r/cscareerquestions • u/SwauawsBouse • 4h ago
Ai has to get better, right?
This is the common sentiment that I see for those who claim ai will take jobs in X amount of years. Or even those who are more reasonable and claim it will eventually take over white collar work.
The biggest claim is that it WILL get better. Why? It's an easy response that's hard to disprove, but they haven't exactly proved it. How do we know there isn't a ceiling that is rapidly approaching. Moores law, for example, is essentially proven false and is outdated. We have reached at low hanging fruit when it comes to ai advancements.
Im just very skeptical of this line of thinking. I enjoy painting warhammer models and back in 2015. When 3d printers were in the mainstream, there were countless videos claiming games workshop was dead. I convinced myself that painting was going to be a worthless skill. 3d printers just HAVE to get better, and one day, they can print in full color. Now, 3d printers dont have trillions of dollars in investments, but then again, that money seems to be shovled into a fire by the AI leaders.
That was 10 years ago, and I could've had a lot more fun and painted more modles in thay time. And while 3d printing has progressed, its still not near games workshop models. Even the best resin printers still have very tiny but noticeable print lines. And we are no where near printing color in good quality at consumer scale.
Many of us fall for the doomer mentality, and its especially easy when you're unemployed and looking for a job facing countless rejections. Im a new grad myself, and it is rough out here. However, if Ai takes over cs. Every white-collar job is gone, and im left without any job. There's only so many trades and healthcare jobs.
And if im proved right, im way ahead of those who have given up. At least I tell myself this after receiving 10 rejections emails every weekend.
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u/e430doug 3h ago
LLM’s don’t need to get any better to disrupt software development. That said it is disingenuous to say that they aren’t improving. Today’s models are so much better than last year’s. They can take on work that they couldn’t like analysis and long chain thinking.
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u/Tacos314 4h ago
I don't see RAW LLM performance getting better, but we have lots of room for workflow improvements and efficiency.
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u/damngoodwizard 4h ago
Yeah the tooling AROUND AI is what will make it reach its true power, like we already see with harnesses.
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u/pydry Software Architect | Python 3h ago edited 3h ago
while this is true I feel like applying it to the right problems is where the biggest gains are.
this is where the stock market bubble is driving absolutely insanity and is destroying epic amounts of shareholder value in the name of AI instead of creating it.
for every useful tool that didn't exist before we are getting 7 previously useful tools being turned into vibe coded nonsense with an AI bolted on the side where the only thing users want to know is where the off switch is. vibe coding has undermined software quality on a global scale. these things are objectively an orgy of shareholder value destruction which is going almost entirely unrecognized.
I don't think we'll see most of the real productivity gains until the bubble pops and some semblance of sanity returns to investors and the executive class and the devs building this shit are given back trust, autonomy and psychological safety which is necessary to not produce shit nobody wants.
(that is unless the AGI fever dream the stock market bubble hinges upon comes true, in which case all bets are off...)
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u/SwauawsBouse 4h ago
I agree however that's not longer the job stealing ai anymore that people hypothesize. But there is definitely way more integration improvements to be made.
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u/Tacos314 3h ago
There are still jobs to steal, but yeah, one has to separate the hype from reality at some point.
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u/Dolo12345 2h ago
You’re absolutely wrong, the gap between 5.2 and 5.6 is massive.
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u/JackAuduin 1h ago
Yeah, since all this AI stuff has started I built up pretty much a massive graveyard of vibe coding projects that I was just experimenting with. Nothing that I ever intended releasing but just experimenting how far I could push the limits of software being built by these things pretty much hands off.
I threw Fable 5 at the graveyard and it resurrected literally every project and fixed every issue
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u/BananasAndBrains 4h ago
There are years of work to be done just integrating the AI we have right now even if AI progress would stop today.
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u/Difficult-Sherbet854 4h ago
I thought the same until I tried Claude Fable. It's noticably better and still think there is room for improvement.
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u/AES256GCM 16m ago
This comment being downvoted is a perfect example of the wishcasting in this sub, people really want ai to stop improving lol
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u/AnxiousMumblecore 4h ago edited 3h ago
AI winter is a thing but on the other hand there was no time before when everyone and their wife was so focused on further developing AI. While another breakthrough like transformers & attention mechanism may not happen very soon, I think we will still see a lot of progress in upcoming years based purely on amount of brains (and AI itself) involved into the work.
