And yet, China is using AI.

…I… don’t know what to think about that.

…I really don’t.

Because it seems that AI is just a scam.

It may “exist” but what it can do is a scam.

Maybe China thinks we have to use it just to “keep up” with the Western powers, but I dunno.

Anyway, interesting discussion with Adam Conover and Ed Zitron. It’s long, but you can listen to it while doing other things. And the comments are interesting too, but then again, there are also trolls in the comments as well (AI supporters here and there).

Frankly, though? I oppose AI. I’m anti-AI. I’m anti-AI in China and anti-AI in America and anti-AI in the whole damn planet.

    • footfaults@lemmygrad.mlEnglish
      1·
      2 days ago

      ok first dumb question, is the block of code that you had below this line

      Given a query of “write a json schema to represent a comment thread on a social media site like reddit”, it’ll do this bit of reasoning:

      Was this an actual output from an LLM or a hypothetical example that you wrote up? It’s not quite clear to me. It’s a lot of output but I don’t want to insult you if you wrote all that yourself

      First, each comment has an ID, author info, content, timestamps, votes, and replies. The replies are nested comments, forming a tree structure. So the schema should allow for nested objects within each comment’s replies.

      I ask because I really want to nitpick the hell out of this design decision:

      First, each comment has an ID, author info, content, timestamps, votes, and replies. The replies are nested comments, forming a tree structure. So the schema should allow for nested objects within each comment’s replies.

      Adding the replies as full items, that is going to absolutely murder performance. A better scheme would be for replies to be a list/array of IDs or URLs, or a URL to an API call that enumerates all the replies, instead of enumerating all the items and embedding them directly. That is going to absolutely kill performance. Depending on the implementation, you could easily be doing the classic N+1 query that a lot of web applications fall for.

      But then again at this point I’m arguing with an LLM which is generating absolutely dogshit code.

      • ☆ Yσɠƚԋσʂ ☆@lemmygrad.ml
        1·
        2 days ago

        Was this an actual output from an LLM or a hypothetical example that you wrote up? It’s not quite clear to me. It’s a lot of output but I don’t want to insult you if you wrote all that yourself

        That was copy pasted straight from the DeepSeek chat response.

        Adding the replies as full items, that is going to absolutely murder performance.

        Like I said earlier, you still have to understand how to code and what the code is doing. Thing is that you could literally paste what you said in, and it’ll make adjustments. Or you can just make adjustments yourself. As a starting point I find that sort of output useful.

        Another example is that I have to use node for an application for work right now. I haven’t touched js in over a decade, I’m not familiar with the ecosystem, and DeepSeek lets me quickly get things running. Things I would’ve spent hours looking up before and doing through trial and error just work out of the box. As I pointed out in an earlier reply, most apps aren’t doing really complex or interesting things. Most of it is just shuffling data between different endpoints and massaging it in some way. LLMs can do a lot of this boring work quickly and efficiently.

        • footfaults@lemmygrad.mlEnglish
          1·
          2 days ago

          I want to say that you’ve piqued my interest, but honestly I’m not sure I can set aside my bias. I deal with enough wrong code already as it is that my co-workers write, so I don’t know if having yet another one giving me bad code suggestions adds much, but I appreciate you putting in the work showing everything.