The only people who would say this are people that don’t know programming.
LLMs are not going to replace software devs.
Wrong, this is also exactly what people selling LLMs to people who can’t code would say.
It’s this. When boards and non-tech savvy managers start making decisions based on a slick slide deck and a few visuals, enough will bite that people will be laid off. It’s already happening.
There may be a reckoning after, but wall street likes it when you cut too deep and then bounce back to the “right” (lower) headcount. Even if you’ve broken the company and they just don’t see the glide path.
It’s gonna happen. I hope it’s rare. I’d argue it’s already happening, but I doubt enough people see it underpinning recent lay offs (yet).
AI as a general concept probably will at some point. But LLMs have all but reached the end of the line and they’re not nearly smart enough.
LLMs have already reached the end of the line 🤔
I don’t believe that. At least from an implementation perspective we’re extremely early on, and I don’t see why the tech itself can’t be improved either.
Maybe it’s current iteration has hit a wall, but I don’t think anyone can really say what the future holds for it.
LLMs have been around since roughly
20162017 (comment below corrected me that Attention paper was 2017). While scaling the up has improved their performance/capabilities, there are fundamental limitations on the actual approach. Behind the scenes, LLMs (even multimodal ones like gpt4) are trying to predict what is most expected, while that can be powerful it means they can never innovate or be truth systems.For years we used things like tf-idf to vectorize words, then embeddings, now transformers (supped up embeddings). Each approach has it limits, LLMs are no different. The results we see now are surprisingly good, but don’t overcome the baseline limitations in the underlying model.
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You’re right, I thought that paper came out in 2016.
I’m not trained in formal computer science, so I’m unable to evaluate the quality of this paper’s argument, but there’s a preprint out that claims to prove that current computing architectures will never be able to advance to AGI, and that rather than accelerating, improvements are only going to slow down due to the exponential increase in resources necessary for any incremental advancements (because it’s an NP-hard problem). That doesn’t prove LLMs are end of the line, but it does suggest that additional improvements are likely to be marginal.
we’re extremely early on
Oh really! The analysis has been established since the 80’s. Its so far from early on that statement is comical
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“at some point” being like 400 years in the future? Sure.
Ok that’s probably a little bit of an exaggeration. 250 years.
I don’t know if you noticed but most of the people making decisions in the industry aren’t programmers, they’re MBAs.
Irrelevant, anyone who tries to replace their devs with LLMs will crash and burn. The lessons will be learned. But yes, many executives will make stupid ass decisions around this tech.
It’s really sad how even techheads ignore how rapidly LLM coding has come in the last 3 years and what that means in the long run.
Just look how rapidly voice recognition developed once Google started exploiting all of its users’ voice to text data. There was a point that industry experts stated ‘There will never be a general voice recognition system that is 90%+ across all languages and dialects.’ And google made one within 4 years.
The natural bounty of a no-salary programmer in a box is too great for this to ever stop being developed, and the people with the money only want more money, and not paying devs is something they’ve wanted since the coding industry literally started.
Yes its terrible now, but it is also in its infancy, like voice recognition in the late 90s it is a novelty with many hiccoughs. That won’t be the case for long and anyone who confidently thinks it can’t ever happen will be left without recourse when it does.
But that’s not even the worst part about all of this but I’m not going into black box code because all of you just argue stupid points when I do but just so you know, human programming will be a thing of the past outside of hobbyists and ultra secure systems within 20 years.
Maybe sooner
Maybe in 20 years. Maybe. But this article is quoting CEOs saying 2 years, which is bullshit.
I think it’s just as likely that in 20 years they’ll be crying because they scared enough people away from the career that there aren’t enough developers, when the magic GenAI that can write all code still doesn’t exist.
yeah 2 years is bullshit but with innovation, 10 years is still reasonable and fucking terrifying.
I can see the statement in the same way word processing displaced secretaries.
There used to be two tiers in business. Those who wrote ideas/solutions and those who typed out those ideas into documents to be photocopied and faxed. Now the people who work on problems type their own words and email/slack/teams the information.
In the same way there are programmers who design and solve the problems, and then the coders who take those outlines and make it actually compile.
