I have no idea what to specialize in, what skills I should master, or where I should be spending my time to build a successful career.
Seems like we’re headed toward a world where you automate someone else’s job or be automated yourself.
It's not encouraging from the point of view of studying hard but the evolution of work the past 40 years seems to show that your field probably won't be your field quite exactly in just a few years. Not because your field will have been made irrelevant but because you will have moved on. Most likely that will be fine, you will learn more as you go, hopefully moving from one relevant job to the next very different but still relevant job. Or straight out of school you will work in very multi-disciplinary jobs anyway where it will seem not much of what you studied matters (it will but not in obvious ways.)
Certainly if you were headed into a very specific job which seems obviously automatable right now (as opposed to one where the tools will be useful), don't do THAT. Like, don't train as a typist as the core of your job in the middle of the personal computer revolution, or don't specialize in hand-drawing IC layouts in the middle of the CAD revolution unless you have a very specific plan (court reporting? DRAM?)
I argue that CAD was a general solution - which still demanded people who knew what they wanted and what they were doing. You can screw around with excellent tools for a long time if you don't know what you are doing. The tool will give you a solution - to the problem that you mis-stated.
I argue that globalisation was a general solution. And it still demanded people who knew what they were doing to direct their minions in far flung countries.
I argue that the purpose of an education is not to learn a specific programming language (for example). It's to gain some understanding of what's going on (in computing), (in engineering), (in business), (in politics). This understanding is portable and durable.
You can do THAT - gain some understanding - and that is portable. I don't contest that if broader AGI is achieved for cheap soon, the changes won't be larger than that from globalisation. If the AGIs prioritize heading to Mars, let them (See Accelerando) - they are not relevant to you anymore. Or trade between them and the humans. Use your beginning of an understanding of the world (gained through this education) to find something else to do. Same as if you started work 2 years ago and want to switch jobs. Some jobs WILL have disappeared (pool typist). Others will use the AGIs as tools because the AGIs don't care or are too clueless about THAT field. I have no idea which fields will end up with clueless AGIs. There is no lack of cluelessness in the world. Plenty to go around even with AGIs. A self-respecting AGI will have priorities.
It doesn't matter if you are bad at using the tool if the AGI can just effectively use it for you.
From there it's a simple leap to the AGI deciding to eliminate this human distraction (inefficient, etc.)
One thing that isn’t clear is how much agency AGI will have (or how much we’ll want it to have). We humans have our agency biologically programmed in—go forth and multiply and all that.
But the fact that an AI can theoretically do any task doesn’t mean it’s actually going to do it, or do anything at all for that matter, without some human telling it in detail what to do. The bull case for humans is that many jobs just transition seamlessly to a human driving an AI to accomplish similar goals with a much higher level of productivity.
And worrysome because school propaganda for example shows that "saving the planet" is the only ethical goal for anyone. If AGIs latch on that, if it becomes their religion, humans are in trouble. But for now, AGI self-chosen goals is anyone's guess (with cool ideas in sci-fi).
The technical act of solving well-defined problems has traditionally been considered the easy part. The role of a technical expert has always been asking the right questions and figuring out the exact problem you want to solve.
As long as AI just solves problems, there is room for experts with the right combination of technical and domain skills. If we ever reach the point where AI takes the initiative and makes human experts obsolete, you will have far bigger problems than career.
Of course it's also yet another case where the AI takes over the creative part and leaves us with the mundane part...
Yet GPT doesn’t even get past step 1 of doing something unprompted in the first place. I’ll become worried when it does something as simple as deciding to start a small business and actually does the work.
also https://mashable.com/article/chatgpt-messaging-users-first-o...
Look at the hackernews comments on alignment faking on how “fake” of a problem that real is. It’s just more reacting to inputs and trying to align them with previous prompts.
Yes a new tool is coming out and will be exponentially improving.
Yes the nature of work will be different in 20 years.
But don’t you still need to understand the underlying concepts to make valid connections between the systems you’re using and drive the field (or your company) forward?
Or from another view, don’t we (humanity) need people who are willing to do this? Shouldn’t there be a valid way for them to be successful in that pursuit?
