23 ms·

AI is slowing down

• ndnjdjdkdjd 4mo ago
  [flagged]
• ElFitz 4mo ago
  I find it difficult to separate this piece’s tone from its content. The tone puts me off and makes it hard for me to judge it on its merits, despite some of the arguments seeming sound and well supported.
  • metadat 4mo ago
    Agreed. I am open to the possibility of the bubble bursting or whatever, but this piece is like 3,000 words and cites everything as evidence the sky is falling. It's just as bad as the pro-AI grifters, just in the other direction. Does the truth normally lie somewhere in the middle of it all?
    • kunai 4mo ago
      Probably. Although I feel more inclined to forgive Ed in this case because it's sort of fighting fire with fire, the insanely hyperbolic and obscenely misleading drivel that's coming out of the most ardent AI boosters is continually unchallenged in the public eye. In a world where we had a more realistic view of AI/ML/LLMs, the limits to its capabilities, and the negative externalities of its widespread adoption in places where it quite frankly does not belong, then I'd be more critical of the Chicken Little sort of writing style
    • viccis 4mo ago
      >Does the truth normally lie somewhere in the middle of it all? Usually does when you decide what constitutes extreme.
    • marcosdumay 4mo ago
      At the /. times, there was somebody there with the best signature line. It was something like: "Some people say the Sun sets at East, other people say it sets at West. The truth, of course, is certainly on the middle."
  • techblueberry 4mo ago
    Given the way tone has been intentionally abused, particularly in this industry, I’ll take a few f bombs and the truth.
    • GaggiX 4mo ago
      >I’ll take a few f bombs and the truth. Don't want to ruin it but go read some old posts from the author about AI, the tone is the same and he is very much wrong.
    • aoeusnth1 4mo ago
      What about all his other articles that had f-bombs and the predictive utility of used toilet paper?
    • JacobAsmuth 4mo ago
      https://www.wheresyoured.at/peakai/ https://www.wheresyoured.at/peakai/ "I believe that artificial intelligence has three quarters to prove itself before the apocalypse comes, and when it does, it will be that much worse, savaging the revenues of the biggest companies in tech. Once usage drops, so will the remarkable amounts of revenue that have flowed into big tech, and so will acres of data centers sit unused, the cloud equivalent of the massive overhiring we saw in post-lockdown Silicon Valley." Ed Zitron. Mar 18, 2024
      • techblueberry 4mo ago
        Prescient
  • sumeno 4mo ago
    Ed's posts are peak preaching to the choir, they're usually factually correct but he is really bad at convincing anyone who doesn't already strongly agree with him.
    • JesseTG 4mo ago
      Have you seen his recent Bloomberg appearance? He's calm, collected, and matter-of-fact -- the complete opposite of how he presents himself on his newsletter and podcasts, but with the same argument. You wouldn't know from listening to him how spicy he usually is.
      • d33d 4mo ago
        I dont really understand the criticism either way. He's in the media business... its in his interest to amp things up.
        • JesseTG 4mo ago
          Yes, of course.
      • nyeah 4mo ago
        It's tuned to the audience. Bloomberg was traditionally for people who actually wanted information. People who were fallible and had limited knowledge. Of course that mentality is obsolete. Now we all have infinite access to perfectly correct information via the internet.
        • lowmagnet 4mo ago
          wow someone tell the philosophers this guy has figured out the knowledge problem!
    • ElFitz 4mo ago
      Perhaps that’s it. I would tend to agree with his position, I think, but don’t appreciate being preached to. Even less so when I agree with what’s being said.
  • nyeah 4mo ago
    Agreed. If the arguments seem sound and well supported, then all we can do is attack the tone.
    • ElFitz 4mo ago
      You can disagree. Sarcastically, or otherwise. But I think you may be reading more into my comment than I put there. I’m not attacking the piece. I’m not saying it’s right. I’m not saying it’s wrong. What I’m saying is, the tone made it hard for me to judge the arguments fairly, despite finding some of them convincing. And as much as I dislike it, persuasion does partly depend on how an argument is made.
      • nyeah 4mo ago
        Thanks, it's very clear what you're saying.
  • deleted 4mo ago
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• deleted 4mo ago
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• bpodgursky 4mo ago
  What's the point of arguing with any of this. It's like someone arguing that cheese isn't real. Yes I can go to the grocery store and take a picture of cheese and show it, but what's the point? They can live in their own world. It doesn't change any of our lives. The world is what it is.
  • happycube 4mo ago
    Lol... in this case, cheese imports from China are much cheaper, just not quite as good. And for those who are all "but dur CCP get all ur data" you can use things like AWS Bedrock (at least for earlier versions of Deepseek and Qwen for now) and have more familiar people get all your data. Or buy (at obnoxiously inflated prices) your own HW and not send your data to anyone.
    • bayarearefugee 4mo ago
      > "but dur CCP get all ur data" The funniest part of this is that people are often talking about how LLMs are now writing 100% of their code, then also saying that they don't want to expose their code to foreign government exfiltration by using foreign models. But, uh, if an LLM is writing 100% of your code you have no actual secret sauce to hide from anyone, so why worry about it.
      • recursive 4mo ago
        Perfect for idea people. All the value is in the prompt. Ideas are important, not execution. A decade or two ago, they would have been looking for a technical co-founder.
      • saltcured 4mo ago
        I think we're going to see a lot of craziness in the future in this regard. Not just "secrets", but hypocrites trying to copyright and patent all the AI outputs. All kinds of rabid attempts at constructing monopolies for every half-baked idea they have tried to utter as a prompt. Meanwhile, like I think you suggest, I would assume everyone can generate similar outputs themselves. The idea that you can claim priority on your dream prompt and lock up the market on prompt responses sounds delusional to me. It's not novel invention when you're spit-balling at the same level of abstraction as every fantasy/scifi writer who ever was. So I also have doubts about the sustainable business model. How long will it take for this fantasy to unravel, as people discover they cannot monetize their AI outputs as much as they dreamed, and in turn cannot afford to pay the AI services they use? My absolute nightmare is that this becomes a "too big to fail" thing and oppressive/fascist governments decide to back full regulatory capture. That instead of letting it unwind, they grant and support enforcement of an increasingly absurd and arbitrary copyright/patent regime to support this monetization scheme.
• swader999 4mo ago
  I think we need to see Open AI's and/or Anthropic's S1's to really know the state of it all.
  • dr_robert 4mo ago
    Totally agree, remember WeWork's S1 and the fall that followed. Don't think it's the same case, but it'll clarify a lot of things
• dkobia 4mo ago
  Zitron is begging for a collapse at this point. Yes, his macro analysis correctly identifies a massive financial risk but his incessant pessimism completely misses the incredible ground-level utility that many of us on HN celebrate every day through undeniable, massive productivity gains. At this point I'm trying to believe there's a middle ground where the level of individual capability this unlocks, leads to major discoveries.
  • oudlys 4mo ago
    Productivity is not value. It's quite possible for you to experience productivity improvements, and actual value to not be created. That is what I think the most robust data is showing. https://unessays.substack.com/p/talk-is-cheap https://unessays.substack.com/p/talk-is-cheap
    • bigstrat2003 4mo ago
      Also, supposed productivity gains are dubious. I personally experience at best no productivity gains when using LLMs to write code, and sometimes it's an active drain on my productivity. There was that one study a year or so ago showing similar results. People are trying to say the productivity gains are there and undeniable, but that is not true. It is very much a subject of controversy whether AI helps productivity.
      • asdfasgasdgasdg 4mo ago
        I can see an argument that the productivity gains are illusory / don’t translate to economic productivity. I’m not denying the possibility. However, most of the engineers I respect have gone from being skeptics a year ago to convinced today. I don’t personally know any true holdouts any more. If there are studies that disprove productivity gains more than six months ago, I’m happy to believe that it was true of the AIs that were available at the time. But I’m going to need something much more recent before I disbelieve my lyin’ eyes where it pertains to the AIs available today.
        • 4mo ago
• zachthewf 4mo ago
  Before you spend 20 minutes reading this article, it's worth understanding that the writer has been posting popular but consistently wrong takes for 2+ years (e.g. https://www.wheresyoured.at/peakai/ https://www.wheresyoured.at/peakai/ from March 2024) arguing that AI is failing, is a waste of money, is bad, will never work, etc.
  • ericmcer 4mo ago
    Yeah they seem clickable because anything Anti-AI is a bit soothing right now, but he is constantly wrong and usually is pushing the angle of "these businesses aren't even profitable!" Instantly close the tab as soon as the popup to subscribe to his newsletter pops up.
    • jimmaswell 4mo ago
      Why is anti-AI soothing?
