[throwworhtthrow]

LLM's still give subpar results with ffmpeg. For example when I asked Sonnet to trim a long video with ffmpeg, it put the input file parameter before the start time parameter, which triggers an unnecessary decode of the video file. [1]

Sure, use the LLM to get over the initial hump. But ffmpeg's no exception to the rule that LLM's produce subpar code. It's worth spending a couple minutes reading the docs to understand what it did so you can do it better, and unassisted, next time.

[1] https://ffmpeg.org/ffmpeg.html#:~:text=ss%20position

[CamperBob2]

That says more about suboptimal design on ffmpeg's part than it does about the LLM. Most humans can't deal with ffmpeg command lines, so it's not surprising that the LLM misses a few tricks.

[nottorp]

Had a LLM generate 3 lines of working C++ code that was "only" one order of magnitude slower than what i edited the code to in 10 minutes.

If you're happy with results like that, sure, LLMs miss "a few tricks"...

[ben_w]

You don't have to leave LLM code alone, it's fine to change it — unless, I guess, you're doing some kind of LLM vibe-code-golfing?

But this does remind me of a previous co-worker. Wrote something to convert from a custom data store to a database, his version took 20 minutes on some inputs. Swore it couldn't possibly be improved. Obviously ridiculous because it didn't take 20 minutes to load from the old data store, nor to load from the new database. Over the next few hours of looking at very mediocre code, I realised it was doing an unnecessary O(n^2) check, confirmed with the CTO it wasn't business-critical, got rid of it, and the same conversion on the same data ran in something like 200ms.

Over a decade before LLMs.

[nottorp]

We all do that, sometimes where it’s time critical sometimes where it isn’t.

But I keep being told “AI” is the second coming of Ahura Mazda so it shouldn’t do stuff like that right?

[ben_w]

> Ahura Mazda

Niche reference, I like it.

But… I only hear of scammers who say, and psychosis sufferers who think, LLMs are *already* that competent.

Future AI? Sure, lots of sane-seeming people also think it could go far beyond us. Special purpose ones have in very narrow domains. But current LLMs are only good enough to be useful and potentially economically disruptive, they're not even close to wildly superhuman like Stockfish is.

[CamperBob2]

Sure. If you ask ChatGPT to play chess, it will put up an amateur-level effort at best. Stockfish will indeed wipe the floor with it. But what happens when you ask Stockfish to write a Space Invaders game?

ChatGPT will get better at chess over time. Stockfish will not get better at anything except chess. That's kind of a big difference.

[CamperBob2]

"I'm taking this talking dog right back to the pound. It told me to short NVDA, and you should see the buffer overflow bugs in the C++ code it wrote. Totally overhyped. I don't get it."

[nottorp]

"We hear you have been calling our deity a talking dog. Please enter the red door for reeducation."