Except the nature of work has ALREADY changed. You don't study for one specific job if you know what's good for you. You study to start building an understanding of a technical field. The grand parent was going for a mix of mechanical engineering and sales (human understanding). If in mechanical engineering, they avoided "learning how to use SolidWorks" and instead went for the general principles of materials and motion systems with a bit of SolidWorks along the way, then they are well on their way with portable, foundation, long term useful stuff they can carry from job to job, and from employer to employer, into self-employment too, from career to next career. The nature of work has already changed in that nobody should study one specific tool anymore and nobody should expect their first employer or even technical field to last more than 2-6 years. It might but probably not.
We do need people who understand how the world works. Tall order. That's for much later and senior in a career. For school purposes we are happy with people who are starting their understanding of how their field works.
Aren't we agreeing?
Most of the blacksmiths in the 19th century drank themselves to death after the industrial revolution. the US culture isn't one of care... Point is, it's reasonable to be sad and afraid of change, and think carefully about what to specialize in.
That said... we're at the point of diminishing returns in LLM, so I doubt any very technical jobs are being lost soon. [1]
[1] https://techcrunch.com/2024/11/20/ai-scaling-laws-are-showin...
What evidence are you basing this statement from? Because, the article you are currently in the comment section of certainly doesn't seem to support this view.
This is hyperbolic and a dramatic oversimplification and does not accurately describe the reality of the transition from blacksmithing to more advanced roles like machining, toolmaking, and working in factories. The 19th century was a time of interchangeable parts (think the North's advantage in the Civil War) and that requires a ton of mechanical expertise and precision.
Many blacksmiths not only made the transition to machining, but there weren't enough blackmsiths to fill the bevy of new jobs that were available. Education expanded to fill those roles. Traditional blacksmithing didn’t vanish either, even specialized roles like farriery and ornamental ironwork also expanded.
Lots of people die for reason X then the world moves on without them.
On the plus side, LLMs don't bring us closer to that dystopia: if unlimited knowledge(tm) ever becomes just One Prompt Away it won't come from OpenAI.
Even if our civilization transforms into an AI robotic utopia, it’s not going to do so overnight. We’re the ones who get to build the infrastructure that underpins it all.
If AI turns out dependent on human input and feedback, then we will still have jobs. Or maybe - AI automates many jobs, but at the same time expands the operational domain to create new ones. Whenever we have new capabilities we compete on new markets, and a hybrid human+AI might be more competitive than AI alone.
But we got to temper these singularitarian expectations with reality - it takes years to scale up chip and energy production to achieve significant work force displacement. It takes even longer to gain social, legal and political traction, people will be slow to adopt in many domains. Some people still avoid using cards for payment, and some still use fax to send documents, we can be pretty stubborn.
How will these people pay for the compute costs if they can't find employment?
This would mean the final victory of capital over labor. The 0.01% of people who own the machines that put everyone out of work will no longer have use for the rest of humanity, and they will most likely be liquidated.
There will be a dedicated cast of ppl to take care of machines that do 90% of work and „the rich”.
Anyone else is not needed. District9 but for ppl. Imagine whole world collapsing like Venesuela.
You are no longer needed. Best option is to learn how to survive and grow own food, but they want to make it illegal also - look at EU..
We’re a long way from that, if we ever get there, and I say this as someone who pays for ChatGPT plus because, in some scenarios, it does indeed make me more productive, but I don’t see your future anywhere near.
And if machines ever get good enough to do all the things I mentioned plus the ones I didn’t but would fit in the same list, it’s not the ultra rich that wouldn’t need us, it’s the machines that wouldn’t need any of us, including the ultra rich.
Venezuela is not collapsing because of automation.
You can even calculate the average number of people that can be operated on before harm occurs: number needed to harm (NNH). If NNH(AI) > NNH(humans), it becomes impossible to recommend that patients submit to surgery at the hands of human surgeons. It is that simple.
If we discover that AI surgeons harm one in every 1000 patients while human surgeons harm one in every 100 patients, human surgeons are done.
And the opposite holds, if the AI surgeon is worse (great for 80%, but sucks at the edge cases for example) then that's it. Build a better one, go through attempts at certification, but now with the burden that no one trusts you.
The assumption, and a common one by the look of this whole thread, that ChatGPT, Sora and the rest represent the beginning of an inevitable march towards AGI seems incredible baseless to me. It's only really possible to make the claim at all because we know so little about what AGI is, that we can project qualities we imagine it would have onto whatever we have now.
It's not going to hold forever though. I'm certain about that. Hopefully it will keep holding until I die. The world is dystopian enough already.
