Ask Lemmy

No, it's basically filling the role of an auto complete and search function for code based. We've had this for a while and it generally works better than a lot of stuff we've had in the past, but it's certainly not replacing anyone any time soon.

I don’t know Python, but I know bash and powershell.

One of the AI things completely reformatted my bash script into a python the other day (that was the intended end result), so that was somewhat impressive.

If you want an example, my last job in telecom was investing hard in automation and while it was doing a poor job at the beginning, it started to do better and better, and while humans were needed, we had to do less work, of course that meant that when someone left the job, my employers didn't look for replacements.

To be honest I don't see the AI doing the job of tech workers to a point we should worry now... But in 20 years? That's another story. And in 20 years if I get fired probably no one will want to hire me, so I'm already working on a plan B.

I’m seeing layoffs of US workers, who are then being replaced by Indian, South American and Ireland nationals… not AI. But they’re calling it AI.

What I'm reading out of this... there's going to be a massive shortage of senior programmers in 20(?) years. If juniors aren't being let go/not hired and AI is doing junior work....

AI will have to massively improve or else it's going to be interesting when companies are trying to hold on to retirement age people and train up replacement seniors to verify the AI delivers proper code.

Yeah kinda, my coworkers talk to ChatGPT like it actually knows stuff and use it to fix their broken terraform code.

It takes them a week or longer to get simple tickets done like this. One dude asked for my help last week, we actually LOOKED at the error codes and fixed his shit in about 15 minutes. Got his clusters up within an hour. Normally a week long ticket – crunched out in 60 minutes by hand.

It feels ridiculous because it's primarily senior tech bro engineer types who fumble their work with this awful tool.

Do the job? No. Noticeably increase productivity, and reduce time spent on menial tasks? Yes.

I suspect the layoffs are partly motivated by the expectation that remaining workers will be able to handle a larger workload with the help of AI.

US companies in particular are also heavily outsourcing jobs overseas, for cheaper. They just don't like to be transparent about that aspect, so the AI excuse takes the focal point.

AI is just another reason for layoffs for companies that are underperforming. It’s more of a buzzword to sell the company to investors. I haven’t seen people actually use AI anywhere in my large ass corp yet.

Yeah, I use it daily for coding. It's a force multiplier. It basically makes me 2 - 3x more effective. My company laid off all our junior engineers and is not hiring juniors any longer.

No, not even close. It's far too unreliable, without someone who knows what they're doing to vet the questionable result, AI is a disaster waiting to happen. Never mind it cannot go fix a computer or server or any physical issue.

It has potential to increase quality but not take over the job. So coders already had various addons that can help complete a line and suggest variables and such. I found the auto commenting great. Not that it did a great job but its one of those things were without it im not doing enough commenting but when it auto comments Im inclined to correct it. I suppose at some point in the future the tech people could be writing better tasks and user stories and then commenting to have ai update the code output or just going in and correcting it. Maybe then comments would indicate ai code vs user intervened code or such. Utlimately though until it can plan the code its only going to be a useful tool and can't really take over. Ill tell ya if ai could write code from an initiative the csuite wrote then we are at the singularity.

"Tech workers" is pretty broad.

Tech Support

There are support chatbots that exist today that act as a support feature for people who want to ask English-language questions rather than search for answers. Those were around even before LLMs, could work on even simpler principles. Having tier-1 support workers work off a flowchart is a thing, and you can definitely make a computer do that even without any learning capability at all. So they definitely can fill some amount of role. I don't know how far that will go, though. I think that there are probably going to be fundamental problems with novel or customer-specific issues, because a model just won't have been trained on it. I think that it's going to have a hard time synthesizing an answer from answers to multiple unrelated problems that it might have in its training corpus. So I'd say, yeah, to some degree, and we've successfully used expert systems and other forms of machine learning in the past to automate some basic stuff here. I don't think that this is going to be able to do the field as a whole.

Writing software

Can existing LLM systems write software? No. I don't think that they are an effective tool to pump out code. I also don't think that the current, "shallow" understanding that they have is amenable to doing so.

I think that the things that LLMs work well at is in producing stuff that is different, but appears to a human to be similar to other content. There are a variety of uses that that work, to varying degrees, for content consumed by humans.

But humans deal well with errors in what we see. The kinds of errors in AI-generated images aren't a big issue for us -- they just need to cue up our memories of things in our head. Programming languages are not very amenable to that. And I don't think that there's a very effective way to lower that rate.

I think that it might be possible to make use of an LLM-driven "warning" system when writing software; I'm not sure if someone has done something like that. Think of something that works the way a grammar checker does for natural language. Having a higher error rate is acceptable there. That might reduce the amount of labor required to write code, though I don't think that it'll replace it.

Maybe it's possible to look for common security errors to flag for a human by training a model to recognize those.