LLM will disrupt the programmers leaving the problem solvers.
There are still secretaries today. But there aren’t vast secretary pools in every business like 50 years ago.
There is no reason to believe that LLM will disrupt anyone any time soon. As it stands now the level of workmanship is absolutely terrible and there are more things to be done than anyone has enough labor to do. Making it so skilled professionals can do more literally just makes it so more companies can produce quality of work that is not complete garbage.
Juniors produce progressively more directly usable work with reason and autonomy and are the only way you develop seniors. As it stands LLM do nothing with autonomy and do much of the work they do wrong. Even with improvements they will in near term actually be a coworker. They remain something you a skilled person actually use like a wrench. In the hands of someone who knows nothing they are worth nothing. Thinking this will replace a segment of workers of any stripe is just wrong.
It’ll have to improve a magnitude for that effect. Right now it’s basically an improved stack overflow.
…and only sometimes improved. And it’ll stop improving if people stop using Stack Overflow, since that’s one of the main places it’s mined for data.
Nah, it’s built into the editors and repos these days.
?
If no one uses Stack Overflow anymore, then no one posts new answers. So AI has no new info to mine.
They are mining the IDE and GitHub.
You seem to be missing what I’m saying, and missing my point. But I’m not going to try to rephrase it again.
I wrote a comment about this several months ago on my old kbin.social account. That site is gone and I can’t seem to get a link to it, so I’m just going to repost it here since I feel it’s relevant. My kbin client doesn’t let me copy text posts directly, so I’ve had to use the Select feature of the android app switcher. Unfortunately, the comment didn’t emerge unscathed, and I lack the mental energy to fix it due to covid brain fog (EDIT: it appears that many uses of
Iwere not preserved). The context of the old post was about layoffs, and it can be found here: https://kbin.earth/m/asklemmy@lemmy.ml/t/12147I want to offer my perspective on the Al thing from the point of view of a senior individual contributor at a larger company. Management loves the idea, but there will be a lot of developers fixing auto-generated code full of bad practices and mysterious bugs at any company that tries to lean on it instead of good devs. A large language model has no concept of good or bad, and it has no logic. happily generate string- templated SQL queries that are ripe for SQL injection. I’ve had to fix this myself. Things get even worse when you have to deal with a shit language like Bash that is absolutely full of God awful footguns. Sometimes you have to use that wretched piece of trash language, and the scripts generated are horrific. Remember that time when Steam on Linux was effectively running rm -rf /* on people’s systems? I’ve had to fix that same type of issue multiple times at my workplace.
I think LLMs will genuinely transform parts of the software industry, but I absolutely do not think they’re going to stand in for competent developers in the near future. Maybe they can help junior developers who don’t have a good grasp on syntax and patterns and such. I’ve personally felt no need to use them, since spend about 95% of my time on architecture, testing, and documentation.
Now, do the higher-ups think the way that do? Absolutely not. I’ve had senior management ask me about how I’m using Al tooling, and they always seem so disappointed when I explain why I personally don’t feel the need for it and what feel its weaknesses are. Bossman sees it as a way to magically multiply IC efficiency for nothing, so absolutely agree that it’s likely playing a part in at least some of these layoffs.
Basically, I think LLMs can be helpful for some folks, but my experience is that the use of LLMs by junior developers absolutely increases the workload of senior developers. Senior developers using LLMs can experience a productivity bump, but only if they’re very critical of the output generated by the model. I am personally much faster just relying on traditional IDE auto complete, since I don’t have to change from “I’m writing code” mode to “I’m reviewing code mode.”
The one colleague using AI at my company produced (CUDA) code with lots of memory leaks that required two expert developers to fix. LLMs produce code based on vibes instead of following language syntax and proper coding practices. Maybe that would be ok in a more forgiving high level language, but I don’t trust them at all for low level languages.
I was trying to use it to write a program in python for this macropad I bought and I have yet to get anything usable out of it. It got me closer than I would have been by myself and I don’t have a ton of coding experience so it’s problems are probably partially on me but everything it’s given me has required me to correct it to work.
Will there even be a path for junior level developers?
