&gt; It&#x27;s coming faster and harder than any tech in history.True; but how is that not expected?We have more and more efficient communication than any point in history, this is a software solution with a very low bar to the building blocks and theory.Software should be expected to move faster and faster.I’m not sure who is wishing it away. No one wanted to wish away search engines, or dictionaries or advice from people who repeat things they read.It’s panic top to bottom on this topic. Surely there are some adults around that can just look at a new thing for what it is now and not what it could turn into in a fantasy future?

1. The Segway had very low market penetration but a lot of PR. LLMs and diffusion models have had massive organic growth.2. Segways were just ahead of their time: portable lithium-ion powered urban personal transportation is getting pretty big now.

I think about the Segway a lot. It&#x27;s a good example. Man, what a wild time. Everyone was so excited and it was held in mystery for so long. People had tried it in secret and raved about it on television. Then... they showed it... and... well...I got to try one once. It was very underwhelming...

&gt; Remember ...No, I don&#x27;t remember it like that. Do you have any serious sources from history showing that Segway hype is even remotely comparable to today&#x27;s AI hype and the half a trillion a year the world is spending on it?You don&#x27;t. I love the argument ad absurdum more than most but you&#x27;ve taken it a teensy bit too far.

That was marketing done before the nature of the device was known. The situation with LLMs is very different, really not at all comparable.

I remember the Segway hype well. And I think AI is to Segway as nuke is to wet firecracker.

Oh yeah I totally remember Segway hitting a 300B valuation after a couple of years.

&gt; Remember the revolutionary, seemingly inevitable tech that was poised to rewrite how humans thought about transportation? The incredible amounts of hype, the secretive meetings disclosing the device, etc.? That turned out to be the self-balancing scooter known as a Segway?Counterpoint: That&#x27;s how I feel about ebikes and escooters right now.Over the weekend, I needed to go to my parent&#x27;s place for brunch. I put on my motorcycle gear, grabbed my motorcycle keys, went to my garage, and as I was about to pull out my BMW motorcycle (MSRP ~$17k), looked at my Ariel ebike (MSRP ~$2k) and decided to ride it instead. For short trips they&#x27;re a game changing mode of transport.

Trend vs single initiative. One company failed but overall personal electric transportation is booming is cities. AI is the future, but along the way many individual companies doing AI will fail. Cars are here to stay, but many individual car companies have and will fail, same for phones, everyone has a mobile phone, but nokia still failed…

ChatGPT has something 300 million monthly users after less than three years and I don&#x27;t think has Segway sold a million scooters, even though their new product lines are sick.I can totally go about my life pretending Segway doesn&#x27;t exist, but I just can&#x27;t do that with ChatGPT, hence why the author felt compelled to write the post in the first place. They&#x27;re not writing about Segway, after all.

The Segway hype was before anyone knew what it was. As soon as people saw the Segway it was obvious it was BS.

&gt; Ironically, this is exactly the technique for arguing that the blog mentions.So? The blog notes that if something is inevitable, then the people arguing against it are lunatics, and so if you can frame something as inevitable then you win the rhetorical upper-hand. It doesn&#x27;t -- however -- in any way attempt to make the argument that LLMs are _not_ inevitable. This is a subtle straw man: the blog criticizes the rhetorical technique of inevitabilism rather than engaging directly with whether LLMs are genuinely inevitable or not. Pointing out that inevitability can be rhetorically abused doesn&#x27;t itself prove that LLMs aren&#x27;t inevitable.

Ironically, this is exactly the technique for arguing that the blog mentions.Remember the revolutionary, seemingly inevitable tech that was poised to rewrite how humans thought about transportation? The incredible amounts of hype, the secretive meetings disclosing the device, etc.? That turned out to be the self-balancing scooter known as a Segway?

&gt; But if you told them about social media, I think the story would be different.It would be utopian, like how people thought of social media in the oughts. It&#x27;s a common pattern through human history. People lack the imagination to think of unintended side effects. Nuclear physics leading to nuclear weapons. Trains leading to more efficient genocide. Media distribution and printing press leading to new types of propaganda and autocracies. Oil leading to global warming. IT leading to easy surveillance. Communism leading to famine.Some of that utopianism is wilful, created by the people with a self-interested motive in seeing that narrative become dominant. But most of it is just a lack of imagination. Policymakers taking the path of local least resistance, seeking to locally (in a temporal sense) appease, avoiding high-risk high-reward policy gambits that do not advance their local political ambitions. People being satisfied with easy just-so stories rather than humility and a recognition of the complexity and inherent uncertainty of reality.AI, and especially ASI, will probably be the same. The material upsides are obvious. The downsides harder to imagine and more speculative. Most likely, society will be presented with a fait accompli at a future date, where once the downsides are crystallized and real, it&#x27;s already too late.

the idea that we could have a stilted and awkward conversation with an overconfident robot would not have surprised a typical mid-century science fiction consumer

&gt; Some would think it would be great, some would see it as dystopian, but neither would be right.No, the people saying it’s dystopian would be correct by objective measure. Bombs are nothing next to Facebook and TikTok.

If you told someone in 1950 that smartphones would dominate they wouldn&#x27;t have a hard time believing you. Hell, they&#x27;d add it to sci-fi books and movies. That&#x27;s because the utility of it is so clear.But if you told them about social media, I think the story would be different. Some would think it would be great, some would see it as dystopian, but neither would be right.We don&#x27;t have to imagine, though. All three of these things have captured people&#x27;s imaginations since before the 50&#x27;s. It&#x27;s just... AI has always been closer to imagined concepts of social media more than it has been to highly advanced communication devices.

Or Copilot.It&#x27;s actions like this that are making me think seriously about converting my gaming PC to Linux - where I don&#x27;t have to eat the corporate overlord shit.

what i like about your last jokey comment is that discussions about ai, both good and bad, are incredibly boringwent to some tech meetups earlier this year and when the topic came up, one of the organizers politely commented to me that pretty much everything said about ai has been said. the only discussions worth having are introductions to the tools then leaving an individual to decide for themselves whether or not its useful to them. those introductions should be brief and discussions of the applications are boringback in the bar scene days discussing work, religion, and politics were social faux pas. im sensing ai is on that list now

Literally from the article--- start quote ---Anyone who sees the future differently to you can be brushed aside as “ignoring reality”, and the only conversations worth engaging are those that already accept your premise.--- end quote ---Mass adoption is not inevitable. Everyone will drop this &quot;faster harder&quot; tech like a hot potato when (not if) it fails to result in meaningful profits.Oh, there will be forced mass adoption alright. Have you tried Gemini? Have you? Gemini? Have you tried it? HAVE YOU? HAVE YOU TRIED GEMINI?!!!

We might not be able to wish it away, but we can, as a society, decide to not utilize it and even actively eradicate it. I honestly believe that llm&#x27;s&#x2F;ai are a net negative to society and need to be ripped out root and stem. If tomorrow all of us decided to do that, nothing bad would happen, and we&#x27;d all be ok.

I still can&#x27;t make some of the things in my imagination so I&#x27;m going to keep coding, using whatever is at my disposal including LLMs if I must.

None of the &quot;failed&quot; innovations you cited were even near the adoption rate of current LLMs.As much as I don&#x27;t like it, this is the actual difference. LLMs are already good enough to be a very useful and widely spread technology. They can become even better, but even if they don&#x27;t there are plenty of use cases for them.VR&#x2F;AR, AI in the 80s and Tesla at the beginning were technology that someone believe could become widespread, but still weren&#x27;t at all.That&#x27;s a big difference

The people claiming that AI in the 80s or VR or robotaxis or self-driving cars in the 2010s were inevitable weren&#x27;t doing it on the basis of the tech available at that point, but on the assumed future developments. Just a little more work and they&#x27;d be useful, we promise. You just need to believe hard enough.With the smartphone in 2009, the web in the late 90s or LLMs now, there&#x27;s no element of &quot;trust me, bro&quot; needed. You can try them yourself and see how useful they are. You didn&#x27;t need to be a tech visionary to predict the future when you&#x27;re buying stuff from Amazon in the 90s, or using YouTube or Uber on your phone in 2009, or using Claude Code today. I&#x27;m certainly no visionary, but both the web and the smartphone felt different from everything else at the time, and AI feels like that now.

<a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=zhr6fHmCJ6k" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=zhr6fHmCJ6k</a> (1min video, &#x27;Elon Musk&#x27;s broken promises&#x27;)Musk&#x27;s 2014&#x2F;2015 promises are arguably delivered, here in 2025 (took a little more than &#x27;1 month&#x27; tho), but the promises starting in 2016 are somewhere between &#x27;undelivered&#x27; and &#x27;blatant bullshit&#x27;.

&gt;Tesla stock has been riding on the self driving robo-taxies meme for a decade nowWe do have self-driving taxis now, and they are so good that people will pay extra to take them. It&#x27;s just not Tesla cars doing it.

