2 ms·

How so?

• mountainriver 4mo ago
  With writing code in english now, why have it use a slow weak language? ML still has a depth of libraries that can't be replicated easily but ML work is decreasing by the day with LLMs.
  • nijave 4mo ago
    Because the English to code translation step is fallible
    • hocuspocus 4mo ago
      Which is precisely a reason for not using Python, despite LLMs being good at it.
      • nijave 4mo ago
        Why is that?
  • wolvesechoes 4mo ago
    > With writing code in english now, why have it use a slow weak language? Because the feedback loop of writing few lines of Python inside Jupyter cell is much shorter than with your currently favorite AI tool. It costs less too.
    • mountainriver 4mo ago
      Implementing whole features is? What are we talking about?
• hocuspocus 4mo ago
  LLMs are leveling the developer experience and productivity in a way that makes Python's strengths almost irrelevant, while it's still suffering from bad tooling (even with uv and friends) and poor performance. AI/ML: interfacing with C++ libraries directly (or in Rust) is now a real option. For everything else, even 5 years ago I wouldn't have used Python, now there are even fewer reasons to do so. As far as I'm concerned the remaining use cases are notebooks and one-shot scripts.