[EdgeExplorer]

Obviously you could train some kind of neural net to calculate any function, but this would never make sense for a well-known function like sine. Neural nets are a great solution when you need to evaluate something that isn't easy to analyze mathematically, but there are already many known techniques for calculating and approximating trigonometric functions.

Training a neural net to calculate sines is like the math equivalent of using an LLM to reverse a string. Sure, you *can*, but the idea only makes sense if you don't understand how fundamentally solvable the problem is with a more direct approach.

It's always worth looking if mathematicians already have a solution to a problem before reaching for AI/ML techniques. Unfortunately, a lot of effort is probably being spent these days programming some kind of AI/ML to solve problems that have a known, efficient, maybe even proven optimal solution that developers just don't know about.

[o11c]

> using an LLM to reverse a string.

  Input: Please reverse the string "Dlrow, Olleh!"
  Output (chatgpt): Sure! The reversed string is "!helleO ,worldD"
  Output (liquid): The reversed string is "!ehT, Llord!"
  Output (llama): The reversed string is "Hellol, Wlod."
  Output (phi): The reversed string of "Dlrow, Olleh!" is "!HoleL ,owrdL" or "Hello, World!" backwards.
  Output (qwen): The reversed string of "Dlrow, Olleh!" is "!hlelo ,wolrD".

Honestly some of them are doing better than I expected.