&gt; Cherrypicking the stuff that worked in retrospect is stupid, plenty of people swore in the inevitability of some tech with billions in investment, and industry bubbles that look mistimed in hindsight.But that isn&#x27;t the argument. The article isn&#x27;t arguing about something failing or succeeding based on merit, they seem to have already accepted strong AI has &quot;merit&quot; (in the utility sense). The argument is that despite the strong utility incentive, there is a case to be made that it will be overall harmful so we should be actively fighting against it, and it isn&#x27;t inevitable that it should come to full fruition.That is very different than VR. No-one was trying to raise awareness of the dangers of VR and fight against it. It just hasn&#x27;t taken off because we don&#x27;t really like it as much as people thought we would.But for the strong AI case, my argument is that it is virtually inevitable. Not in any predestination sense, but purely because the incentives for first past the post are way too strong. There is no way the world is regulating this away when competitive nations exist. If the US tries, China won&#x27;t, or vice versa. It&#x27;s an arms race, and in that sense is inevitable.

What are you on? The only potential is AR? What?!!! The problem is AR is not enough innovation and high cost. That&#x27;s not the case with AI. All it needs is computing, not some ground breaking new technology.

If you claimed that AI was inevitable in the 80s and invested, or claimed people would be inevitably moving to VR 10 years ago - you would be shit out of luck. Zuck is still burning billions on it with nothing to show for it and a bad outlook. Even Apple tried it and hilariously missed the demand estimate. The only potential bailout for this tech is AR, but thats still years away from consumer market and widespread adoption, and probably will have very little to do with shit that is getting built for VR, because its a completely different experience. But I am sure some of the tech&#x2F;UX will carry over.Tesla stock has been riding on the self driving robo-taxies meme for a decade now ? How many Teslas are earning passive income while the owner is at work ?Cherrypicking the stuff that worked in retrospect is stupid, plenty of people swore in the inevitability of some tech with billions in investment, and industry bubbles that look mistimed in hindsight.

Well there are like 500 nuclear powerplants online today supplying 10% of the world&#x27;s power, so it wasn&#x27;t too far off. Granted it&#x27;s not the Mr. Fusion in every car as they imagined it back then. We probably also won&#x27;t have ASI taking over the world like some kind of vengeful comic book villain as people imagine it today.

The comparison is apt because nuclear would have been inevitable if it wasn&#x27;t for doomerism and public opinion turning against it after 3 mile Island &#x2F; Chernobyl

Back in 1950s nuclear tech was seen as inevitable. Many people had even bought plates made from uranium glass. They still glow somewhere in my parents&#x27; cabinet or maybe I broke them

We haven&#x27;t even barely extracted the value from the current generation of SOTA models. I would estimate less then 0.1% of the possible economic benefit is currently extracted, even if the tech effectively stood still.That is what I find so wild about the current conversation and debate. I have claude code toiling away building my personal organization software right now that uses LLMs to take unstructured input and create my personal plans&#x2F;project&#x2F;tasks&#x2F;etc.

Big Tech can jam X everywhere and not get actual adoption though, it&#x27;s not magic. They can nudge people but can&#x27;t force them to use it. And yes a lot of AI jammed everywhere is getting the Clippy reaction.

Feels somewhat like a self fulfilling prophecy though. Big tech companies jam “AI” in every product crevice they can find… “see how widely it’s used? It’s inevitable!”I agree that AI is inevitable. But there’s such a level of groupthink about it at the moment that everything is manifested as an agentic text box. I’m looking forward to discovering what comes after everyone moves on from that.

And with everyone constantly touting robotics as the next next frontier, every blue collar job as well.

For the way you speak you seem to be fairly certain that they still gonna need you as it&#x27;s user, that they aren&#x27;t going to find a better monetization than selling it to people like you (or even small companies in general), I wouldn&#x27;t be so sure, remember we are talking about the machine that is growing with the aim of being able to do do every single white-collar job.

That&#x27;s how people probably felt about the first cars, the first laptops, the first &lt;anything&gt;.People like you grumbled when their early car broke down in the middle of a dirt road in the boondocks and they had to eat grass and shoot rabbits until the next help arrived. &quot;My horse wouldn&#x27;t have broken down&quot;, they said.Technologies mature over time.

I’ve tried to use AI for “real work” a handful of times and have mostly come away disappointed, unimpressed, or annoyed that I wasted my time.Given the absolutely insane hard resource requirements for these systems that are kind of useful, sometimes, in very limited contexts, I don’t believe its adoption is inevitable.Maybe one of the reasons for that is that I work in the energy industry and broadly in climate tech. I am painfully aware of how much we need to do with energy in the coming decades to avoid civilizational collapse, and how difficult all of that will be, without adding all of these AI data centers into the mix. Without several breakthroughs in one or more hard engineering disciplines, the mass adoption of AI is not currently physically possible.

If you are seriously equating these two with AI, then you have horrible judgements and should learn to think critically, but unfortunately for you, I don&#x27;t think critical thinking can be learned despite what people say.Note that I&#x27;m not even going to bother arguing against your point and instead resort to personal attacks,because I believe it would be a waste of time to argue against people with poor judgment.

they said the same about VR glasses, about cryptocurrency ...

Chatgpt Has 800 million weekly active users. That&#x27;s roughly 10% of the planet.I get that it&#x27;s not the panacea some people want us to believe it is, but you don&#x27;t have to deny reality just because you don&#x27;t like it.

&gt; Most people except for the gamers and plagiarists don&#x27;t want it.As someone who doesn&#x27;t actually want or use AI, I think you are extremely wrong here. While people don&#x27;t necessarily care about the forced integrations of AI into everything, people by and large want AI massively.Just look at how much it is used to do your homework, or replaces Wikipedia &amp; Google in day to day discussions. How much it is used to &quot;polish&quot; emails (spew better sounding BS). How much it is used to generate meme images instead of trawling the web for them. AI is very much a regular part of day to day life for huge swaths of the population. Not necessarily in economically productive ways, but still very much embedded and unlikely to be removed - especially since it&#x27;s current capabilities today are already good enough for these purposes, they don&#x27;t need smarter AI, just keep it cheap enough.

Smartphones are different. People really wanted them since the relatively primitive Nokia Communicator.&quot;AI&quot; was introduced as an impressive parlor trick. People like to play around, so it quickly got popular. Then companies started force-feeding it by integrating it into every existing product, including the gamification and bureaucratization of programming.Most people except for the gamers and plagiarists don&#x27;t want it. Games and programming fads can fall out of fashion very fast.

It&#x27;s weird noone can measure and show us the numbers of this ultimate advantage. Is &quot;ultimate advantage&quot; in the room right now?

Exactly. Anyone who has learned to use these tools to your ultimate advantage (not just short term perceived one, but actually) knows their value.This is why I&#x27;ve been extremely suspicious of the monopolisation of the LLM services by single business&#x2F;country. They may well be loosing billions on training huge models now. But once the average work performance shifts up sufficiently so as to leave &quot;non AI enhanced&quot; by the wayside we will see huge price increases and access to these AI tools being used as geopolitics leverage.Oh, you do not want to accept &quot;the deal&quot; where our country can do anything in your market and you can do nothing? Perhaps we put export controls on GPT5 against your country. And from then on its as if they disconnected you from the Internet.For this reason alone local AI is extremely important and certain people will do anything possible to lock it in a datacenter (looking at you Nvidia).

Except there is a perverse dynamic in that the more AI&#x2F;LLM is used, the less it will be used.

While we can&#x27;t wish it away we can shun it, educate people why it shouldn&#x27;t be used, and sabotage efforts to included it in all parts of society.

&gt; If in 2009……is exactly inevitablist framing. This claims perfect knowledge of the future based on previous uncertain knowledge of the future (which is now certain). You could have been making the same claims about the inevitability of sporks in the late 19th century and how cutlery drawers should adapt to the inevitable single-utensil future.

If in 2009 you claimed that the dominance of the smartphone was inevitable, it would have been because you were using one and understood its power, not because you were reframing away our free choice for some agenda. In 2025 I don&#x27;t think you can really be taking advantage of AI to do real work and still see its mass adaptation as evitable. It&#x27;s coming faster and harder than any tech in history. As scary as that is we can&#x27;t wish it away.

Those machines unlocked more work, different work, that led to better paying jobs!I am all up for AI if it leads to &quot;better&quot; work and jobs but cutting jobs to cut cost sound like a race to bottom!!Are AI time
&#x2F;cost savings going to help me pursue creative hobbies, open source, help my community without worrying about livelihood then great. If it is a means to make rich people richer by making most of us worse off, maybe we should stop and think for a while?There may be a risk here that a zero&#x2F;negative-sum game is advertised as a positive-sum game (e.g war).

Yes, of course. What is AI freeing us of? Communicating with other human beings?Ah what a chore. Other human beings. Wish I could just enter into a cocoon of solitude for the rest of my life. I mean I&#x27;m kind of being glib here but the ~amazing future~ we all seem to take as inevitable has me playing solo orchestra conductor, prompt pupettering a massive fleet of hyper intelligent code bots, prompting an AI to make prompts for its sub AIs in a giant scintillating cyberprism. Talking to an AI customer service agent. Having an AI secretary. Having an AI lover.All alone, in the middle of it all.Sorry, I actually like talking to my real human colleagues!

What a fascinatingly out-of-touch comment.

Just remember that machines already do most of the work. Nobody ploughs fields anymore.

Billions will die from starvation and conflict in that future. Be careful what you wish for.

I&#x27;m just hoping for a huge solar flare to reset this once and for all.

These senate hearings are happening right now.There is no moment in history when we all look back and go, ah, that was a mistake. Nope. That only happens right now, we&#x27;re all creating the world we want to live in today.

