4 ms·

Anyone who says AI is useless never had to do the old method of cobbling together git and ffmpeg commands from StackOverflow answers. I have no interest in lea

by hbn 2y ago

Anyone who says AI is useless never had to do the old method of cobbling together git and ffmpeg commands from StackOverflow answers. I have no interest in learning the horrible unintuitive UX of every CLI I interact with, I'd much rather just describe in English what I want and have the computer figure it out for me. It has practically never failed me, and if it does I'll know right away and I can fall back to the old method of doing it manually. For now it's saving me so much time with menial, time-wasting day-to-day tasks.

jghn 2y ago
I had a debate recently with a colleague who is very skeptical of LLMs for every day work. Why not lean in on searching Google and cross referencing answers, like we've done for ages? And that's fine. But my counterargument is that what I find to be so powerful about the LLMs is the ability to refine my question, narrow in on a tangent and then pull back out, etc. And *then* I can take its final outcome and cross reference it. With the old way of doing things, I often felt like I was stumbling in the dark trying to find the right search string. Instead I can use the LLM to do the heavy lifting for me in that regard.
ADeerAppeared 2y ago
> Anyone who says AI is useless Most of those people are a bit bad at making their case. What they mean but don't convey well is that AI is useless for it's proclaimed uses. You are correct that LLMs are pretty good at guessing this kind of well-documented & easily verifiable but hard to find information. That is a valid use. (Though, woe betide the fool who uses LLMs for irreversible destructive actions.) The thing is though, this isn't enough. There just aren't that many questions out there that match those criteria. Generative AI is too expensive to serve that small a task. Charging a buck a question won't earn the $100 billion OpenAI needs to balance the books. Your use case gets dismissed because on it's own, it doesn't sustain AI.
- wenc 2y ago
  I think you’re on to something. I find the sentiment around LLMs (which is at the early adoption stage) to be unnecessarily hostile. (beyond normal HN skepticism) But it can be simultaneously true that LLMs add a lot of value to some tasks and less to others —- and less to some people. It’s a bit tautological, but in order to benefit from LLMs, you have to be in a context where you stand to most benefit from LLMs. These are people who need to generate ideas, are expert enough to spot consequential mistakes, know when to use LLMs and when not to. They have to be in a domain where the occasional mistake generated costs less than the new ideas generated, so they still come out ahead. It’s a bit paradoxical. LLMs are good for: (1) bite-sized chunks of code; (2) ideating; (3) writing once-off code in tedious syntax that I don’t really care to learn (like making complex plots in seaborn or matplotllib); (4) adding docstrings and documentation to code; (5) figuring out console error messages, with suggestions as to causes (I’ve debugged a ton of errors this way — and have arrived at the answer faster than wading through Stackoverflow); (6) figuring out what algorithm to use in a particular situation; etc. They’re not yet good at: (1) understanding complex codebases in their entirety (this is one of the overpromises; even Aider Chat’s docs tell you not to ingest the whole codebase); (2) any kind of fully automated task that needs to be 100% deterministic and correct (they’re assistants); (3) getting math reasoning 100% correct (but they can still open up new avenues for exploration that you’ve never even thought about); It takes practice to know what LLMs are good at and what they’re not. If the initial stance is negativity rather than a growth mindset, then that practice never comes. But it’s ok. The rest of us will keep on using LLMs and move on.
