Friendship, love, sex, art, even faith and childrearing are opportunities for substitution with AI. Ask an AI to create a joke for you at a party. Ask an AI to write a heartfelt letter to somebody you respect. Have an AI make a digital likeness of your grandmother so you can spend time with her forever. Have an AI tell you what you should say to your child when they are sad.
Hell. Hell on earth.
The graph says horse ownership per person. People probably stopped buying horses, they let theirs retire (well, to be honest, probably also sent to the glue factory), and when they stopped buying new horses, horse breeding programs slowed down.
One of the many terrible things about software engineers their the tendency to think and speak as if they were some kind of aloof galaxy-brain, passively observing humanity from afar. I think that's at least partially the result of 1) identifying as an "intelligent person" and 2) computers and the internet allowing them to in-large-part become disconnected from the rest of humanity. I think they see that aloofness as being a "more intelligent" way to engage with the world, so they do it to act out their "intelligence."
Yes, actually, because this has been a deep vein of writing for the past 100 or more years. There's The Phools, by Stanislav Lem. There's the novels written by Boris Johnson's father that are all about depopulation. There's Aldous Huxley's Brave New World. How about Logan's Run? There has been so much writing about the automation / technology apocalypse for humans in the past 100 years that it's hard to catalog it -- much of what I have read or seen go by in the vein I've totally forgotten.
It's not remotely a surprise to see this amp up with AI.
Yes, here's a youtube classic that put forth the same argument over a decade ago, originally titled "Humans need not apply": https://youtu.be/7Pq-S557XQU
Computerization, automation and robotics, document digitization, the telecoms and wireless revolution, etc. have been upending peoples' employment on a massive scale since before the 1970s. The reaction of the technologists has been a rather insensitive "adapt or die", "go and retrain", and analogies to buggy whip manufacturers when the automobile became popular. The only reason people here suddenly give a hoot is because they think the crosshairs are drifting towards them.
It reminds me of "You maniacs! You blew it up! Goddamn you all to hell!" from the original Planet of the Apes (1968), https://youtu.be/mDLS12_a-fk?t=71
Quite ironically, the scene features a horse.
We collectively have a lot of choice on the how we deal with it part. I'm personally optimistic that people will vote in people friendly policies when it comes to it.
So much money is spent on developing gambling, social media, crypto (fraud and crime enabler) and surveillance software. All of these are making people's lives worse, these companies aren't even shy about it. They want to track you, they want you to spend as much time as possible on their products, they want to make you addicted to gambling.
Just by how large these segments are, many of the people developing that software must be posting here, but I have never seen any actual reflection on it.
Sure, I guess developing software making people addicted to gambling pays the bills (and more than that), but I haven't seen even that. These industries just exist and people seem to work for them as if it was just a normal job, with zero moral implications.
In this instance, in particular, I wouldn't expect our preferences to bear any relevance.
It shines through that the most fervent AI Believers are also Haters of Humans.
In the US at least, there is a Congress incapable of taking action and a unilateral President fully on the side of tech CEOs with the heaviest investments in AI.
There is no evidence supporting short term optimism. Every indication the large corporations dictating public policy will treat us exactly like those horses when it comes to economic value.
However, it does seem like time for humanity to collectively think hard about our values and goals, and what type of world and lives we want to have in an age where human thought, and perhaps even human physical labor are economically worthless. Unfortunately this could not come at a worse time with humanity seemingly experiencing a widespread rejection of ideals like ethics, human rights, and integrity and embracing fascism and ruthless blind financial self interest as if they were high minded ideals.
Ironically, I think tech people could learn a lot here from groups like the Amish- they have clearly decided what their values and goals are, and ruthlessly make tech serve them, instead of the other way around. Despite stereotypes, Amish are often actually heavy users of, and competent with modern tech in service of making a living, but in a way that enforces firm boundaries about not letting the tech usurp their values and chosen way of life.
It was always like this. Look at the history, and sometimes quite recent - people were always treated like a tool - for getting rich, for getting in power, to conquer other countries, to serve them.
For the Romans, winning wars was the main source of elite prestige. So the Empire had to expand to accommodate winning more wars.
Today, the stock market and material wealth dominates. If elite dominance of the means of production requires the immiseration of most of the public, that's what we'll get.
Not sure if by accident or not, but that’s what we are according today’s “tech elite”.
Therefore, the most profitable disposition for this dubious form of capital is to convert them into biodiesel, which can help power the Muni buses
And low information business leaders will attempt to do all the awful things described here and the free market will eliminate them from the game grid one horrible boss at a time. But if you surround yourself with the AI doomers and bubblers, how will you ever encounter or even consider positive uses of the technology? What an awful place to work Anthropic must be if they truly believe they are working on the metaphorical equivalent of the Alpha Omega bomb. Spoilers: they're not.