      • recursive 4mo ago
        For some of us it is, I suppose as an alternate view to AI booster-ism, particularly if you think the long term effects would be mostly negative.
      • freejazz 4mo ago
        [flagged]
      • simonw 4mo ago
        Because there are still a huge number of people who would be very relieved if the whole AI thing just went away.
      • raziel2701 4mo ago
        It's seen as an existential threat to young people. If you can't get a job you starve.
      • Jtarii 4mo ago
• aogaili 4mo ago
  Some people seem to see the world only through bubbles. But if you look at human history, despite the ups and downs, we have a trajectory; generally speaking, human-created systems evolve toward ever-increasing complexity, impact, and efficiency. The current wave of AI unlocked language - the tools are now speaking and understanding. This, on its own, is astonishing progress. Language is the foundation of our culture and society; it is the very technology that got us, as a species, to where we are today. To have tools that can understand, manipulate, and produce it is a massive leap forward. Once you see things that way, it is clear that we are not in a bubble; we are in a transition. Yes, there is tons of hype and over-investment, but the demand is real, and so is the impact. Unless you are deep in the tech and have that structural depth, it is easy to dismiss. This is like the invention of the personal computer, but with 100x the impact and speed.
  • partiallypro 4mo ago
    The only "bubble" with AI is that the initial build out is cyclical, and many of the high flying chip stocks with no software arms (ala Nvidia's CUDA) will come back to Earth. I think anyone that thinks AI is going away or won't have massive impact (though maybe not in the doomsday scenario) are in complete denial.
    • aogaili 4mo ago
      I share the same perspective.
    • hungryhobbit 4mo ago
      RTFA; it's not about AI's massive impact or lack thereof ... it's about these businesses not having a viable business model that will sustain them (beyond the next couple years).
      • cogman10 4mo ago
        I think Zitron's problem is he's equating AI to OpenAI and Anthropic. I'd agree with him that both those businesses are in a dangerous position given how fast they've burnt through cash. However, that's not the entirety of the industry and there are a lot smaller labs doing more for a lot less capital. The business model does appear to be viable for these labs. But that viability comes because they aren't wasting a bunch of R&D money developing worthless products like AI video production.
• simianwords 4mo ago
  Ed Zitron speaks to a particular type of angry tech conservative. He’s not speaking truth or exposing anything. He’s the soothing voice the tech nerds of yesterday year are yearning for. The angry polemic that goes on and on and on with cuss words used liberally is just meant to evoke emotion and cathartic resolution to the type of people mentioned above. Not truth. The thing is, there are a lot of people that find comfort in what he’s writing - primarily because it’s a coping mechanism against how quickly things are moving and a way to deal with being left behind. When you spend time, years, building institutional knowledge and making a whole identity out of it, you obviously will feel bad with the threat of it being commoditised. I would write against the content of the article but I find it easier and more illuminating to write what he has said before instead. Then it shows how incorrect the guy has been and with what confidence he keeps speaking with.
  • simianwords 4mo ago
    I'm collecting many kinds of predictions Ed Zitron made so that you can see for yourself whether he has a good track record. ------- > While complex, generative AI is a technology that probabilistically generates answers, and has no "intelligence." It is inherently limited by its architecture, and in turn can only get "better" in a linear fashion. I see no signs that the transformer-based architecture can do significantly more than it currently does. He wrote this in 2024 before reasoning models came out. Remember how ChatGPT was in 2024? Do you think this person is someone who gets predictions right? > Furthermore, I hypothesize a race to the bottom in generative AI will significantly hamper OpenAI's ability to expand revenue, compounded by the fact that we're approaching the limits of transformer-based architecture. He wrote this in 2024 and since then Anthropic's revenue increased by 160x to $40 B dollars a year and OpenAI's increased by 6x. Do you think this person gets predictions right still? > I believe we're reaching the upper limits about what generative AI can do and how accurate its outputs can be, He wrote this in 2024, do you really think we have reached upper limits? Huh?? What I'm using today is significantly more accurate and 2 tiers above what we had. > And if there are true industry-changing possibilities waiting for us on the other side, I am yet to hear them outside of the fan fiction of Silicon Valley hucksters. He says this about AI when we have with all honesty have had industry changing possibilities like agentic coding. > There are indications that consumers have also lost interest. As pointed out by Alex Kantrowitz’ Big Technology newsletter, traffic to ChatGPT on both mobile and web has started to stagnate, if not decline. In January 2024, ChatGPT had 1.6 billion visits — 11% below the all-time peak of 1.8 billion. This makes it only modestly more popular than Bing, which had 1.3 billion unique visits during that period. On the mobile front, ChatGPT has an estimated 6.3 million US users — or 1.7 times less than the total of new Snapchat users added during Q4 2023. He agrees with the claim that the consumer interest has declined. Since he said this, there was a 9x growth in active users. ----- https://www.youtube.com/watch?v=_wStScmT748&t=1s https://www.youtube.com/watch?v=_wStScmT748&t=1s "AI Bubble Already Bursting?" (8 months back) https://www.youtube.com/watch?v=T8ByoAt5gCA&t=1s https://www.youtube.com/watch?v=T8ByoAt5gCA&t=1s "A.I bubble is bursting with Ed Zitron" (1 year back) He's been constantly crying bubble for years now. ----- > AI video won’t get truly fixed just by waiting a year. This is what he had said in 2024, and you just need to compare video from then and now to check whether the predictions came true. Why would anyone trust what this guy has to say?
• Kim_Bruning 4mo ago
  Buried lede (if the title is the actual promise), the sources don't seem to back the title either. Someone with more patience can correct me if I accidentally missed a bombshell anyway. Edit: > If you’re wondering what the story is, [...] I expect it to be out in the next two weeks [...] I can guarantee you it’ll be worth it, and you’ll be stunned by what I report. Ok, this takes clickbait to new lows. The headline is trying to sell the teaser here, with very limited meat in the middle of the sandwich.
  • helloplanets 4mo ago
    Given this, his righteous anger towards craven boosters and grifters is pretty funny. Pot calling the kettle black.
  • JimDabell 4mo ago
    > the sources don't seem to back the title either. This is nothing new for Zitron. The last article of his I saw: > I also severely doubt that Anthropic managed to make the cost of running its services profitable in the space of six months. > [Per The Information in January], Anthropic missed on its gross margin projections, saying that its inference costs were 23% higher than the company had anticipated. > How did Anthropic, which faced a massive influx of new business to the point that Anthropic was forced to buy more compute from Elon Musk, magically become profitable? Other than that discount, of course. If you follow the link to The Information, you’ll see that it’s a paid article with the headline “Anthropic Lowers Gross Margin Projection as Revenue Skyrockets”. But what happens when you actually read the article? > Anthropic last month projected it would generate a 40% gross profit margin from selling AI to businesses and application developers in 2025, according to two people with knowledge of its financials. That margin was 10 percentage points lower than its earlier optimistic expectations, though it’s still a big improvement from the year before. — https://archive.is/aKFYZ https://archive.is/aKFYZ So, according to Zitron’s own source, Anthropic are actually earning 40% gross profit margin on inference, and that is a dramatic jump upwards! This totally contradicts his position that it’s an implausible “swindle” for Anthropic to claim profitability. He’s counting on the fact that most of his readers don’t subscribe to The Information and will only see the headline, or that they will just see a citation and trust that it backs him up without checking.
• feverzsj 4mo ago
  I predict the bubble is going to pop right after the midterm election.
  • saulpw 4mo ago
    Concur.
• brindleth 4mo ago
  Whenever I read these kind of articles about AI financials, I'm reminded of identical screeds I read about Uber a few years ago. They were angrily insistent that Uber was a scam company run by criminals and charlatans and could never, ever become profitable or make money for its investors. It was a house of cards that would come crashing down sooner or later, and take everyone's money with it. Now it's 2026. Uber still exists, has revenues of $50bn and is apparently a highly profitable business. I don't know if the original investors have made their money back yet, but Uber certainly hasn't collapsed. Maybe AI is different. Certainly, the level scale of investment is on a different order of magnitude. But I'm wary of believing anything about the financial impossibility of AI being sustainable when I've seen such similarly confident arguments proved wrong in the past.
  • kunai 4mo ago
    Uber used the classic triple-E philosophy of Microsoft and entered a market that was ripe for disruption -- many cities lacked reliable taxi service entirely, others were cartels that fixed prices. They undercut prices to an extreme degree, subsidized fares, and when it either drove local taxi companies out of business and spurred widespread adoption as the default, it had a captive market and duopoly with Lyft which allowed them to raise fares without losing any market share whatsoever. It's a pretty classic business strategy, and not directly comparable to any of the AI companies. There's a reason people compare the current situation to the dotcom era and not Uber. Also, don't take Uber as an example of a slam-dunk VC success story and leave it at that -- plenty of dumb ideas get pitched and funded and go bankrupt for every Uber.
