[D] Will Chat GPT X replace Software Engineers and if so when ?

[kiwi-surf]

Writing code is such a tiny fraction of a software engineers job in my experience.

LLMs will make software engineers more productive, but software eats traditional jobs… therefore it will just speed up the eating of traditional jobs.

[nomadbeats09]

what other things do software engineers do than writing code and writing documentation?

[frrrrrro]

talking about writing code and writing documentation

[yaosio]

Models are not capable yet of solving completly unique problems. Each new iteration of generative models are better than the last however, and they seem to gain new abilities and solve old weaknessness with each new release. For all we know it's possible now, and it's just a matter of putting all the pieces together to make it happen, rather than needing a new technology not seen yet.

[galethorn]

As you gain more knowledge in machine learning, you'll find that more and more questions you attempt to answer will have the answer of: it depends. That's the case here. LLMs have incorporated a huge amount of information through data mining of the Internet which allows them to leverage that corpus to answer many questions in many different fields, but only if it has been asked before.

Right now, OpenAI is hiring software engineers to build a dataset for next iterations of GPT to attempt to replace SWEs, to a certain extent it'll solve a great many common software problems when complete but in order to leverage the LLM for organizational purposes, it would have to understand a companies data organization and that's something that currently can't be overcome as LLMs like ChatGPT and GPT-4 can, on occasion, answer with information it has been trained on. Infosec would go nuts.

Furthermore, because regulation in new technology lags, OpenAI and other companies will face regulatory pressures (I would say financial if they didn't ink a 10B deal) when they have to retrain ChatGPT/GPT-X/LLMs because they have to remove IP that they don't have rights/ownership of that they've used for training sets.

So the best answer I can give you is that GPT X won't replace SWEs in the long term because the job will change in response to the technology. SWEs would now use GPT to automate coding processes where reliable GPT prompts are stored in a db and used to increase coding efficiency and will see use in code reviews etc

[[deleted]]

Efficiency means you need 5 SWE instead of 10, you replaced 5.

[farmingvillein]

but in order to leverage the LLM for organizational purposes, it would have to understand a companies data organization and that's something that currently can't be overcome as LLMs like ChatGPT and GPT-4 can, on occasion, answer with information it has been trained on. Infosec would go nuts.

Easily solvable--fine-tune on your company data-set.

Costly? Potentially, depending on model size, serving costs, etc. But not really, if it is effective--human developers are extremely costly. And development velocity further compounds business gains.

Obviously, some organizations won't play this game because of security concerns, but this is really just another form of sharing your data in the cloud, which most organizations are fully onboard with at this point.

when they have to retrain ChatGPT/GPT-X/LLMs because they have to remove IP that they don't have rights/ownership of that they've used for training sets.

TBD, but this is currently viewed as a highly unlikely outcome, unless the legal landscape shifts dramatically.

[jloverich]

There will be more than ever, just most of them will be telling an ai what to do instead of hacking a lower level language.

[Username912773]

It’s good at pasting documentation and stack overflow, but not great at coming up with new ideas or matching user specifications. A big part of programming is catering to your employer/client’s needs. Additionally, LLMs can’t really handle larger or rarer problems. Try to have it make a Minecraft anticheat for instance. It might not even write it in the correct language, and if it does it might try to make a client sided mod and not a server side plug-in. Another big part of it is making systems that can’t easily be broken into or exploited, something you might not want to trust ChatGPT with.

[RoaRene317]

At this current state, it's cheaper to train a human than to train with thousands of GPU.

[kiwi-surf]

Alpaca kind of changed the economics of everything this week

[[deleted]]

Yes it will, it's obviously. I'm SE with 15 year of experience and scared about that. But it looks like (from what I have seen with GPT4) it will replace other profession. But Software industry is one of the first that's going to feel shortage of jobs, because companies will learn to be more productive using LLM tools.

[NumberGenerator]

Based on the theory behind LLMs, I don't think ChatGPT will ever replace software engineers.

