Developer and refugee from Reddit

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Joined 2 years ago
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Cake day: July 2nd, 2023

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  • I genuinely don’t know what to do with people like him. On the one hand… Yeah. He knowingly hired undocumented people, making him a hypocrite, and he just voted to have those people forcibly deported against his own interests, making him a fucking dumbass.

    At the same time, he seems to be showing actual remorse, and that should definitely be encouraged. The only - only - way this country has even the slightest shot at recovery is by flipping large numbers of the orange shit-gibbon’s supporters, like this guy.

    I really want to believe that’s possible. I don’t think it is, but I want to believe it.

    Edit: Missed the part in the article where these guys had valid work visas.





  • But it still manages to fuck it up.

    I’ve been experimenting with using Claude’s Sonnet model in Copilot in agent mode for my job, and one of the things that’s become abundantly clear is that it has certain types of behavior that are heavily represented in the model, so it assumes you want that behavior even if you explicitly tell it you don’t.

    Say you’re working in a yarn workspaces project, and you instruct Copilot to build and test a new dashboard using an instruction file. You’ll need to include explicit and repeated reminders all throughout the file to use yarn, not NPM, because even though yarn is very popular today, there are so many older examples of using NPM in its model that it’s just going to assume that’s what you actually want - thereby fucking up your codebase.

    I’ve also had lots of cases where I tell it I don’t want it to edit any code, just to analyze and explain something that’s there and how to update it… and then I have to stop it from editing code anyway, because halfway through it forgot that I didn’t want edits, just explanations.








  • Not true. Not entirely false, but not true.

    Large language models have their legitimate uses. I’m currently in the middle of a project I’m building with assistance from Copilot for VS Code, for example.

    The problem is that people think LLMs are actual AI. They’re not.

    My favorite example - and the reason I often cite for why companies that try to fire all their developers are run by idiots - is the capacity for joined up thinking.

    Consider these two facts:

    1. Humans are mammals.
    2. Humans build dams.

    Those two facts are unrelated except insofar as both involve humans, but if I were to say “Can you list all the dam-building mammals for me,” you would first think of beavers, then - given a moment’s thought - could accurately answer that humans do as well.

    Here’s how it goes with Gemini right now:

    Now Gemini clearly has the information that humans are mammals somewhere in its model. It also clearly has the information that humans build dams somewhere in its model. But it has no means of joining those two tidbits together.

    Some LLMs do better on this simple test of joined-up thinking, and worse on other similar tests. It’s kind of a crapshoot, and doesn’t instill confidence that LLMs are up for the task of complex thought.

    And of course, the information-scraping bots that feed LLMs like Gemini and ChatGPT will find conversations like this one, and update their models accordingly. In a few months, Gemini will probably include humans in its list. But that’s not a sign of being able to engage in novel joined-up thinking, it’s just an increase in the size and complexity of the dataset.



  • It’s absolutely taking off in some areas. But there’s also an unsustainable bubble because AI of the large language model variety is being hyped like crazy for absolutely everything when there are plenty of things it’s not only not ready for yet, but that it fundamentally cannot do.

    You don’t have to dig very deeply to find reports of companies that tried to replace significant chunks of their workforces with AI, only to find out middle managers giving ChatGPT vague commands weren’t capable of replicating the work of someone who actually knows what they’re doing.

    That’s been particularly common with technology companies that moved very quickly to replace developers, and then ended up hiring them back because developers can think about the entire project and how it fits together, while AI can’t - and never will as long as the AI everyone’s using is built around large language models.

    Inevitably, being able to work with and use AI is going to be a job requirement in a lot of industries going forward. Software development is already changing to include a lot of work with Copilot. But any actual developer knows that you don’t just deploy whatever Copilot comes up with, because - let’s be blunt - it’s going to be very bad code. It won’t be DRY, it will be bloated, it will implement things in nonsensical ways, it will hallucinate… You use it as a starting point, and then sculpt it into shape.

    It will make you faster, especially as you get good at the emerging software development technique of “programming” the AI assistant via carefully structured commands.

    And there’s no doubt that this speed will result in some permanent job losses eventually. But AI is still leagues away from being able to perform the joined-up thinking that allows actual human developers to come up with those structured commands in the first place, as a lot of companies that tried to do away with humans have discovered.

    Every few years, something comes along that non-developers declare will replace developers. AI is the closest yet, but until it can do joined-up thinking, it’s still just a pipe-dream for MBAs.