6 ms·

why would I do that kind of research if it can identify the problem I am trying to solve, and spit out the exact solution. also, it was a rough implementation a

why would I do that kind of research if it can identify the problem I am trying to solve, and spit out the exact solution. also, it was a rough implementation adapted to my exact tech stack

kazinator 1y ago
So you could stick your own copyright notice on the result, for one thing.
- ben_w 1y ago
  What's the point holding copyright on a new technical solution, to a problem that can be solved by anyone asking an existing AI, trained on last year's internet, independently of your new copyright?
  - kazinator 1y ago
    All sorts of stuff containing no original ideas is copyrighted. It legally belongs to someone and they can license it to others, etc. E.g. pop songs with no original chord progressions or melodies, and hackneyed lyrics are still copyrighted. Plagiarized and uncopyrightable code is radioactive; it can't be pulled into FOSS or commercial codebases alike.
  - alabastervlog 1y ago
    Someone raised the point in another recent HN LLM thread that the primary productivity benefit of LLMs in programing is the copyright laundering. The argument went that the main reason the now-ancient push for code reuse failed to deliver anything close to its hypothetical maximum benefit was because copyright got in the way. Result: tons and tons of wheel-reinvention, like, to the point that most of what programmers do day to day is reinvent wheels. LLMs essentially provide fine-grained contextual search of existing code, while also stripping copyright from whatever they find. Ta-da! Problem solved.
  - cmsj 1y ago
    There is one very specific risk worth mentioning: AI code is a potentially existential crisis for Open Source. An ecosystem that depends on copyright can't exist if its codebase is overrun by un-copyrightable code.
    - deleted 1y ago
      [deleted]
    - kazinator 1y ago
      It's not an existential crisis. You just don't merge radioactive contributions. If it sneaks in under your watchful radar, the damage control won't be fun though.
kmeisthax 1y ago
Because that path lies skill atrophy. AI research has a thing called "the bitter lesson" - which is that the only thing that works is search and learning. Domain-specific knowledge inserted by the researcher tends to look good in benchmarks but compromise the performance of the system[0]. The bitter-er lesson is that this also applies to humans. The reason why humans still outperform AI on lots of intelligence tasks is because humans are doing lots and lots of search and learning, repeatedly, across billions of people. And have been doing so for thousands of years. The only uses of AI that benefit humans are ones that allow you to do more search or more learning. The human equivalent of "inserting domain-specific knowledge into an AI system" is cultural knowledge, cliches, cargo-cult science, and cheating. Copying other people's work only helps you, long-term, if you're able to build off of that into something new; and lots of discoveries have come about from someone just taking a second look at what had been considered to be generally "known". If you are just "taking shortcuts", then you learn nothing. [0] I would also argue that the current LLM training regime is still domain-specific knowledge, we've just widened the domain to "the entire Internet".
- gtirloni 1y ago
  Here on HN you frequently see technologists using words like savant, genius, magical, etc, to describe the current generation of AI. Now we have vibe coding, etc. To me this is just a continuation of StackOverflow copy/paste where people barely know what they are doing and just hammer the keyboard/mouse until it works. Nothing has really changed at the fundamental level. So I find your assessment pretty accurate, if only depressing.
  - mirsadm 1y ago
    It is depressing but equally this presents even more opportunities for people that don't take shortcuts. I use Claude/Gemini day to day and outside of the most average and boring stuff they're not very capable. I'm glad I started my career well before these things were created.
- tombert 1y ago
  > Because that path lies skill atrophy. Maybe, but I'm not completely convinced by this. Prior to ChatGPT, there would be times where I would like to build a project (e.g. implement Raft or Paxos), I write a bit, find a point where I get stuck, decide that this project isn't that interesting and I give up and don't learn anything. What ChatGPT gives me, if nothing else, is a slightly competent rubber duck. It can give me a hint to why something isn't working like it should, and it's the slight push I need to power through the project, and since I actually finish the project, I almost certain learn more than I would have before. I've done this a bunch of times now, especially when I am trying to directly implement something directly from a paper, which I personally find can be pretty difficult. It also makes these things more fun. Even when I know the correct way to do something, there can be lots of tedious stuff that I don't want to type, like really long if/else chains (when I can't easily avoid them).
csto12 1y ago
I was pointing out that if you spent 2 weeks trying to find the solution but AI solved it within a day (you don’t specify how long the final solution by AI took), it sounds like those two weeks were not spent very well. I would be interested in knowing what in those two weeks you couldn’t figure out, but AI could.
- codingwagie 1y ago
  it was two weeks tossing around ideas in my head
  - financypants 1y ago
    idk why people here are laser focusing on "wow 2 weeks", I totally understand lightly thinking about an idea, motivations, feasibility, implementation, for a week or two
margalabargala 1y ago
Because as far as you know, the "rough implementation" only works in the happy path and there are really bad edge cases that you won't catch until they bite you, and then you won't even know where to look. An open source project wouldn't have those issues (someone at least understands all the code, and most edge cases have likely been ironed out) plus then you get maintenance updates for free.
- codingwagie 1y ago
  ive got ten years at faang in distributed systems, I know a good solution when i see one. and o3 is bang on
  - margalabargala 1y ago
    If you thought about it for two weeks beforehand and came up with nothing, I have trouble lending much credence to that.
    - qt31415926 1y ago
      the commenter never said they came up with nothing, they said o3 came up with something better.
  - deleted 1y ago
    [deleted]
  - lossolo 1y ago
    So 10 years at a FANG company, then it’s 15 years in backend at FANG, then 10 years in distributed systems, and then running interviews at some company for 5 years and rising capital as founder in NYC. Cool. Can you share that chat from o3?
    - themanmaran 1y ago
      How are those mutually exclusive statements? You can't imagine someone working on backend (focused on distributed systems) for 10-15 years at a FANG company. And also being in a position to interview new candidates?
titzer 1y ago
Who hired you and why are they paying you money? I don't want to be a hater, but holy moley, that sounds like the absolute laziest possible way to solve things. Do you have training, skills, knowledge? This is an HN comment thread and all, but you're doing yourself no favors. Software professionals should offer their employers some due diligence and deliver working solutions that at least they understand.

