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Human coders are still better than LLMs

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Re: Human coders are still better than LLMs

#91

Post by jdiff »

cortesoft wrote: post #58
mattnewton wrote: post #5

This matches my experience. I actually think a fair amount of value from LLM assistants to me is having a reasonably intelligent rubber duck to talk to. Now the duck can occasionally disagree and sometimes even refine. https://en.m.wikipedia.org/wiki/Rubber_duck_debugging I think the big question everyone wants to skip right to and past this conversation is, will this continue to be true 2 years from now? I don’t kno…

Currently, I find AI to be a really good autocomplete

The crazy thing is that people think that a model designed to predict sequences of tokens from a stem, no matter how advanced the model, to be much more than just "really good autocomplete."

It is impressive and very unintuitive just how far that can get you, but it's not reductive to use that label. That's what it is on a fundamental level, and aligning your usage with that will allow it to be more effective.

Re: Human coders are still better than LLMs

#92

Post by janalsncm »

loudmax wrote: post #83

Companies that leverage LLMs and AIs to let their employees be more productive will thrive. Companies that try to replace their employees with LLMs and AIs will fail. Unfortunately, all that's in the long run. In the near term, some CEOs and management teams will profit from the short term valuations as they squander their companies' future growth on short-sighted staff cuts.

Very well said. Using code assistance is going to be table stakes moving forward, not something that can replace people. It’s not like competitors can’t also purchase AI subscriptions.

Re: Human coders are still better than LLMs

#93

Post by jonator »

jppittma wrote: post #16
vouaobrasil wrote: post #3

The question is, for how long?

It's really gonna depend on the project. When my hobby project was greenfield, the AI was way better than I am. It was (still is) more knowledgable about the standards that govern the field and about low level interface details. It can shit out a bunch of code that relies on knowing these details in seconds/minutes, rather than hours/days. Now that the project has grown and all that stuff is hammered out, it can't se…

We can slightly squeeze more juice out of them with larger projects by providing better context, docs, examples of what we want, background knowledge, etc.

Like people, LLMs don't know what they don't know (about your project).

Re: Human coders are still better than LLMs

#94

Post by Epa095 »

marcosdumay wrote: post #65
smokel wrote: post #46

Earlier quoted context omitted.

Stating this without any arguments is not very convincing. Perhaps you remember that language models were completely useless at coding some years ago, and now they can do quite a lot of things, even if they are not perfect. That is progress, and that does give reason to extrapolate. Unless of course you mean something very special with "solving programming".

Why state the same arguments everybody has been repeating for ages? LLMs can only give you code that somebody has wrote before. This is inherent. This is useful for a bunch of stuff, but that bunch won't change if OpenAI decides to spend the GDP of Germany training one instead of Costa Rica.

First, how much of coding is really never done before?

And secondly, what you say are false (at least if taken literally). I can create a new programming language, give the definition of it in the prompt, ask it to code something in my language, and expect something out. It might even work.

Re: Human coders are still better than LLMs

#95

Post by antirez »

AlotOfReading wrote: post #74

Unrelated to the LLM discussion, but a hash function function is the wrong construction for the accumulator solution. The hashing part increases the probability that A and B have a collision that leads to a false negative here. Instead, you want a random invertible mapping, which guarantees that no two pointers will "hash" to the same value, while distributing the bits. Splitmix64 is a nice one, and I believe the mur…

Any Feistel Network has the property you stated actually, and this was one of the approaches I was thinking using as I can have the seed as part of the non linear transformation of the Feistel Network. However I'm not sure that this actually decreases the probability of A xor B xor C xor D being accidentally zero, bacause the problem with pointers is that they may change only for a small part. When you using hashing because of avalanche effect this is going a lot harder since you are no longer xoring the pointer structure.

What I mean is that you are right assuming we use a transformation that still while revertible has avalanche effect. Btw in practical terms I doubt there are practical differences.

Re: Human coders are still better than LLMs

#96

Post by joshdavham »

mattnewton wrote: post #5

This matches my experience. I actually think a fair amount of value from LLM assistants to me is having a reasonably intelligent rubber duck to talk to. Now the duck can occasionally disagree and sometimes even refine. https://en.m.wikipedia.org/wiki/Rubber_duck_debugging I think the big question everyone wants to skip right to and past this conversation is, will this continue to be true 2 years from now? I don’t kno…

> I actually think a fair amount of value from LLM assistants to me is having a reasonably intelligent rubber duck to talk to.