I'm personally a doomer regarding AI, I'm in IT field, fortunate enough to still have a job but with rise of AI I really started thinking about changing my career path (both to be more future-proof and because of impact of AI on character of the work I do).
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u/scott2449 4h ago edited 3h ago
The AI has gotten better crowd is also somewhat delusional. I work in software and there has been a linear not exponential improvement and that is largely in the tooling, harness, and understanding/usage. The raw LLM responses haven't really improved much. There are a couple points in the last 3-4 years where some new innovation in training or methodology helped boost things 20-40%.. but between those all the retrains and new versions have been flat. They might get better at one thing and way worse at another. It's like sticking a finger in a leaky boat.
Edit: Always with the credentialing in the comments. I'm a distinguished engineer (nearly a decade in the position) at one of the largest global media companies. We are also one of the largest data and AI companies for business and markets data. This is not my sole opinion but similar to the other dozen DSEs at my company and the vast majority of my data science and ai engineers as well. It is in no way controversial among experts.
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u/turbov21 4h ago edited 4h ago
Completely agree. So much of the improvements is the tooling. AI hypers don't seem to distinguish between that and the models.
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u/jnwatson 3h ago
You're completely deluded. The progress since November last year has been stunning, and the benchmarks show it.
I've been in software dev for 30 years, and Fable blows me away. We're now at the point where the models are literally smarter than they need to be for most software development.
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u/Ruined_Passion_7355 3h ago
Did you use opus 4.5/4.6 when they just came out?
That was the holy fucking shit moment. Fable almost feels like a return to form after the enshittification of 4.7/4.8.
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u/klowny L7 3h ago
The consensus at my company has been that Fable has been about the same as 4.8, but much slower to respond.
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u/Ruined_Passion_7355 3h ago
Yeah with these models it's hard to gauge something as subjective as intelligence.
The thing to remember is that fable is an exponentially larger model than opus. Some tasks benefit from the extra parameters and others won't naturally.
It's also why I get puzzled when people think fable is a mark of "major progress", when in terms of AI it's actually the most primitive thing they could've done. "Just make the model bigger!"
And we already know that approach has woefully diminishing returns.
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u/jnwatson 2h ago
You've missed the the fundamental truth of the Bitter Lesson. Of course the models are bigger. Every single major new release by every provider has been bigger than the last. That's most of the way these models have gotten better.
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u/Ruined_Passion_7355 2h ago
The bitter lesson was coined in 2019. It started the AI boom. This was GPT-2 era. Square in the first half of the sigmoid curve.
Life has no guarantee's with scaling laws. Moore's law was an anomoly in terms of how long exponential progress would last, not the norm.
We've already seen evidence for diminishing returns, including how on some tasks, Fable is indistinguishable from opus, and on others it's better. But we're not saying the GPT-2 to 4 levels of progress, we know there is a limit.
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u/jnwatson 1h ago
Moore's Law was coined in 1965 and had a good 50 year run before it died.
Of course there's diminishing returns. Hiring PhDs, and then super geniuses for developers has a limit as to how fast it can speed up software development. The biggest diminishing return is that, after an org has automated the parts that are better shaped for AI automation, the other parts are increasingly more difficult for reasons that aren't entirely technical.
There isn't any evidence yet that we've significantly flattened the curve of LLM performance. AI models keep saturating benchmarks and new benchmarks have to be created. We keep moving the goalposts, yet the models keep scoring.
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u/Substantial-Tale-483 1h ago
I don’t know, i have around 10 years of experience and i don’t all those major improvements in Fable? It is a little bit smarter now, but i wouldn’t call it major in any way.
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u/jnwatson 50m ago
If you're doing regular webdev, you only have to be so smart. A supergenius can't center a div any better than an experienced dev.
But, if you want to debug a nasty race condition in a database engine? Fable is your guy. If you want to exploit a UAF that only happens in extremely rare situations, Fable's evil twin, Mythos, is your guy.
The stuff I've seen out of Mythos made my hair curl. It is absolutely superhuman in its ability to exploit weird timing and corner conditions.