The same one they have now, perhaps with a steeper learning curve. The market for software developers is already saturated with disillusioned junior devs who attended a boot camp with promises of 6 figure salaries. Some of them did really well, but many others ran headlong into the fact that it takes a lot more passion than a boot camp to stand out as a junior dev.
From what I understand, it’s rough out there for junior devs in certain sectors.
The problem with this take is the assertion that LLMs are going to take the place of secretaries in your analogy. The reality is that replacing junior devs with LLMs is like replacing secretaries with a network of typewriter monkeys who throw sheets of paper at a drunk MBA who decides what gets faxed.
I’m saying that devs will use LLM’s in the same way they currently use word processing to send emails instead of handing hand written notes to a secretary to format, grammar/spell check, and type.
I thought by this point everyone would know how computers work.
That, uh, did not happen.
The one thing that LLMs have done for me is to make summarizing and correlating data in documents really easy. Take 20 docs of notes about a project and have it summarize where they are at so I can get up to speed quickly. Works surprisingly well. I haven’t had luck with code requests.
That’s not what was said. He specifically said coding.
Guys that are putting billions of dollars into their AI companies making grand claims about AI replacing everyone in two years. Whoda thunk it
He who knows, does not speak. He who speaks, does not know.
–Lao Tzu…
Great answer to interview questions
What does the person “who knows” do when they have to give a presentation?
But coding never was the difficult part. It’s understanding a concept, identify a problem and solve it with the possible methods. An AI just makes the coding part faster and gives me options to quicker identify a possible solution. Thankfully there’s a never ending pile of projects, issues, todos and stackholder wants, that I don’t see how we need less programmers. Maybe we need more to deal with AI, as now people can do a lot more in house instead of outsourcing, but as soon as that threshold is reached, companies will again contact large software companies. If people want to put AI into everything, you need people feeding the AI with company specific data and instruct people to use this AI.
All I see is middle management getting replaced, because instead of a boring meeting, I could just ask an AI.
I dread meetings and I can’t wait for AIs to replace those managers. Or perhaps we’ll have even more meetings because the management wants to know why we’re so late despite the AI happily churning out meaningless codes that look so awesome like all that CSI VB GUI crap.
That’s when you write an AI auto reply cron. Let the snake eat its tail. Hehe
It’s been said before but the whiter your collar the more likely you are to be replaced by AI simply because the grunts tend to do more varied less pleibeon things.
Middle managers tend to write a lot of documents and emails which is something AI excels at. The programmers meanwhile have to come up with creative solutions to problems, and AI is less good at being creative, it basically just copy pastes known solutions from the web.
Realises devs have always joked about their jobs just being about copy-pasting solutions from StackOverflow 80% of the time
Oh God…
CEOs without a clue how things work think they know how things work.
I swear if we had no CEOs from today on the only impact would be that we wouldve less gibberish being spoken
If AI could replace anyone… it’s those dingbats. I mean, what would you say, in this given example, the CEO does… exactly? Make up random bullshit? AI does that. Write a speech? AI does that. I love how these overpaid people think they can replace the talent but they… they are absolutely required and couldn’t possibly be replaced! Talent and AI can’t buy and enjoy the extra big yacht, or private jets, or over priced cars, or a giant over sized mansion… no you need people for that.
If, 24 months from now, most people aren’t coding, it’ll be because people like him cut jobs to make a quicker buck. Or nickel.
Well if it works, means that job wasn’t that important, and the people doing that job should improve themselves to stay relevant.
Edit: wow what a bunch of hypersensitive babies. I swear, y’all just allergic to learning or something. I just said people need to improve themselves to stay relevant, and people freak out and send me death threats. What a joke.
job wasn’t that important
I keep telling you that changing out the battery in the smoke alarm isn’t worth the effort and you keep telling me that the house is currently on fire, we need to get out of here immediately, and I just roll my eyes because you’re only proving my point.
Sure, believe what you want to believe. You can either adapt to what’s happening, or just get phased out. AI is happening whether you like it or not. You may as well learn to use it.
I get why you’re enthusiastic about AI. This whole comment reads like it was AI generated.