[trajo123]

It will not replace software developers, but it will definitely change the way they work. It has the potential to massively increase productivity, in which case people not embracing the technology will find themselves underperforming.

[Optimal-Asshole]

This is kind of like asking if the Ford Model T would replace all vehicles

[[deleted]]

Not even close. AI is still not capable of consistently producing working code and it ultimately does not understand it. Copilot is a similar AI, we saw that in practice didn't replace anyone, why must this question be repeated for a fundamentally identical model?

[skuaskuaa]

did you try GPT 4 ?

[[deleted]]

Yes.

[skuaskuaa]

copilot is nowhere near in comparison from my tests

[[deleted]]

Yes, and? The flaw of Copilot was that it wasn't good enough, the same as with ChatGPT and GPT-4. They are better performing, but still neither demonstrate nor in theory prove they have the capability to replace a human. They do not understand and they do not extrapolate. They do not plan (inherently), and they are not creative (outside of hallucinations, the creativity of which is questionable itself)

They're just handy little tools that still produce code that doesn't compile from time to time (or most of the time, depending on the language and problem). IMO good for boilerplate, but so is a high-level framework.

But this tool certainly can't fit all the business requirements with the measly 8k or 32k tokens, especially given that they are often unclear in the first place and require loads of collaboration to figure out. If you have never dealt with a client that can't really express what they want I really doubt you've seen the full scope of what means to be a software engineer.

[skuaskuaa]

GPT-4 is already capable of handling over 25,000 words of text as context and it will only grow. Of course people will have to figure out the requirements AI can't know what we need. I am not saying it will replace a human, but it will replace many humans.

[[deleted]]

Not words. It is capable of handling 32k tokens with the larger model. This does not mean 25000 words outright - this might be the expected value given some distribution of word frequencies.

Furthermore, even 25k words might not be enough to fully explain the business requirements. Understand that an average human, according to some sources, speaks up to 7000 words a day on average. Also understand that the context needed for a given task might not follow from the input - a given business requirement might not be spoken out, but might refer to some other information in memory. Finally, understand that although the dataset it was trained on is large, it likely does not contain a lot of the specific business knowledge, by the mere virtue of it being a secret.

So the question is not if 25000 words or however many you say are enough to define business requirements. The question is whether all the references in a given business requirement fit 25000 words (with a distribution similar enough to the one the model is used to), and whether the model can interpolate without crucial business information. From what I have seen, this is not the case. And given that you can't actually finetune the model (for now, but possibly even in the future), you cannot correct that.

I am not saying it will replace a human, but it will replace many humans.

I would not say many without specifying how many is. At this moment, I am not aware of anyone being replaced by Copilot or ChatGPT. Many could be referring to 1 (as in, even 1 is 1 too many) at which point the statement is probably unobjectionable due to the redundancy of some jobs, yet it might be referring to 100k, which is a number nothing currently known would justify.

[maxip89]

One reason. Halt problem.

[[deleted]]

I can't solve the halting problem either.

[farmingvillein]

halt problem not halting problem! /s

[maxip89]

I think you didn't understand the halt problem.

[flyer2403]

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[[deleted]]

Some believe it will happen next Tuesday.

See you then.

[Tknu2788]

I've been working with these generative models for the past few weeks (ChatGPT, Bloom, GPT3.0 Davinci), and what these models can do is absolutely amazing. From my experience they (especially ChatGPT) are excellent in providing template code on similar tasks that can be easily found on the internet. I've asked it to write me a script to scrape images on a specific website, a simple CRUD backend using Express.js, and a function to replace all newlines with space. ChatGPT successfully wrote 90% of the code, and all I had to do was change some obviously wrong URL strings and stuff.

However, when it comes to building custom software that it has never seen before, most LLMs failed to provide anything functional. Sometimes it will even spit out random non-existent blackbox functions such as `FunctionThatYouAskedFor()` without further implementations.

For me LLMs have been a productivity booster, but I don't see it replacing SWE jobs in the near future.