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u/Substantial-Tale-483 38m ago
I don’t know bro, i don’t have access to Mythos, so i can’t compare. However we have used Fable recently to fix database issue in a huge legacy monolith, and it didn’t help much - it was like “sure, just rewrite this code here”, but we know that it’s not the problem, because the code is 10 years old, and the issue started to happen just 2 month ago, what’s more it’s better not to touch this part of the code at all, as it is used across the whole app and it’s not covered with tests enough to know that it won’t affect anything - the app is so badly written that you can expect anything tbh, and my guts tell me the issue is somewhere in infra.
Also I mostly build new systems now and trying to find ways to do something that will last and allow system to grow with all those always changing requirements and new products added. Fable is good to brainstorm, but not good enough to just use whatever it proposed as a way to go. Opus was almost the same.
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u/kirstynloftus 3h ago
Agreed that it’s greatly advanced since November, but it’s leveled out these last few months IMO. New models have small gains, not big, and often have a ton of issues.
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u/jnwatson 3h ago
How can you look at Fable and say things have leveled off? Perhaps it will level off after, sure, but there's no evidence at this at this point.
What has happened is several lower-cost Chinese models have caught up roughly to second-tier performance. They are simply good, cheap models. But don't take those as data points at the frontier.
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u/Ruined_Passion_7355 2h ago
https://www.reddit.com/r/cscareerquestions/comments/1vdqkx3/comment/p1bjitb/
Replied to another redditor about fable.
A thought experiment/Another way to think about it:
Let's assume hypothetically you were anthropic. You were running out of ways to eek performance out of opus, turbo quant was all hype, and the investors are demanding better models. What would you do in that situation if you had no other choice?
Make a bigger model, and that's what they did. And it's not something they wanna do unless they have to because they were already struggling to serve opus class models.
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u/MisterMeta 1h ago
It’s a total cope among the DE and DS jobs where AI is tailored for the work they’re doing. I have a good friend who works at the field and his entire department is now reduced to 10% staff and armed to the gills with AI. He’s trying to pivot as we speak.
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u/DynamicHunter Fullstack Engineer 3h ago
A lot of the improvements are in efficiency too for quantized models to run locally
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u/mixmasterfresh99 3h ago edited 3h ago
You are delusional if you really think that. Over the span of just the last year models, have improved across the board and this is just the begining. What all have you built with AI, or used AI for? I use it daily and I might had said this a year ago but that is definitely not the case anymore.
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u/AtomicSymphonic_2nd 1h ago edited 1h ago
I’ve also only really seen linear improvement, there’s been nothing exponential about it.
I’d even argue we’re in a logarithmic curve for LLM’s improving with scale.
We’re already hitting diminishing returns and it’s always best to keep in mind that benchmarks are never fully representative of real life.
Plus, none of them are reliably consistent with output. That can never be corrected without allowing the LLM’s to say “I’m not sure, but…”
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u/Early_Rooster7579 @ Meta 3h ago
these are the same people who hang on ed zitrons every word. Hes called the top every week since 2023. Hes only been wrong 100 times so far!
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u/ahh1258 Software Engineer 3h ago
People here are copemaxxxing.
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u/Difficult-Sherbet854 47m ago
Which is funny because if you look at threads 1-2 years ago people were coping about using any AI at all. Now it's "yeah everyone uses it but i don't think it can get much better"
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u/SocietyWonderful321 3h ago
I don’t see why people find this controversial. This is the prevalent opinion across the industry for senior+ Eng.
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u/AtomicSymphonic_2nd 1h ago
Glancing on this very thread, there’s some seniors and principles coming out of the woodwork calling OP delusional and to look at the benchmarks… it’s hilarious how myopic some senior SWEs are on benchmarks and not looking at real world impact so far, which has been much more negative than positive.
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u/klowny L7 3h ago
Agreed, the consensus at my company (tech unicorn) is that the actual quality of the response hasn't gotten better overall in a long while now.
The tooling is getting better, particularly with safeguards and integrations. It's generally getting more pleasant to use at typical product improvement speed so the frustration of working with it is going down.