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AI can’t do anything that hasn’t been done before. That’s never going to change.
You can adapt, but how you adapt matters.
AI in tech companies is like a hammer or drill. You can either get rid of your entire construction staff and replace them with a few hammers, or you can keep your staff and give each worker a hammer. In the first scenario, nothing gets done, yet jobs are replaced. In the second scenario, people keep their jobs, their jobs are easier, and the house gets built.
Yup. Most of us aren’t CEOs, so we don’t have a lot of say about how most companies are run. All we can do is improve ourselves.
For some reason, a lot of people seem to be against that. They prefer to whine.
Define “works”?
If you’re a CEO, cutting all your talent, enshittifying your product, and pocketing the difference in new, lower costs vs standard profits might be considered as “working”.
Hmmm maybe you’re misunderstanding me.
What I mean is “coding” is basically the grunt work of development. The real skill is understanding the requirements and building something efficiently. Tbh, I hate coding.
What tools like Gemini or ChatGPT brings to the table is the ability to create small, efficient snippets of code that works. We can then just modify it to meet our more specific requirements.
This makes things much faster, for me at least. If the time comes when the AI can generate more efficient code, making my job easier, I’d count that as “works” for me.
Oh perhaps the CEOs are the ones that need to be replaced?
Yup, notice nowhere did I say they shouldnt. People read and infer what they want
Like in Twitter?
Nah that was just a bad CEO
😜 👢
Define “works.”
Because the goals of a money-hungry CEO don’t always align with those of the workers in the company itself (or often, even the consumer). I imagine this guy will think it worked just fine as he’s enjoying his golden parachute.
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Lets wait for any LLM do a single sucessful MR on Github first before starting a project on its own. Not aware of any.
there isn’t a single serious project written exclusively or mostly by an LLM? There isn’t a single library or remotely original application
IMHO “original” here is the key. Finding yet another clone of a Web framework ported from one language to another in order to push online a basic CMS slightly faster, I can imagine this. In fact I even bet that LLM, because they manipulate words in languages and that code can be safely (even thought not cheaply) tested within containers, could be an interesting solution for that.
… but that is NOT really creating value for anyone, unless that person is technically very savvy and thus able to leverage why a framework in a language over another creates new opportunities (say safety, performances, etc). So… for somebody who is not that savvy, “just” relying on the numerous existing already existing open-source providing exactly the value they expect, there is no incentive to re-invent.
For anything that is genuinely original, i.e something that is not a port to another architecture, a translation to another language, a slight optimization, but rather something that need just a bit of reasoning and evaluating against the value created, I’m very skeptical, even less so while pouring less resources EVEN with a radical drop in costs.
My last employer had many internal tools that were fine.
They had only a moderate amount of oversight.
I had to find a new job, I’m actually thinking of walking away from software development now that there are so few jobs :(
It sucks but there’s no sense pretending this won’t have a large impact on the job landscape.
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Mostly internal data cleaning stuff, close etc, which I accept is less in scope than you’re original comment.
The things you are describing sound like if-statement levels of automation, GitHub Actions with preprogrammed responses rather than LLM whatever.
If you’re worrying about being replaced by that… Go find the code, read it, and feel better.
The code was non trivial and relatively sophisticated. It performed statistical analysis on ingested data and the approach taken was statistically sound.
I was replaced by that. So was my colleague.
The job market is exceptionally tough right now and a large part of that is certainly llms.
I think taking people with statistical training out of the equation is quite dangerous, but it’s happening. In my area, everybody doing applied mathematics, statistics or analysis has been laid off.
In saying that, the produced program was quite good.
Certainly sounds more interesting than my original read of it! Sorry about that, I was grumpy.
All good man.
I think the point is that LLMs can replace people and they are quite good.
But they absolutely shouldn’t replace people, yet, or possibly ever.
But that’s what’s happening and it’s a massive problem because it’s leading to mediocre code in important spaces.
Of course they won’t be; somebody has to debug all the crap AI writes.
Todays news: Rich assholes in suits are idiots and don’t know how their own companies are working. Make sure to share what they’re saying.
Yeah, that’s not going to happen.