    • hungryhobbit 4mo ago
      Yeah, people forget the risk to Uber was real in the early days. If municipalities had enforced their taxi laws, the company would have died and all those millions invested would have been lost (or pivoted into something else). It was only because Uber successfully bulldozed over all regulations that it was able to succeed ... and that was hard to predict before it happened.
    • james2doyle 4mo ago
• adamtaylor_13 4mo ago
  Ed is an interesting character. His financial analysis of the AI industry makes logical sense to me (though I am not knowledgeable enough to actually know if it is correct.) However, he seems to be so angry at AI in general, that he misses the obvious areas where LLMs are actually changing the State of the Art. Coding seems to be one of the core use-cases for LLMs (as Simon Willison pointed out recently) and even if that's the only real use-case for LLMs, they're wildly useful. I do understand that useful != profitable and that's where I think Ed has a real point: until inference becomes much cheaper these companies cannot be profitable. Some mega-players will pay the API token price, but most will not.
  • hungryhobbit 4mo ago
    I don't think whether "LLMs are actually changing the State of the Art" or not matters for anything he wrote. If the AI companies need $X billion in revenue to stay afloat, it doesn't matter if 0.5% or 5% or 50% of that revenue is from transforming the State of the Art. It's 100% irrelevant: what matters is that, transformation or no, these companies won't have the income to pay their bills. And if they can't pay their bills, a whole lot of other companies can't either. So again, transformation or no, it's still a house of cards waiting to collapse. The only thing that would change that is not more "transformation" ... it's a feature set that lets them multiply their current user base (or multiply how much they charge them) several times over.
    • anthonypasq 4mo ago
      maybe its insane to think this, but if all AI providers turned off free plans tomorrow i think they would easily have enough people willing to pay $20 a month for it to sustain all their spending. everyone is still fighting for market share so they are giving stuff away, but that doesnt mean people wouldnt be willing to pay for it if it wasnt free.
      • FromTheFirstIn 4mo ago
        This proposition boils down to a belief that there are 3 billion people who are interested in AI for free but aren’t currently paying $20, but who would pay $20 if that was the price. The global median income is around $12k, so this would mean that there’s roughly be a global budget of 0.5% of everyone’s annual income going to chatbots. If you’re off by half, the price doubles for each person. I think you’d make a lot of money betting against the existence of 3 billion ghost customers
• bilater 4mo ago
  every week I see this guy on HN. only forum where ppl still buy this c**
  • tim333 4mo ago
    The top twenty comments are negative about Ed. I think maybe HN just likes being skeptical.
• stephc_int13 4mo ago
  His rhetoric is a bit obsessive and frankly biased against AI. That said, I think his voice is useful as a counter to the mainstream opinion. Given the amount of investments, approaching AI from the angle of economics seems correct. We all have some level of personal experience using AI/LLMs, both chatbots and coding tools, and I personally enjoy using them, but I am sure this experience is relevant in this discussion. I also enjoy luxury hotels, gourmet food, jet skis and helicopters, but this is not something I indulge in often because of the cost-utility ratio. The real cost of AI may or may not be lower than its utility. The bet is that utility is increasing while cost is falling.
• dwaltrip 4mo ago
  I'm so sick of people who peddle outrage for a living.
• tencentshill 4mo ago
  All the top comments are commenting on the author. And now I add this metacommentary. Probably good it was flagged.
• vb-8448 4mo ago
  Zitron is in the business of content creation and not successful predictions. It doesn't matter how many times he (and several others around) will say the end is here, they have to be right only once. BTW, one thing for sure he is right about are the economics, as of today there is no way these massive investments are gone be paid.
  • DonsDiscountGas 4mo ago
    For the purposes of content creation they don't even have to be right once
  • JacobAsmuth 4mo ago
    Now that you mention it, has Ed ever made a single testable prediction that came true?
    • disgruntledphd2 4mo ago
      That prices would increase for the frontier models, and that usage limits would go down.
  • raincole 4mo ago
    They don't have to be right even once. Why do they?
• titzer 4mo ago
  > This is a hysterical era perpetuated by liars, cowards, imbeciles, craven boosters and the easily-fooled. Those excited about generative AI are either the victim or the perpetrator of a con centered around a technology to ingratiate at the highest cost possible. Who writes like this? When you lead with "everyone who doesn't agree with me is a lying cheat coward imbecile" I think we should just turn the volume down on you to zero. This is breakdown in dialog. If it leads like this then I I don't care how accurate the critical analysis to follow is. I didn't read the rest of the article and don't think anyone else should either out of sheer disdain for this argumentation style.
• binyu 4mo ago
  AI has been slowing down relatively, considering its trajectory over the past 20-30 years. For one, even if LLM may have plateaud in terms of intelligence-parameters ratio, research is on-going on new frontiers for ML, including (but not limited to) world models. Other research directions are studying backpropagation and its physical analogies, such as equilibrium of chaotic states. In addition, there's a lot of research on the hardware angle and actual prototypes are already being built such as AI-on-chip Cerebra and Taalas for one.
• voxleone 4mo ago
  [flagged]
• Animats 4mo ago
  * * *
  • josephlord 4mo ago
    Isn’t the thing that an LLM never knows (at all)? It just guesses words based on the context and previous words and often gets lucky. It isn’t thinking or knowing and then expressing the resulting understanding but just spitting out contextual words and hoping it reaches a conclusion or ending of some sort.
  • kgeist 4mo ago
    >LLM-type AI exacts huge costs because it is terrible at reporting "I don't know". When it doesn't know, it generates noise and polishes it. >If a "confidence too low for output" signal could be extracted, this whole technology would be a lot more useful Anthropic's interpretability research explored this topic a bit in 2025. Apparently, the signal is extractable: It turns out that, in Claude, refusal to answer is the default behavior: we find a circuit that is "on" by default and that causes the model to state that it has insufficient information to answer any given question. However, when the model is asked about something it knows well—say, the basketball player Michael Jordan—a competing feature representing "known entities" activates and inhibits this default circuit (see also this recent paper for related findings). This allows Claude to answer the question when it knows the answer. In contrast, when asked about an unknown entity ("Michael Batkin"), it declines to answer. By intervening in the model and activating the "known answer" features (or inhibiting the "unknown name" or "can’t answer" features), we’re able to cause the model to hallucinate (quite consistently!) that Michael Batkin plays chess. Sometimes, this sort of “misfire” of the “known answer” circuit happens naturally, without us intervening, resulting in a hallucination. In our paper, we show that such misfires can occur when Claude recognizes a name but doesn't know anything else about that person. In cases like this, the “known entity” feature might still activate, and then suppress the default "don't know" feature—in this case incorrectly. Once the model has decided that it needs to answer the question, it proceeds to confabulate: to generate a plausible—but unfortunately untrue—response. https://www.anthropic.com/research/tracing-thoughts-language-model https://www.anthropic.com/research/tracing-thoughts-language...
• Kiro 4mo ago
  [dead]
• bazaah 4mo ago
  I hadn't heard of the TMobile and Brex spend caps, only knew about Uber's because it went viral last week. I expect we'll see more of that now that everyone is paying per token, and it sort of feels like you cannot both have spending caps and require extensive AI usage for performance reviews -- I wonder that will shake out in the end? Anecdotally, $dayJob consumes Anthropic models via Azure subscriptions which lend themselves pretty neatly to the spending dashboards Ed mentions are missing from Anthropic themselves, and finance seems ok with the current usage, but there's no real hard incentives internally for AI usage either. I guess Q3-4 are going to be interesting to see where this all goes.
• simonw 4mo ago
  Ed's argument for why "AI is slowing down" rests on company spending caps, in particular the Uber $1,500/engineer/tool cap. I interpret the exact same evidence in the opposite direction. A year ago the idea that a company would spend $1,500/month/employee on AI tooling felt absurd, what could people possible want to do with AI that would cost that much? Then coding agents (and, increasingly, general purpose agents) happened and suddenly companies are having to set limits because otherwise the demand from their employees is too high. The TAM of these AI companies just leapt up to $1,500/knowledge-worker/month, how is that "slowing down"?
  • gdcbe 4mo ago
    Maybe in USA in big tech where companies give absurd wages to engineers anyway in some states, that might be acceptable. But to make their ROI they need that (and more) to be spend world wide... no way that is gonna be a budget that is gonna fly in the long term... Companies love to cut costs, and just like they axe employee numbers at will, they will just as well make that kind of budget quickly dissapear the moment they realize they can go a different path for same or better value... Or simply because share holder short-term value demands it...