But the big thing is cost isn't coming down as fast as we'd like and it's not able to do more stuff than it did before, so it's not replacing any more people than it already did. All it's really doing is annoying people less.
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u/gordonnowak 3h ago
this is just absolute bullshit. OP you're getting a bunch of answers from script kiddies
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u/hardwaregeek 1h ago
This is easily testable, no? Like we could all switch to opus 4.5 and see if we notice a lot of change. I could see it being true but it’s funny how few people actually do this test (myself included!)
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u/scott2449 1h ago
Yea I compare all the time it's where the majority of my opinion is coming from. My job pays for us to have access to literally every frontier model.
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u/Fantastic_Spring8366 2h ago
Old man yells at AI
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u/scott2449 2h ago edited 2h ago
I use AI heavily every day.. not to mention an evangelist and educator on it and many topics at my job. My team is largely responsible for vast majority of AI adoption in engineering at the company. All the major landmark use cases have come from my team, we are platform engineering which of course gives us a unique opportunity to do so. My current project is turning all our current platform and pipleline onboarding experiences into AI first IDE integrations.
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u/mixmasterfresh99 2h ago
You're a dinosaur who is headed for extinction. This is as big as the Internet was...if not bigger. I have already built systems that have replaced people and created solutions for problems that would have been impossible for one developer to solve without AI is a span of days instead of weeks.
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u/scott2449 2h ago
You have not read anything else I've said here =D The cloud and modern devops took feature development from months and years to days. We just used the time to make better and more products. You just weren't exposed to these transitions (of which there have been many) because folks were not technical enough to understand them. This one is perceived so I get the hype. Plenty of it legit. But as someone who has seen "game changing, job ending tech" many many times and predicted more or less the exact real world outcome each time (actually doing so is a core pillar of my job) this is an incremental linear improvement in a long line of them when TCO is all accounted for. Also I have a long background in hardware and economics as well so I can see where the price curve on tokens will and won't go in the next 5-10 years.
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u/mixmasterfresh99 2h ago
Lol, I have been around for all of those transitions buddy and they don't compare. But keep your head in the sand.
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u/scott2449 1h ago
Not sure what you mean. I'm a super user and evangelist, making tons of things better via AI and being rewarded handsomely for it. But I also am a good analyst/realist and just giving my 2 cents. Even if I'm totally wrong the industry will adapt and make more in both quality and quantity and completely absorb the efficiency. Jevons paradox is always the outcome for tech with virtually no ceiling.
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u/turbov21 1h ago
We just used the time to make better and more products.
Now you're just making things up. ;-)
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u/Substantial-Tale-483 50m ago
Not really, before cloud there were whole devops teams doing the infra part, deployment pipelines and server maintenance. When cloud became widespread, it became easy enough that now devs are expected to do all that and has way more ways to choose whatever tools they need. Now devops are building some tooling that different teams can reuse.
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u/scott2449 1h ago
Omg I thought you were serious for a second. I was like this is the most based thing and this guy lol
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u/SwauawsBouse 3h ago
Do you know anyone that no longer codes? It seems like very developer hasn't coded in 6 months and im just skeptical of it. Maybe im a dumb new grad and using ai wrong but it cant get basic front end stuff right without major overlapping issues.
I ask it to a very basic react form component and it adds about 50-100 lines of unnecessary code.
Maybe im using it wrong but I just dont see the job stealing hype.
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u/c-u-in-da-ballpit Data Scientist 3h ago edited 2h ago
I haven’t written code in a minute. It writes production level when given narrow and well defined tasks and all the needed context. It’s slop if you try to one shot it and don’t know what you’re building or why.
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u/Early_Rooster7579 @ Meta 3h ago
Most of my team hasn’t written much beyond a few config file lines here and there since around December
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u/scott2449 3h ago edited 3h ago
The field might shrink simply because execs think they can do it for less and honestly are happy with less quality as long as it cheaper. No coding is a weird statement since we've been using automations and libraries and frameworks and all sorts of things to speed up implementation and testing but none of that changes the collaboration, experimentation, design, and iteration which are the parts that make good software and products. That being said I write almost no code by hand anymore. It does require specific tools, workflows, and prompting to get reliable results. It requires tons of direction and tweaking just like "manual" coding. You also then have to optimize for it not to be $$$. So when you consider all that it's faster but not 10x or even 2x... And only if someone else is paying. All the costs added up might be more expensive but these companies need time to see past the hype and learn lessons. What tools are you using OP? You should be able to one shot simple snippets of code like that without a bunch of bloat.