Meanwhile, in the rest of the world, many look forward to harnessing AI to ameliorate hunger, take care of the elderly, and perform the more dangerous and tedious jobs out there. Anthropic guy needs to go get a room with Eliezer Yudkowsky. I guess the US is about get horsed by the other 96% of the planet.
Go ahead, compare me to a horse, a gasoline engine, or even call me a meatbag. Have we become little more than Eloi snowflakes to be so offended by that?
But I guess as long as an electoral majority here continues to cheer on one man draining the juice of this country down to a bitter husk, the fun and games will continue.
https://www.census.gov/library/visualizations/interactive/te... Look at all the professions on the bottom right: Teachers, therapists, clergy, social workers, etc. It’s not a coincidence that cruel people take top positions.
My comments being downvoted, pretty rare lately, were about never discussed but legitimate points about AI that I validated IRL. I have no resonance about the way AI is discussed on HN and IRL, to the point that I can't rule out more or less subtle manipulation on the discussions.
I think the comparisons are useful enough as metaphors, though I wonder at analysis, because it sounds like if someone took a Yudkowsky idea and talked about it like a human, which might make a bad assumption go down more smooth than it should. But I don't know.
Economically it is no different from the demand for Mitsubishi's decreasing except the vehicle in this case eats grass, poops, and feels pain.
If you want to analogize with humans, a gradual reduction in breeding (which is happening anyways with or without AI) is probably a stronger analogy than a Skynet extinction scenario.
Truth is this is no different than the societal trends that were introduced with industrialization, simply accelerated on a massive scale.
The threshold for getting wealth through education is bumping up against our natural human breeding timeline, delaying childbirth past natural optimal human fertility ages in the developed world. The amount of education needed to achieve certain types of wealth will move into the decades causing even more strain on fertility metrics. Some people will decide to have more kids and live off purely off whatever limited wellfare the oligarchs in charge decide is acceptable. Others will delay having children far past natural human fertility timespans or forgo having children at all.
1. Even if LLMs made everyone 10x as productive, most companies will still have more work to do than resources to assign to those tasks. The only reason to reduce headcount is to remove people who already weren’t providing much value.
2. Writing code continues to be a very late step of the overall software development process. Even if all my code was written for me, instantly, just the way I would want it written, I still have a full-time job.I wish corporations really acted this rationally.
At least where I live hospitals fired most secretaries and assistants to doctors a long time ago. The end result? High-paid doctors spending significant portion of their time on administrative and bureaucratic tasks that were previously handled by those secretaries, preventing them from seeing as many patients as they otherwise would. Cost savings may look good on spreadsheet, but really the overall efficiency of the system suffered.
There seems to be a running theme of “okay but what about” in every discussion that involves AI replacing jobs. Meanwhile a little time goes by and “poof” AI is handling it.
I want to be be optimistic. But it’s hard to ignore what I’m doing and seeing. As far as I can tell, we haven’t hit serious unemployment yet because of momentum and slow adoption.
I’m not replying to argue, I hope you are right. But I look around and can’t shake the feeling of Wile E. Coyote hanging in midair waiting for gravity to kick in.
There were many secretaries up until the late 20th century that took dictation, either writing notes of what they were told or from a recording, then they typed it out and distributed memos. At first, there were many people typing, then later mimeograph machines took away some of those jobs, then copying machines made that faster, then printers reduced the need for the manual copying, then email reduced the need to print something out, and now instant messaging reduces email clutter and keep messages shorter.
All along that timeline there were fewer and fewer people involved, all for the valuable task of communication. While they may not have held these people in high esteem, they were critical for getting things done and scaling.
I’m not saying LLMs are perfect or will replace every job. They make mistakes, and they always will; it’s part of what they are. But, as useful as people are today, the roles we serve in will go away and be replaced by something else, even if it’s just to indicate at various times during the day what is or isn’t pleasing.
This is very important yet rarely talked about. Having worked in a well-run group on a very successful product I could see that no matter how many people would be on a project there was alway too much work. And always too many projects. I am no longer with the company but I can see some of the ideas talked about back then being launched now, many years later. For a complex product there is always more to do and AI would simply accelerate development.
Instead our productivity went way above anything he could imagine, yet there was no radical shift in labor. We just instead started making billionaires by the thousand, and soon enough we can add trillionaires. He underestimated how many people were willing to designate the pursuit of wealth as the meaning of life itself.