I am more and more convinced that social networks are causing the increased political instability and breakdown of communication. In the past media was centralized. So the powers that be focused on it and controlled the message. We had a kind of common understanding and language. Some idealize BBC or the great newspapers of the past, but they have been lying to us since forever. Remember the WMD discussions leading to Iraq war?But now, because everyone can publish, they lost control. So instead they are bombarding us with all sorts of contradictory theories and conspiracies. We have come to be unable to communicate. And maybe that is the intended goal. If you can&#x27;t control the message, make communication itself worthless. People choose emotionally and based on tribal allegiances. It has become an identity war. We can&#x27;t even communicate with our parents now, there is an &quot;explanatory gap&quot; between identity tribes.

Oh but they realize. They just don&#x27;t care because they (the Elites, the wealthy, who are the real decisionmakers, not the politicians) have enough money to never have to interact with the proletariat, the common man, ever again. Enough money to be shielded from the consequences from their actions.

The issue, unfortunately, is that society has failed to recognize the real dangers of social technologies (social media, social AI, perhaps AI in general). 30 years from now if we&#x27;re lucky, we&#x27;ll be watching senate hearings with AI billionaires being asked how they didn&#x27;t realize their products were so harmful.

My intellectual strategy to get to the bottom of these grand questions is very straightforward: look at my own life and evaluate what’s important.In my life, I have found the answer to these questions. Telling a joke and making a colleague laugh. Looking at my 1yo niece crawling toward me. Hanging out in the garden with my wife and my dogs.I look at these things, and it’s just so obvious. AI boyfriends? Ai email readers or AI taxi drivers or AI app makers? I can talk to a Tesla robot behind the counter at Wendy’s instead of a bored teenager? And that’s gonna ~transform~ my life? What?You are right to point out that these questions are not adequately resolved. They never will be, not in the abstract and certainly not by technology. In some sense this dialogue has been happening for thousands of years, starting with Plato or before. “What is the point?”When I was younger I used to wonder a lot intellectually about this stuff as many do but I’ve realized pretty recently that the answer is right here in my own short life and it has god damn nothing to do with technology.I like solving puzzles and programming and I have a half built robot in the garage. But I will never confuse that with my living breathing niece. They just aren’t the same, my god isn’t it obvious!?&gt; now we&#x27;re trying to create AGI by turning humans into robotsVery succinctly put.

&gt;Because many of us working on AI were working on it for different reasons. To me, it was to liberate us. To let me go spend more time outside, to stare at trees, and ask people &quot;can I pet your dog?&quot;If you think automation or any other increase in productivity is passed back down to workers, then I&#x27;d say I have a bridge to sell you, but you probably already bought 5 of them.

It&#x27;s insane too. Because many of us working on AI were working on it for different reasons. To me, it was to liberate us. To let me go spend more time outside, to stare at trees, and ask people &quot;can I pet your dog?&quot;We use language and images because they are easier to evaluate. Because we don&#x27;t know what to actually evaluate. So it&#x27;s as good of a direction as any, right?I&#x27;m not sure if another direction would have had a different result. But it feels like now we&#x27;re trying to create AGI by turning humans into robots. It can create works of art, poetry, music, but it has no soul, no depth.This should tell us that we&#x27;ve still have a long way to go to make AGI, that this ineffable depth needs further exploration. To learn what it truly means to be human (which definitely requires time outside). But I feel many of my peers do not want to see this. It feels like I&#x27;m being gaslight. It&#x27;s like everyone is raving about the genius of Rauschenberg&#x27;s White Paintings [3 panel], and I see a canvas waiting to be filled. Am I really so out of touch? To think it weird to talk about the &quot;gospel&quot; of Ilya or Karpathy? It seems everyone has found religion&#x2F;god, but me.I can see the beauty of a sunset, of a crashing wave, of the complexity of the atom so delicately constructed, the abstraction and beauty of math, but maybe I just do not have a refined enough taste to appreciate the genius of a blank canvas with no soul. Is not the beauty in what it can become? Because I thought the point was to make life. I thought the point was to give it a soul.

I agree with you wholeheartedly. I feel the same way, though I want to nit with one point you made:&gt; but at least we’ll all have a ton of money?I just don’t see it going that way. The only ones that are going to win if this stuff actually makes it out of the primordial AI swamp are the ones training and running the models. It’s like any other capitalistic thing, the ones owning the means (the models and infrastructure and whatnot) make all the money.The only thing I see in all of this is widening the wealth gap. Sure, there may be some performative, pity pennies thrown in the direction of a lucky few, to keep the envy alive, but it’s just going to enable amassing more and more wealth and resources to those that already have a pile of gold too large to spend even in one hundred thousand lifetimes.I’ll tend to my tomatoes.

I don’t think we will all have a ton of money in that Blade Runner future unless you mean everything will have inflated like Zimbabwe dollars, and that may be the case.

If it&#x27;s any consolation, living in Blade Runner will be optional! You&#x27;ll also have the option of living in full-dive VR where it&#x27;s permanently 1999. No AI in sight, just print outs of MapQuest directions.

Well, some people will have a ton of money

Surely the fact that you&#x27;re on hackerNEWS does not imply that you like all the news?

Imagine that...real people with different values, some of whom even prefer unmediated reality, and on a site called Hacker News?

You hate AI and want to go outside and stare at a tree? How are posts like this on HACKERnews? What is the point of all these types of posts on a site that is literally about hacking technology?

&gt;They spend 18 hours a day in conversation with chatbots.Engagement metrics like that are what product managers love to see. Promotions incoming. &#x2F;sSad to see it, but I believe these &quot;companions&quot; and &quot;spiritual gurus&quot; will generate the most revenue in B2C. If you have a user base that&#x27;s on the slop drip 24&#x2F;7, you can make them pay premium and target them with ads at the same time. The trend is already here: people listen to podcasts, follow influencers and streamers on every platform just for the surrogate friendship effects. Why not automate it away and make the spiritual guru bot sell you the next vpn subscription?

I hate AI. I&#x27;m so sick of it.I read a story about 14 year olds that are adopting AI boyfriends. They spend 18 hours a day in conversation with chatbots. Their parents are worried because they are withdrawing from school and losing their friends.I hate second guessing emails that I&#x27;ve read, wondering if my colleagues are even talking to me or if they are using AI. I hate the idea that AI will replace my job.Even if it unlocks &quot;economic value&quot; -- what does that even mean? We&#x27;ll live in fucking blade runner but at least we&#x27;ll all have a ton of money?I agree, nobody asked what I wanted. But if they did I&#x27;d tell them, I don&#x27;t want it, I don&#x27;t want any of it.Excuse me, I&#x27;ll go outside now and play with my dogs and stare at a tree.

&gt; do not get to define our future simply because they have more moneyI don&#x27;t like it, but it seems that more money is exactly why they get to define our future.

Would you say the industrial revolution would have been able to be stopped by enough humans not wanting to achieve it?&gt;The unstated premise of this essay is that venture capital and oligarchs do not get to define our future simply because they have more money.AI would progress without them. Not as fast, but it would.In my mind the inevitability of technological progress comes from our competition with each other and general desire do work more easily and effectively. The rate of change will increase with more resources dedicated to innovation, but people will always innovate.

Things “happen” in human history only because humans make them happen. If enough humans do or don’t want something to happen, then they can muster the collective power to achieve it.The unstated corollary in this essay is that venture capital and oligarchs do not get to define our future simply because they have more money.

But the claim is not &quot;it&#x27;s going to happen&quot;, the claim is &quot;it is inevitable that it will happen&quot;, which is a much more stronger claim.

I think you are confusing &quot;I don&#x27;t like it&quot; with &quot;It&#x27;s not going to happen&quot;.Just because you don&#x27;t like it, it doesn&#x27;t mean it&#x27;s not going to happen.Observe the world without prejudice. Think rationally without prejudice.

If someone invested a lot of money in something, they probably are convinced that something is inevitable. Otherwise they would not invest their money. However, sometimes they may be a little bit helping their luck

Isn&#x27;t that what was said about the next year, the last two years?

2026 will be the year that defines AI, and whether it lives up to the hype

There&#x27;s plenty of examples where important people framed an inevitable future and then it didn&#x27;t pan out.Somewhat objective proof of &quot;progress&quot; will inevitably win out, yes inevitable framing might help sell the vision a bit, for now, but it won&#x27;t be the inevitabism that causes it to succeed but its inherit value towards &quot;progress&quot;.The definition of &quot;progress&quot; being endlessly more productive humans at the cost of everything else.

The majority of the comments here reflect an acceptance of or even an enthusiasm for an LLM-using future. An embracing of the technology regardless of its downsides. A disregard of those who question whether it’s all a desirable future.I’d have thought perhaps we’d learn the lessons of eg. smart phones, social media, cloud, VR, crypto, NFTs, etc, and think a little more deeply about where and how we want to go as a society and species beyond just adopting the latest hype.

We have no idea how they work. We know the training making a model and generating things from it, but the thing we want from it being an Oracle or something, we have no idea how that works at the level of the specific knowledge it generates. And when we dig into it doesn&#x27;t reveal anything very interesting. The premise of put everything digital in a pile and see if makes something like a god is a neat idea, but the god is literally playing dice.