I wonder if the term "rubber duck debugging" will still be used much longer into the future.

Re: Human coders are still better than LLMs

#97

Post by Bukhmanizer »

mattnewton wrote: post #5

This matches my experience. I actually think a fair amount of value from LLM assistants to me is having a reasonably intelligent rubber duck to talk to. Now the duck can occasionally disagree and sometimes even refine. https://en.m.wikipedia.org/wiki/Rubber_duck_debugging I think the big question everyone wants to skip right to and past this conversation is, will this continue to be true 2 years from now? I don’t kno…

There are a couple people I work with who clearly don’t have a good understanding of software engineering. They aren’t bad to work with and are in fact great at collaborating and documenting their work, but don’t seem to have the ability to really trace through code and logically understand how it works.

Before LLMs it was mostly fine because they just didn’t do that kind of work. But now it’s like a very subtle chaos monkey has been unleashed. I’ve asked on some PRs “why is this like this? What is it doing?” And the answer is “ I don’t know, ChatGPT told me I should do it.”

The issue is that it throws basically all their code under suspicion. Some of it works, some of it doesn’t make sense, and some of it is actively harmful. But because the LLMs are so good at giving plausible output I can’t just glance at the code and see that it’s nonsense.

And this would be fine if we were working on like a crud app where you can tell what is working and broken immediately, but we are working on scientific software. You can completely mess up the results of a study and not know it if you don’t understand the code.

Re: Human coders are still better than LLMs

#98

Post by joshdavham »

loudmax wrote: post #83

Companies that leverage LLMs and AIs to let their employees be more productive will thrive. Companies that try to replace their employees with LLMs and AIs will fail. Unfortunately, all that's in the long run. In the near term, some CEOs and management teams will profit from the short term valuations as they squander their companies' future growth on short-sighted staff cuts.

> In the near term, some CEOs and management teams will profit from the short term valuations

That's actually really interesting to think about. The idea that doing something counter-productive like trying to replace employees with AI (which will cause problems), may actually benefit the company in terms of valuations in the short run. So in effect, they're hurting and helping the company at the same time.

Re: Human coders are still better than LLMs

#99

Post by bluefirebrand »

prophesi wrote: post #54
ehutch79 wrote: post #24

Earlier quoted context omitted.

Uh, no. I've seen the twitter posts saying llms will replace me. I've watched the youtube videos saying llms will code whole apps on one prompt, but are light on details or only show the most basic todo app from every tutorial. We're being told that llms are now reasoning, which implies they can make logical leaps and employ creativity to solve problems. The hype cycle is real and setting expectations that get higher…

> The hype cycle is real and setting expectations that get higher with _the less you know about how they work_. I imagine on HN, the expectations we're talking about are from fellow software developers who at least have a general idea on how LLM's work and their limitations.

Right below this is a comment

> you will almost certainly be replaced by an llm in the next few years

So... Maybe not. I agree that Hacker News does have a generally higher quality of contributors than many places on the internet, but it absolutely is not a universal for HNers. There are still quite a few posters here that have really bought into the hype for whatever reason

Re: Human coders are still better than LLMs

#100

Post by sofal »

vouaobrasil wrote: post #79
sofal wrote: post #64

Earlier quoted context omitted.

I'm constantly disappointed by how little I'm able to delegate to AI after the unending promises that I'll be able to delegate nearly 100% of what I do now "in the not too distant future". It's tired impatience and merited skepticism that you mistake for fear and coping. Just because people aren't on the hype train with you doesn't mean they're afraid.

Personally, I am. Lots of unusual skills I have, have already been taken by AI. That's not to say I think I'm in trouble, but I think it's sad I can't apply some of these skills that I learned just a couple of years ago like audio editing because AI does it now. Neither do I want to work as an AI operator, which I find boring and depressing. So, I've just moved onto something else, but it's still discouraging. Also,…

I don't acquire skills and apply them just to be able to apply them. I use them to solve problems and create things. My learned skills for processing audio are for the purpose of getting the audio sounding the way I want it to sound. If an AI can do that for me instead, that's amazing and frees up my time to do other things or do a lot more different audio things. None of this is scary to me or impacts my personal dignity. I'm actually constantly wishing that AI could help me do even more. Honestly I'm not even sure what you mean by AI doing audio editing, can I get some of that? That is some grunt work I don't need more of.
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