  - esafak 2y ago
    An example that might be of interest to readers: I gave it two logs, one failing and one successful, and asked it to troubleshoot. It turned out a loosely pinned dependency (Docker image) had updated in the failing one. An error mode I was familiar with and could have solved on my own, but the LLM saved me time. They are reliable at sifting through text.
  - mistercheph 2y ago
    Hostility and a few swift kicks are in order when the butt scratchers start saying their stochastic parrot machine is intelligent and a superman.
hyhconito 2y ago
You're still doing it the hard way. I just use Handbrake. Pick a hammer, not a shitty hammer factory to assemble bits of hammer.
- sunnybeetroot 2y ago
  How do you use handbrake to write a script that uses ffmpeg?
arkh 2y ago
> if it does I'll know right away and I can fall back to the old method of doing it manually It's well and ok with things you can botch with no consequence other than some time wasted. But I've bricked enough VMs trying commands I did not understand to know that if you need to not fuck up something you'll have to read those docs and understand them. And hope they're not out of date / wrong.
dangoodmanUT 2y ago
> Anyone who says AI is useless never had to do the old method of cobbling together git and ffmpeg commands from StackOverflow answers. The best ffmpeg and regex command generators
jv981 2y ago
try asking an LLM how to add compressed data to a tar through standard input, see how that goes (don't forget to check the answer :)
cootsnuck 2y ago
I use LLMs to help me with ffmpeg commands more than I care to admit
momentoftop 2y ago
> Anyone who says AI is useless never had to do the old method of cobbling together git and ffmpeg commands from StackOverflow answers. It's useful for that yes, but I'd rather just live in a world where we didn't have such disasters of CLI that are git and ffmpeg. LLMs are very useful for generating the obscure boilerplate needed because the underlying design is horrible. Relying on it means acquiescing to those terrible designs rather than figuring out redesigns that don't need the LLMs. For comparison, IntelliJ is very good at automating all the boilerplate generation that Java imposes on me, but I'd rather we didn't have boilerplate languages like Java, and I'd rather that IntelliJ's boilerplate generation didn't exist. I fear in many cases that if an LLM is solving your problem, you are solving the wrong problem.
- skydhash 2y ago
  I'm not arguing against the UX of those tools, but isn't this a case of the problem being a hard one to solve and people having different needs? ffmpeg has a lot of knobs, but that's just the nature of media conversion and manipulation, just like ImageMagick. I'm not against using LLMs for restricting the search space to a specific problems, but I'm often seeing people not even understanding the problem itself, just its apparent physicality.
skydhash 2y ago
> Anyone who says AI is useless never had to do the old method of cobbling together git and ffmpeg commands from StackOverflow answers. These days, I'm more likely to read the manual pages and take notes on interesting bits. If I'm going to rely on some tooling for some time, dedicating a few hours of reading is a good trade-off for me. No need to even remember everything, just the general way it solves the problem. Anything more precise is captured in notes, scripts, shell history,... I dare anyone to comes out with an essay like this from LLMs: https://karthinks.com/software/avy-can-do-anything/ https://karthinks.com/software/avy-can-do-anything/