&gt; I’m certainly not convinced that they’re the future I want. But what I’m most certain of is that we have choices about what our future should look like, and how we choose to use machines to build it.While I must admit we have some choice here, it is limited. No matter what, there will be models of language, we know how they work, there is no turning back from it.We might wish many things but one thing we can&#x27;t do is to revert time to a moment when these discoveries did not exist.

It&#x27;s as inevitable as the cotton gin, which ironically I just saw some news on how the Chinese continue to improve it, which will be the same for AI.

John Gray the philosopher expands on this by saying that Progress as a whole is thought of as inevitable. The last couple of years I think have shown the cracks in this thinking. Western notions of progress, the liberal movement to increase and improve humanity is actually something to be activiely fought for, it&#x27;s not something that will organically happen. It&#x27;s not a human right. But that&#x27;s what we are told: &quot;the right side of history&quot; is the framing.People today think progress is a natural thing. That it&#x27;s inevitable that human rights increase, the individual liberty increases, that my self expression becomes more secure with time, naturally. We still see this inevitablism in culture and politics.That the political inevitablists don&#x27;t see the history and origins of progress and liberalism (e.g. partly Christianity) is part of the diagnosis.We might see parallels with AI. We might see anti-AI stances equated to those who want to take away personal autonomy (e.g. &quot;to claim I cannot have an AI boyfriend means you are advocating for violence against me&quot;).One has to actively defend and campaign for these things and not fall into a sense of it&#x27;s all natural and inevitable.Inevitability is a kind of psychological blindness. It&#x27;s to be encouraged in some as it does actually work but it can give some pain when sight is restored.

This is the same strategy Hillary Clinton supporters tried to use too. The author is right, it&#x27;s just a framing technique. We can choose the future we want.

&gt; For example, I love Cursor. Especially for boilerplating. But SOTA models with tons of guidance can still not reliably implement features in my larger codebases within the timeframe it would take me to do it myself. Test-time compute and reasoning makes things even slower.Importantly it also takes you guiding it to complete the task. Meaning you still need to pay a human and the cost of the LLM, so it&#x27;s slower and a bit more expensive.I am not convinced either that AI working on complex programming tasks could be guided by less skilled devs, meaning you still need to pay the skilled dev.In my experience so far, the cost analysis doesn&#x27;t work for more complex application development. Even if the cost of the LLM was free it is often wasting the skilled dev&#x27;s time.All these metrics will change over the years and maybe the math works out eventually, or in specific circumstances, and I forsee LLMs assisting in development into the future.I am not seeing the cataclysmic wholesale replacement of humans in the workforce some are predicting, at this stage.

It’s also possible for LLMs to be inevitable, generate massive amounts of wealth and still be mostly fluff in terms of objective human progress.The major change from my perspective is new consumer behavior: people simply enjoy talking to and building with LLMs. This fact alone is generating a lot (1) new spend and (2) content to consume.The most disappointing outcome of the LLM era would be increasing the amount of fake, meaningless busywork humans have to do just to sift through LLM generated noise just to find signal. And indeed there are probably great products to be built that help you do just that; and there is probably a lot of great signal to be found! But the motion to progress ratio concerns me.For example, I love Cursor. Especially for boilerplating. But SOTA models with tons of guidance can still not reliably implement features in my larger codebases within the timeframe it would take me to do it myself. Test-time compute and reasoning makes things even slower.

Lots of crypto boosters said that crypto had use cases beyond grift and that anyone who couldn’t see that was a moron.

Also I’m going to go ahead and say that “it’s slightly better than classical NLP for grammar check but requires 10,000x as much compute resources” is not an improvement

I never really get the cryptocurrency comparison. AI has an application beyond grift. Like, even if they stopped developing it now, an AI “style hints” in the style of spellcheck and grammar rule check would be a no-brainer as a thing to add to an office suite.The valuations are totally and completely nuts. But, LLMs have little legitimate applications in a way that cryptocurrencies never will.

Maybe not crypto, but LISP machine was gonna change the world for sure.<a href="https:&#x2F;&#x2F;en.m.wikipedia.org&#x2F;wiki&#x2F;Lisp_machine" rel="nofollow">https:&#x2F;&#x2F;en.m.wikipedia.org&#x2F;wiki&#x2F;Lisp_machine</a><a href="https:&#x2F;&#x2F;en.m.wikipedia.org&#x2F;wiki&#x2F;AI_winter" rel="nofollow">https:&#x2F;&#x2F;en.m.wikipedia.org&#x2F;wiki&#x2F;AI_winter</a>

Wasn’t crypto supposed to have replaced fiat currency by now, or something?

Yeah, I can&#x27;t wait for this slop generation hype circlejerk to end either. But in terms of being used by people who don&#x27;t care about quality, like scammers, spammers, blogspam grifters, people trying to affect elections by poisoning the narrative, people shitting out crappy phone apps, videos, music, &quot;art&quot; to grift some ad revenue, gen AI is already the perfect product. Once the people who do care wake up and realise gen AI is basically useless to them, the internet will already be dead, we&#x27;ll be in a post-truth, post-art, post-skill, post-democracy world and the only people whose lives will have meaningfully improved are some billionaires in california who added some billions to their net worth.It&#x27;s so depressing to watch so many smart people spend their considerable talents on the generation of utter garbage and the erosion of the social fabric of society.

The more I learn about prompt engineering the more complex it seems to be, but perhaps I&#x27;m an idiot.

A couple of typical comments about LLMs would be:&quot;This LLM is able to capably output useful snippets of code for Python. That&#x27;s useful.&quot;and&quot;I tried to get an LLM to perform a niche task with a niche language, it performed terribly.&quot;I think the right synthesis is that there are some tasks the LLMs are useful at, some which they&#x27;re not useful at; practically, it&#x27;s useful to be able to know what they&#x27;re useful for.Or, if we trust that LLMs are useful for all tasks, then it&#x27;s practically useful to know what they&#x27;re not good at.

The sad thing is that it seems to work. Lots of people are falling for the &quot;you&#x27;re holding it wrong&quot; narrative.

Unless you have automated fine-tuning pipelines that self-optimize optimize models for your tasks and domains, you are not even close to utilizing LLMs to their potential. But stating that you don’t need extensive, specialized skills is enough of a signal for most of us to know that offering you feedback would be fruitless. If you don’t have the capacity by now to recognize the barrier to entry, experts are not going to take the time to share their solutions with someone unwilling to understand.

&gt; Or it might just be astroturfing, it&#x27;s hard to tell.Compare the hype for commercial SaaS models to say Deepseek. I think there is an insane amount of astroturfing.

It&#x27;s probably not astroturfing, or at least not all astroturfing. At least some software engineers tend to do this. We&#x27;ve seen it before, with Lisp, and then with Haskell. &quot;It doesn&#x27;t work for you? You just haven&#x27;t tried it for long enough to become enlightened!&quot; Enthusiastic supporters that assume that if was highly useful for them, it must be for everyone in all circumstances, and anyone who disagrees just hasn&#x27;t been enlightened yet.

Simple thought I had reading this:I&#x27;ve used a tool to do a task today. I used a suction sandblasting machine to remove corrosion from a part.Without the tool, had I wanted to remove the corrosion, I would&#x27;ve spent all day (if not more) scraping it with sandpaper (is that a tool too? With the skin of my hands then?) - this would have been tedious and could have taken me all day, scraping away millimeter by millimeter.With the machine, it took me about 3 minutes. I necessitated 4-5 minutes of training to attain this level of expertise.The worth of this machine is undeniable.How is it that LLMs are not at all so undeniably efficient? I keep hearing people tell me how they will take everyones job, but it seems like the first faceplant from all the big tech companies.(Maybe second after Meta&#x27;s VR stuff)

&gt; Look for frantic efforts by companies to offload responsibility for LLM mistakes onto consumers.Not just by companies. We see this from enthusiastic consumers as well, on this very forum. Or it might just be astroturfing, it&#x27;s hard to tell.The mantra is that in order to extract value from LLMs, the user must have a certain level of knowledge and skill of how to use them. &quot;Prompt engineering&quot;, now reframed as &quot;context engineering&quot;, has become this practice that separates anyone who feels these tools are wasting their time more than they&#x27;re helping, and those who feel that it&#x27;s making them many times more productive. The tools themselves are never the issue. Clearly it&#x27;s the user who lacks skill.This narrative permeates blog posts and discussion forums. It was recently reinforced by a misinterpretation of a METR study.To be clear: using any tool to its full potential does require a certain skill level. What I&#x27;m objecting to is the blanket statement that people who don&#x27;t find LLMs to be a net benefit to their workflow lack the skills to do so. This is insulting to smart and capable engineers with many years of experience working with software. LLMs are not this alien technology that require a degree to use correctly. Understanding how they work, feeding them the right context, and being familiar with the related tools and concepts, does not require an engineering specialization. Anyone claiming it does is trying to sell you something; either LLMs themselves, or the idea that they&#x27;re more capable than those criticizing this technology.

&gt; People can&#x27;t be trusted to do anything either, which is why we have guardrails and checks and balances and audits. That is why in software, for instance, we have code reviews and tests and monitoring and other best practices. That is probably also why LLMs have made the most headway in software development; we already know how to deal with unreliable workers that are humans and we can simply transfer that knowledge over.The difference is that humans eventually learn. We accept that someone who joins a team will be net-negative for the first few days, weeks, or even months. If they keep making the same mistakes that were picked out in their first code review, as LLMs do, eventually we fire them.

