Voice of the DBA

Category: Editorial

  • Finely Tuned Models

    I have no idea if this is true, but this post on X says that Thomson Reuters used information they’ve collected for decades to fine tune and train a model. They started with one of the qwen models and then spent $40 million to add their knowledge to the model. The post says this model is comparable to the Gpt5.5 and Sonnet 5 models. They have used 10% of their data, which spans over 100 years.

    I have many questions. But first, $40mm? How many tokens is USD$40mm? A quick calculation is trillions of tokens, and while I’m sure there is some payback if lots of their customers use the model for work, there’s also a compute cost every time they use the model. Perhaps they can fine-tune and train the model more efficiently over time, but I can’t see many individual companies spending this effort on training their own model.

    I also wonder what the time it took to train this. The story notes 2 years, but if I want to update this, then how much more effort. What’s the cost? This certainly reduces the dependence on the frontier models from Antropic/OpenAI/etc., but is this something that makes sense for other companies? If I choose to use the TR model, would it be cheaper than Sonnet 5? Maybe it uses less power, which is always good, but will T-R charge me less than Anthropic?

    I do think that fine-tuned models might make sense, especially if you can use a small language model and train it for a reasonable cost. Like $100,000, not millions. In that case, would it make sense to you? Would your company fund this themselves? Is this something that a trade group could do with support from multiple organizations? Or is the competition between companies so high that they can’t work together?

    I do think that AI has a lot of possibilities to assist humans, and focused models can be useful to solve specific problems, with a lot less cost than the best frontier models. I’m just not sure if the training effort is something that many are willing to put forth. It will be interesting to see how GenAI models evolve as the costs and resources needed by the frontier models continue to rise and smaller models become more capable.

    Steve Jones

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

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

  • Make It Routine

    The first one is hard. The rest are boring.

    I hear this statement from someone recently, and it sounds like something a technical person would do with a task. It’s often been a goal of mine, or maybe a direction to aim, that I want to make things easier with some script or automation. Sometimes I think it’s more aspirational than actual. I might want to make most things routine and automated, but that doesn’t always work out.

    The first time I tackle something, it should be hard. It’s new work. It’s a new process/code/thought/action/etc. It’s unfamiliar and I spend more time on it than I want. After that, I’d hope I could repeat the thing again in much less time. That’s the goal, and that’s what we aim for in a lot of DevOps work. Make the things we think are hard, less hard. Make them boring by codifying things, using automation, have the computer replicate the things.

    I think the second time I tackle a task is often hard as well. How often have you tried to reproduce something you did and can’t quite get it? Heck, I now depend (and use) SQL History constantly because I will write some code, change it a bunch, and then realize that I can’t reproduce the version that did the thing (or broke the thing) I was working on. I need to rewind things and figure them out again. Usually by the 4th time I’ve done something, it’s starting to become easier. By the 10th its boring.

    Unless I’m playing guitar, in which case, some things take a few more reps than 10.

    I’ve had plenty of developers say never repeat yourself. If you can automate it, you should. In practice, that’s hard. Sometimes I’m unsure of whether I’ll do something again, or often enough to spend the time automating it. There are also times I’m not sure it’s worth the effort. I spent a day once trying to automate a bunch of Outlook appointments, only to realize the whole Office API and deluge of information out there made this much harder than the 15 minutes a year I spend putting in all my Database Weekly reminders.

    I don’t want to discourage you from automating things and making them routine or boring. My database deployments ought to be routine. The daily checks should be so boring and automated that I don’t bother with them because I know the machine is doing the work and will let me know if there is something I should examine. The efforts to refresh dev dbs, or respond to audit requests, or even reset a password ought to be boring and easy. Some of us build ways to smooth these tasks and ease our jobs, and some of us treat every one as an ad hoc thing that we do over and over.

    The over and over stuff is going to be taken over by AI. Maybe soon, maybe in a few years, but a lot of simple stuff that you keep doing, that mindless, tedious stuff that doesn’t require a lot of thought, is going to be handled by AI agents. Either you’ll direct them, or your boss will ask someone else to do it after you leave. AI can handle things like figuring out disks are full and cleaning out old log files, shrinking disks, archiving things, and then writing scripts (and scheduling them) to prevent issues. If that’s your job, your days are numbered.

    Make things routine by thinking about the pattern, how we could reduce or eliminate a lot of labor, and how we can use a computer to handle them. Even better, learn how to guide an AI to do that work and prove your worth to your employer.

    Steve Jones

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

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

  • Your Favorite Quotes

    I love seeing thoughtful, pithy, witty quotes. A good saying can often spur me in some way. Maybe I’ll stop and think about what the words mean. Perhaps I’ll get inspired. Sometimes the quotes improve my day by making me smile.

    In any case, I was visiting Epic Systems a few months ago and they have a screensaver in one of the meeting rooms that displayed a number of quotes, along with some lovely backgrounds. I grabbed pictures of a number of them, but a few that stood our to me were these:

    • If you want to go fast, go alone. If you want to go far, go together
    • If it was easy, everyone would do it – John Suby
    • It is not change, but resistance to change that takes time – Mary Doria Russell
    • An investment in knowledge pays the best interest – Benjamin Franklin
    • Yes, if … ” rather than “No, because …”
    • Life is what happens while you’re busy making other plans.

    Maybe you recognize the last one, but all of these are things that are motivating to me. It’s the way that I think we accomplish things as a team. How we drive forward and achieve things. I think it’s important to move forward and make the world a little better. With code, with manners, with compassion, with hard work, with respect, and with adulting. Some days that last one is really, really hard.

    Today I’m wondering if you have some favorite quotes that make you smile, or feel better, or inspire you to move forward. Share something today in the discussion that touched you.

    If you want to read more quotes or thoughts, I share some thoughts on my blog, with a series on Advice I Like, based on a book I bought.

    Steve Jones

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

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

  • Editorial Republish: Evaluating a DBA (or AI)

    How do you evaluate a DBA? Can you pick someone that will do a good job? History says that most of us don’t do a great job in picking candidates to offer a job.

    I wrote Evaluating a DBA in 2021 and it’s being republished as I’m at VS Live today. Does it still make sense? Have we learned anything?

    Let me know, and by the way, this applies to “hiring” (using) an AI.