this post was submitted on 07 Jun 2024
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[–] dual_sport_dork@lemmy.world 226 points 5 months ago* (last edited 5 months ago) (40 children)

Say it with me again now:

For fact-based applications, the amount of work required to develop and subsequently babysit the LLM to ensure it is always producing accurate output is exactly the same as doing the work yourself in the first place.

Always, always, always. This is a mathematical law. It doesn't matter how much you whine or argue, or cite anecdotes about how you totally got ChatGPT or Copilot to generate you some working code that one time. The LLM does not actually have comprehension of its input or output. It doesn't have comprehension, period. It cannot know when it is wrong. It can't actually know anything.

Sure, very sophisticated LLM's might get it right some of the time, or even a lot of the time in the cases of very specific topics with very good training data. But its accuracy cannot be guaranteed unless you fact-check 100% of its output.

Underpaid employees were asked to feed published articles from other news services into generative AI tools and spit out paraphrased versions. The team was soon using AI to churn out thousands of articles a day, most of which were never fact-checked by a person. Eventually, per the NYT, the website's AI tools randomly started assigning employees' names to AI-generated articles they never touched.

Yep, that right there. I could have called that before they even started. The shit really hits the fan when the computer is inevitably capable of spouting bullshit far faster than humans are able to review and debunk its output, and that's only if anyone is actually watching and has their hand on the off switch. Of course, the end goal of these schemes is to be able to fire as much of the human staff as possible, so it ultimately winds up that there is nobody left to actually do the review. And whatever emaciated remains of management are left don't actually understand how the machine works nor how its output is generated.

Yeah, I see no flaws in this plan... Carry the fuck on, idiots.

[–] dependencyinjection@discuss.tchncs.de -1 points 5 months ago (13 children)

Simply false in my experience.

We use CoPilot at work and there is no babysitting required.

We are software developers / engineers and it’s saves countless hours writing boilerplate code, giving code blocks based on a comment, and sticking to our coding conventions.

Sure it isn’t 100% right, but the owner and lead engineer calculates it to be around 70% accurate and even if it misses the mark, we have a whole lot less key presses to make.

[–] HauntedCupcake@lemmy.world 17 points 5 months ago (9 children)

Using Copilot as a copilot, like generating boilerplate and then code reviewing it is still "babysitting" it. It's still significantly less effort than just doing it yourself though

[–] dave@feddit.uk 1 points 5 months ago (1 children)

Surely boilerplate code is copy / paste or macros, then edit the significant bits—a lot less costly than copilot.

[–] dependencyinjection@discuss.tchncs.de 5 points 5 months ago (1 children)

That would still make more effort.

So, for an example we use a hook called useChanges() for tracking changes to a model in the client, it has a very standard set of arguments.

Why would we want to waste time writing it out all the time when we can write the usual comment “Product Model” and have it do the work.

Copy and Paste takes more effort as we WILL have to change the dynamic parts every time, macros will take longer as we have to create the macros for every different convention we have.

If you can’t see the benefit of LLMs as a TOOL to aid developers then I would hazard a guess you are not in the industry or you just haven’t even given them a go.

I will say I am a new developer and not amazing, but my boss the owner and lead engineer is a certified genius, who will write flawless code on damn teams to help me along at times, and if he can benefit from it in time saved then anybody would.

[–] dave@feddit.uk 2 points 5 months ago (1 children)

My PhD was in neural networks in the 1990s and I’ve been in development since then.

Remember when digital cameras came out? They were pretty crappy compared to film—if you had a decent film camera and knew what you were doing. I fell like that’s where we’re at with LLMs right now.

Digital cameras are now pretty much on par with film, perhaps better in some circumstances and worse in others.

Shifting gear from writing code to reviewing someone else’s is inefficient. With a good editor setup and plenty of screen real estate, I’m more productive just writing than constantly worrying about what the copilot just inserted. And yes, I’ve tested that.

Clearly what works for our company ain’t what would work for you, even if I think it’s preposterous what you’re claiming.

My boss was working on Open Source from the BSD days and is capable of very low level programming. He has forgotten more than I’ll ever know, and if he can find LLMs a useful tool for our literal company to improve productivity then I’m inclined to stick with what I have seen and experienced. Just not having to do and search documentation alone is a massive time saver. Unless obviously you know everything, which nobody does.

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