People can&#x27;t be trusted to do anything either, which is why we have guardrails and checks and balances and audits. That is why in software, for instance, we have code reviews and tests and monitoring and other best practices. That is probably also why LLMs have made the most headway in software development; we already know how to deal with unreliable workers that are humans and we can simply transfer that knowledge over.As was discussed on a subthread on HN a few weeks ago, the key to developing successful LLM applications is going to be figuring out how to put in the necessary business-specific guardrails with a fallback to a human-in-the-loop.

Are models capable of generating citations? Every time I&#x27;ve asked for citations on ChatGPT they either don&#x27;t exist or are incorrect.

I think that if LLMs have any future, it is this. The LLM will only be a user interface to a system that on the back end is deterministic and of consistent quality, i.e., a plain old computer program.

We need to put the LLMs inside systems that ensure they can only do correct things.Put an LLM on documentation or man pages. Tell the LLM to output a range of lines, and the system actually looks up those lines and quotes them. The overall effect is that the LLM can do some free-form output, but is expected to provide a citation to support its claims; and the citation can&#x27;t be hallucinated, since the LLM doesn&#x27;t generate the citation, a plain old computer program does.And we haven&#x27;t seen LLMs integrated with type systems yet. There are very powerful type systems, like dependent types, that can prove things like &quot;this function returns a list of sorted number&quot;, and the type system ensures that is ALWAYS true [0], at compile time. You have to write a lot of proof code to help the compiler do these checks at compile time, but if a LLM can write those proofs, we can trust they are correct, because only correct proofs will compile.[0]: Or rather, almost always true. There&#x27;s always the possibility of running out of memory or the power goes out.

What literally useful functions worth the trillions needed for ROI are you talking about? What are the numbers? How did you measure it? Please share!

I find these LLM doomer takes as silly as LLM maximalist takes.LLMs are literally performing useful functions today and they&#x27;re not going away. Are they AGI? No, but so what?There is waaay too much projecting and philosophizing going on in these comments and not enough engineering-minded comments from objective observers.Is AI hyped? Sure. Are LLMs overshadowing other approaches? Sure. Are LLMs inefficient? Somewhat. Do they have problems like hallucinations? Yes. Do they produce useful output? Yes.

We may be underestimating the effort that goes into cleaning up LLM messes. LLMs learn to program from code bases written by humans. Not just written by humans, maintained by humans. So the bugs that humans spot and remove are under-represented in the training data. Meanwhile, the bugs that evade human skill at debugging lurk indefinitely and are over-represented in the training data.We have created tools to write code with bugs that humans have difficulty spotting. Worse, we estimate the quality of the code that our new tools produce on the basis that they are inhuman and have no special skill at writing bugs that we cannot spot, despite the nature of their training data.

I think this a big side effect of the field moving way too fast for it to be evaluated properly. I don&#x27;t recall seeing such a big rally in the CS research like this. Nearly every group I know that tackled really totally different topics are converging to LLMs. Talk about eco-diversity in the CS reaearch, all that is reduced now, LLMs are the palm trees of this field now.

There may be an &quot;LLM Winter&quot; as people discover that LLMs can&#x27;t be trusted to do anything. Look for frantic efforts by companies to offload responsibility for LLM mistakes onto consumers. We&#x27;ve got to have something that has solid &quot;I don&#x27;t know&quot; and &quot;I don&#x27;t know how to do this&quot; outputs. We&#x27;re starting to see reports of LLM usage having negative value for programmers, even though they think it&#x27;s helping.
Too much effort goes into cleaning up LLM messes.

I do agree that those who claim AI is inevitable are essentially threatening you.

Well many have come true, a few have not. As someone who gets vertigo from headsets, I’m a VR skeptic. But his AI predictions are pretty much spot on

What is your take on the outcome of his predictions?

The book I’m currently reading-Kevin Kelly’s The Inevitable-feels pretty ironic given this post

This concept is closely reated to politics of inevitability coined by Timothy Snyder.&quot;...the politics of inevitability – a sense that the future is just more of the present, that the laws of progress are known, that there are no alternatives, and therefore nothing really to be done.&quot;[0][0] <a href="https:&#x2F;&#x2F;www.theguardian.com&#x2F;news&#x2F;2018&#x2F;mar&#x2F;16&#x2F;vladimir-putin-russia-politics-of-eternity-timothy-snyder" rel="nofollow">https:&#x2F;&#x2F;www.theguardian.com&#x2F;news&#x2F;2018&#x2F;mar&#x2F;16&#x2F;vladimir-putin-...</a>This article in question obviously applied it within the commercial world but at the end it has to do with language that takes away agency.

Calling LLMs trivial is a new one. Yea just consume all of the information on the internet and encode it into a statistical model, trivial, child could do it &#x2F;s

Imagine telling a person from five years ago that the programs that would basically solve NLP, perform better than experts at many tasks and are hard not to anthropomorphize accidentally are actually &quot;trivial&quot;. Good luck with that.

LLM can give you thousands of lines of perfectly working code for less than 1 dollar. How is that trivial or expensive?

But the thing is, LLMs are already incredibly cheap to operate compared to the alternatives. Both for trivial things and for complex things.

LLMs need significant optimization or we get significant improvement on computing power while keeping the energy cost the same. It&#x27;s similar with smartphone, when at the start it&#x27;s not feasible because of computing power, and now we have one that can rival 2000s notebooks.LLMs is too trivial to be expensiveEDIT: I presented the statement wrongly. What I mean is the use case for LLM are trivial things, it shouldn&#x27;t be expensive to operate

Every booster argument is like this one. $trite_analogy triumphant smile

&gt; Developers haven&#x27;t even started extracting the value of LLMs with agent architectures yetThere are thousands of startups doing exactly that right now, why do you think this will work when all evidence points towards it not working? Or why else would it not already have revolutionized everything a year or two ago when everyone started doing this?

Theyre doing it so much it&#x27;s practically a cliche.There are underserved areas of the economy but agentic startups is not one.

&gt;evelopers haven&#x27;t even started extracting the value of LLMs with agent architectures yet.Which is basically what? The infinite monkey theorem? Brute forcing solutions for problems at huge costs? Somehow people have been tricked to actually embrace and accept that now they have to pay subscriptions from 20$ to 300$ to freaking code? How insane is that, something that was a very low entry point and something that anyone could do, is now being turned into some sort of classist system where the future of code is subscriptions you pay for companies ran by sociopaths who don&#x27;t care that the world burns around them, as long as their pockets are full.

&gt;&gt; Developers haven&#x27;t even started extracting the value of LLMs with agent architectures yet.What does this EVEN mean?
Do words have any value still, or are we all just starting to treat them as the byproduct of probabilistic tokens?&quot;Agent architectures&quot;. Last time I checked an architecture needs predictability and constraints. Even in software engineering, a field for which the word &quot;engineering&quot; is already quite a stretch in comparison to construction, electronics, mechanics.Yet we just spew the non-speak &quot;Agentic architectures&quot; as if the innate inability of LLMs in managing predictable quantitative operations is not an unsolved issue. As if putting more and more of these things together automagically will solves their fundamental and existential issue (hallucinations) and suddenly makes them viable for unchecked and automated integration.

3 years into automating all white collar labor in 6 months.

&gt; Developers haven&#x27;t even started extracting the value of LLMs with agent architectures yet.For sure there is a portion of developers who don&#x27;t care about the future, are not interested in current developements and just live as before hoping nothing will change. But the rest already gave it a try and realized tools like Claude Code can give excellent results for small codebases to fail miserably at more complex tasks with the net result being negative as you get a codebase you don&#x27;t understand, with many subtle bugs and inconsistencies created over a few days you will need weeks to discover and fix.

Developers haven&#x27;t even started extracting the value of LLMs with agent architectures yet. Using an LLM UI like open ai is like we just figured fire and you use it to warm you hands (still impressive when you think about it, but not worth the burns), while LLM development is about building car engines (here is you return on investment).

Most prominent example was this one: <a href="https:&#x2F;&#x2F;www.reuters.com&#x2F;technology&#x2F;microsoft-pulls-back-more-data-center-leases-us-europe-analysts-say-2025-03-26&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.reuters.com&#x2F;technology&#x2F;microsoft-pulls-back-more...</a>

&gt; first signs of pulling back investmentsI agree with you, but I’m curious; do you have link to one or two concrete examples of companies pulling back investments, or rolling back an AI push?(Yes it’s just to fuel my confirmation bias, but it’s still feels nice:-) )

Nah, if TSMC got exploded and there was a world war, in 20 years all the LLMs would bit rot.

ML models have the good property of only requiring investment once and can then be used till the end of history or until something better replaces them.Granted the initial investment is immense, and the results are not guaranteed which makes it risky, but it&#x27;s like building a dam or a bridge. Being in the age where bridge technology evolves massively on a weekly basis is a recipe for being wasteful if you keep starting a new megaproject every other month though. The R&amp;D phase for just about anything always results in a lot of waste. The Apollo programme wasn&#x27;t profitable either, but without it we wouldn&#x27;t have the knowledge for modern launch vehicles to be either. Or to even exist.I&#x27;m pretty sure one day we&#x27;ll have an LLM&#x2F;LMM&#x2F;VLA&#x2F;etc. that&#x27;s so good that pretraining a new one will seem pointless, and that&#x27;ll finally be the time we get to (as a society) reap the benefits of our collective investment in the tech. The profitability of a single technology demonstrator model (which is what all current models are) is immaterial from that standpoint.