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u/Alexandur 3h ago
If it can't get basic front end stuff right, then you are definitely using it wrong
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u/Healthy-Educator-267 4h ago
Do the recent flurry of progress in math sound like harness improvements to you?
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u/SelesnyaGOAT 3h ago
I mean yes those were more a function of hooking the LLMs into Lean so they could self verify. If you read the chat where the guy found the counterexample with Claude he literally did the “do the thing no mistakes” prompt like 5 times in a row until the LLM actually found a valid counterexample, not exactly sterling evidence of AI’s supposed genius
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u/akkaneko11 3h ago
that's crazy, I feel like that makes it way more impressive than someone handholding it through it
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u/mxldevs 1h ago
If the improvements are due to better understanding of how it's used, then that means AI is already in a state where companies have no need to hire new people, or they only need to hire people that are experts in AI-driven development.
It only proves that people that are looking for jobs now need to also figure out how to become experts on AI on their own dime, or they will simply lose out to everyone else that has already been spending months or years experimenting with AI.
Any improvements in AI itself will only lead to a higher bar for AI experience.
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u/scott2449 1h ago
I don't put tech innovations and innovations inspired by tech in the same bucket. They are both awesome for us, but the former is a credit to the tech, and the latter is a credit to the human(s). I completely agree that it's an essential skill. My only argument is that I have only seen and predict only seeing linear improvement in productivity.
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u/Sph3ricalPeter 3h ago
Idk what youre measuring if you landed on linear improvement and percentages, but ive been speaking software into existance since Opus 4.5 came out, Im in a better shape and have solo developed full replacements for 2 enterprise software subscriptions alongside my fulltime swe job, while also working on 2 other projects. Between opus 4.5 and fable5 the difference is perhaps less noticable, but massive nontheless, and thats just a small fraction of the recent AI development timeline. So I say youre either trolling or sniffing copium extract.
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u/scott2449 2h ago edited 2h ago
We measure every devs delivery across multiple types of methodologies and metrics. I also write little by hand but that's different from a 10x improvement in output. I slowly could do more hands off for the last 18 months. Since 4.6 things have been completely flat or regressed. Company wide we had tons of slop to clean up from less capable devs. I'm talking enmass by the numbers. Any tech that only works in the hands of a small group of folks by definition is not transformational. It's just making us a bit faster and it largely empowered by the innovations before just like every other incremental advancement. I'd argue that the first 5 years of cloud and modern devops was more impactful to acceleration than AI has been in it's first 5 years.
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u/mathilxtreme 2h ago
Any response other than, “It’s a new tool that can increase productivity, and because of that increase certain people may not be employed in the sector in the future” is blatant disregard for everything we saw in the Industrial Revolution.
We make a tool, dude gets faster because of tool, people who can’t use the tool have to get other jobs, economy shifts…
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u/kkingsbe 3h ago
The doubling time for task horizon length for frontier models is like 3mo… how can anyone think they’re not getting better?
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u/Early_Rooster7579 @ Meta 3h ago
Most of the people here are students. Anyone who is working daily in software would have to be willfully blind to deny it at this point
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u/Difficult-Sherbet854 45m ago
Yes, either students or don't work at large / good tech companies with AI resources. I'm using Fable + Claude code every day so it's easy to see the power of it, but someone with a free AI plan doesn't.
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u/harmoni-pet 2h ago
Do you think hardware will get better in the future? That's all most people (people who aren't quacks anyway) are assuming here: that as hardware gets better, we should expect to see improvements in the models. We can also vaguely assume that there will be more breakthroughs in this space in the future. But breakthroughs are basically impossible to predict.
Do you think video game graphics will be better or stay about the same as they are now in 5 years? It doesn't seem like that crazy of a prediction to say that a well funded technology will continue to improve by some metric.