Yeah writing the code isn’t really the hard part. It’s knowing what code to write and how to structure it to work with your existing code or potential future code. Knowing where things might break so you can add the correct tests or alerts. Giving time estimates on how long it will take to build the parts of the system and building in phases to meet your teams needs.
I’ve always thought that design and maintenance are the difficult and gruelling parts, and writing code is when you get to relax for a bit. Most of the time you’re in maintenance mode, and it’s harder than writing new code.
This. I’m learning a new skill right now & hardly any of it is actual writing— it’s how to arrange the pieces someone else wrote (& which sometimes AI can decently reproduce.)
When you use a computer you don’t start by mining iron, because the thing is already built
It’ll replace brain dead CEOs before it replaces programmers.
I’m pretty sure I could write a bot right now that just regurgitates pop science bullshit and how it relates to Line Go Up business philosophy.
Edit: did it, thanks ChatJippity
def main(): # Check if the correct number of arguments are provided if len(sys.argv) != 2: print("Usage: python script.py <PopScienceBS>") sys.exit(1) # Get the input from the command line PopScienceBS = sys.argv[1] # Assign the input variable to the output variable LineGoUp = PopScienceBS # Print the output print(f"Line Go Up if we do: {LineGoUp}") if __name__ == "__main__": main()if lineGoUp { CollectUnearnedBonus() } else { FireSomePeople() CollectUnearnedBonus() }I think we need to start a company and commence enshittification, pronto.
This company - employee owned, right?
I’m just going to need you to sign this Contributor License Agreement assigning me all your contributions and we’ll see about shares, maybe.
I love how even here there’s line metric coding going on
ChatJippity
I’ll start using that!
I know just enough about this to confirm that this statement is absolute horseshit
Sounds like the no-ops of a decade ago and cloud will remove the need for infrastructure engineers. 😂🤣😂🤣😂🤣😂😂😂🤣
SHUT UP AND GO BACK TO OUR SHITTY YAML BASED INFRASTRUCTURE!
Fuck yml, all my homies hate yml
JSON or bust!
Ok, since YAML is a superset, I can just put the JSON into the YAML.
That sounds cursed.
Please don’t 🙏🏻
🤣😂😪😥😢😭
It isn’t that AI will have replaced us in 24 months, it’s that we will be enslaved in 24 months. Or in the matrix. Etc.
Will the matrix it puts us in be in 1999? Because I’d take that deal.
Matrix lookin pretty good rn - 1999, stable climate, free apartment, 90s gf (she loves u) etc
This will be used as an excuse to try to drive down wages while demanding more responsibilities from developers, even though this is absolute bullshit. However, if they actually follow through with their delusions and push to build platforms on AI-generated trash code, then soon after they’ll have to hire people to fix such messes.
A company I used to work for outsourced most of their coding to a company in India. I say most because when the code came back the internal teams anways had to put a bunch of work in to fix it and integrate it with existing systems. I imagine that, if anything, LLMs will just take the place of that overseas coding farm. The code they spit out will still need to be fixed and modified so it works with your existing systems and that work is going to require programmers.
So instead of spending 1 day writing good code, we’ll be spending a week debugging shitty code. Great.
Good luck debugging AI-generated code…
They think it will be easier than having people write the code from scratch. I don’t know shit about coding but I know that’s definitely not right.
AI is quite good at writing small sections of code. Usually because it’s more or less just copying something off the internet that it’s found, maybe changing a few bits around, but essentially just regurgitating something that’s in its data set. I could of course just have done that but it saves time since the AI can find the relevant piece of code to copy and modify more or less instantly.
But it falls apart if you ask it to build entire applications. You can barely even get it to write pong without a lot of tinkering around after the fact which rather defeats the point really.
It also doesn’t deal well if the thing you’re trying to program for is not very well documented, which would include things like drivers, which presumably is their bread and butter.
That might actually be a good test for managers who think coders can be replaced by this. Have them try to make a working version of Pong using AI prompts.
Really simple. Just ask it to point out the error. Also maybe tell it how the code is wrong. And then hope that the new code didn’t introduce new errors in formerly working sections. And that it understood what you meant. In a language that is inherently vague.