Thanks for the link. The comparison to electricity is a good one, and this is a nice reflection on why it took time for electricity’s usefulness to show up in productivity stats:&gt; What eventually allowed gains to be realized was redesigning the entire layout of factories around the logic of production lines. In addition to changes to factory architecture, diffusion also required changes to workplace organization and process control, which could only be developed through experimentation across industries.

This seems like one the only sane arguments in this whole sea of articles.

Exactly. This is basically the argument of “AI as Normal Technology”.<a href="https:&#x2F;&#x2F;knightcolumbia.org&#x2F;content&#x2F;ai-as-normal-technology" rel="nofollow">https:&#x2F;&#x2F;knightcolumbia.org&#x2F;content&#x2F;ai-as-normal-technology</a><a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=43697717">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=43697717</a>

&gt;&gt; There are many technologies that have seemed inevitable and seen retreats under the lack of commensurate business return120+ Cable TV channels must have seemed like a good idea at the time, but like LLMs the vast majority of the content was not something people were interested in.

It&#x27;s not a great analogy. The only parallel with Concorde is energy consumption. I think a better analogy would have been VR.

The number of things it can actually do is significantly lower than the number of things the hype men are claiming it can do.

Most of the comments here feel like cope about AI TBH. There&#x27;s never been an innovation like this ever, and it makes sense to get on board rather than be left behind.

I think the difference between all previous technologies is scope. If you make a super sonic jet that gets people from place A to place B faster for more money, but the target consumer is like &quot;yeah, I don&#x27;t care that much about that at that price point&quot;, then your tech sort is of dead. You are also fully innovated on that product, like maybe you can make it more fuel efficient, sure, but your scope is narrow.AI is the opposite. There are numerous things it can do and numerous ways to improve it (currently). There is lower upfront investment than say a supersonic jet and many more ways it can pivot if something doesn&#x27;t work out.

No, because if they stop to focus on optimizing and minimizing operating costs, the next competitor over will leapfrog them with a better model in 6-12 months, making all those margin improvements an NPV negative endeavor.

It’s just the natural counterpart to dogmatic inevitabilism — dogmatic denialism. One denies the present, the other the (recent) past. It’s honestly an understandable PoV though when you consider A) most people understand “AI” and “chatbot” to be synonyms, and B) the blockchain hype cycle(s) bred some deep cynicism about software innovation.Funny seeing that comment on this post in particular, tho. When OP says “I’m not sure it’s a world I want”, I really don’t think they’re thinking about corporate revenue opportunities… More like Rehoboam, if not Skynet.

Making money and operating at a loss contradict each other.  Maybe someday they’ll make money —but not just yet. As many have said they’re hoping capturing market will position them nicely once things settle.  Obviously we’re not there yet.

&gt; that&#x27;s because they are racing improve models. If they stopped today to focus on optimization of their current models to minimize operating cost and monetizing their user base you think they don&#x27;t have a successful business model?I imagine they would’ve flicked that switch if they thought it would generate a profit, but as it is it seems like all AI companies are still happy to burn investor money trying to improve their models while I guess waiting for everyone else to stop first.I also imagine it’s hard to go to investors with “while all of our competitors are improving their models and either closing the gap or surpassing us, we’re just going to stabilize and see if people will pay for our current product.”

Are you saying they&#x27;d be profitable if they didn&#x27;t pour all the winnings into research?From where I&#x27;m standing, the models are useful as is. If Claude stopped improving today, I would still find use for it. Well worth 4 figures a year IMO.

&gt; If they stopped today to focus on optimization of their current models to minimize operating cost and monetizing their user base you think they don&#x27;t have a successful business model?Actually, I&#x27;d be very curious to know this. Because we already have a few relatively capable models that I can run on my MBP with 128 GB of RAM (and a few less capable models I can run much faster on my 5090).In order to break even they would have to minimize the operating costs (by throttling, maiming models etc.) and&#x2F;or increase prices. This would be the reality check.But the cynic in me feels they prefer to avoid this reality check and use the tried and tested Uber model of permanent money influx with the &quot;profitability is just around the corner&quot; justification but at an even bigger scale.

They might generate 10b ARR, but they lose a lot more than that. Their paid users are a fraction of the free riders.<a href="https:&#x2F;&#x2F;www.wheresyoured.at&#x2F;openai-is-a-systemic-risk-to-the-tech-industry-2&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.wheresyoured.at&#x2F;openai-is-a-systemic-risk-to-the...</a>

One thing we&#x27;re seeing in the software engineering agent space right now is how many people are angry with Cursor [1], and now Claude Code [2] (just picked a couple examples; you can browse around these subreddits and see tons of complaints).What&#x27;s happening here is pretty clear to me: Its a form of enshittification. These companies are struggling to find a price point that supports both broad market adoption ($20? $30?) and the intelligence&#x2F;scale to deliver good results ($200? $300?). So, they&#x27;re nerfing cheap plans, prioritizing expensive ones, and pissing off customers in the process. Cursor even had to apologize for it [3].There&#x27;s a broad sense in the LLM industry right now that if we can&#x27;t get to &quot;it&quot; (AGI, etc) by the end of this decade, it won&#x27;t happen during this &quot;AI Summer&quot;. The reason for that is two-fold: Intelligence scaling is logarithmic w.r.t compute. We simply cannot scale compute quick enough. And, interest in funding to pay for that exponential compute need will dry up, and previous super-cycles tell us that will happen on the order of ~5 years.So here&#x27;s my thesis: We have a deadline that even evangelists agree is a deadline. I would argue that we&#x27;re further along in this supercycle than many people realize, because these companies have already reached the early enshitification phase for some niche use-cases (software development). We&#x27;re also seeing Grok 4 Heavy release with a 50% price increase ($300&#x2F;mo) yet offer single-digit percent improvement in capability. This is hallmark enshitification.Enshitification is the final, terminal phase of hyperscale technology companies. Companies remain in that phase potentially forever, but its not a phase where significant research, innovation, and optimization can happen; instead, it is a phase of extraction. AI hyperscalers genuinely speedran this cycle thanks to their incredible funding and costs; but they&#x27;re now showcasing very early signals of enshitifications.(Google might actually escape this enshitification supercycle, to be clear, and that&#x27;s why I&#x27;m so bullish on them and them alone. Their deep, multi-decade investment into TPUs, Cloud Infra, and high margin product deployments of AI might help them escape it).[1] <a href="https:&#x2F;&#x2F;www.reddit.com&#x2F;r&#x2F;cursor&#x2F;comments&#x2F;1m0i6o3&#x2F;cursor_quality_is_getting_worse_every_day&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.reddit.com&#x2F;r&#x2F;cursor&#x2F;comments&#x2F;1m0i6o3&#x2F;cursor_qual...</a>[2] <a href="https:&#x2F;&#x2F;www.reddit.com&#x2F;r&#x2F;ClaudeAI&#x2F;comments&#x2F;1lzuy0j&#x2F;claude_code_has_gone_from_gamechanger_to_garbage&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.reddit.com&#x2F;r&#x2F;ClaudeAI&#x2F;comments&#x2F;1lzuy0j&#x2F;claude_co...</a>[3] <a href="https:&#x2F;&#x2F;techcrunch.com&#x2F;2025&#x2F;07&#x2F;07&#x2F;cursor-apologizes-for-unclear-pricing-changes-that-upset-users&#x2F;" rel="nofollow">https:&#x2F;&#x2F;techcrunch.com&#x2F;2025&#x2F;07&#x2F;07&#x2F;cursor-apologizes-for-uncl...</a>

How many of those MAUs are crappy startups building a janky layer on top of the OpenAI API which will cease to exist in 2 years?

I&#x27;m confused with your second point. LLM companies are not making any money from current models? Openai generates 10b USD ARR and has 100M MAUs. Yes they are running at a loss right now but that&#x27;s because they are racing to improve models. If they stopped today to focus on optimization of their current models to minimize operating cost and monetizing their massive user base you think they don&#x27;t have a successful business model? People use this tools daily, this is inevitable.

But there are a ton of LLM powered products in the market.I have a friend in finance that uses LLM powered products for financial analysis, he works in a big bank. Just now anthropic released a product to compete in this space.Another friend in real estate uses LLM powered lead qualifications products, he runs marketing campaigns and the AI handles the initial interaction via email or phone and then ranks the lead in their crm.I have a few friends that run small businesses and use LLM powered assistants to manage all their email comms and agendas.I&#x27;ve also talked with startups in legal and marketing doing very well.Coding is the theme that&#x27;s talked about the most in HN but there are a ton of startups and big companies creating value with LLMs

I do wonder where in the cycle this all is given that we&#x27;ve now seen yet another LLM&#x2F;&quot;Agentic&quot; VSCode fork.I&#x27;m genuinely surprised that Code forks and LLM cli things are seemingly the only use case that&#x27;s approached viability. Even a year ago, I figured there&#x27;d be something else that&#x27;s emerged by now.