I agree with all the limitations you've written about the current state of AI and LLMs. But the fact is that the tech behind AI and LLMs never really gets worse. I also agree that just scaling and more compute will probably be a dead end, but that doesn't mean that I don't think that progress will still happen even when/if those barriers are broadly realized.
Unless you really believe human brains have some sort of "secret special sauce" (and, FWIW, I think it's possible - the ability of consciousness/sentience to arise from "dumb matter" is something that I don't think scientists have adequately explained or even really theorized), the steady progress of AI should, eventually, surpass human capabilities, and when it does, it will happen "all at once".
They have more work to do until they don't.
The number of bank tellers went up for a while after the invention of the ATM, but then it went down, because all the demand was saturated.
We still need food, farming hasn't stopped being a thing, nevertheless we went from 80-95% of us working in agriculture and fishing to about 1-5%, and even with just those percentages working in that sector we have more people over-eating than under-eating.
As this transition happened, people were unemployed, they did move to cities to find work, there were real social problems caused by this. It happened at the same time that cottage industries were getting automated, hand looms becoming power-looms, weaving becoming programmable with punch cards. This is why communism was invented when it was invented, why it became popular when it did.
And now we have fast-fashion, with clothes so fragile that they might not last one wash, and yet still spend a lower percentage of our incomes on clothes than the pre-industrial age did. Even when demand is boosted by having clothes that don't last, we still make enough to supply demand.
Lumberjacks still exist despite chainsaws, and are so efficient with them that the problem is we may run out of rainforests.
Are there any switchboard operators around any more, in the original sense? If I read this right, the BLS groups them together with "Answering Service", and I'm not sure how this other group then differs from a customer support line: https://www.bls.gov/oes/2023/may/oes432011.htm
> 2. Writing code continues to be a very late step of the overall software development process. Even if all my code was written for me, instantly, just the way I would want it written, I still have a full-time job.
This would be absolutely correct — I've made the analogy to Amdahl's law myself previously — if LLMs didn't also do so many of the other things. I mean, the linked blog post is about answering new-starter questions, which is also not the only thing people get paid to do.
Now, don't get me wrong, I accept the limitations of all the current models. I'm currently fairly skeptical that the line will continue to go up as it has been for very much longer… but "very much longer" in this case is 1-2 years, room for 2-4 doublings on the METR metric.
Also, I expect LLMs to be worse at project management than at writing code, because code quality can be improved by self-play and reading compiler errors, whereas PM has slower feedback. So I do expect "manage the AI" to be a job for much longer than "write code by hand".
But at the same time, you absolutely can use an LLM to be a PM. I bet all the PMs will be able to supply anecdotes about LLMs screwing up just like all the rest of us can, but it's still a job task that this generation of AI is still automating at the same time as all the other bits.
plenty of charts you can look at - net productivity by virtually any metric vs real adjusted income. the example I like are kiosks and self checkout. who has encountered one at a place where it is cheaper than its main rival and is directly attributable to (by the company or otherwise) to lower prices?? in my view all it did was remove some jobs. that's the preview. that's it. you will lose jobs and you will pay more. congrats.
even with year 2020 tech you could automate most work that needs to be done, if our industry wouldn't endlessly keep disrupting itself and have a little bit of discipline.
so once ai destroys desk jobs and the creative jobs, then what? chill out? too bad anyone who has a house won't let more be built.
Compare sorting by median vs average to get a sense of the issue; https://en.wikipedia.org/wiki/List_of_countries_by_wealth_pe...
This is a recent development where the median wealth of citizens in progressively taxes nations has quickly overtaken the median wealth of USA citizens.
All it takes is tax on the extremely wealthy and lessening taxes on the middle class… seems obvious right? Yet things gave consistently been going the other way for along time in the USA.
Tech and AI have taken off in the US partially because they’re in the domain of software, which hasnt bee regulated to the point of deliberate inefficiency like other industries in the US.
Think of it another way. It's not that these things are more expensive. It's that the average US worker simply doesn't provide anything of value. China provides the things of value now. How the government corrected for this was to flood the economy with cash. So it looks like things got more expensive, when really it's that wages reduced to match reality. US citizens selling each other lattes back and forth, producing nothing of actual value. US companies bleeding people dry with fees. The final straw was an old man uniting the world against the USA instead of against China.
If you want to know where this is going, look at Britain: the previous world super power. Britain governed far more of the earth than the USA ever did, and now look at it. Now the only thing it produces is ASBOs. I suppose it also sells weapons to dictators and provides banking to them. That is the USA's future.
That's just an example, but the pattern will easily repeat. One thing that came out of the post-pandemic era is that the lowest deciles saw the biggest rises in income. Consequently, things like Doordash became more expensive, and stuff like McDonald's stopped staffing as much.