    • simonw 4mo ago
      The Uber $1,500/engineer/month thing is just the first signal we have had of the price companies may be willing to accept. This price will clearly vary wildly across professions, industries and geographies. I think it's a poor number to build an "AI is slowing down" narrative around.
      • B56b 4mo ago
        The problem is that $1500/engineer/month would be a pretty modest amount of demand for labs. OpenAI/Anthropic are basing their $1T valuations on the explosive uncapped growth of unlimited agentic token spending. On so many levels of the industry this growth is now priced in. You don't think so?
        • 4mo ago
• 1vuio0pswjnm7 4mo ago
  "Last week I went on Bloomberg and discussed the state of the AI bubble with a clarity that rattled even the sweatiest boosters, mostly because I spoke with clarity about an investment frenzy whipped up through hype, deceit and mythology." Bloomberg is interested in what he has to say But not HN commenters
  • tim333 4mo ago
    Well there are a lot of commenters so presumably some interest. I just had a look at the Bloomberg bit https://youtu.be/zbKDmkJPVvI https://youtu.be/zbKDmkJPVvI and didn't see sweaty boosters rattled, just Ed doing his usual spiel - they are loss making and so it's all a big con. Which is kind of unproven on the big con bit.
  • deleted 4mo ago
    [deleted]
  • 1vuio0pswjnm7 4mo ago
    "Can I Advertise On Your Newsletter? Yes! Email me at ed@ezpr.com. I have an extremely high bar both for advertisers and the cost of advertising on here - I have 84,000 subscribers and a 55-60% open rate, as well as an 8-11% clickthrough rate. I do not do any kind of outcome-based advertisement (IE: X number of people click through and you pay me Y), so any kind of agreement would effectively be a sponsorship. I have an engaged reader base and you will have to pay to get in front of them, as I also do not need advertising to support this newsletter." Maybe the "AI" companies could pay for sponsorship Would he take the money and run their ads
• putzdown 4mo ago
  One of the "smells" that gives away a quacky ranter is they speak in impassioned, "Why doesn't everyone understand this?" tones, but in fact their argument just doesn't flow. If Zitron's argument were as solid as he keeps saying it is, you would read it and understand it and see that it is solid. He would begin somewhere–statistics on AI demand, say–and then walk the calculations carefully over to the next step–maybe revenue needed for profitability by AI companies–and you could follow the argument. But no. He jumps. He leaps. He circles back. If the situation were really "Gosh why can't you see it?!"-clear, his explanation of the situation would be clear. It isn't, because it isn't.
  • Terr_ 4mo ago
    > He would begin somewhere–statistics on AI demand, say–and then walk the calculations carefully over to the next step–maybe revenue needed for profitability by AI companies–and you could follow the argument. Which of the hyperlinks provided at the beginning sounded like what you wanted, and after you clicked it* how did it disappoint you? The information you are describing is stuff I would not expect anybody to repeatedly duplicate across periodic blog-posts. * (Yes, I'm being sardonic, but if you did bother to click them, then I'm legitimately interested in your answer.)
    • athrowaway3z 4mo ago
      He's right that its all going to pop dramatically and catastrophically for some. But having read a bunch of his stuff, there are two things he's just plain wrong about and they make his martyrdom tone too grating. - His own objectivity - he consistently throws shade (rightfully) at the pro-AI side being financially 'required' to hold a certain world view, but is completely blind to his own claim to fame effecting him similarly. - He consistently claims AI can't be made to work, and tries to prove this by calculating with the bubble prices. Its like saying tulips could never be profitable in the middle of the mania because ships were too expensive as proven by their current price to use for shipping tulips. Add in the semi regular instance downplaying AI's usefulness contradicting my own experience and I mostly dont bother reading him anymore. Its not like I'll be surprised that shit hits the fan, and he's not going to call the 'when' any better than wallstreetbets or an octopus.
• ainch 4mo ago
  As WIRED reported[0], despite constantly writing about how an AI collapse is just about to come, Zitron privately does PR for AI firms on the side. The man is an obvious hack, and it's disappointing that he has become one of the mainstream faces of AI skepticism. [0]: https://www.wired.com/story/ai-pr-ed-zitron-profile/ https://www.wired.com/story/ai-pr-ed-zitron-profile/
• qaq 4mo ago
  Anthropic has made $330 billion in compute and chip commitments between Google, Amazon, and Microsoft, another $30 billion with CoreWeave and another $15 billion with SpaceX. To pay for this compute, Anthropic must meet its projected revenue of $174 billion a year by 2029. Anthropic has raised $95 billion across rounds in February, April (from Google and Amazon), and May. These funds will be insufficient to cover Anthropic’s costs, as will Anthropic’s cash flow, meaning that it will have to raise at least another $200 billion in the next year. How people take this seriously? Anthropic is at 45B ARR S-1 shows inference margin climbed to 70% (obviously could drop) So where that 200B number is coming from ?
  • thereitgoes456 4mo ago
    Anthropic's S-1 is not public yet
  • bandrami 4mo ago
    That wasn't an S1 and we have zero idea what GAAP compliant numbers for Anthropic or OpenAI would look like
• micromacrofoot 4mo ago
  It doesn't matter if it's slowing down, pretty much no one has implemented it to its full extent yet. It could stop right now and we'll be finding new implementations a decade from now. Anthropic and Open AI could evaporate tomorrow and we'll still be using the models. The market may collapse, but the people who think AI is going to disappear as a result don't understand what it is.
• andrewstuart 4mo ago
  AI companies are racing to win the future of computing. They are possibly in a winner take all death race against each other. The stakes are so high that these cash rich companies cannot afford not to throw everything they have into this. The sunk costs are irrelevant when it’s a question of survival. Whether you hate or love AI computing is being completely reinvented - at the absolute core of this is computers programming computers. Anthropic is winning this race by a country mile right now. This is such an important future bet for these companies that the trillions must be spent because there’s no future or a greatly diminished future for some of them unless they have ownership of the technology.
  • Supermancho 4mo ago
    > Anthropic is winning this race by a country mile right now. How's that?
• SubiculumCode 4mo ago
  I stopped as soon as the popup hit.
• dsign 4mo ago
  The way I see it, AI is going to change the world radically. It could be for the worse, the better, or a mix of both, but in my mind there's no doubt. We are only five or six years into the leap LLMs represent. For reference, radio waves were discovered in 1886, Marconi used them for communications in 1895, and while telephone and radio coexisted for many decades, it wasn't until the 1995 that mobile phones and wireless technologies started picking up. It took so long not because of the physics of radio waves required time to mature and improve, but because everything else needed to profit from it did require time. To me, LLMs are not so much AI as it is a building block. Radiowaves maybe, or the equivalent of transistors. We are already seeing that it's possible to chain LLMs into agents. Currently, price is a strict limiting factor for coding and agents.It's probably fine-ish if all you want is Claude Code or Codex, but there are many other possible compositions of LLMs that most people don't dare to experiment with. For example, LLMs to drive NPC dialog and world mechanics in games is not a thing due to cost. Were prices of inference hardware go down and inference algorithms keep improving, I'm convinced (and afraid) we would see things very difficult to imagine today.
  • A_D_E_P_T 4mo ago
    > For example, LLMs to drive NPC dialog and world mechanics in games is not a thing due to cost. Hah, I'm actually working on just this problem. Cost isn't the issue. There are only so many coherent (in context) responses and scenarios, that you don't need an LLM to generate text in the game, in real time. Instead, you can have LLMs build a vast corpus of "atoms" (dialog messages, fragments, cues, etc.) that can be stringed together in a deterministic way in response to player input. These can also be pre-screened and subjected to various tests prior to implementation. To a player interacting in the game, a system like this would seem functionally indistinguishable from generated text within the game's designed interaction envelope. And it has huge advantages: Although it can expose seams if the player breaks character and decides to probe it, it won't be exploitable the way an LLM would be.
  • 48terry 4mo ago
    > The way I see it, AI is going to change the world radically. It could be for the worse, the better, or a mix of both, but in my mind there's no doubt. Worthless statement. Wow, you suspect something can make things better, worse, or both? That's a keen insight there. > For reference, radio waves were discovered in 1886, Marconi used them for communications in 1895, and while telephone and radio coexisted for many decades, it wasn't until the 1995 that mobile phones and wireless technologies started picking up. We are still so early. I mean, we have advertised them in multiple super bowls, have companies that basically own tech news (incredulous journalists will repeat any stupid insane shit a CEO wants to say), that say they're valued at over a trillion dollars and nobody with the power to argue those finances seems willing to do anything but agree. We have built hundreds and hundreds of acres of data centers (and made deals for data centers that are never going to happen) that demand *billions* per month. They are devouring all the silicon to where people are visibly seeing the price of hardware double, triple, more in price. Work places insist on employees using AI (then pulled back because it turns out this stuff costs money and it's not fun anymore when it's not subsidized). But we just need more time, more eyes, more people looking at it. Where in the radio wave timeline did this happen?
