    , 'Customer' + CAST (num AS nvarchar)
    , 'Contact' + CAST (num AS nvarchar)
    , 'Title' + CAST (num AS nvarchar)
    , 'Address' + CAST (num AS nvarchar)
    , 'City' + CAST (num AS nvarchar)
    , 'Region' + CAST (num AS nvarchar)
    , 'PostalCode' + CAST (num AS nvarchar)
    , 'Country' + CAST (num AS nvarchar)
    , 'Phone' + CAST (num AS nvarchar)
    , 'Fax' + CAST (num AS nvarchar)
    FROM numbers;

    Then I decided to go big. I changed my prompt, as you see below, and got more data. My new prompt: expand this to add 10GB of data to this table

    I got this code:

    -- This script adds approximately 10GB of data to the dbo.Customers table
    -- Firstly, we need to calculate the approximate size of each row. 
    -- For simplicity, we'll assume each row is ~1KB in size after considering nvarchar data expansion.
    -- Therefore, to add 10GB of data, we need approximately 10,000,000 rows.
    WITH numbers
    AS ( SELECT TOP (10000) -- This will generate 10,000 rows in the CTE
                 ROW_NUMBER () OVER (ORDER BY
                                       (SELECT NULL)) AS num
          FROM
            sys.all_objects a
          , sys.all_objects b)
    INSERT INTO dbo.Customers
       (CustomerID, CompanyName, ContactName, ContactTitle, Address, City, Region, PostalCode, Country, Phone, Fax)
    SELECT
       'CUST' + RIGHT('00000000' + CAST (numbers.num + seqnum AS nvarchar), 8) -- 8 character CustomerID to accommodate large number of rows
    , 'Customer' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'Contact' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'Title' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'Address' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'City' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'Region' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'PostalCode' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'Country' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'Phone' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    , 'Fax' + CAST (numbers.num AS nvarchar) + CAST (seqnum AS nvarchar)
    FROM
       numbers
       CROSS JOIN
         ( SELECT TOP (1000)
                  ROW_NUMBER () OVER (ORDER BY
                                        (SELECT NULL)) AS seqnum
           FROM sys.all_objects) seq;

    The Results

    The results were a bit underwhelming. I ran it and got this:

    8-2-2024-0005

    The problem here is that the CustomerID is a 5 character field. The comment in the code notes that this is now an 8 character field, but that’s not great as I might not want to change the size of the field.

    I then asked this: change this script to ensure the customerID is less than 5 characters and alphanumeric

    I got the same script, but the first line of the select was:

    'CUST' + RIGHT('00000000' + CAST (numbers.num + seqnum AS nvarchar), 8) 
    -- 8 character CustomerID to accommodate large number of rows

    Now when I run it, I get a problem with postal code, which now has the truncation error.

    My Thoughts

    It’s easy to say this was a failed experiment. I didn’t get working code. But I got a bunch of code that was close to what I need, in a fraction of the time that it would take me to write this, even with SQL Prompt. Then add in the fact that I can edit this code to what I need, which works, and saves me times.

    I think this has potential for shortcutting some work and getting me closer to what I need quickly, even if it’s not perfect. If I’d have asked a junior dev to help me with this, I might still have to edit their code. Just as I do with my AI assistant.

  • Using AI for the First Draft

    At the Redgate Summit in London, I ran a panel talking about Platform Engineering and how we can make developers more productive. One of the questions from our audience revolved around AI (Artificial Intelligence) technologies and how they might assist. As a note, AI tech includes a lot of different things, like machine learning (ML) among other things, but a lot of people seeing the media and hype around LLMs (large language models)  think those are AI. They see AI as what is implemented in ChatGPT and Copilot, which is correct, but incomplete.

    One of the panelists, Jeff Smith of Redgate, said that he views the output from AI as a first draft, something that bootstraps further work by a human. This can save time and can help someone be more productive, but it’s a starting point and a boost, not a final product.