This isn't some grand secret, but most Americans who post on Twitter, HN, or Reddit consider the results some kind of tragedy, though it is the natural thing that happens when people become much higher income: you can't hire many of them to do low-productivity jobs like bus a McD's table.
That's what life looks like when others get richer relative to you. You can't consume the fruits of their labor for cheap. And they will compete for you with the things that you decided to place supply controls on. The highly-educated downwardly-mobile see this most acutely, which is why you see it commonly among the educated children of the past elite.
The key issue upstream is that too many good jobs are concentrated in too few places, and that leads to consumerism stimulating those places and making them further more attractive. Technology, through Covid, actually gave governments a get out of jail free card by allowing remote work to become more mainstream. Only to just not grasp the golden egg they were given. Pivot economies more to remote working more actively helps distribute people to other places with more affordable home. Over time, and again slowly, those places become more attractive because people now actually live there.
Existing homeowners can still wrap themselves in the warm glow of their high house prices which only loses "real" value through inflation which people tend not to notice as much.
But we decided to try to go back to the status quo so oh well
physical products & energy are the two things that are relevant to people's wellbeing.
right now A.I is sucking up the energy & the RAM - so is it gonna translate into a net positive ?
Pretty much everything gets more expensive, with the outliers being tech which has gotten much cheaper, mostly because the rate at which it progresses is faster than the rate at which governments can print money. But everything we need to survive, like food, housing, etc, keeps getting more expensive. And the asset class get richer as a result.
The way the average dev structures their code requires like 10x the number of lines as I do and at least 10x the amount of time to maintain... The interest on technical debt compounds like interest on normal debt.
Whenever I join a new project, within 6 months, I control/maintain all the core modules of the system and everything ends up hooked up to my config files, running according to the architecture I designed. Happened at multiple companies. The code looks for the shortest path to production and creates a moat around engineers who can make their team members' jobs easier.
IMO, it's not so different to how entrepreneurship works. But with code and processes instead of money and people as your moat. I think once AI can replace top software engineers, it will be able to replace top entrepreneurs. Scary combination. We'll probably have different things to worry about then.
1: https://www.lbec-law.com/blog/2025/04/the-majority-of-driver...
I am regularly tempted to do this (I have done this a few times), but unless I truly own the project (being the tech lead or something), I stop myself. One of the reasons is reluctance to trespass uninvited on someone's else territory of responsibility, even if they do a worse job than I could. The human cost of such a situation (to the project and ultimately to myself) is usually worse than the cost of living with status quo. I wonder what your thoughts are on this.
You’re assuming the LLM produces extra complexity because it’s mimicking human code. I think it’s more likely that LLMs output complex code because it requires less thought and planning, and LLMs are still bad at planning.
6 months is also average time it takes people like you to burn out on a project. Usually starting with relatively simple change/addition requested by customer that turns into 3 month long refactor - "because architecture is wrong". And we just let you do it, because we know fighting windmills is futile.
There is a strange dynamic currently at play in the software labour market where the demand is so huge that the market can bear completely inefficient coders. Even though the difference between a good and a bad software engineer is literally orders of magnitude.
Quite a few times I encountered programmers "in the wild" - in a sauna, on the bus etc, and overheard them talking about their "stack". You know the type, node.js in a docker container. I cannot fathom the amount of money wasted at places that employ these people.
I also project that actually, if we adopt LLMs correctly, these engineers (which I would say constitute a large percentage) will disappear. The age of useless coding and infinite demand is about to come to an end. What will remain is specialist engineer positions (base infra layer, systems, hpc, games, quirky hardware, cryptographers etc). I'm actually kind of curious what the effect on salary will be for these engineers, I can see it going both ways.
I'm still waiting for something that can learn and adapt itself to new tasks as well as humans can, and something that can reason symbolically about novel domains as well as we can. I've seen about enough from LLMs, and I agree with the critique that som type of breakthrough neuro-symbolic reasoning architecture will be needed. The article is right about one thing: in that moment AI will overtake us suddenly! But I doubt we will make linear progress toward that goal. It could happen in one year, five, ten, fifty, or never. In 2023 I was deeply concerned about being made obsolete by AI, but now I sleep pretty soundly knowing the status quo will more or less continue until Judgment Day, which I can't influence anyway.
So, while I don't think AGI will happen any time soon, I wonder what 'roads' we'll build to squeeze the most out of our current AI. Probably tons of power generation.
To companies like Anthropic, “AGI” really means: “Liquidity event for (AI company)” - IPO, tender offer or acquisition.
Afterwards, you will see the same broken promises as the company will be subject to the expectations of Wall St and pension funds.