• Havoc 4mo ago
  >have to be roughly twice the size they are today, and then double again basically every year until 2029 or 2030. Anthropic is growing way faster than doubling yearly so don't think this is entirely implausible
  • aronowb14 4mo ago
    I asked around my network recently - in the last month or two basically every large company has put in spending limits per engineer. Curious what their S1 will look like when they go public.
    • Havoc 4mo ago
      In the long run I’d say the real question is how much of the labour market you can displace rather than looking at tool spend That’s really the only way the math works - outright displacement of labour
• atleastoptimal 4mo ago
  This is wishful thinking. AI is still getting better rapidly. Anthropic's revenue is still growing at an unprecedented rate and they haven't even released their best model (Mythos) for 4 months now.
• hereme888 4mo ago
  Funny I just read an article on how it was actually speeding up.
• zuzululu 4mo ago
  I don't think anybody actually believes that the current investment is going to yield returns that they are projecting. Neither did people back in Dotcom or Railways or any other hype/bubbles. Yet these technology did transform and the returns came to fruition. Internet continued to thrive and grow even after the stock market came and went, it took 13 years to roughly nasdaq to recover but the explosion of GDP from internet has been largely decoupled from the previous bubble boom and bust. If you use the stock market as a yard stick to project new revolutionary technology we shouldn't have had trains, internet. In fact internet should've stopped with the bust of Nasdaq and everybody would've moved back to using paper but we didn't it gave rise to the next wave of economic output powered by this new tech. I don't see AI to be any different.
  • degamad 4mo ago
    > it took 13 years to roughly nasdaq to recover So it's okay for everyone's who's due to retire in the next 13 years to have their 401k or equivalent wiped out when the correction happens?
    • zuzululu 4mo ago
      do you think so ?
• RigelKentaurus 4mo ago
  The handwringing tone of the article is off-putting. Ed is confused between whether AI is useful, and whether the current level of funding and valuations are sustainable. The following statements can both be true: 1. AI is already quite useful and will continue to be so. This is true even if AGI doesn’t happen. 2. The funding and valuations of many AI companies are too far ahead of their skis, and will probably roll back. Some may fail entirely. About the “where’s the productivity in AI?” question: I think it’s entirely possible that the primary benefit of AI will not be top-line growth but reduced costs (through reduced human labor). Companies will need to reduce prices to prevent losing market share to existing or new competitors, meaning that GDP may not increase, but costs will.
• yalogin 4mo ago
  As a tangent, I don’t understand where and why meta fits into the AI race. They did not get any mind share (consumers) from the llms so far, granted they started the open source side to this but the Chinese companies produce far better models and have essentially become the default for on device set up. They have ai glasses and integration into instagram and facebook as the other avenues. I don’t see ai glasses as compelling yet, and don’t know how much more ad revenue or user engagement they can squeeze out with llms baked into the IG of FB flows. They are spending a lot and not seeing any returns. Am I wrong in being pessimistic about meta with AI?
  • overgard 4mo ago
    You should probably be more pessimistic about Meta. Look at their last major venture, the Metaverse, which was basically embarassing. Their AI strategy is incoherent.
• gnarbarian 4mo ago
  if you think AI is slowing down, you may not be smart enough to tell the difference anymore.
• paulbjensen 4mo ago
  I find it nuts that I can use Claude Code for $20pm - I imagine that won't last forever but have to say it is great value for money. So when I see monthly budgets in the thousands for developers at some larger companies, I'm curious to learn how they are managing to spend that kind of figure: how much code/documentation are they feeding into their prompts, are they using agent orchestration systems to make the code factory run 24/7, and how much value is coming out the other end versus before? And, if they are pouring thousands into LLMs per developer, have they considered looking at alternatives like having LLMs running locally on own hardware with their own agent harness? Those are the kind of questions I'd love to ask - I just wonder how much stuff is truly cutting edge and how much might be wasteful?
  • bloomca 4mo ago
    Developers at big companies need to pay per token, they don't have subscription available. So in case you use that, you likely spend way more than $20 in tokens. As for how to spend that much -- not that hard, to be honest. Just give it a lot of context and some relatively open-ended problem and it will easily eat through tons of tokens. I have $200 subscription for Codex and it is crazy what it can do in terms of debugging. I have a pretty complex Electron setup with some native code linked via Node addons, a few App Extensions and it can easily read the source code to see how the builder works internally (e.g. if your end Info.plist is not correct), debug the xcodebuild output to see at which step something is not linked correctly (like after XCode major version bump), etc. It is not a silver bullet but if you are not the one paying for it, there is no downside to throw a problem at it and see if it can come up with a fix. > And, if they are pouring thousands into LLMs per developer, have they considered looking at alternatives like having LLMs running locally on own hardware with their own agent harness? I am curious about that myself. I have a good machine now (Macbook Pro M5 Pro with 48GB memory), so I'll give it a try; I don't have high expectations so if it is actually helpful would be very neat.
  • overgard 4mo ago
    I just looked at ccusage for a personal project. In 5 days (doing it as a hobby) I've managed to spend $250 in API tokens on a $200 subscription. 5 days, and thats on one computer (I split time using 3 of them). If I had to pay $2000 a month -- no fricking way, not worth it.
• tossandthrow 4mo ago
  Given how I can manage and develop a huge production code base with an incredibly small team - and the rest of the industry apparently is not able to do it - I deem that we are still in the very early days.
• ilaksh 4mo ago
  Although I see huge utility in AI, I think he is right in terms of overspending and overenthusiastic build out. Because of for example what Apple is doing by putting an extremely efficient model with task adapters right onto phones. Also because we now have a massive demonstration that vastly more efficient hardware is desperately needed. Similarly other effective efforts towards on-device AI like Nvidia RTX Spark PCs and 2bit quants of strong models like DS4. So inevitably, significant investment will be going into vastly more efficient CIM efforts like Mythic AI and new FeFET devices etc. in order to make human-level and beyond AI at scale feasible. There is so much demand for this and the power requirements of current hardware are so excessive, it seems unlikely that the data center build-outs will be able to recoup their costs before the more efficient paradigms make it out of the lab and start scaling.
• jollyllama 4mo ago
  Lots of dismissive comments ITT, very few tackling the substance of the article. > AI Cannot Afford To Slow Down — It Needs $3 Trillion Or More In Revenue By End Of 2030 To Sustain Its Existence Is this true? With the total 2024 wages being 11.7 trillion USD [0], and nonfarm payrolls totaling 158,000 in the same year [1], it's an order of magnitude higher than my back of the napkin guesses I've made that AI needs to take or create 1/20 jobs minimum to break even. [0] https://fred.stlouisfed.org/series/BA06RC1A027NBEA https://fred.stlouisfed.org/series/BA06RC1A027NBEA [1] https://fred.stlouisfed.org/series/PAYEMS https://fred.stlouisfed.org/series/PAYEMS
  • irishcoffee 4mo ago
    If I thought there were some actual small cabal of people running the global economy, this is almost like a novel: massive amounts of money entered the economy starting in 2008 and 2020-2023, the rich became insanely wealthy. Their wealth is now all tied up in the 2020s version of the railroad/fiber, we're going to essentially erase trillions of dollars from the global economy and reset. We sure do need a reset.
    • philipallstar 4mo ago
      [flagged]
    • marcosdumay 4mo ago
      I really doubt the US will erase any money any time soon. The reset is prone to happen by other means.
      • irishcoffee 4mo ago
        I consider myself of average intelligence, and I see this coming. Maybe I assume too much.
        • marcosdumay 4mo ago
          Every government has complete control on how much of their money exists. If it disappears from the private finance market, it can compensate with any amount it wishes.