    I had not thought of AI this way, even though I expect to have to test, refine, and edit the results I’ve gotten from various assistants. While it might be possible for me to keep refining my prompt and perhaps generate better results (code and/or text), I don’t know that it’s often worth the time to do much of this. I might do a little, but it’s much easier to take the result of AI as a first draft and then make it fit my requirements.

    In much the same way I use Stack Overflow or SQL Server Central for code snippets. They often give me a starting point and something I can then adapt to my needs without all of the time and effort spent on reading an API or SDK, experimenting with the syntax, and then actually using this in some code I’m writing. Similarly, I can get a head start on writing a summary or a pitch, though I’ll admit I’ve found it less useful there. In fact, for many of my editorials, I’ve tried to use it to summarize an article or web link, and it does a very poor job (IMHO).

    Some of you might be concerned or worried about this, and some might not. To me, the average-to-poor code produced isn’t any different than the legions of Stack Overflow developers or SQL Server Central DBAs who take code from an online forum and fail to test it. Anyone using any code (or prose) should test (proof) it and verify it works appropriately in their situation. We have a lot of people who don’t do that now and AI might exacerbate that with more code, but I don’t know if we are in a worse situation. We certainly seem to be able to produce lots of average tech professionals now who turn out plenty of average code.

    Ultimately AI is a tool that does exist in the world and will continue to exist. We have to learn to work with it and use it to our advantage. Good developers and DBAs will do that. I’d like to think that many organizations will look to hire and use those people as their staff and use fewer of the people who don’t bother to test and improve the results from their tools.

    Steve Jones

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

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

  • Common Algorithm Concerns

    When we build software, many of us use the same algorithms to solve problems. We might choose a similar method for a quicksort or a lambda validation or a regular expression. For database work, your code for a running total (or other common challenge) is likely very similar to many other people. At least on the same platform. You might solve this differently in SQL Server and Oracle, but for the same type of database, many of us write very similar code.

    Actually, many developers might copy and paste an answer from SQL Server Central, Stack Overflow, or another site. I’m not sure if I think this is good or bad, as it’s a good idea to reuse code if it solves the same problem. If you copy it and don’t test it, that’s bad. After all, the code might not solve your slightly different problem if you don’t check it.

    In the modern world, if we build software for our business using an AI assistant, could our company be liable if we knew our competitors were using the same AI service? Is this any different than a human developer performing a copy/paste from SQL Server Central? I don’t think it is in many cases, though the same concerns about intellectual property might be present in either case.

    The concerns over AI seem murky in some sense, especially as the AI might “generate” code that isn’t directly available on some public resource. I do think that this is more of a collusion using a service than an algorithm. Still, in the hyper-connected world, where many of our applications might look to take advantage of some service instead of implementing it ourselves, this could be an issue.

    I ran across a piece that discusses a lawsuit about a common pricing algorithm being used by different hotels. In this case, it’s not that the developers at different hotels used the same code, but rather that the hotels used the same service from a company, which of course, used the same code for all their customers. Whether you think this is a valid lawsuit or not, this is the type of legal action that others might bring if two competitors ended up using the same AI service and developed very similar code that might behave the same way.

    I don’t think that AIs (at present) can actually develop new algorithms or solve problems in a new way. Instead, they predict the likely solution based on how they’ve been trained by similar scenarios. In that case, how concerned are we about how getting common solutions in disparate pieces of software? For most of us, I think we’ve be pleased that we have well-tested (hopefully) code that runs efficiently (again, hopefully) being re-used in many places. That would be better for most systems in the world.

    What isn’t better is if humans become more adept at specifying prompts and producing software without lots of specialized expertise. For many developers that might be average, or even slightly below average, this might cause them concern for the security of their position. With good reason, as labor is one of the most expensive parts of building software.

    Ultimately, just as with any other position, the best way to build a safe, secure career, is to continue to build your skills and produce value for your employer. That way it’s unlikely any AI will ever outperform you.

    Steve Jones

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

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