Remember when "AGI" was the weasel word because 1980s AI kept on not delivering?
That's highly irrelevant because if it were otherwise, we would already be replaced. The article was talking about the future.
It only appears “simple” because you're used to see working engines everywhere without never having to maintain them, but neither the previous generations nor the engineers working on modern engines would agree with you on that.
An engine performs “a simple mechanical operation” the same way an LLM performs a “simple computation”.
The question is how do our individuals, and more importantly our various social and economic systems handle it when exactly what humans can do to provide value for each other shifts rapidly, and balances of power shift rapidly.
If the benefits of AI accrue to/are captured by a very small number of people, and the costs are widely dispersed things can go very badly without strong societies that are able to mitigate the downsides and spread the upsides.
Banks used to have rooms full of bank clerks who manually did double-entry bookkeeping for all the bank's transactions. For most people, this was a very boring job, and it made bank transactions slow and expensive. In the 50's and 60's we replaced all these people with computers. An entire career of "bank clerk" vanished, and it was a net good for humanity. The cost of bank transactions came down (by a lot!), banks became more responsive and served their customers better. And the people who had to do double-entry bookkeeping all day long got to do other, probably more interesting, jobs.
There are a ton of current careers that are just email + meetings + powerpoint + spreadsheet that can go the same way. They're boring jobs (for most people doing them) and having humans do them makes administration slow and expensive. Automating them will be a net good for humanity. Imagine if "this meeting could have been an email" actually moves to "this meeting never happened at all because the person making the decision just told the LLM and it did it".
You are right that the danger is that most of the benefits of this automation will accrue to capital, but this didn't happen with the bank clerk automation - bank customers accrued a lot of the benefits too. I suspect the same will be true with this automation - if we can create and scale organisations easier and cheaper without employing all the admin staff that we currently do, then maybe we create more agile, responsive, organisations that serve their customers better.
AI, at the limit, is a vampiric technology, sucking the differentiated economic value from those that can train it. What happens when there are no more hosts to donate more training-blood? This, to me, is a big problem, because a model will tend to drift from reality without more training-blood.
The owners of the tech need to reinvest in the hosts.
I can’t help but smile at the possibility that you could be a bot.
Before someone says "but benchmark doesn't reflect real world..." please name what metric you think is meaningful if not benchmark. Token consumption? OpenAI/Anthropic revenue?
Too much is on the line here regardless of what ultimately ends up being true or just hype.
AI is not identical to, as the article compares, mechanical power.
But your weather-forecasting comment suggests a possible similarity (though not the one you go to): for all the millions-fold increase in compute power, and the increased density and specificity of meterological measurements, our accurate weather-forecasting window has only extended by a factor or so of two (roughly five days to ten). That is, there are applications for which vastly more information-processing capacity provides fairly modest returns.
And there are also those in which it's transformative. I'd put reusable rockets in that category, where we can now put sufficiently-reliable compute (and a whole bunch of rocket-related hardware) on a boost-phase rocket such that it can successfully soft-land.
For some years I've been thinking of the notion of technology not as some general principle ("efficiency" is the classic economics formulation), but as a set of specific mechanisms each of which has specific capabilities and limitations.[1] I've held pretty constant with nine of these:
1. Fuels. Applying more (or more useful) energy to a process.
2. Energy transmission and transformation.
3. Materials. Specific properties, abundance, costs, effects, limitations.
4. Process knowledge --- how to do things. What's generally described as "technical knowledge", here considered as a specific mechanism of technology.
5. Structural or causal knowledge --- why things work. What's generally described as "scientific knowledge".
6. Networks. Interactions between nodes via links, physical or virtual, over which matter, energy, information, or some mix flow. Transport, comms, power, information.
7. Systems. Constructs including sensing, processing, action, and feedback. Ranging from conceptual to mechanical to human and social.
8. Information. Sensing, perceiving, processing, storing, retrieving, and transmitting. Ranging from our natural senses to augmented ones, from symbolic systems (language, maths) to algorithms.
9. Hygiene. Sinks and unintended consequences, affecting the function and vitality of systems, and their mitigations or limits.
AI / AGI falls into the 8th category: information, specifically information processing. And as such, getting back to my original point, we can compare it with other information-related technological innovations: speech, writing, maths, boolean logic, switches (valves, transistors, etc.), information storage/retrieval, etc. And, yes, human thought processes. We do have some priors we can look at here, and they might help guide us in what a true AGI might be able to accomplish, and what its limitations may be.