• ofcourseyoudo 4mo ago
  I guess my ears kind of turn off when you say "it's all slop, none of the apps are good, and it's a failure because no one has used AI to make the next Salesforce". I have found agentic coding to be extremely useful for a bunch of small, middleware, very focused bits of software for small businesses: * A company had a very specific scheduling need, they needed to move about 8-15 staff around with a bunch of different shifts, and have custom reports on who was working how many hours, and have the employees get a nice clean email summarizing their schedule * A manager wanted a very simple "let me send a text to add a to-do to the group list" need * A sales team of 3 wanted to be able to type pricing of raw goods into their phone, have it compared to other market sources, and have it text the other 2 salespeople and their manager when they were out in the field All of these were coded with Codex in about 4 hours with further refinements over the next week of back-and-forth with the people using the tools. I suppose yes we could have found some custom middleware solutions that did similar things, but it's nice to be able to make a web page or tiny mobile app that just does EXACTLY what the person wants. It's hard to do that and then listen to someone who says it's all just garbage.
• jillesvangurp 4mo ago
  I think it's time to distinguish between what frontier AI companies need regarding AI, and what will happen with AI if these companies don't get everything they need. Probably there's a bit more to this. Much of the technology is available via open source already and there's a growing ecosystem of AI tech that isn't really dependent on anything else than the hardware infrastructure needed to run it. A good analogy might be networking companies and infrastructure companies during the dot com bubble. It devalued a lot of companies but the internet stayed. A lot of dot com companies didn't make it. Much of the infrastructure investment did not go to waste, however. Nor did a the technology go away. I think it will be the same with data centers, related infrastructure, GPU hardware, algorithms, OSS components, etc. for AI companies. More companies need that stuff than is currently available. The ones that don't make it will have a lot of assets that they can pass on to the one that still have a chance. I don't think a lot of that stuff will get decommissioned or will be underutilized. It might get a little hair cut in value though. And like during the dot com bubble, some companies actually survived and did quite well. Especially those in the business of selling shovels during a gold rush. After the inevitable consolidation that follows the next logical stages in the hype cycle, I don't think AI will go away. It might be a bit of a bloodbath for some silicon valley investors that placed the wrong bets in the last few years. But that's the price of doing business over there. That doesn't mean it's all bad. And the smarter ones probably spread their risk enough that they still might come out looking alright. And like with the dot com bubble, many financial types have no clue what is happening and are running around like headless chickens. Which is why they ended up sinking a lot of money in exactly the wrong things. You'd hope they would have learned something. But articles like this suggest that that might be too much to hope. They still don't really get how technology tends to not stagnate and might continue to deliver potential for performance and cost optimization. The current level of investment is only unsustainable if that doesn't happen and nothing else changes. I don't think those kind of closed world assumptions are a safe bet at all.
• josefritzishere 4mo ago
  He may be bombastic but Zitron is right about the AI problem. These companies do hemorrhage cash, and have no viable plan to even become solvent. It may not be a scam but it sure looks like one. The problem it poses for the economy... is just as he says.
• dofm 4mo ago
  Today Apple launched its revamped AI offering. Judging by several reports, Apple pays Google a mere billion dollars a year to operate it. Essentially just licensing the IP. Google are (allegedly) happy to turn over the right to operate and distill their models for only a billion a year. Consumer revenue is only a smallish share of the puzzle, but still: If you are a consumer and you have a Mac or an iPhone, what do you need from AI that Apple's new offering won't provide? Why would you pay for ChatGPT, or even tolerate its inevitably increasingly desperate ad placements? Assume Google will have similar tools in their phones, and Google search will continue to have the offering it does. In short, where is the evidence that once Apple's tech exists, consumer AI is worth, to Anthropic or OpenAI, anything noticeably more than that $1B a year? Maybe OpenAI strikes a deal to put something in Samsung phones. Let's say Samsung is ten times as desperate as Apple (which is how it looks, often). Still only $10B a year? 2026 consumer revenue projections from OpenAI are pitched at $14-15 billion, apparently. If they get that, it's the only year they will get that, because by late this year, everyone with an iPhone will have something useful built in. Ed Zitron is a mouthy British rabble-rouser, but I think he is probably mostly on the money.
  • jredwards 4mo ago
    I expect that a lot of the money will be in Enterprise AI.
    • dofm 4mo ago
      Right but OpenAI are for real making that prediction about their consumer revenue, which seems decidedly ambitious (considering that they are making nothing from their current phone placement). And they have said that they expect it to be quite a large share! https://mlq.ai/news/openai-projects-over-280-billion-revenue-by-2030-amid-adjusted-compute-spending/ https://mlq.ai/news/openai-projects-over-280-billion-revenue... "OpenAI projects revenue will be divided nearly equally between its consumer and enterprise business units by 2030" That it is so absurdly ambitious and so likely to run up against reality strikes me as really indicative of the quality of the envelopes these calculations are being sketched on.
• kachoio 4mo ago
  Bbut.. Elon said we are all going to be billionaires
• pxeger1 4mo ago
  This rests on a lot of assumptions that the published figures for "planned" datacentres, "committed" AI spend, etc. are irreversible. I suspect that at least some of it is possible to back out of.
  • bandrami 4mo ago
    That's true but then that's basically the end of Nvidia if that happens
• brianwmunz 4mo ago
  The thread keeps smushing two separate questions into one. "Can these companies hit the revenue they need to justify the capex" and "are the tools actually useful day to day" are different arguments, and you can answer yes to the second while still being worried about the first.
• real_winidi 4mo ago
  The chart seems logical to me. Most problems are solved in the app space. New apps don't have to be the new facebook. They just need to be useful for the right audience (even a small one). It's like you have meat and bread in the supermarket, and add all other stuff you dont really need. Will be bought, but not as much as meat and bread, right?
• thewebguyd 4mo ago
  Whats a bit wild to me is Google's only selling point for their Pixel phones are increasingly Gemini. Now that you can get Gemini, operated by Apple (with the Apple privacy features that come along with that), why would you ever consider going Android/Pixel (outside of running GrapheneOS, but I'm talking regular consumers here)? Google isn't even making anything on the deal with Apple. They pay $20B/year to be the default search engine. This is Apple just giving a $1B a year discount to that to be able to license Gemini.
  • cflewis 4mo ago
    I switched from iPhone to Pixel after I couldn't stand Liquid Glass and found myself using Gemini more than I expected. If you're in the Google ecosystem like Gmail and Calendar, it is exceptionally refreshing to be able to use an assistant that uses that ecosystem, instead of iOS requiring you to use Mail or its own Calendar app. I don't think there's any real gap between Pixel and iPhone on the things that matter: UX jank, battery life, camera. Even the messaging issue in the US has closed with encrytped RCS support between them launching. So now it's just an ecosystem question, which might be why Gemini is mentioned so much with Pixel.
  • nicoburns 4mo ago
    Android phones are also quite a bit more capable than iPhones in a number of ways due to being more open. Plenty of people just straight up prefer the experience (and plenty of others prefer the cheaper prices).
  • dofm 4mo ago
    Yes. And there is only one other major phone brand in the West with this kind of clout: Samsung. Who I think will want their own thing that isn't Google's, and who do have some connections to OpenAI. But given how dependent OpenAI are on Samsung, it's hard to believe they will see a radically better deal in material terms.
• kingofbits 4mo ago
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• vineyardmike 4mo ago
  The obvious answer to where the AI Labs get customers is Cloud GPUs. Most users (globally) have cheap phones with poor CPUs and small amounts of RAM. They can't run usable models locally, and it's not clear from the Google-Apple deal if G is selling access to their cloud compute as part of that $1B, or just sharing the weights/IP. Apple themselves have said there is usage limits, with a subscription upgrade for more usage. So clearly AI Labs are directly competing on that front, it's just a normal default/chosen decision. Considering there are defaults and still successful competitors (eg. safari v chrome), there's no reason to think that competition can't handle this too. Edit: I want to add that Google is also probably willing to give the model away at a discount to its true value in exchange for guaranteeing that their primary competition (who has tons of cash) won’t have an economic incentive to enter the foundation model training arms race. Most users who actually want these features for anything more serious than summarization and style updates will probably find value in a modest subscription or ad-supported tier of higher quality models, even if just for occasional usage. Apple can provide this, but once you're comparing features, for many Gemini/Claude/ChatGPT may be a better fit. Oh, and I think there is an unfortunate but real risk that once again, apple totally over-promises here, and their AI models that they ship end up being pretty poor, and that drives users further into subscriptions.
  • dofm 4mo ago
    > Oh, and I think there is an unfortunate but real risk that once again, apple totally over-promises here, and their AI models that they ship end up being pretty poor, and that drives users further into subscriptions. OK, that I would concede is a possibility. Though Gemini is clearly capable, and the (alleged) story is that they have licensed a one-trillion parameter form of Gemini. I don't think they are making the same mistake. ETA: I also concede they could make a different mistake ;-)
  • avidphantasm 4mo ago
    The AI labs are racing to create a moat out of trillion-parameter models and the GPUs that can run them. The problem is this is the wrong architecture for most AI inference use cases. On-device inference is where this is going, clearly Apple believes this too. So Zitron is entirely correct about this AI datacenter build out being a boondoggle with no ROI.