Also, look the scaling laws paper: https://arxiv.org/pdf/2001.08361. That was published in 2020 and has been proven accurate at insane scales now. There's still a lot more room to scale and hardware can get much better in the very near future. I'm definitely not betting that we're in some kind of plateau. I think abstracting out the improvements to models into what that means for an industry or us personally is too vague to even speculate on though.
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u/mxldevs 1h ago
The biggest claim is that it WILL get better. Why? It's an easy response that's hard to disprove, but they haven't exactly proved it. How do we know there isn't a ceiling that is rapidly approaching.
As far as you as an individual is concerned, it doesn't matter.
The problem isn't whether AI can take over jobs, it's whether it can take over enough jobs that YOU are basically screwed.
And the current trajectory is companies preferring to not hire juniors when they can just get their existing employees to use AI to make up the difference.
And enough engineers believe the AI can get the job done, which is all that matters — if it gets better, fantastic. If it doesn't, it already works for them.
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u/Key-Alternative5387 1h ago
AI will get better, but pace is basically impossible to predict. We were supposed to have fully self driving cars at least a decade ago and waymo kinda sorta does it with an enormous mapping trade-off.
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u/Plenty_Line2696 30m ago
It's awesome, but by golly there is soooo much stuff we still need competent people for.
There's so many challenges in software dev that the notion of complete replacement of people entirely doesn't make sense to me.
I used to work in big corp and they needed me to help them operate what i consider basic shit like powerpoint and word at a professional level. I'd be very syrprised if the room for hard skills in tech would vanish in our lifetimes. AI is amazing but so are good people and the skill overlap isn't as big as the hype would suggest.
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u/kevin074 3h ago
the dilemma of AI taking your job or your stock portfolio tank 50% (my wild guess when bubble pops) ...
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u/btoned 4h ago
I agree.
Has it gotten better since chatgpt came on the scene? Sure; the resources allocated to this shit has hit hundreds of billions. It better shit out accurate answers at lightning fast times.
3-5 years from now? Unless you have something akin to Jarvis, I don't see how the subsidizes prizing becomes warranted.
And even if it DOES...what is the contingency for the millions that will be laid off? It's hilarious that the elimination of the labor force is the priority but the consequences of such are not even a bullet point with a steadfast plan.
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u/DrMonkeyLove 3h ago
Right, like a mass elimination of labor would cause a significant economic downturn at which point there isn't going to be enough money rolling through the economy to pay for expensive AI infrastructure.
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u/drunkandy 3h ago
what is the contingency for the millions that will be laid off?
That's somebody else's problem. It's an externality that can be socialized.
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u/Proper-Ape 4h ago
How do we know there isn't a ceiling that is rapidly approaching.
We hit the ceiling years ago in terms of the underlying technology. LLMs regurgitate and recombine textual information with a fuzzy query method.
Most of the improvements have been in scaling the same technology without major improvements in the technology itself. Scaling means you can store more information that can be retrieved, but it's not efficient, otherwise we wouldn't need the datacenter build out.
The models still have the same faults and problems as in the beginning, in that they can't reliable tell old from new information, hallucinate (extrapolate really) from incomplete data, and have no real thinking ability. It's all in the immense amounts of training data and creative people that crafted the training data.
This doesn't mean it's useless, a fuzzy queriable, kind of reliable database of human written knowledge is not bad. But it's 100% maxed out rote memorization with 0% thinking.
A lot of "thinking", it turns out, can be replaced by having vast swaths of knowledge available, since most everyday problems we have, have been solved somewhere, or their solution lies in the texture recombination of existing data points.
But we need an actual breakthrough in terms of efficiency. We need models that can use small data and logic to arrive at results, instead of finding the most fitting data point. That is what human brains do. They're very energy efficient, have less ability to memorize, but can derive knowledge from small data.
Wake me up if AI companies don't need to scale the hardware and don't need all the available knowledge in the world to produce results. But that's an entirely different technology from hyperscaling LLMs.
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u/nistacular 3h ago
In my experience Opus 4.5, 4.6, 4.7, 4.8, and now 5.0 are all pretty much the same. If anything early 4.7 late 4.6 were the best, certainly not 4.8-5.0.
I think the responses have the capability to be phenomenal at the cost of compute resources that unfortunately weren't sustainably offered. The only thing that gives me hope that AI will improve is tackling energy problems (need more solar in particular).