It's often noted (including in this thread) that AGI would not presently be able to persist without copious human assistance, in that it's predicated on a vast technological infrastructure only a small portion of which it would be capable of substituting for. It's quite likely that AGI would be both competitive with and complementary to much human activity. In the horse analogy, it's worth noting that the first stage of mechanised transport development, with steam shipping and rail technology, horses were strongly complementary in that they fulfilled the last-mile delivery role which steamships and locomotives couldn't furnish. Horse drayage populations actually boomed during this period. It was development of ICE-powered lorries which finally out-competed the horse-drawn cart for intra-urban delivery. AGI-as-augmenting-humans is an already highly-utilised model, and will likely persist for some time. Experiments in AGI replacing humans will no doubt occur, some successful, others not. I'd suggest that my 9th category, hygiene, and specifically failure modes of AGI, will likely prove highly interesting.
Mechanised transport also relies heavily on fuels and/or energy storage. The past 200 or so years were predicated on nonrenewable fossil fuels, first coal then oil, and there were several points in that timeline where continued availability of cheap fuels was seriously in question. We're now reaching the point where even given abundant supply, the relatively-clean byproducts of use are proving, at scales of current use, incompatible with climatic stability, possibly extending to incompatible with advanced technological civilisation or even advanced life on Earth (again, category 9).
AGI relies on IC chip manufacture (the province of vanishingly few companies), on copious amounts of electricity, scarce physical resources, and various legal regimes concerning use of intellectual works, property, profit, and more (categories 1, 2, 3, and 7, at a minimum). Whether or not a world with pervasive AGI proves to be a stable or unstable point is another open question.
________________________________
Notes:
1. A sampling of prior HN discussions may be found with this search: <https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...>.
It's really changing cultural expectations. Don't ping a human when an LLM can answer the question probably better and faster. Do ping a human for meaningful questions related to product directions / historical context.
What LLMs are killing is:
- noisy Slacks with junior folks questions. Those are now your Gemini / chat gpt sessions.
- tedious implementation sessions.
The vast majority of the work is still human led from what I can tell.
What I want to know when I join a company is "why" the system does what it does. Sure, give me pointers, some overview of how the code is structured, that always helps, but if you don't tell me why how am I supposed to work?
$currentCompany has the best documentation I've seen in my career. It's been spun off from a larger company, from people collaborating asynchronously and remotely whenever they had some capacity.
No matter how diligent we've been, as soon as the company started in earnest and we got people fully dedicated to it, there's been a ton of small decisions that happened during a quick call, or on a slack thread, or as a comment on a figma design.
This is the sort of "you had to be there" context the onboarding should aim to explain, and I don't see how LLMs help with that.
In times past, the only people on earth who had their standard of living raised to a level that allowed them to cast there gaze upon the stars were the Kings and there courts, vassals, and noblemen. As time passed we have learned to make technologies that provide enough energy slaves to the common man that everyone lives a life that a king would have envied in times past.
So the question arises as to whether AI or the pursuit of AGI provides more or less energy slaves to the common man?
AI kinda breaks this; there is a real risk that human labor is going to become almost worthless this century, and this might mean that the common man ends up worse off despite nominal economic growth.
And not very long after, 93 per cent of those horses had disappeared.
I very much hope we'll get the two decades that horses did."
I'm reminded of the idiom "be careful what you wish for, as you might just get it." Rapid technogical change has historically lead to prosperity over the long term but not in the short term. My fear is that the pace of change this time around is so rapid that the short term destruction will not be something that can be recovered from even over the longer term.
4,500,000 in 1959
and even an increase to
7,000,000 in 1968
largely due to increase in recreational horse population.
https://time.com/archive/6632231/recreation-return-of-the-ho...
So that recreational existence at the leisure of our own machinery seems like an optional future humans can hope for too.
Turns out the chart is about farm horses only as counted by the USDA not including any recreational horses. So this is more about agricultural machinery vs. horses, not passenger cars.
---
City horses (the ones replaced by cars and trucks) were nearly extinct by 1930 already.
City horses were formerly almost exclusively bred on farms but because of their practical disappearance such breeding is no longer necessary. They have declined in numbers from 3,500,000 in 1910 to a few hundred thousand in 1930.
https://www2.census.gov/library/publications/decennial/1930/...
No one wants to say the scary potential logical conclusion of replacing the last value that humans have a competitive advantage in; that being intelligence and cognition. For example there is one future scenario of humanity where only the capital and resource holders survive; the middle and lower classes become surplus to requirements and lose any power. Its already happening slowly via inflation and higher asset prices after all - it is a very real possibility. I don't think a revolution will be possible in this scenario; with AI and robotics the rich could outnumber pretty much everyone.
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But would you rather be a horse in 1920 or 2020? Wouldn't you rather have modern medicine, better animal welfare laws, less exposure to accidents, and so on?