The huge leap that is getting pushback is the sentiment that LLMs will consume every use case and replace human labor.  I don&#x27;t think many are arguing LLMs will die off entirely.

The difference is that the future is now with LLMs. There is a microwave (some multiple) in almost every kitchen in the world. The Concord served a few hundred people a day. LLMs are already ingrained into hundreds of millions if not billions of people’s lives, directly and indirectly. My dad directly uses LLMs multiple times a week if not daily in an industry that still makes you rotate your password every 3 months. It’s not a question of whether the future will have them, it’s a question of whether the future will  get tired of them.

They didn&#x27;t really need the cloud either and yet...

Investments are mostly in model training. We have trained models now, we&#x27;ll see a pullback in that regard as businesses will need to optimize to get the best model without spending billions in order to compete on price, but LLMs are here to stay.

&gt; model capabilities are plateauing at a level where most people agree that the output is trite and unpleasant to consume.What are you basing this on? Personal feelings?

The next step is clearly improved vision and everyday-physics models. These can also solve hallucinations.

My take since day one:(1) Model capabilities will plateau as training data is exhausted. Some additional gains will be possible by better training, better architectures, more compute, longer context windows or &quot;infinite&quot; context architectures, etc., but there are limits here.(2) Training on synthetic data beyond a very limited amount will result in overfitting because there is no new information. To some extent you could train models on each other, but that&#x27;s just an indirect way to consolidate models. Beyond consolidation you&#x27;ll plateau.(3) There will be no &quot;takeoff&quot; scenario -- this is sci-fi (in the pejorative sense) because you can&#x27;t exceed available information. There is no magic way that a brain in a vat can innovate beyond available training data. This includes for humans -- a brain in a vat would quickly go mad and then spiral into a coma-like state. The idea of AI running away is the information-theoretic equivalent of a perpetual motion machine and is impossible. Yudkowski and the rest of the people afraid of this are crackpots, and so are the hype-mongers betting on it.So I agree that LLMs are real and useful, but the hype and bubble are starting to plateau. The bubble is predicated on the idea that you can just keep going forever.

You aren’t extrapolating enough. Nearly the entire history of computing has been one that isolates between shared computing and personal computing. Give it time. These massive cloud bills are building the case for accelerators in phones. It’s going to happen just needs time.

We actually aren&#x27;t too far off from that reality. There are several models you can run fully offline on your phone (phi-3, Gemma-3n-E2b-it, Qwen2.5-1.5b-instruct all run quite well on my Samsung S24 ultra). There are a few offline apps that also have tool calling (mostly for web search but I suspect this is extendable).If you want to play around a bit and are on android there is PocketPal,ChatterUI, MyDeviceAI, SmolChat are good multi-model apps and Google&#x27;s Edge gallery won&#x27;t keep your chats but is a fun tech demo.All are on github and can be installed using Obtainium if you don&#x27;t want to

&gt; 2. Almost three years in, companies investing in LLMs have not yet discovered a business model that justifies the massive expenditure of training and hosting them, the majority of consumer usage is at the free tier, the industry is seeing the first signs of pulling back investments, and model capabilities are plateauing at a level where most people agree that the output is trite and unpleasant to consume.You hit the nail on why I say to much hatred from &quot;AI Bros&quot; as I call them, when I say it will not take off truly until it runs on your phone effortlessly, because nobody wants to foot a trillion dollar cloud bill.Give me a fully offline LLM that fits in 2GB of VRAM and lets refine that so it can plug into external APIs and see how much farther we can take things without resorting to burning billions of dollars&#x27; worth of GPU compute. I don&#x27;t care that my answer arrives instantly, if I&#x27;m doing the research myself, I want to take my time to get the correct answer anyway.

Sort of a followup to myself if I come back searching this comment or someone sees this thread later... here&#x27;s a study that just came out on AI attitudes: <a href="https:&#x2F;&#x2F;report2025.seismic.org&#x2F;" rel="nofollow">https:&#x2F;&#x2F;report2025.seismic.org&#x2F;</a>I don&#x27;t think it supports the bits I quoted, but it does include more negativity than I would have predicted before seeing it.

I don&#x27;t really buy your point 2. Just the other day Meta announced hundreds of billions of dollars investment into more AI datacenters. Companies are bringing back nuclear power plants to support this stuff. Earlier this year OpenAI and Oracle announced their $500bn AI datacenter project, but admittedly in favor of your point have run into funding snags, though that&#x27;s supposedly from tariff fears with foreign investors, not lack of confidence in AI. Meta can just finance everything from their own capital and Zuck&#x27;s decree, like they did with VR (and it may very well turn out similarly).Since you brought up supersonic jetliners you&#x27;re probably aware of the startup Boom in Colorado trying to bring it back. We&#x27;ll see if they succeed. But yes, it would be a strange path, but a possible one, that LLMs kind of go away for a while and try to come back later.You&#x27;re going to have to cite some surveys for the &quot;most people agree that the output is trite and unpleasant&quot; and &quot;almost universally disliked attempts to cram it everywhere&quot; claims. There are some very vocal people against LLM flavors of AI, but I don&#x27;t think they even represent the biggest minority, let alone a majority or near universal opinions. (I personally was bugged by earlier attempts at cramming non-LLM AI into a lot of places, e.g. Salesforce Einstein appeared I think in 2016, and that was mostly just being put off by the cutesy Einstein characterization. I generally don&#x27;t have the same feelings with LLMs in particular, in some cases they&#x27;re small improvements to an already annoying process, e.g. non-human customer support that was previously done by a crude chatbot front-end to an expert system or knowledge base, the LLM version of that tends to be slightly less annoying.)

Maybe he&#x27;s referencing how people don&#x27;t like when other humans post LLM responses in the comments.&quot;Here&#x27;s what chatGPT said about...&quot;I don&#x27;t like that, either.I love the LLM for answering my own questions, though.

I&#x27;m not really countering that ChatGPT is popular, it certainly is, but it&#x27;s also sort of like &quot;fastest growing tire brand&quot; that came along with the adoption of vehicles. The amount of smartphone users is also growing at the fastest rate ever so whatever the new most popular app is has a good chance of being the fastest growing app ever.

...I do wonder what percent of ChatGPT usage is just students cheating on their homework, though.

&gt; AI apps like Perplexity are now beginning to challenge Google’s search dominanceNow that is a wild claim. ChatGPT might be challenging Google&#x27;s dominance, but Perplexity is nothing.

&gt; That is a such a wild claim. People like the output of LLMs so much that ChatGPT is the fastest growing app ever.The people using ChatGPT like its output enough when they&#x27;re the ones reading it.The people reading ChatGPT output that other people asked for generally don&#x27;t like it. Especially if it&#x27;s not disclosed up front.

&gt; That is a such a wild claim.Some people who hate LLMs are absolutely convinced everyone else hates them. I&#x27;ve talked with a few of them.I think it&#x27;s a form of filter bubble.

&gt; People like the output of LLMs so much that ChatGPT is the fastest growing app everWhile people seem to love the output of their own queries they seem to hate the output of other people&#x27;s queries, so maybe what people actually love is to interact with chatbots.If people loved LLM outputs in general then Google, OpenAI and Anthropic would be in the business of producing and selling content.

At some point, Groupon was the fastest growing company ever.

People &quot;like&quot; or people &quot;suffice&quot; with the output? This &quot;rise of whatever&quot; as one blog put it gives me feelings that people are instead lowering their standards and cutting corners. Letting them cut through to stuff they actually want to do.

&gt; People like the output of LLMs so much that ChatGPT is the fastest growing app everAnd how much of that is free usage, like the parent said? Even when users are paying, ChatGPT&#x27;s costs are larger than their revenue.

I would pay $5000 to never have to read another LLM-authored piece of text ever again.

&gt; That is a such a wild claim. People like the output of LLMs so much that ChatGPT is the fastest growing app ever.And this kind of meaningless factoid was immediately usurped by the Threads app release, which IMO is kind of a pointless app. Maybe let&#x27;s find a more meaningful metric before saying someone else&#x27;s claim is wild.

&gt; &gt; “most people agree that the output is trite and unpleasant to consume”&gt; That is a such a wild claim.I think when he said &quot;consume&quot; he meant in terms of content consumption. You know, media - the thing that makes Western society go round. Movies, TV, music, books.Would I watch an AI generated movie? No. What about a TV show? Uh... no. What about AI music? I mean, Spotify is trying to be tricky with that one, but no. I&#x27;d rather listen to Remi Wolf&#x27;s 2024 Album &quot;Big Ideas&quot;, which I thought was, ironically, less inspired than &quot;Juno&quot; but easily one of the best albums of the year.ChatGPT is a useful interface, sure, but it&#x27;s not entertaining. It&#x27;s not high-quality. It doesn&#x27;t provoke thought or offer us some solace in times of sadness. It doesn&#x27;t spark joy or make me want to get up and dance.

&gt; “most people agree that the output is trite and unpleasant to consume”That is a such a wild claim. People like the output of LLMs so much that ChatGPT is the fastest growing app ever. It and other AI apps like Perplexity are now beginning to challenge Google’s search dominance.Sure, probably not a lot of people would go out and buy a novel or collection of poetry written by ChatGPT. But that doesn’t mean the output is unpleasant to consume. It pretty undeniably produces clear and readable summaries and explanations.