by hbn 2y ago

jghn 2y ago

I had a debate recently with a colleague who is very skeptical of LLMs for every day work. Why not lean in on searching Google and cross referencing answers, like we've done for ages? And that's fine. But my counterargument is that what I find to be so powerful about the LLMs is the ability to refine my question, narrow in on a tangent and then pull back out, etc. And *then* I can take its final outcome and cross reference it. With the old way of doing things, I often felt like I was stumbling in the dark trying to find the right search string. Instead I can use the LLM to do the heavy lifting for me in that regard.

ADeerAppeared 2y ago

> Anyone who says AI is useless Most of those people are a bit bad at making their case. What they mean but don't convey well is that AI is useless for it's proclaimed uses. You are correct that LLMs are pretty good at guessing this kind of well-documented & easily verifiable but hard to find information. That is a valid use. (Though, woe betide the fool who uses LLMs for irreversible destructive actions.) The thing is though, this isn't enough. There just aren't that many questions out there that match those criteria. Generative AI is too expensive to serve that small a task. Charging a buck a question won't earn the $100 billion OpenAI needs to balance the books. Your use case gets dismissed because on it's own, it doesn't sustain AI.

wenc 2y ago
I think you’re on to something. I find the sentiment around LLMs (which is at the early adoption stage) to be unnecessarily hostile. (beyond normal HN skepticism) But it can be simultaneously true that LLMs add a lot of value to some tasks and less to others —- and less to some people. It’s a bit tautological, but in order to benefit from LLMs, you have to be in a context where you stand to most benefit from LLMs. These are people who need to generate ideas, are expert enough to spot consequential mistakes, know when to use LLMs and when not to. They have to be in a domain where the occasional mistake generated costs less than the new ideas generated, so they still come out ahead. It’s a bit paradoxical. LLMs are good for: (1) bite-sized chunks of code; (2) ideating; (3) writing once-off code in tedious syntax that I don’t really care to learn (like making complex plots in seaborn or matplotllib); (4) adding docstrings and documentation to code; (5) figuring out console error messages, with suggestions as to causes (I’ve debugged a ton of errors this way — and have arrived at the answer faster than wading through Stackoverflow); (6) figuring out what algorithm to use in a particular situation; etc. They’re not yet good at: (1) understanding complex codebases in their entirety (this is one of the overpromises; even Aider Chat’s docs tell you not to ingest the whole codebase); (2) any kind of fully automated task that needs to be 100% deterministic and correct (they’re assistants); (3) getting math reasoning 100% correct (but they can still open up new avenues for exploration that you’ve never even thought about); It takes practice to know what LLMs are good at and what they’re not. If the initial stance is negativity rather than a growth mindset, then that practice never comes. But it’s ok. The rest of us will keep on using LLMs and move on.
- esafak 2y ago
  An example that might be of interest to readers: I gave it two logs, one failing and one successful, and asked it to troubleshoot. It turned out a loosely pinned dependency (Docker image) had updated in the failing one. An error mode I was familiar with and could have solved on my own, but the LLM saved me time. They are reliable at sifting through text.
- mistercheph 2y ago
  Hostility and a few swift kicks are in order when the butt scratchers start saying their stochastic parrot machine is intelligent and a superman.

hyhconito 2y ago

You're still doing it the hard way. I just use Handbrake. Pick a hammer, not a shitty hammer factory to assemble bits of hammer.

sunnybeetroot 2y ago
How do you use handbrake to write a script that uses ffmpeg?

arkh 2y ago

> if it does I'll know right away and I can fall back to the old method of doing it manually It's well and ok with things you can botch with no consequence other than some time wasted. But I've bricked enough VMs trying commands I did not understand to know that if you need to not fuck up something you'll have to read those docs and understand them. And hope they're not out of date / wrong.

dangoodmanUT 2y ago

> Anyone who says AI is useless never had to do the old method of cobbling together git and ffmpeg commands from StackOverflow answers. The best ffmpeg and regex command generators

jv981 2y ago

try asking an LLM how to add compressed data to a tar through standard input, see how that goes (don't forget to check the answer :)

cootsnuck 2y ago

I use LLMs to help me with ffmpeg commands more than I care to admit

momentoftop 2y ago

> Anyone who says AI is useless never had to do the old method of cobbling together git and ffmpeg commands from StackOverflow answers. It's useful for that yes, but I'd rather just live in a world where we didn't have such disasters of CLI that are git and ffmpeg. LLMs are very useful for generating the obscure boilerplate needed because the underlying design is horrible. Relying on it means acquiescing to those terrible designs rather than figuring out redesigns that don't need the LLMs. For comparison, IntelliJ is very good at automating all the boilerplate generation that Java imposes on me, but I'd rather we didn't have boilerplate languages like Java, and I'd rather that IntelliJ's boilerplate generation didn't exist. I fear in many cases that if an LLM is solving your problem, you are solving the wrong problem.

skydhash 2y ago
I'm not arguing against the UX of those tools, but isn't this a case of the problem being a hard one to solve and people having different needs? ffmpeg has a lot of knobs, but that's just the nature of media conversion and manipulation, just like ImageMagick. I'm not against using LLMs for restricting the search space to a specific problems, but I'm often seeing people not even understanding the problem itself, just its apparent physicality.

skydhash 2y ago

> Anyone who says AI is useless never had to do the old method of cobbling together git and ffmpeg commands from StackOverflow answers. These days, I'm more likely to read the manual pages and take notes on interesting bits. If I'm going to rely on some tooling for some time, dedicating a few hours of reading is a good trade-off for me. No need to even remember everything, just the general way it solves the problem. Anything more precise is captured in notes, scripts, shell history,... I dare anyone to comes out with an essay like this from LLMs: https://karthinks.com/software/avy-can-do-anything/ https://karthinks.com/software/avy-can-do-anything/