I’ll take “things business people dont understand” for 100$.
No one hires software engineers to code. You’re hired to solve problems. All of this AI bullshit has 0 capability to solve your problems, because it can only spit out what it’s already stolen from seen somewhere else
I’m at the point where what I work on requires such a depth of knowledge that I just manage my own projects. Doesn’t help that my work’s PM team consistently brings in new hires only to toss them on the difficult projects no one else is willing to take. They see a project is doomed to fail so they put their least skilled and newest person on it so the seniors don’t suffer any failures.
Simplifying things to a level that is understandable for the PMs just leads to overlooked footguns. Trying to explain a small subset of the footguns just leads to them wildly misinterpreting what is going on, causing more work for me to sort out what terrible misconceptions they’ve blasted out to everyone else.
If you can’t actually be a reliable force multiplier, or even someone I can rely on to get accurate information from other teams, just get out of my way please.
That’d be an exciting world, since it’d massively increase access to software.
I am also very dubious about that claim.
In the long run, I do think that AI can legitimately handle a great deal of what humans do today. It’s something to think about, plan for, sure.
I do not think that anything we have today is remotely near being on the brink of the kind of technical threshold required to do that, and I think that even in a world where that was true, that it’d probably take more than 2 years to transition most of the industry.
I am enthusiastic about AI’s potential. I think that there is also – partly because we have a fair number of unknowns unknowns, and partly because people have a strong incentive to oversell the particular AI thing that they personally are involved with to investors and the like – a tendency to be overly-optimistic about the near-term potential.
I have another comment a while back talking about why I’m skeptical that the process of translating human-language requirements to machine-language instructions is going to be as amenable as translating human-language to human-consumable output. The gist, though, is that:
Humans rely on stuff that “looks to us like” what’s going on in the real world to cue our brain to construct something. That’s something where the kind of synthesis that people are doing with latent diffusion software works well. An image that’s about 80% “accurate” works well enough for us; the lighting being a little odd or maybe an extra toe or something is something that we can miss. Ditto for natural-language stuff. But machine language doesn’t work like that. A CPU requires a very specific set of instructions. If 1% is “off”, a software package isn’t going to work at all.
The process of programming involves incorporating knowledge about the real world with a set of requirements, because those requirements are in-and-of-themselves usually incomplete. I don’t think that there’s a great way to fill in those holes without having that deep knowledge of the world. This “deep knowledge and understanding of the world” is the hard stuff to do for AI. If we could do that, that’s the kind of stuff that would let us create a general artificial intelligence that could do what a human does in general. Stable Diffusion’s “understanding” of the world is limited to statistical properties of a set of 2D images; for that application, I think that we can create a very limited AI that can still produce useful output in a number of areas, which is why, in 2024, without producing an AI capable of performing generalized human tasks, we can still get some useful output from the thing. I don’t think that there’s likely a similar shortcut for much by way of programming. And hell, even for graphic arts, there’s a lot of things that this approach just doesn’t work for. I gave an example earlier in a discussion where I said “try and produce a page out of a comic book using stuff like Stable Diffusion”. It’s not really practical today; Stable Diffusion isn’t building up a 3D mental model of the world, designing an entity that stably persists from image to image, and then rendering that. It doesn’t know how it’s reasonable for objects and the like to interact. I think that to reach that point, you’re going to have to have a much-more-sophisticated understanding of the world, something that looks a lot more like what a human’s looks like.
The kind of stuff that we have today may be a component of such an AI system. But I don’t think that the answer here is going to be “take existing latent diffusion software and throw a lot of hardware at it”. I think that there’s going to have to be some significant technical breakthroughs that have not happened yet, and that we’re probably going to spend some time heading down dead-end approaches before we get to that. There’s probably going to be a lot of hard R&D before we get there, and that’s going to take time.
If you go forward 12 months the AI bubble will have burst. If not sooner.
Most companies who bought into the hype are now (or will be soon) realizing it’s nowhere near the ROI they hoped for, that the projects they’ve been financing are not working out, that forcing their people to use Copilot did not bring significant efficiency gains, and more and more are realizing they’ve been exchanging private and/or confidential data with Microsoft and boy there’s a shitstorm gathering on that front.
The most successful ML in-house projects I’ve seen took at least 3 times as long than initially projected to become usable, and the results were underwhelming.
You have to keep in mind that most of the corporate ML undertakings are fundamentally flawed because they don’t use ML specialists. They use eager beavers who are enthusiastic about ML and entirely self-taught and will move on in 1 year and want to have “AI” on their resume when they leave.