why would I do that kind of research if it can identify the problem I am trying to solve, and spit out the exact solution. also, it was a rough implementation adapted to my exact tech stack

kazinator 1y ago

So you could stick your own copyright notice on the result, for one thing.

ben_w 1y ago
What's the point holding copyright on a new technical solution, to a problem that can be solved by anyone asking an existing AI, trained on last year's internet, independently of your new copyright?
- kazinator 1y ago
  All sorts of stuff containing no original ideas is copyrighted. It legally belongs to someone and they can license it to others, etc. E.g. pop songs with no original chord progressions or melodies, and hackneyed lyrics are still copyrighted. Plagiarized and uncopyrightable code is radioactive; it can't be pulled into FOSS or commercial codebases alike.
- alabastervlog 1y ago
  Someone raised the point in another recent HN LLM thread that the primary productivity benefit of LLMs in programing is the copyright laundering. The argument went that the main reason the now-ancient push for code reuse failed to deliver anything close to its hypothetical maximum benefit was because copyright got in the way. Result: tons and tons of wheel-reinvention, like, to the point that most of what programmers do day to day is reinvent wheels. LLMs essentially provide fine-grained contextual search of existing code, while also stripping copyright from whatever they find. Ta-da! Problem solved.
- cmsj 1y ago
  There is one very specific risk worth mentioning: AI code is a potentially existential crisis for Open Source. An ecosystem that depends on copyright can't exist if its codebase is overrun by un-copyrightable code.
  - deleted 1y ago
    [deleted]
  - kazinator 1y ago
    It's not an existential crisis. You just don't merge radioactive contributions. If it sneaks in under your watchful radar, the damage control won't be fun though.