AGI can replace capitalists just as much as laborers.
people, what I mean people is government have tremendous power over capitalist that can force the entire market granted that government if still serving its people
I guess this could be a facet of whether you see economic advantage as a legal conceit or a difference in productivity/capability.
Does a billionaire stop being wealthy if they hire a money manager and spend the rest of their lives sipping drinks on the beach?
"Legally" will have to mop up now and then, but for now the basics are already in place.
I was responding to this. Yes an AGI could hire someone to do the stuff - but she needs money, hiring and contract kinds of thing - for that. And once she can do that, she probably doesn't need to hire someone to do it since she is already doing it. This is not about capital versus labor or money management. This is about agency, ownership and AGI.
(With legality far far down the list.)
> [deleted]: I've wondered about this for a while-- how can such an employment-centric society transition to that utopia where robots do all the work and people can just sit back?
> appleseed1234: It won't, rich people will own the robots and everyone else will eat shit and die.
https://www.reddit.com/r/TrueReddit/comments/k7rq8/are_jobs_...
This is my view but with a less positive spin: you are not going to be the only person whose livelihood will be destroyed. It's going to be bad for a lot of people.
So at least you'll have a lot of company.
I hear you, I’m not that much older but I graduated in 2011. I also studied industrial design. At that time the big wave was the transition to an app based everything and UX design suddenly became the most in demand design skill. Most of my friends switched gears and careers to digital design for the money. I stuck to what I was interested in though which was sustainability and design and ultimately I’m very happy with where I ended up (circular economy) but it was an awkward ~10 years as I explored learning all kinds of tools and ways applying my skills. It also was very tough to find the right full time job because product design (which has come to really mean digital product design) supplanted industrial design roles and made it hard to find something of value that resonated with me.
One of the things that guided me and still does is thinking about what types of problems need to be solved? From my perspective everything should ladder up to that if you want to have an impact. Even if you don’t keep learning and exploring until you find something that lights you up on the inside. We are not only one thing we can all wear many hats.
Saying that, we’re living through a paradigm shift of tremendous magnitude that’s altering our whole world. There will always be change though. My two cents is to focus on what draws your attention and energy and give yourself permission to say no to everything else.
AI is an incredible tool, learn how to use it and try to grow with the times. Good luck and stay creative :) Hope something in there helps, but having a positive mindset is critical. If you’re curious about the circular economy happy to share what I know - I think it’s the future.
Unlike most other benchmarks where LLMs have shown large advances (in law, medicine, etc.), this benchmark isn't directly related to any practically useful task. Rather, the benchmark is notable because it's particularly easy for untrained humans, but particularly hard for LLMs; though that difficulty is perhaps not surprising, since LLMs are trained on mostly text and this is geometric. An ensemble of non-LLM solutions already outperformed the average Mechanical Turk worker. This is a big improvement in the best LLM solution; but this might also be the first time an LLM has been tuned specifically for these tasks, so this might be Goodhart's Law.
It's a significant result, but I don't get the mania. It feels like Altman has expertly transformed general societal anxiety into specific anxiety that one's job will be replaced by an LLM. That transforms into a feeling that LLMs are powerful, which he then transforms into money. That was strongest back in 2023, but had weakened since then; but in this comment section it's back in full force.
For clarity, I don't question that many jobs will be replaced by LLMs. I just don't see a qualitative difference from all the jobs already replaced by computers, steam engines, horse-drawn plows, etc. A medieval peasant brought to the present would probably be just as despondent when he learned that almost all the farming jobs are gone; but we don't miss them.
I'm aware that LLMs can solve problems other than coloring grids, and I'd tend to agree those are likely to be more near-term useful. Those applications (coding, medicine, law, education, etc.) have been endlessly discussed, and I don't think I have much to add.
In my own work I've found some benefits, but nothing commensurate to the public mania. I understand that founders of AI-themed startups (a group that I see includes you) tend to feel much greater optimism. I've never seen any business founded without that optimism and I hope you succeed, not least because the entire global economy might now be depending on that. I do think others might feel differently for reasons other than simple ignorance, though.
In general, performance on benchmarks similar to tests administered to humans may be surprisingly unpredictive of performance on economically useful work. It's not intuitive at all to me that IBM could solve Jeopardy and then find no profitable applications of the technology; but that seems to be what happened.