It wouldn&#x27;t be general purpose if it fails to bring change. I&#x27;d take every previous iteration of &quot;AI&quot; as example, IBM Watson, that stuff

&gt; (the supersonic jetliner) ... (the microwave oven)But have we ever had a general purpose technology (steam engine, electricity) that failed to change society?

Let&#x27;s not ignore the technical aspects as well: LLMs are probably a local minima that we&#x27;ve gotten stuck in because of their rapid rise. Other areas in AI are being starved of investment because all of the capital is pouring into LLMs. We might have been better off in the long run if LLMs hadn&#x27;t been so successful so fast.

&gt; most people agree that the output is trite and unpleasant to consumeThis is likely a selection bias: you only notice the obviously bad outputs. I have created plenty of outputs myself that are good&#x2F;passable -- you are likely surrounded by these types of outputs without noticing.Not a panacea, but can be useful.

&gt; I just wanted to say LLMs with MCP are definitely good enough for almost every use case you can come up with as long as you can provide them with high quality context.This just shows you lack imagination.I have a lot of use cases that they are not good enough for.

LLMs with tools*MCP isn’t inherently special. A Claude Code with Bash() tool can do nearly anything a MCP server will give you - much more efficiently.Computer Use agents are here and are only going to get better.The conversation shouldn’t be about LLMs any longer. Providers will be providing agents.

There are pretty hidden assumption in this comment. First of all, not every business in the AI space is _training_ models, and the difference between training and inference is massive - i.e. most businesses can easily afford inference, perhaps depending on model, but they definitely can.Another several unfounded claims were made here, but I just wanted to say LLMs with MCP are definitely good enough for almost every use case you can come up with as long as you can provide them with high quality context. LLMs are absolutely the future and they will take over massive parts of our workflow in many industries. Try MCP for yourself and see. There&#x27;s just no going back.

I think this is both right and wrong. There was a good book that came out probably 15 years ago about how technology never stops in aggregate, but individual technologies tend to grow quickly and then stall. Airplane jets were one example in the book. The reason why I partially note this as wrong is that even in the 70s people recognized that supersonic travel had real concrete issues with no solution in sight. I don&#x27;t think LLMs share that characteristic today.A better example, also in the book, are skyscrapers. Each year they grew and new ones were taller than the ones last year. The ability to build them and traverse them increased each year with new technologies to support it. There wasn&#x27;t a general consensus around issues that would stop growth (except at more extremes like air pressure). But the growth did stop. No one even has expectations of taller skyscrapers any more.LLMs may fail to advance, but not because of any consensus reason that exists today. And it maybe that they serve their purpose to build something on top of them which ends up being far more revolutionary than LLMs. This is more like the path of electricity -- electricity in itself isn&#x27;t that exciting nowadays, but almost every piece of technology built uses it.I fundamentally find it odd that people seem so against AI. I get the potential dystopian future, which I also don&#x27;t want. But the more mundane annoyance seems odd to me.

From a system optimisation perspective, SSTs solved the wrong problem.Want to save people time flying? Solve the grotesque inefficiency pit that is airport transit and check-in.Like, I&#x27;m sorry, STILL no high speed, direct to terminal rail at JFK, LAX and a dozen other major international airports? And that&#x27;s before we get to the absolute joke of &quot;border security&quot; and luggage check-in.Sure, supersonic afterburning engines are dope. But it&#x27;s like some 10GHz single-core CPU that pulls 1.2kW out of the wall. Like it or not, an iPhone 16 delivers far more compute utility in far more scenarios.

The problem with supersonic commercial jets was mainly one of marketing&#x2F;politics. The so called &quot;sonic boom&quot; problem was vastly overhyped, as anyone who lives near an air force base can tell you.The conspiracy theorist tells me the American aerospace manufacturers at the time (Boening, McDonnell-Douglas, etc.), did everything they could to kill the Concorde. With limited flyable routes (NYC and DC to Paris and London I think were the only ones), the financials didn&#x27;t make sense. If overland routes were available, especially opening up LA, San Francisco and Chicago, it might have been a different story.

Oh no, LLMs won&#x27;t disappear but they will be a lot less loud.Progress is often an S shaped curve and we are nearing saturation.

&gt; So maybe in 2075 we&#x27;ll all be watching documentaries about LLMs (maybe even on our phones or laptops that look basically the same), and reminiscing about the mid-2020s and wondering why what seemed to be such a promising technology disappeared almost entirely.It&#x27;s hard for me to believe that anyone who works with technology in general, and LLMs in particular, could think this.

The crucial point is that we simply do not know yet if there is an inherent limitation in the reasoning capabilities of LLMs, and if so whether we are currently near to pushing up against them. It seems clear that American firms are still going to increase the amount of compute by a lot more (with projects like the Stargate factory), so time will tell if that is the only bottleneck to further progress. There might also still be methodological innovations that can push capabilities further.

slower, no fast option, no smoking in the cabins, less leg room, but with TVs plastered on the back of every chair, sometimesits actually kind of scary to think of a world where generative AI in the cloud goes away due to costs, in favor of some other lesser chimera version that can&#x27;t currently be predictedbut good news is that locally run generative AI is still getting better and better with fewer and fewer resources consumed to use

I don&#x27;t think we&#x27;re anywhere near peak capability for LLMs yet. It won&#x27;t take 50 years but still it&#x27;s been just 4 years.

&gt; There are many technologies that have seemed inevitable and seen retreats under the lack of commensurate business return (the supersonic jetliner)I think this is a great analogy, not just to the current state of AI, but maybe even computers and the internet in general.Supersonic transports must&#x27;ve seemed amazing, inevitable, and maybe even obvious to anyone alive at the time of their debut. But hiding under that amazing tech was a whole host of problems that were just not solvable with the technology of the era, let alone a profitable business model. I wonder if computers and the internet are following a similar trajectory to aerospace. Maybe we&#x27;ve basically peaked, and all that&#x27;s left are optimizations around cost, efficiency, distribution, or convenience.If you time traveled back to the 1970s and talked to most adults, they would have witnessed aerospace go from loud, smelly, and dangerous prop planes to the 707, 747 and Concorde. They would&#x27;ve witnessed the moon landings and were seeing the development of the Space Shuttle. I bet they would call you crazy if you told this person that 50 years later, in 2025, there would be no more supersonic commercial airliners, commercial aviation would basically look the same except more annoying, and also that we haven&#x27;t been back to the moon. In the previous 50 years we went from the Wright Brothers to the 707! So maybe in 2075 we&#x27;ll all be watching documentaries about LLMs (maybe even on our phones or laptops that look basically the same), and reminiscing about the mid-2020s and wondering why what seemed to be such a promising technology disappeared almost entirely.

&gt; 2. Almost three years in, companies investing in LLMs have not yet discovered a business model that justifies the massive expenditure of training and hosting them,I always think back to how Bezos and Amazon were railed against for losing money for years. People thought that would never work. And then when he started selling stuff other than books? People I know were like: please, he&#x27;s desperate.Someone, somewhere will figure out how to make money off it - just not most people.

My guess is that LLM&#x27;s are bridge technology, the equivalent of cassette tapes. A big step forward, allowing things that we couldn&#x27;t before. But before long they&#x27;ll be surpassed by much better technology, and future generations will look back on them as primitive.You have top scientists like LeCun arguing this position. I&#x27;d imagine all of these companies are desperately searching for the next big paradigm shift, but no one knows when that will be, and until then they need to squeeze everything they can out of LLMs.

Oh wow I forgot that the microwave oven was once marketed as the total replacement of cooking chores and in futuristic life people can just press a button and have a delicious good meal ( well you can now but microwave meals are often seen as worse than fastfood ).

To use the Internet as a comparison:Phase 1 - mid to late 1990s:- &quot;The Internet is going to change EVERYTHING!!!&quot;Phase 2 - late 1990s to early 2000s:- &quot;It&#x27;s amazing and we are all making SO much money!&quot;- &quot;Oh no! The bubble burst&quot;- &quot;Of course everyone could see this coming: who is going to buy 40 lb bags of dogfood or their groceries over the Internet?!?!?&quot;Phase 3 - mid 2000s to 2020:- &quot;It is astounding the amount of money being by tech companies&quot;- &quot;Who could have predicted that social media would change the ENTIRE landscape??&quot;

I think two things can be true simultaneously:1. LLMs are a new technology and it&#x27;s hard to put the genie back in the bottle with that. It&#x27;s difficult to imagine a future where they don&#x27;t continue to exist in some form, with all the timesaving benefits and social issues that come with them.2. Almost three years in, companies investing in LLMs have not yet discovered a business model that justifies the massive expenditure of training and hosting them, the majority of consumer usage is at the free tier, the industry is seeing the first signs of pulling back investments, and model capabilities are plateauing at a level where most people agree that the output is trite and unpleasant to consume.There are many technologies that have seemed inevitable and seen retreats under the lack of commensurate business return (the supersonic jetliner), and several that seemed poised to displace both old tech and labor but have settled into specific use cases (the microwave oven). Given the lack of a sufficiently profitable business model, it feels as likely as not that LLMs settle somewhere a little less remarkable, and hopefully less annoying, than today&#x27;s almost universally disliked attempts to cram it everywhere.

LLM Inevitabilism