I also think that software development is probably one of the more-heavily-automated fields out there because, well, people who write software make systems to do things over and over. High-level programming languages rather than writing assembly, software libraries, revision control...all that was written to automate away parts of tasks. I think that in general, a lot of the low-hanging fruit has been taken.

Does that mean that I think that software cannot be written by AI? No. I am sure that AI can write software. But I don't think that the AI systems that we have today, or systems that are slightly tweaked, or systems that just have a larger model, or something along those lines, are going to be what takes over software development. I also think that the kind of hurdles that we'd need to clear to really fully write software from an AI require us to really get near an AI that can do anything that a human can do. I think that we will eventually get there, and when we get there, we'll see human labor in general be automated. But I don't think that OpenAI or Microsoft are a year away from that.

System and network administration

Again, I'm skeptical that interacting with computers is where LLMs are going to be the most-effective. Computers just aren't that tolerant of errors. Most of the things that I can think of that you could use an AI to do, like automated configuration management or something, already have some form of automated tools in that role.

Also, I think that obtaining training data for this corpus is going to be a pain. That is, I don't think that sysadmins are going to generally be okay with you logging what they're doing to try to build a training corpus, because in many cases, there's potential for leaks of sensitive information.

And a lot of data in that training corpus is not going to be very timeless. Like, watching someone troubleshoot a problem with a particular network card...I'm not sure how relevant that's going to be for later hardware.

Quality Assurance

This involves too many different things for me to make a guess. I think that there are maybe some tasks that some QA people do today that an LLM could do. Instead of using a fuzzer to throw input in for testing, maybe have an AI to predict what a human would do.

Maybe it's possible to build some kind of model mapping instructions to operations with a mouse pointer on a screen and then do something that could take English-language instructions to try to generate actions on that screen.

But I've also had QA people do one-off checks, or things that aren't done at mass scale, and those probably just aren't all that sensible to automate, AI or no. I've had them do tasks in the real world ("can you go open up the machine seeing failures and check what the label on that chip on the machine that's getting problems reads, because it's reporting the same part number in software"). I've written test plans for QA to run on things I've built, and had them say "this is ambiguous". My suspicion is that an LLM trained on what information is out there is going to have a hard time, without a deep understanding of a system, to be able to say "this is ambiguous".

Overall

There are other areas. But I think that any answer is probably "to some degree, depending upon what area of tech work, but mostly not, not with the kind of AI systems that exist today or with minor changes to existing systems".

I think that a better question than "can this be done with AI" is "how difficult is this job to do with AI". I mean, I think that eventually, pretty much any job could probably be done by an AI. But I think that some are a lot harder than others. In general, the ones that are more-amenable are, I think, those where one can get a good training corpus -- a lot of recorded data showing how to do the task correctly and incorrectly. I think that, at least using current approaches, tasks that are somewhat-tolerant of errors are better. For any form of automation, AI or no, tasks that need to be done repeatedly many times over are more-amenable to automation. Using current approaches, problems that can be solved by combining multiple things from a training corpus in simple ways, without a deep understanding, not needing context about the surrounding world or such, are more amenable to being done by AI.

Nope. In fact, it's actually generating more work for me, because managers are commiting their shitty generated code and then we have to debug and refactor it for productiuon. It would actually save time if they just made a ticket and let us write it traditionally.

But as long as they're wasting their own time, I'm not complaining.

I went to taco bell the other day and they had an AI taking orders in the drive thru, but it seemed like they had the same number of workers.

They also weren't happy I tried to mess with the ai.

Had a new hire try to do all his automation programming in python with an AI. It was horrifying.

Lists and lists and lists of if else statements they caught if a button errored but never caught if it did the right thing. 90% of their bug reports were directly due to their own code. Trivially provable.

Work keeps trying to tell us to use more AI but refuses to mention whether the training data is using company emails. If it is then a buttload of unlabeled non public data is getting fed into it. So only a matter of time until a "fun fact" from the AI turns into a nightmare.

Most of our stuff is in an obscure field with outdated code, so any coding assistance is not really that impressive.

There are lots of types of work in the tech space. The layoffs I seen have impacted sales and marketing (probably happens elsewhere too) because AI makes the day to day work efficient enough they don't need as many people.

Some things like image recognition, text classification, are way way easier using pretrained transformers.

As for generating code, I already used to spent a lot of time chasing bugs juniors made but can't figure out. The process of making such bugs has now been automated.

Well, some jobs are probably being replaced. Like, I can imagine someone being paid to describe in detail what's in a picture and writing it down would be replaced pretty quickly.

But if the article means programmers, devops, sysadmins etc., then hell no, there's no way the current iteration of AI can replace them and instead of spreading misinformation, the article authors should focus on real reasons the layoffs happen.

But that doesn't bring as many interactions as doom news of companies replacing us with a smart text predict software, does it?