It very nearly is. I knew a professional, career photographer. He was probably in his late 50s. Just a few years ago, it had become extremely difficult to convince clients that actual, professional photos were warranted. With high-quality iPhone cameras, businesses simply didn't see the value of professional composition, post-processing, etc.
These days, anyone can buy a DSLR with a decent lens, post on Facebook, and be a 'professional' photographer. This has driven prices down and actual professional photographers can't make a living anymore.
And then when I peruse these photographers websites, I'm reminded how good 'professional' actually is and value them. Even in today's incredible cameraphone and AI era.
But I take your point for almost all industries, things are changing fast.
So we'll find out if this model is real or not by 2-3 months. My guess is that it'll turn out to be another flop like O1. They needed to release something big because they are momentum based and their ability to raise funding is contingent on their AGI claims.
Significantly better at what? A benchmark? That isn't necessarily progress. Many report preferring gpt-4 to the newer o1 models with hidden text. Hidden text makes the model more reliable, but more reliable is bad if it is reliably wrong at something since then you can't ask it over and over to find what you want.
I don't feel it is significantly smarter, it is more like having the same dumb person spend more thinking than the model getting smarter.
Now they just have to make it cheap.
Tell me, what has this industry been good at since its birth? Driving down the cost of compute and making things more efficient.
Are you seriously going to assume that won’t happen here?
No they haven't, these results do not generalize, as mentioned in the article:
"Furthermore, early data points suggest that the upcoming ARC-AGI-2 benchmark will still pose a significant challenge to o3, potentially reducing its score to under 30% even at high compute"
Meaning, they haven't solved AGI, and the task itself do not represent programming well, these model do not perform that well on engineering benchmarks.
But what they’ve done is show that progress isn’t slowing down. In fact, it looks like things are accelerating.
So sure, we’ll be splitting hairs for a while about when we reach AGI. But the point is that just yesterday people were still talking about a plateau.
You can also use the full o3 model, consume insane power, and get insane results. Sure, it will probably take longer to drive down those costs.
You’re welcome to bet against them succeeding at that. I won’t be.
They’ve been doing it literally this entire time. O3-mini according to the charts they’ve released is less expensive than o1 but performs better.
Costs have been falling to run these models precipitously.
Like they've been making it all this time? Cheaper and cheaper? Less data, less compute, fewer parameters, but the same, or improved performance? Not what we can observe.
>> Tell me, what has this industry been good at since its birth? Driving down the cost of compute and making things more efficient.
No, actually the cheaper compute gets the more of it they need to use or their progress stalls.
Yes exactly like they’ve been doing this whole time, with the cost of running each model massively dropping sometimes even rapidly after release.
Yes, it costs a lot to train a model. Those costs go up. But once you trained it, it’s done. At that point inference — the actual execution/usage of the model — is the cost you worry about.
Inference cost drops rapidly after a model is released as new optimizations and more efficient compute comes online.
Inference always starts expensive. It comes down.
This is a thing, you should know. It's called Jevon's Paradox:
In economics, the Jevons paradox (/ˈdʒɛvənz/; sometimes Jevons effect) occurs when technological progress increases the efficiency with which a resource is used (reducing the amount necessary for any one use), but the falling cost of use induces increases in demand enough that resource use is increased, rather than reduced.[1][2][3][4]
https://en.wikipedia.org/wiki/Jevons_paradox
Better check those pills then.
Oh but, you know, merry chrimbo to you too.
Oh yes indeed-ee-o and I'm referring to training and not inference because the big problem is the cost of training, not inference. The cost of training has increased steeply with every new generation of models because it has to, in order to improve performance. That process has already reached the point where training ever larger models is prohibitively expensive even for companies with the resources of OpenAI. For example, the following is from an article that was posted on HN a couple days ago and is basically all about the overwhelming cost to train GPT-5:
In mid-2023, OpenAI started a training run that doubled as a test for a proposed new design for Orion. But the process was sluggish, signaling that a larger training run would likely take an incredibly long time, which would in turn make it outrageously expensive. And the results of the project, dubbed Arrakis, indicated that creating GPT-5 wouldn’t go as smoothly as hoped.
(...)
Altman has said training GPT-4 cost more than $100 million. Future AI models are expected to push past $1 billion. A failed training run is like a space rocket exploding in the sky shortly after launch.
(...)
By May, OpenAI’s researchers decided they were ready to attempt another large-scale training run for Orion, which they expected to last through November.