The only way horses conceivably have it worse is that there are fewer of them (a kind of "repugnant conclusion")...but what does that matter to an individual horse? No human regards it as a tragedy that there are only 9 billion of us instead of 90 billion. We care more about the welfare of the 9 billion.
I have met some transhumanists and longtermists who would really like to see some orders of magnitude increase in the human population. Maybe they wouldn't say "tragedy", but they might say "burning imperative".
I also don't think it's clearly better for more beings to exist rather than fewer, but I just want to assure you that the full range of takes on population ethics definitely exists, and it's not simply a matter of straightforward common sense how many people (or horses) there ought to be.
I think that it's true that governments want the efficiency gains but it's false that they don't anticipate the consumption increases. Nobody is spending trillions on datacenters without knowing that demand will increase, that doesn't mean we shouldn't make them efficient.
So I guess we should check to see if computers are good at scaling or doing things concurrently. If not, no worries!
Is it really possible to make this claim given the vast sums of money that have gone in to AI/LLM training?
Early factories were expensive, too (compared to the price of a horse), but that was never a show-stopper.
Cars went from a luxury to a necessity, though largely not until after WWII in the US, and somewhat later in other parts of the world.
There remain areas where a car is not required, or even a burden. NYC, and a few major metropolitan regions, as well as poorer parts of the world (though motorcycles and mopeds are often prevalent there).
Where did they go?
> I very much hope we'll get the two decades that horses did.
> But looking at how fast Claude is automating my job, I think we're getting a lot less.
This "our company is onto the discovery that will put you all out of work (or kill you?)" rhetoric makes me angry.
Something this powerful and disruptive (if it is such) doesn't need to be owned or controlled by a handful of companies. It makes me hope the Chinese and their open source models ultimately win.
I've seen Anthropic and OpenAI employees leaning into this rhetoric on an almost daily basis since 2023. Less so OpenAI lately, but you see it all the time from these folks. Even the top leadership.
Meanwhile Google, apart from perhaps Kilpatrick, is just silent.
Meanwhile, my own office is buried in busywork that there are currently no AI tools on the market that will do the work for us, and AI entering a space sometimes increases busywork workloads. For example, when writing descriptions of publications or listings for online sales, we have to put more effort now into not sounding like it was AI-generated or we will lose sales. The AI tools for writing descriptions / generating listings are not very helpful either. (An inaccurate listing/description is a nightmare.)
I was able to help set up a client with AI tools to help him generate basically a faux website in a few hours that has lots of nice graphic design, images, etc. so that his new venture looks like a real company. Well, except for the "About Us" page that hallucinated an executive team plus a staff of half a dozen employees. So I guess work like that does get done faster now.
And that really is the entire question at this point: Which domains will AI win in by a sufficient margin to be worth it?
This is an assumption for the best-case scenario, but I think you could also just take the marginal case. Steady progress builds until you get past the state of the art system, and then the switch becomes easy to justify.
1. The release of Claude Code in February
2. The release of Opus 4.5 two weeks ago
In both of these cases, it felt like no big new unlocks were made. These releases aren’t like OpenAI’s o1, where they introduced reasoning models with entirely new capabilities, or their Pro offerings, which still feel like the smartest chatbots in the world to me.
Instead, these releases just brought a new user interface, and improved reliability. And yet these two releases mark the biggest increases in my AI usage. These releases caused the utility of AI for my work to pass thresholds where Claude Code became my default way to get LLMs to read my code, and then Opus 4.5 became my default way to make code changes.
1. we aren’t good at building cars yet,
2. they break down so often that using horses often still ends up faster,
3. we have dirt tracks and feed stations for horses but have few paved roads and are not producing enough gasoline.
What exactly does specifically engine efficiency have to do with horse usage? Cars like the Ford Model T entered mass production somewhere around 1908. Oh, and would you look at the horse usage graph around that date! sigh
The chess ranking graph seems to be just a linear relationship?
> This pink line, back in 2024, was a large part of my job. Answer technical questions for new hires.
>
> Claude, meanwhile, was now answering 30,000 questions a month; eight times as many questions as me & mine ever did.
So more == better. sigh. Ran any, you know, studies to see the quality of those answers? I too can consult /dev/random for answers at a rate of gigabytes per second!
> I was one of the first researchers hired at Anthropic.
Yeah. I can tell. Somebody's high on their own supply here.
With this setup, you would need batteries that can sustain load for weeks on end, in many parts of the world.
And they often do it at the expense of the rest of us
The big thing this AI boom has showed us that we can all be thankful to have seen is what a human in a box will eventually look like. The first generation of humans to be able to see that is a super lucky experience to have.