Meanwhile, any software architect worth their salt will diplomatically avoid to give you any clear estimate for anything having to do with ML – because it’s basically a black box full of hopes and dreams. They’ll happily give you estimates and build infrastructure around the box but refuse to touch the actual thing with a ten foot pole.
There aren’t enough AI specialists. More are being created by picking up these projects.
The problem is that AI is too hyped and people are trying to solve things it probably can’t solve. The projects I have seen work are basically fancy data ingress/parsing/summarisation apps. That’s where the current AI tech can really shine.
I seem to recall about 13 years ago when “the cloud” was going to put everyone in IT Ops out of a job. At least according to people who have no idea what the IT department actually does.
“The cloud” certainly had an impact but the one thing it definitely did NOT do was send every system and network admin to the unemployment office. If anything it increased the demand for those kinds of jobs.
I remain unconcerned about my future career prospects.
Yes… because there will be users who will always refuse to fix their own computer issues. Even if there’s an easy solution at their fingertips. Many don’t even try to reboot. They just tell IT to fix it… then go get coffee for a half hour.
As software developer I am not scared that A.I will take away our jobs. What I am scared is that at that point A.I good enough to do most jobs out there.
All it really needs to do is replace large chunk of the service industry to wreck massive havock in our society.
If enshitification isn’t stopped, the job market could devolve to the point everyone that isn’t an “elite” will be living in a medival-like society and the only way to get food is by using a barter system to trade with other destitute poor people. The second hyperinflation hits, the rich and the poor will practically be living in different worlds. Learn either a medival skill or a skill that would be beneficial in such a society. I’m doing machining and blacksmithing. Might start dabbling in chemistry too. If I can’t be successful in modern society maybe I can be highly skilled and successful in whatever secondhand society emerges.
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
<span style="color:#323232;">def main():
</span><span style="color:#323232;"> # Check if the correct number of arguments are provided
</span><span style="color:#323232;"> if len(sys.argv) != 2:
</span><span style="color:#323232;"> print("Usage: python script.py <PopScienceBS>")
</span><span style="color:#323232;"> sys.exit(1)
</span><span style="color:#323232;"> # Get the input from the command line
</span><span style="color:#323232;"> PopScienceBS = sys.argv[1]
</span><span style="color:#323232;"> # Assign the input variable to the output variable
</span><span style="color:#323232;"> LineGoUp = PopScienceBS
</span><span style="color:#323232;"> # Print the output
</span><span style="color:#323232;"> print(f"Line Go Up if we do: {LineGoUp}")
</span><span style="color:#323232;">if __name__ == "__main__":
</span><span style="color:#323232;"> main()
</span>
It’s the same claim when tools like Integromat, WayScript, PureData, vvvv and other VPLs (Visual Programming Languages) started to get some hype. I once worked for a company that strongly believed they’d “retire the need for coding”, and my ex-boss was so confident and happy about that… Although VPLs were a practical thing, time is the ruler of truth, and for every dev-related job vacancy I see, they ask some programming language, the written ones (JS, PHP, Python, Ruby, Lua, and so on).
Because if you look closely, deep inside, voila, there’s code in anything that is claimed to be no-code! Wow, could anyone imagine that? 🤯 /sarcasm
It’s still code. What makes scratch special is that it structurally rules out syntax errors while still looking quite like ordinary code. Node editors – I have a love and hate relationship with them. When you’re in e.g. Blender throwing together a shader it’s very very nice to have easy visualisation of literally everything, but then you know you want to compute abs(a) + sin(b) + c^2 and yep that’s five nodes right there because apparently even the possibility to type in a formula is too confusing for artists. Never mind that Blender allows you to input formulas (without variables though) into any field that accepts a number.
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.
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.
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
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.
I left my job in fast food to go to school for tech because it seemed like the thing to do and I wanted to have a good life and be able to afford stuff. So I ruined my life getting a piece of paper only for them to enshittify things to oblivion and destroy the job market to the point it’s fast food or retail only again. I suppose getting a masters in something is the logical next step but at a certain point a scam’s a scam and I’m not digging a deeper hole.
There are already automated kiosks selling Pizza here and most fast food places already allow people to order using their phone or self-service kiosks.
Delivery is also quickly getting automated with small delivery robots that can likely be remote controlled if they get stuck.
While LLMs cannot reason they can imitate which can be combined with more traditional A.I like utility A.I that makes decisions based on a scoring system. I am guessing LLMs will just be used to make A.I systems talk and execute actions while the actual “inteligence” will be handled through more traditional methods.
Look, if you go back to fast food after getting a B.S. because some disconnected CEO said that programmers aren’t going to exist in a couple years, you’re not digging a hole, you’re jumping head first into it.
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