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This has been observed by more people than just Terence Tao. Try using chatgpt to program something of higher complexity than tutorial code or write a basic blog post, it lacks creativity and the code is poorly designed.


Even for like basic Rust programs it ties itself into countless borrow checker issues and cannot get out of it, both the OpenAI as well as Sonnet (Anthropic).

It doesn't really get logic still, but it does small edits well when the code is very clear.

I think this will always remain a problem. Because it can never shut up, it keeps making stuff up and "hallucinate" (works normally, just incorrectly) to dig itself further and further into a hole.

Autocomplete on steroids is what peak AI will look like till the time we can crack consciousness and AGI (which the modern versions are nothing even close to).


To me it's quite good for Rust as it usually suggests me some (unknown to me) borrow checker API that actually helps me either solve the issue at hand or at least point me in the right direction to figure what is actually wrong with my code and it doesn't compile


Funny it just wrote this for me:

  fn parse_image_url(html: &str) -> Option<String> {
      let re = regex::Regex::new(r#"src="([^"]+)""#).ok()?;
      re.captures(html)
          .and_then(|caps| caps.get(1))
          .map(|m| m.as_str().to_string())
  }
Prompt was "write a function which extracts image urls from a given block of html"


Of the 40 or so definitions of consciousness, I have no reason to think any is either necessary nor sufficient for any of the things we want AI to do that Transformer models can't (or can but badly and we want them to do better).




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