• brap 4mo ago
  It always seemed very natural to me that AI will move “down the stack”, where Open AI and Anthropic don’t really have a foot in the door. Who makes consumer devices? Google Who makes operating systems? Google Who makes browsers? Google Who makes the world’s most popular websites? Google By the time 90% of average internet users get to chatgpt.com or whatever, they already went through several Google chokepoints, each layer is one more place Google can answer their questions. And that’s not even getting into the chips, the data centers, the data, the talent, the consumer apps, the enterprise apps, the cloud platform, the brand, and of course the biggest cash printing machine in human history. You would honestly have to be insane to bet against G.
  • chronci3740 4mo ago
    [dead]
    • ordinarily 4mo ago
      Google literally invented the boat (transformers) to be fair.
      • graphime 4mo ago
        > Google literally invented the boat (transformers) to be fair. Isn’t that more damming for Google? Invent the boat, don’t know how to use it, abandon it, then someone else comes along and steals your boat.
        • ordinarily 4mo ago
          I think most of Google's deep research projects were done in the pursuit of pure science, not monetization or productization. In hindsight sure, it looks like they missed an opportunity. But not everything needs to be about money.
  • dwaite 4mo ago
    Part of the pitch of AI companies is that they mediate and provide a new surface for ads, for taking an affiliate cut of sales, etc. But it isn't like this hasn't been the long-running strategy for Google as well - provide more results on search so that people don't go to the site with ads, provide paid product results for shopping, to offer more services to keep people providing personal/behavioral queues to Google and more opportunities for ad placement. If anything, AI turned up the heat such that the frog noticed what temperature the pot was. But that doesn't really put them in a better position to execute than Google.
• guluarte 4mo ago
  I think the frontier labs are gonna launch new models under a new tier, but they're still figuring out how to announce it.
• loloquwowndueo 4mo ago
  So I open this page and the first line of the article should be the last, right? > If you liked this piece, you should subscribe to my premium newsletter. It’s $70 a year Ok let me read the thing so I can make up my mind… start scrolling down and get slapped by some subscribe pop up. That’s where I decided to just cut my losses and go do something else.
• jeffreyrogers 4mo ago
  I'm sort of an AI skeptic but I have been seeing this guy's essays for years now and he has always been super pessimistic on AI progress. I think a much more reasoned critique of AI is that of Tyler Cowen, whose argument is basically that most processes aren't constrained by lack of intelligence but by organizational and social factors which mean for AI to be useful you have to redesign organizations and work to take advantage of what AI is good at. Since most organizations are fairly bureaucratic that takes a while, especially in the large industries that are the most economically important. Ed's criticism of the large AI companies seems particularly misguided to me since they are the ones actually advancing the technology and seem to have real moats given their access to large amounts of training data from their users. I don't see any possible future in which 5 or 10 years from now there is less AI than we have now and I would expect usage to be much higher.
  • danny_codes 4mo ago
    Completely agree. AI is here to stay, it's going to garner more and more use overtime. However, I'm skeptical that the investments being made right now are at of the right scale & at the right time. I completely agree that over time we'll rework more and more of our society around LLMs or their successors. However, like you say it's a slow process: we have to learn how to do it effectively, organizations need to change, people's attitudes and behaviors have to adapt. I just don't see is "getting there" fast enough to justify current spending levels.
• synapsehire 4mo ago
  [flagged]
• vatsachak 4mo ago
  Yeah. Models haven't really improved much from last year to this year. I really love LLMs for debugging and rubber ducking, but I kinda want to write all my code. LLMs tend to have a hard time understanding composition.
• shillsimon 4mo ago
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• naasking 4mo ago
  > that the infrastructure being built and compute commitments being made are being done so at a level that demands that generative AI and AI compute generate over $2 trillion in annual revenue by 2030 That seems doable. Next generation architectures and the models they produce are accelerating progress. More capable with less data and compute, which ironically will drive more demand, aka Jevon's paradox. > If you are someone in the executive team of any major tech company, know that your employees are, for the most part, completely and utterly miserable. I agree this is a problem. Adopting too eagerly and too early, and not listening to feedback from the people who are using these tools is a recipe for disaster.
• lz400 4mo ago
  Already many comments saying this but Ed Zitron is not a person I trust. He's been so biased and wrong on stuff that I consider very obvious and trivial that his complicated analysis with numbers and trends I can't just take at face value. As an example of obvious wrong things, I remember a tweet of his where he was mocking people talking about agents and agentic coding. He was kind of saying that he was going crazy as agents weren't a thing really and people talking about them like they were real. Something like "agents?! what agents?! these guys hear themselves?!". The answers were full of hundreds of people patiently explaining how they were actually _using_ agents. This wasn't in 2023, it was a couple of months ago. He just has an audience and an engagement target. His objective is clicks, not informing.
  • JoeJonathan 4mo ago
    He also calls everyone a grifter, when he seems like one himself. Im deeply skeptical of our AI overlords, but its disingenuous to keep pretwnding theres nothing there.
  • Grombobulous 4mo ago
    He provided a lot of quantitative analysis in this article. Perhaps an example or two you think these numbers are off-base could help bolster this point? I think the most compelling part of the article is that these numbers point to a situation where the level of investment required seems unsustainably high by plain dollars. You don’t really have to agree with the author to see how it plays out. OpenAI and SpaceX and Anthropic need to go public this year to avoid running out of money. There’s no more private money, not enough to fund them. The IPO is the last funding round. They can continue growing extremely quickly and AI can still be highly useful and maybe be transformative, but still not have the money to fund that growth. That part he wrote about an AI company gone bust canceling their Oracle contract made Oracle feel like a Nortel analogy to me. If they have a sudden lapse with a big chunk of their customers they are writing down triple digit billions of dollars.
    • lz400 4mo ago
      I guess what I'm saying is that I won't look at his numbers since he's an unreliable source from my point of view and there's a chance that he's going to try to deceive me and it's a waste of time for me to listen to him. I do have other sources of information and I probably agree in general that AI companies are doing pretty shady financial shenanigans. I even think it's possible that openai is in real trouble. But I don't extrapolate that into "AI is useless", which is what he does.
• akoboldfrying 4mo ago
  It's possible that AI is the greatest technological leap forward since the Industrial Revolution, and simultaneously a bubble that will pop in the near future. I don't know much about the economics side; TFA gives a barrage of stats that seem to make a compelling case for bubblehood. OTOH, the claims about the utility of LLMs being unmeasurable are weak (the same criticism applies to hiring programmers, or indeed most office workers) and the metal spider straw man is frankly embarrassing to anybody who has actually used recent frontier agents for programming and seen what they can do.
• datsci_est_2015 4mo ago
  Always a bit eyebrow-raising to me how much people focus on Ed’s style rather than his message, which is, broadly, that the tech industry is deeply morally corrupted. He struggles to speak about it without becoming impassioned, but I read it as incredulousness rather than baseless hyperbole: “How are you still investing in and working for companies like Meta, despite the overwhelming evidence that they are terrible company that does terrible things to people?”
  • minimaxir 4mo ago
    Style is relevant to how humans communicate and it's not always about the message, and it can sometimes work against it. AP Style is an editorial standard for a reason. IF I WROTE AN ENTIRE BLOG POST IN ALL CAPS ABOUT HOW AI IS LITERALLY SATAN PEOPLE WOULD JUST THINK I AM A CRAZY PERSON
    • tsunamifury 4mo ago
      You're right style does matter, and the flat tone of AP is basically extinct now because it was not a meaningful or widely desired style.
  • bawolff 4mo ago
    > his message, which is, broadly, that the tech industry is deeply morally corrupted If that's his message, why is he going on about ecconomic sustainability? Whether or not you have a coherent business model has nothing to do with how morally corrupt you are. Ultimately i agree with the GP post, the article reads like something preaching to the choir. If you already agree it seems natural. If you don't agree it looks like an incoherent rant that is not particularly convincing.
    • datsci_est_2015 4mo ago
      Arguing against the business model is a method of exposing the tactics of AI businesses as a short term grift rather than a principled venture. The entire economy suffers when grifters profit - there’s not infinite money to spread around.
• LoganDark 4mo ago
  > currently gooning > No matter how horny or flaccid you are These analogies are great.
• deleted 4mo ago
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• labrador 4mo ago
  Missing from Zitron's calculations is government ownership/bailout of American AI in national security interest and winning the race to AGI with China. Trump has been making noise lately of owning 50% of these companies. Taxpayers will prop them up in other words.