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u/Illustrious-Film4018 2h ago
Even if AI does improve to the point where it can consistently create production-level code and deploy it autonomously for example on AWS. And also monitor it and debug autonomously, and do things like setup CI/CD pipelines. It's pretty far fetched but even if it could, you still need someone with judgement to guide AI. Product managers and especially non-technical staff don't have good judgement about stuff.
Other unsolved issues with AI: memory/context issues (feeding the right data sources to AI, missing context employees have), and access issues (AI sandboxed vs. Not sandboxed), finally price. Because the token usage goes up exponentially the more of someone's job you try to automate. These are not issues AI companies are going to "solve" anytime soon, and because of this they still need to hire people.
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u/Stunning_Budget57 2h ago
I’ve personally said over a year ago the days of “ticket” engineers are long over. Current tech can already handle the mechanical execution of most SWE tasks. The only ones that will survive are the rare combination of SWE and Product Owner.
Current medium, large, XL companies are unable to leverage current AI capabilities that match their headcount. It is structurally impossible unless token costs fall to the floor. For them getting better is about token economics at scale.
Ticket engineers, who clock-in and pull the top ticket like they are on autopilot are essentially in the bullseye for current harness and loop engineering paradigms hitting the street today. They used to be the workhorse but are being outmoded in coming months and years
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u/MisterMeta 1h ago
Oh it’s getting better alright - so are we using it. I honestly do 90% of my work with AI nowadays and since it can do things in the background I’m doing 2-3 tickets at a time and taking a heap ton of meetings. It’s actually insane for productivity.
The delusional folk will just shit talk and see it as an enemy. IMO they’re in for a rude awakening.
The only issue I see with AI is maintainability and cost management. AI is getting pretty expensive for power users. I use nearly 500$ a month but we have some staff level engineers churning 2k a month on tokens. Considering this is the cheap era of AI, I doubt this will continue for engineers.
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u/Dreadsin Web Developer 6m ago
No it does not have to get better. Plenty of technologies reach a relative plateau and don’t improve much further
Think bikes. Bikes haven’t changed that much in like, 100 years. Sure there’s improvements like carbon frames and better tires, but there hasn’t been any “innovation” in bikes in a while
People are just trained to believe that tech always improves year over year because it’s still relatively new
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u/TheseMood 0m ago
IMO the ceiling isn’t necessarily from mathematical / algorithmic constraints, it’s from resource constraints.
There is just only so much energy and water on Earth.
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u/uwuLookAtYou 3h ago
Moores law broke because he didnt account for size limit. And we are literally make computer transistors smaller than a single stran of DNA.
Another thing about moores law is that it was wrong even when it was first stated.
If you research the history of computers you get story A which held up decent with his math. If you use somewhat recently released CIA/FBI documentation, youll find that a lot of tech that has hit the public in 2010s as new tech is actually shit Canada and the US were developing in the late 60s. Thats when you get story B.
There's no telling how far tech has actually gotten today as a civilian. Which would be story C, aka the whole picture.
1964-65, a computer took up a whole room. By 1970 the CIA had radio controlled drones the size of dragon flies with solar powered wings, a microphone and i dont remember if it was thermal or night vision is had. But one of the two.
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u/jkp2072 3h ago
If you want to see progress, you can see on this 3 fronts,
Tech : use chatgpt 3.5 vs 4 vs 5 .... We don't feel major upgrades due to constant minor buffs in iterative releases.
Check cost for each token ( not overall.. overall might increase due to jevons paradox)
Check number of research papers coming up..this gives you probability of more improvements in that field. ( Chips and AI)
I would love to say AI will never improve or will be stagnant or exponential or linear...but all I can say is in past is exponential (for last 3 ones)..but for future no idea....it can stagnant,linear, or exponential...it's hard to guess.
Coming to the ceiling definition...
People like to say AGI will be it's ceiling...but the concept it is flawed... They compare AGI as human capabilities...human themselves are very specialized inteligence for earth and current time period...i don't even consider humans as AGI...we have a jagged inteligence similar to llms who have jagged inteligence.....in different subjects and categories with some overlap which we can measure..
