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Joined 1 year ago
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Cake day: December 13th, 2024

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  • The personal computer market is not going anywhere. It may get smaller, but there will always be enough people who want to do their computing on their own hardware that there will be a market for personal computers. The market has only been affected by other personal computing devices. Personally, I don’t think many will be interested in cloud desktops. They’ve existed for a long time, and I don’t know anyone who uses them. Why on God’s green earth would I want to lug around a laptop just to not use it to be a laptop?

    The kind of people who would be interested in cloud desktops are the kind of people who already get by just fine with a Chromebook. And how are you going to convince those people to instead spend not only $200 on a device, but then also $30/month on a cloud browser?





  • Feel free to try. Here’s the library I use: https://nymph.io/

    It’s open source, and all the docs and code are available at that link and on GitHub. I always ask it to make a note entity, which is just incredibly simple. Basically the same thing as the ToDo example.

    The reason I use this library (other than that I wrote it, so I know it really well) is that it isn’t widely known and there aren’t many example projects of it on GitHub, so the LLM has to be able to actually read and understand the docs and code in order to properly use it. For something like React, there are a million examples online, so for basic things, the LLM isn’t really understanding anything, it’s just making something similar to its training data. That’s not how actual high level programming works, so making it follow an API it isn’t already trained on is a good way to test if it is near the same abilities as an actual entry level SWE.

    I just tested it again and it made 9 mistakes. I had to explain each mistake and what it should be before it finally gave me code that would work. It’s not good code, but it would at least work. It would make a mistake, I would tell it how to fix it, then it would make a new mistake. And keep in mind, this was for a very simple entity definition.


  • I played around with it a lot yesterday, giving it documentation and asking it to write some code based on the API documentation. Just like every single other LLM I’ve ever tried, it just bungled the entire thing. It made up a bunch of functions and syntax that just doesn’t exist. After I told it the code was wrong and gave it the right way to do it, it told me that I got it wrong and converted it back to the incorrect syntax. LLMs are interesting toys, but shouldn’t be used for real work.