• KennyBlanken 4mo ago
  This is apparently news to all the hardware retailers who are continuing to maintain the insanely overinflated prices on NVME storage, DDR5, and even DDR4 memory. Some are still steadily increasing prices. A 1TB NVME drive - a good one - cost about $70. Now it costs anywhere from $150 for shit-tier drives to $300+ for the higher end stuff that used to cost $100-120.
• anshumankmr 4mo ago
  Let us see if Mythos breaks the trend :) or it is another overhyped model (once it is supposedly released)
• zarzavat 4mo ago
  This article would be improved if the author passed it through an AI to tone it down. The writing style is too much for me.
• zkmon 4mo ago
  Ed's posts always sing the same tune - AI spend is unsustainable. But why are the investors pouring into these megacorps allowing them to burn cash? What calculations are the investors making? I would like to see those projections, assumptions and backout plans.
  • fodkodrasz 4mo ago
    The idea is the same as in all hype cycles: Ride the wave and let the small investors hold the bag in the end.
  • yason 4mo ago
    Why bubbles happen? Because investors, out of greed, pour into corporations that burn their cash. The internet was a bubble: you could make a web page and sell it for millions because next year it was going to be worth billions. And then internet grew up. AI is technology that's still beginning to find its place to settle. It's far from mature and that's perfectly fine. We'll have reached a reasonable plateau once the technology and the related stack stops changing every month and instead develops incrementally and boringly over the span of few years. That's like internet in the 2008-2010, and many investors will have a collection of new burn marks by that time. Not only financially there's an unsustainable push for AI by the zealots du jour who are more often than not managers rather than engineers. AI is championed most ruthlessly as a silver bullet revolution by people who least grasp the limitations of AI. It'll take some time to figure out the dreamed-up proceeds won't be there, and "then what?". I predict that the real bottlenecks of development will re-emerge as soon as the limitations of AI will manifest out of the hype. They bottlenecks are human-based, in development processes and in human interactions. A large part of development is trying to understand what we want and what we need and you can't offload that to AI.
  • lelanthran 4mo ago
    Greater fool theory, obviously :-/
  • ndsipa_pomu 4mo ago
    I suspect that it's merely a long-shot bet that AI/LLMs will drastically change the nature of the world's economy and workforce. If there's only a 0.1% chance of that happening, but promises a chance of giving out 10,000% the return, then it kind of makes sense.
• clauderoux 4mo ago
  I have been a pretty consistent user of AI since 2022 (Instruct-GPT), so I don't have a bad opinion about the topic. However, I think the real problem now has become pretty obvious. We are hitting a reality wall, where we simply don't have enough ressources to feed the AI industry. We don't generate enough electrical power nor enough GPU or TPU. For the first time in computer science, the real issue here is the finitude of the physical world. Unless, we start digging asteroids, we are already facing a shortage of raw material and industrial output. In my opinion, the only way to go is small models running on regular hardwares.
  • alerighi 4mo ago
    The future is clearly that, model inference running on consumer hardware not a network datacenter. We are getting there, local models gets better and better, it's only a matter of time. Of course this would be bad news for big AI companies (and whoever invested in them).
  • gbalduzzi 4mo ago
    Aren't small local models worse efficiency-wise? It means that every person must have a powerful enough machine to power a small model, and we are very, very far away from that. The best solution, from an efficiency point of view, is to use smaller models on datacenters, requiring much less of them.
    • pbmonster 4mo ago
      There's an efficiency sweet spot where hardware that people have anyway gets a higher percentage of load. MacBooks have a lot of memory and a lot of FLOPs. They mostly sit unused all day. Yes, the excess energy use will be higher than a GPU in a datacenter doing the same work, but you have to generate an absurd amount of tokens before the dollar-efficiency catches up with the MacBook.
      • gbalduzzi 4mo ago
        You need to have a 3k dollar machine available though, I think you are overestimating how many people have access to it
• crnkofe 4mo ago
  There's a reason why everyone must use agents and LLMs exclusively or be left behind. The entire Silicon valley livelihood is now a stack of cards built on a promise of infinite productivity gains based on LLMs. If that falls we're likely seeing a repeat of the 2008 financial crisis given the insane commitments made.
• jlintc 4mo ago
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• lionelgarnier 4mo ago
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• itsgrimetime 4mo ago
  I don’t think the idea is that these companies are going to make their $ selling their services, that’s just step one. they’re betting that they’ll have their own “country of geniuses in a data center” to put toward whatever thing they think will make them the most money.
• terekhindc 4mo ago
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• 0xpgm 4mo ago
  The best outcome of the AI hype for was to be the investment into next generation nuclear power plants, ushering the world into a post energy scarcity era. Maybe we'll get there, maybe not. These days I only hear of datacenter investments.
• Bombthecat 4mo ago
  Xiaomi just announced a super fast 1t model, doesn't look like it's slowing down
• mayankgoel28 4mo ago
  I see this kind of arguments made all the time by people I know in finance etc, who seem willing to look at AI only from a finance/sociopolitical lens, disregarding tech altogether. The very fact that they are still writing about this for me is impact enough.
• sunkeeh 4mo ago
  Ed Zitron with his subpar takes again. You could kill all the major AI labs today, and even just today's open-weight models are enough to absolutely transform society, with video-game GPU stuck together at homes.
  • gizmo686 4mo ago
    The internet transformed society. That didn't save us from the .com bubble bursting.
  • sownkun 4mo ago
    How would they transform society and why haven't they yet?
    • anthonypasq 4mo ago
      because theyve been out for 6 months? i mean what the hell are you people expecting?
  • daveguy 4mo ago
    From what I've seen lately, Ed isn't saying the technology isn't significant. He criticizes the fact that AI companies are dumping this kind of money into it with circular financing deals. If it goes like you say, (GPUs at home) the AI labs will be destroyed, because no one will need the inference capacity they're dumping money into when they can do the decent part at home. From what I've seen he says it's more "not worth the investment" rather than not a breakthrough. It just sucks compared to the trillions they're spending which they'll never recover, is the argument. But I guess it's easier to strawman the argument to "this stuff isn't going to change anything".
    • watwut 4mo ago
      He is saying technology isnt significant. Again and again and he puts a lot of emphasis on it. He is also focusing the circular financing deals, on it being a bubble etc. Obviously, you can agree with one thing and not with other. And he can be right in one thing and not the other. But, if you listen to what he is saying, he is absolutely saying the technology is not significant.
• dada216 4mo ago
  Am I missing something or does the author not count the existing revenue to cover the buildout? I think they have it covered even in the worst case scenario (and requiring every piece of cash flow they have). Also, if Anthropic or OpenAI fail in their revenue requirements I believe they would be absorbed by the guys with the money printing machines (Google, Microsoft and Meta).
• mkesper 4mo ago
  Hank Green also explains 400 billions are really very much cash: https://www.youtube.com/watch?v=AcjnLc4TH4M https://www.youtube.com/watch?v=AcjnLc4TH4M
• Eighth 4mo ago
  Number of active users on ChatGPT is at an all-time high. Number of tokens consumed on OpenRouter is at an all-time high. I'm not seeing the plateau.
• frozenseven 4mo ago
  The gulf between reality and this tech-illiterate grifter continues to widen. I strongly suspect his shtick will fall apart before this year is over. And I hope at least some have been keeping close track of what he's been saying.
• pcthrowaway 4mo ago
  > The AI Companies Are Going To Start Getting Desperate This is the part that concerns me the most, AI companies will start bidding on increasingly contentious contracts out of desperation. In practice, this means building services that facilitate killing to anyone they're not legally prevented from doing business with... and even then, they may be able to do business with them still through intermediaries.
• hypfer 4mo ago
  It has been a day, and HN is still angry at Ed Zitron for insulting its current gods. Impressive.
• malkosta 4mo ago
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• 1vuio0pswjnm7 4mo ago
  How are the author's missed predictions different from the missed predictions of "AI" believers For example, https://news.ycombinator.com/item?id=48464333 https://news.ycombinator.com/item?id=48464333
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• maxjackson92 4mo ago
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• sermakarevich 4mo ago
  AI or AI adoption? AI in general is not slowing down. New smarter / bigger models popping up, get blocked, new open source models exceed commercial https://x.com/prz_chojecki/status/2065741640635990128?s=20 https://x.com/prz_chojecki/status/2065741640635990128?s=20. All is good here. AI adoption is nowhere near the current capabilities of AI. I think its because of the lack of expertise at companies. Everyone has an opinion but in fact nobody knows how to work with AI. There is neither AI dedicated positions at companies nor AI transformation leaders on the market. What companies can do in this case? Install Claude Code and wait how things change over time.