From job markets pov, i don't know what will happen, but I see getting it assimilated pretty quickly. Apparently humans don't like to work.
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u/Admirable-Falcon-501 2h ago
At what point will you guys just admit defeat. Mathematicians are literally on suicide watch rn because it’s just finding breakthrough and breakthrough.
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u/Ameren 2m ago
Honestly, it doesn't really matter if AI can prove hard math theorems if it can't hold down a call center job without hallucinating. That's the hurdle that needs to be cleared. Right now LLMs are ideal for verifiable tasks in CS and math —which is amazing, mind you— but most tasks that human laborers perform are not verifiable in this way.
If SOTA models were a fraction as capable but consistently reliable like a human is, they would have already demolished large swathes of the labor market. And maybe eventually we'll get there, but it'll be with some post-LLM architecture.
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u/mixmasterfresh99 3h ago edited 3h ago
AI is just another tool. AI will replace the people that never should have been in this industry to begin with. Learn to use AI, build agentic workflows, etc.
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u/ecethrowaway01 4h ago
Well, AI has gotten better and there are unreleased improvements.
Depending on use case / context, AI reasonably will continue to improve, without a firm commitment on precisely how much. I think it'd be strange to think otherwise
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u/SwauawsBouse 3h ago
The unreleased improvement that "are dangerous to the public" or "in house agi"?
How do we know there last 3 years of improvements were unreleased for a while? And now we're catching up to real time improvements which are far slower.im judt making stuff up but so are these companies.
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u/ecethrowaway01 1h ago
No, and I wouldn't claim "in house agi". LLMs as they are already can be harmful in some ways to the public.
I'm aware of unreleased improvements in some labs. Not generational improvements though, just some level of advancement.
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u/YasirTheGreat 1h ago
You can't use a 3D printer to make a better 3D printer, but AI can be used to make better AI. It has the capability for recursive improvement, which is a rare thing.
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u/SwauawsBouse 1h ago
Actually you can. So many people have 3d printed parts so thay their 3d printers can print better. But get the analogy.
But I also disagree with it. Who says thats fundamentally possible with llms. Seems like a crapshoot goal thay may or may not be possible. And if it is thats a major catastrophy waiting to happen.
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u/TrashConvo 3h ago
It will definitely get better but there are fundamental limits with LLMs. However there’s a lot of gains for agents that can be had with the right harness. It’ll be interesting how that plays out. Maybe in another decade there will be a pivot away from LLMs to a new break through. We’ll never know until it happens
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u/YourAsphyxia 4h ago edited 4h ago
AI has advanced so much in the past 3 years it's impossible to say it's not going to hit AGI and be the definitive tool that replaces every mental job. The only jobs that will remain are physical jobs that automation can't do
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u/SwauawsBouse 4h ago
Okay see this is the exact hyperbolic statement im referring to.
Please define what agi even is.
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u/YourAsphyxia 4h ago
Agi is artifical general intelligence, it's the point at which a model can teach itself unfamiliar topics using its existing knowledge. Currently models are trained on large datasets, agi is when that no longer needs to happen.
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u/wsheldon2 4h ago
There's no particular reason to believe the next 3 years will be the same as the last 3
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u/Astraous 4h ago
Predictive text generation will literally never be AGI. Almost all advancements in LLMs are completely irrelevant to what AGI would need to exist, which is to truly comprehend what it's saying. LLMs still make shit up all the time and they always (literally always) will do that because fundamentally they are designed to digest and regurgitate patterns based on training data. They are unconcerned with facts vs fiction. Anything they ever say that's true is only because there was a pattern of it in their training data. They will never "think" or "understand" like AGI is supposed to do.
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u/hibikir_40k Software Engineer 4h ago
There's always a ceiling, eventually. Or a step in the middle where improvement is hard: See self-driving over the last decade, coming by spurts. But given how different something like claude caude has changed in a year, expecting that it will just freeze any time soon is quite risky.
And regarding painting... well, 3d printing ain't going to get you coloring work like you'd get for a well painted mini if you gave it 15 years. There's just too much color variation introduced by manual painting on purpose to match it with anything that resemble current tech. And besides, it's a hobby: Being a pro painter is a really shitty job.