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Joined 1 year ago
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Cake day: July 3rd, 2023

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  • I got a laptop back in 2018, and it shipped really fast. It’s not my daily driver, but it works well when I’m on the road, and the battery life is pretty good. Granted, I replaced the OS with a distro I prefer and customized the hell out of it, so that might contribute to my experience. Tbh, I was pretty impressed with it (still am), and I was going to buy a Librem 5 when they came out. I wanted to wait and not just throw money at them because I didn’t want to get burned. After all the horror stories and crap reviews, I passed on that and won’t touch the company with a 10 foot pole, and I thank past me for not throwing money at them.

    I think that the company started with noble intentions and made a decent product at first, but they got in way over their heads and now they’re floundering.


  • The original paper itself, for those who are interested.

    Overall, this is really interesting research and a really good “first step.” I will be interested to see if this can be replicated on other models. One thing that really stood out, though, was that certain details are obfuscated because of Sonnet being proprietary. Hopefully follow-on work is done on one of the open source models to confirm the method.

    One of the notable limitations is quantifying activation’s correlation to text meaning, which will make any sort of controls difficult. Sure, you can just massively increase or decrease a weight, and for some things that will be fine, but for real manual fine tuning, that will prove to be a difficulty.

    I suspect this method is likely generalizable (maybe with some tweaks?), and I’d really be interested to see how this type of analysis could be done on other neural networks.



  • I agree with this in general, but you still may want to consider using Windows or Mac if there’s university only software that is Windows/Mac-based and doesn’t play nicely with VMs, which is really common in test-taking software (since it’s essentially spyware). An alternative would be dual-booting if you want to deal with that.

    The reason I say this is that when I went back to school and started course work, there was an online class that mandated the use of certain test-taking software. I tried to get it to work in a VM (by masking the clues of being in a VM), and it kept shutting me down. I ultimately had to borrow a friend’s laptop to take all of my quizzes and tests, which was a real pain. Thankfully, I only had that one class like that, but any others would have driven me to get a cheap throw-away Windows-only box.

    In the end, I’d stay away from bleeding-edge for school work, so Fedora is probably your better bet, but there may come a time that you will need to use Windows (much to your chagrin).


  • Congratulations on making the switch! I remember when I switched full time almost 10 years ago. It always feels like there’s something new to explore or to try with your computer. One of the most freeing things I learned was that most things are within my grasp if I put in the effort to learn about it. There’s nothing quite as fun as whittling the day away going down a configuration rabbit-hole to make something just right.


  • This is a much better article. OP’s article just shows the author’s surface understanding of how coding works and how well an LLM can actually code. There’s way more that goes into a programming task than just coding.

    I see LLMs as having the potential of being almost like a super library. I can prompt GPT, Claude, etc. to write me a custom function that I copy, paste, test, scrutinize, and almost certainly change. It’s a tool that will make someone a more productive programmer. It won’t completely subsume a human’s ability to be creative and put the pieces together.

    At the absolute worst over the next decade, I could see programming changing from writing and debugging code to prompting, stitching together, and debugging.