Maybe it's one massive breakthrough away or maybe it's dozens away. But there is no way to predict when some massive breakthrough will occur Illya said 5-20 that really just means we don't know.
> Then in December, Claude finally got good enough to answer some of those questions for us.
What getting high on your own supply actually looks like. These are not the types of questions most people have or need answered. It's unique to the hiring process and the nascent status of the technology. It seems insane to stretch this logic to literally any other arena.
On top of that horses were initially replaced with _stationary_ gasoline engines. Horses:Cars is an invalid view into the historical scenario.
AI is like that, but instead with dudes in slim fitting vests blogging about alignment
> Then in December, Claude finally got good enough to answer some of those questions for us.
> … Six months later, 80% of the questions I'd been being asked had disappeared.
Interesting implications for how to train juniors in a remote company, or in general:
> We find that sitting near teammates increases coding feedback by 18.3% and improves code quality. Gains are concentrated among less-tenured and younger employees, who are building human capital. However, there is a tradeoff: experienced engineers write less code when sitting near colleagues.
https://pallais.scholars.harvard.edu/sites/g/files/omnuum592...
AI, faster please!
I don't think applies for general human intelligence - yet.
- Radical massive multimodality. We perceive the world through many wide-band high-def channels of information. Computer perception is nowhere near. Same for ability to "mutate" the physical world, not just "read" it.
- Being able to be fine-tuned constantly (learn things, remember things) without "collapsing". Generally having a smooth transition between the context window and the weights, rather than fundamental irreconcilable difference.
These are very difficult problems. But I agree with the author that the engine is in the works and the horses should stay vigilant.
I am not an AI sceptic.. I use it for coding. But this article is not compelling.
Glad I noticed that footnote.
Article reeks of false equivalences and incorrect transitive dependencies.
I really doubt horses would be ambivalent about this, let alone about anything. Or maybe I'm wrong, they were in two minds: oh dear I'm at risk of being put to sleep, or maybe it could lead to a nice long retirement out on a grassy meadow. But they're in all likelihood blissfully unaware.
This is the context wherein the valuation of AI companies makes sense, particularly those that already got a head start and have captured a large swath of that market.
Ambivalent??
Horses and cars had a clearly defined, tangible, measurable purpose: transport... they were 100% comparable as a market good, and so predicting an inflection point is very reasonable. Same with Chess, a clearly defined problem in finite space with a binary, measurable outcome. Funny how Chess AI replacing humans in general was never considered as a serious possibility by most.
Now LLMs, what is their purpose? What is the purpose of a human?
I'm not denying some legitimate yet tedious human tasks are to regurgitate text... and a fuzzy text predictor can do a fairly good job of that at less cost. Some people also think and work in terms of text prediction more often than they should (that's called bullshitting - not a coincidence).
They really are _just_ text predictors, ones trained on such a humanly incomprehensible quantity of information as to appear superficially intelligent, as far as correlation will allow. It's been 4 years now, we already knew this. The idea that LLMs are a path to AGI and will replace all human jobs is so far off the mark.
Anybody who tells you they can predict the future is shoveling shit in his mouth then smiling brown teeth at the audience. 10 years from now there's a real possibility of "AI" being remembered as that "stuff that almost got to a single 9 reliability but stopped there".
(A parenthetical comment explaining where he ballparked the measurements for himself, the "cheapest human labor," and Claude numbers would also have supported the argument, and some writers, especially web-focused nerd-type writers like Scott Alexander, are very good at this, but text explanations, even in parentheses, have a way of distracting readers from your main point. I only feel comfortable writing one now because my main point is completed.)
Also maybe go out for some fresh air. Maybe knowledge work will go down for humans, but plumbing and such will take much longer since we'll need dextrous robots.
The article is a Misanthropic advertisement. The "AI" mafia feels that no one wants their products and doubles down.
They are so desperate that Pichai is now talking about data centers in space on Fox News. Next up are "AI" space lasers.
TL;DR If your work is answer questions, that can be retrieved from a corpus of data with inverted index + embedding, you'll be obsolete pretty fast.
As the potential of AI technical agents has gone from an interesting discussion to extraordinarily obvious as to what the outcome is going to be, HN has comically shifted negative in tone on AI. They doth protest too much.
I think it's a very clear case of personal bias. The machines are rapidly coming for the lucrative software jobs. So those with an interest in protecting lucrative tech jobs are talking their book. The hollowing out of Silicon Valley is imminent, as other industrial areas before it. Maybe 10% of the existing software development jobs will remain. There's no time to form powerful unions to stop what's happening, it's already far too late.