Once the training began, researchers discovered a problem in the data: It wasn’t as diversified as they had thought, potentially limiting how much Orion would learn.
The problem hadn’t been visible in smaller-scale efforts and only became apparent after the large training run had already started. OpenAI had spent too much time and money to start over.
From:
HN discussion:
https://news.ycombinator.com/item?id=42485938
"Once you trained it it's done" - no. First, because you need to train new models continuously so that they pick up new information (e.g. the name of the President of the US). Second because companies are trying to compete with each other and to do that they have to train bigger models all the time.
Bigger models means more parameters and more data (assuming there is enough which is a whole other can of worms) more parameters and data means more compute and more compute means more millions, or even billions. Nothing in all this is suggesting that costs are coming down in any way, shape or form, and yep, that's absolutely about training and not inference. You can't do inference before you do training, you need to train continuously, and for that reason you can't ignore the cost of training and consider only the cost of inference. Inference is not the problem.
This type of compute will be cheaper than Claude 3.5 within 2 years.
It's kinda nuts. Give these models tools to navigate and build on the internet and they'll be building companies and selling services.
We may have progressed from a 99%-accurate chatbot to one that's 99.9%-accurate, and you'd have a hard time telling them apart in normal real world (dumb) applications. A paradigm shift is needed from the current chatbot interface to a long-lived stream of consciousness model (e.g. a brain that constantly reads input and produces thoughts at 10ms refresh rate; remembers events for years and keep the context window from exploding; paired with a cerebellum to drive robot motors, at even higher refresh rates.)
As long as we're stuck at chatbots, LLM's impact on the real world will be very limited, regardless of how intelligent they become.
(See why objective benchmarks exist?)
Also, all that stuff is shady in the way that it is just numbers from OAI, which are not reproducible on benchmark sponsored by OAI. If we say OAI could be bad actor, they had plenty of opportunities to cheat on this.
Or let's talk about the breakthroughs. SVMs would lead us to AGI. Then LSTMs would lead us to AGI. Then Convnets would lead us to AGI. Then DeepRL would lead us to AGI. Now Transformers will lead us to AGI.
Benchmarks fall right and left and we keep being led to AGI but we never get there. It leaves one with such a feeling of angst. Are we ever gonna get to AGI? When's Godot coming?
99% of engineering is distilling through bullshit and nonsense requirements. Whether that is appealing to you is a different story, but ChatGPT will happily design things with dumb constraints that would get you fired if you took them at face value as an engineer.
ChatGPT answering technical challenges is to engineering as a nailgun is to carpentry.
1) Just give up computing entirely, the field I've been dreaming about since childhood. Perhaps if I immiserate myself with a dry regulated engineering field or trade I would perhaps survive to recursive self-improvement, but if anything the length it takes to pivot (I am a Junior in College that has already done probably 3/4th of my CS credits) means I probably couldn't get any foothold until all jobs are irrelevant and I've wasted more money.
2) Hard pivot into automation, AI my entire workflow, figure out how to use the bleeding edge of LLMs. Somehow. Even though I have no drive to learn LLMs and no practical project ideas with LLMs. And then I'd have to deal with the moral burden that I'm inflicting unfathomable hurt on others until recursive self-improvement, and after that it's simply a wildcard on what will happen with the monster I create.
It's like I'm suffocating constantly. The most I can do to "cope" is hold on to my (admittedly weak) faith in Christ, which provides me peace knowing that there is some eternal joy beyond the chaos here. I'm still just as lost as you.
The scenario I fear is a "selectively general" model that can successfully destroy the field I'm in but keep others alive for much longer, but not long enough for me to pivot into them before actually general intelligence.
It's powerful and world changing but it's also terrible overhyped at the moment.
If you want to work in computing, then make it happen! Use the tools available and make great stuff. Your computing experience will be different from when I graduated from college 25 years ago, but my experience with computers was far different from my Dad's. Things change. Automation changes jobs. So far, it's been pretty good.
It's a massive bubble, and things like these "benchmarks" are all part of the hype game. Is the tech cool and useful? For sure, but anyone trying to tell you this benchmark is in any way proof of AGI and will replace everyone is either an idiot or more likely has a vested interest in you believing them. OpenAI's whole marketing shtick is to scare people into thinking their next model is "too dangerous" to be released thus driving up hype, only to release it anyway and for it to fall flat on its face.