kmeisthax 1y ago

Because that path lies skill atrophy. AI research has a thing called "the bitter lesson" - which is that the only thing that works is search and learning. Domain-specific knowledge inserted by the researcher tends to look good in benchmarks but compromise the performance of the system[0]. The bitter-er lesson is that this also applies to humans. The reason why humans still outperform AI on lots of intelligence tasks is because humans are doing lots and lots of search and learning, repeatedly, across billions of people. And have been doing so for thousands of years. The only uses of AI that benefit humans are ones that allow you to do more search or more learning. The human equivalent of "inserting domain-specific knowledge into an AI system" is cultural knowledge, cliches, cargo-cult science, and cheating. Copying other people's work only helps you, long-term, if you're able to build off of that into something new; and lots of discoveries have come about from someone just taking a second look at what had been considered to be generally "known". If you are just "taking shortcuts", then you learn nothing. [0] I would also argue that the current LLM training regime is still domain-specific knowledge, we've just widened the domain to "the entire Internet".

gtirloni 1y ago
Here on HN you frequently see technologists using words like savant, genius, magical, etc, to describe the current generation of AI. Now we have vibe coding, etc. To me this is just a continuation of StackOverflow copy/paste where people barely know what they are doing and just hammer the keyboard/mouse until it works. Nothing has really changed at the fundamental level. So I find your assessment pretty accurate, if only depressing.
- mirsadm 1y ago
  It is depressing but equally this presents even more opportunities for people that don't take shortcuts. I use Claude/Gemini day to day and outside of the most average and boring stuff they're not very capable. I'm glad I started my career well before these things were created.
tombert 1y ago
> Because that path lies skill atrophy. Maybe, but I'm not completely convinced by this. Prior to ChatGPT, there would be times where I would like to build a project (e.g. implement Raft or Paxos), I write a bit, find a point where I get stuck, decide that this project isn't that interesting and I give up and don't learn anything. What ChatGPT gives me, if nothing else, is a slightly competent rubber duck. It can give me a hint to why something isn't working like it should, and it's the slight push I need to power through the project, and since I actually finish the project, I almost certain learn more than I would have before. I've done this a bunch of times now, especially when I am trying to directly implement something directly from a paper, which I personally find can be pretty difficult. It also makes these things more fun. Even when I know the correct way to do something, there can be lots of tedious stuff that I don't want to type, like really long if/else chains (when I can't easily avoid them).

csto12 1y ago

I was pointing out that if you spent 2 weeks trying to find the solution but AI solved it within a day (you don’t specify how long the final solution by AI took), it sounds like those two weeks were not spent very well. I would be interested in knowing what in those two weeks you couldn’t figure out, but AI could.

codingwagie 1y ago
it was two weeks tossing around ideas in my head
- financypants 1y ago
  idk why people here are laser focusing on "wow 2 weeks", I totally understand lightly thinking about an idea, motivations, feasibility, implementation, for a week or two

margalabargala 1y ago

Because as far as you know, the "rough implementation" only works in the happy path and there are really bad edge cases that you won't catch until they bite you, and then you won't even know where to look. An open source project wouldn't have those issues (someone at least understands all the code, and most edge cases have likely been ironed out) plus then you get maintenance updates for free.

codingwagie 1y ago
ive got ten years at faang in distributed systems, I know a good solution when i see one. and o3 is bang on
- margalabargala 1y ago
  If you thought about it for two weeks beforehand and came up with nothing, I have trouble lending much credence to that.
  - qt31415926 1y ago
    the commenter never said they came up with nothing, they said o3 came up with something better.
- deleted 1y ago
  [deleted]
- lossolo 1y ago
  So 10 years at a FANG company, then it’s 15 years in backend at FANG, then 10 years in distributed systems, and then running interviews at some company for 5 years and rising capital as founder in NYC. Cool. Can you share that chat from o3?
  - themanmaran 1y ago
    How are those mutually exclusive statements? You can't imagine someone working on backend (focused on distributed systems) for 10-15 years at a FANG company. And also being in a position to interview new candidates?

titzer 1y ago

Who hired you and why are they paying you money? I don't want to be a hater, but holy moley, that sounds like the absolute laziest possible way to solve things. Do you have training, skills, knowledge? This is an HN comment thread and all, but you're doing yourself no favors. Software professionals should offer their employers some due diligence and deliver working solutions that at least they understand.