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.
Of course they won’t be; somebody has to debug all the crap AI writes.
Seriously how can these CEOs of a GPU company not talk to a developer. You have loads of them to interview
They obviously have to sell something. I doubt that they honestly think that this will happen.
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.
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.
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
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.
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 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/[email protected]/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.
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.
That’s not what was said. He specifically said coding.
I don’t know if you noticed but most of the people making decisions in the industry aren’t programmers, they’re MBAs.
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.
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.
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
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.
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?
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.
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.
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.
It has already happened… And the results are a bit… “Cringe”
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.
I get why you’re enthusiastic about AI. This whole comment reads like it was AI generated.
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.
Everybody talks about AI killing programming jobs, but any developer who has had to use it knows it can’t do anything complex in programming. What it’s really going to replace is program managers, customer reps, makes most of HR obsolete, finance analysts, legal teams, and middle management. This people have very structured, rule based day to days. Getting an AI to write a very customized queuing system in Rust to suit your very specific business needs is nearly impossible. Getting AI to summarize Jira boards, analyze candidates experience, highlight key points of meetings (and obsolete most of them altogether), and gather data on outstanding patents is more in its wheelhouse.
I am starting to see a major uptick in recruiters reaching out to me because companies are starting to realize it was a mistake to stop hiring Software Engineers in the hopes that AI would replace them, but now my skills are going to come at a premium just like everyone else in Software Engineering with skills beyond “put a react app together”
Copilot can’t even suggest a single Ansible or Terraform task without suggesting invalid/unsupported options. I can’t imagine how bad it is at doing anything actually complex with an actual programming language.
Trouble is, you’re basing all that on now, not a year from now, or 6 months from now. It’s too easy to look at it’s weaknesses today and extrapolate. I think people need to get real about coding and AI. Coding is language and rules. Machines can learn that enormously faster and more accurately than humans. The ones who survive will be those who can wield it as a tool for creativity. But if you think it won’t be capable of all the things it’s currently weak at you’re just kidding yourself unfortunately. It’ll be like anything else - a tool for an operator. Middlemen will be wiped out of the process, of course, but those with money remain those without time or expertise, and there will always be a place for people willing to step in at that point. But they won’t be coding. They’ll be designing and solving problems.
It’s based on the last few years of messaging. They’ve consistently said AI will do X, Y, and Z, and it ends up doing each of those so poorly that you need pretty much the same staff to babysit the AI. I think it’s actually a net-negative in terms of productivity for technical work because you end up having to go over the output extremely carefully to make sure its correct, whereas you’d have some level of trust with a human employee.
AI certainly has a place in a technical workflow, but it’s nowhere close to replacing human workers, at least not right now. It’ll keep eating at the fringes for the next 5 years minimum, if not indefinitely, and I think the net result will be making human workers more productive, not replacing human workers. And the more productive we are per person, the more valuable that person is, and the more work gets generated.
We are 18 months into AI replacing me in 6 months. I mean… the CEO of OpenAI as well as many researchers have already said LLMs have mostly reached their limit. They are “generalizers” and if you ask them to do anything new they hallucinate quite frequently. Trying to get AI to replace developers when it hasn’t even replaced other menial office jobs is like saying “we taught AI to drive, it will replace all F1 drivers in 6 months”.
An inherent flaw in transformer architecture (what all LLMs use under the hood) is the quadratic memory cost to context. The model needs 4 times as much memory to remember its last 1000 output tokens as it needed to remember the last 500. When coding anything complex, the amount of code one has to consider quickly grows beyond these limits. At least, if you want it to work.
This is a fundamental flaw with transformer - based LLMs, an inherent limit on the complexity of task they can ‘understand’. It isn’t feasible to just keep throwing memory at the problem, a fundamental change in the underlying model structure is required. This is a subject of intense research, but nothing has emerged yet.
Transformers themselves were old hat and well studied long before these models broke into the mainstream with DallE and ChatGPT.
How many times does the public have to learn if the CEO says it, he probably doesn’t know what he’s talking about. If the devs say it, listen
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.
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.
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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.
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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I feel sorry for all those people in AWS that now have him as a leader…