Also, if there's any jobs LLMs can replace right now, it's the useless managerial and C-suite, not the people doing the actual work. If these people weren't charlatans they'd be the first ones to go while pushing this on everyone else.
I told him it was at least 5 years, probably 10, though he was sure it would be 2.
I was arguably “right”, 2023-ish is probably going to be the date people put down in the books, but the future isn’t evenly distributed. It’s at least another 5 years, and maybe never, before things are distributed among major metros, especially those with ice. Even then, the AI is somehow more expensive than human solution.
I don’t think it’s in most companies interest to price AI way below the price of meat, so meat will hold out for a long time, maybe long enough for you to retire even
There’s an incredibly massive amount of stuff the world needs. You probably live in a rich country, but I doubt you are lacking for want. There are billionaires who want things that don’t exist yet. And, of course, there are billions of regular folks who want some of the basics.
So long as you can imagine a better world, there will be work for you to do. New tools like AGI will just make it more accessible for you to build your better future.
This has essentially been happening for thousands of years. Any optimization to work of any kind reduces the number of man hours required.
Software of pretty much any form is entirely that. Even early spreadsheet programs would replace a number of jobs at any company.
That is: If you don't believe there will be a future, you give up on trying to make one. That means that any kind of future that takes persistent work becomes unavailable to you.
If you do believe that there will be a future, you keep working. That doesn't guarantee there will be a future. But not working pretty much guarantees that there won't be one, at least not one worth having.
If AI lives up to hype, you could be the excavator driver. Or, the AI will create a ton of upstream and downstream work. There will be no mass unemployment.
Are there no limits to this argument? Is it some absolute universal law that all new creations just create increasing economic opportunities?
Investment in human talent augmented by AI is the future.
Having used AI extensively I don't feel my future is at risk at all, my work is enhanced not replaced.
The computing cost, on the other hand, is a continuous improvement. If (and it's a big if) a computer can do your job, we know the costs will keep getting lower year after year (maybe with diminishing returns, but this AI technology is pretty new so we're still seeing increasing returns)
Everyone needs to know how to either build or sell to be successful. In a world where the ability to the former is rapidly being commoditised, you will still need to sell. And human relationships matter more than ever.
You're in a position to invest substantial amounts of time compared to your seniors. Leverage that opportunity to your advantage.
We all have access to these tools for the most part, so the distinguishing factor is how much time you invest and how much more ambitious you become once you begin to master the tool.
This time its no different. Many Mechanical and Sales students in the past never got jobs in those fields either. Decades before AI. There were other circumstances and forces at play and a degree is not a guaranteed career in anything.
Keep going because what we DO know is that trying wont guarantee results, we DO know that giving up definitely won't. Roll the dice in your favor.
I want to criticize Art’s comment on the grounds of ageism or something along the lines of “any amount life outside of programming is wasted”, but regardless of Art’s intention there is important wisdom here. Use your free time wisely when you don’t have much responsibilities. It is a superpower.
As for whether to spend it on AI, eh, that’s up to you to decide.
I'm a greybeard myself.
It'll be some time before there is a robot with enough spatial reasoning to do complicated physical work with no prior examples.
These benchmark accomplishments are awesome and impressive, but you shouldn't operate on the assumption that this will emerge as an engineer because it performs well on benchmarks.
Engineering is a discipline that requires understanding tools, solutions and every project requires tiny innovations. This will make you more valuable, rather than less. Especially if you develop a deep understanding of the discipline and don't overly rely on LLMs to answer your own benchmark questions from your degree.
But the arc of time intersects quite nicely with your skills if you steer it over time.
Predicting it or worrying about it does nothing.
Especially with AI provably getting extremely smart now, surely engineering disciplines would be having a boon as people want these things in their homes for cheaper for various applications.
Either this is the dawn of something bigger than the industrial revolution or you'll have ample career opportunity. Understanding how things work and how people work is a powerful combination.
when the last job has been automated away, millions of AIs globally will do commerce with each other and they will use bitcoin to pay each other.
as long as the human race (including AIs) produces new goods and services, the purchasing power of bitcoin will go up, indefinitely. even more so once we unlock new industries in space (settlements on the Moon and Mars, asteroid mining etc).
The only thing that can make a dent into bitcoin's purchasing power would be all out global war where humanity destroys more than it creates.
The only other alternative is UBI, which is Communism and eternal slavery for the entire human race except the 0.0001% who run the show.
Chose wisely.