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  dofm
  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.
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  putzdown
  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.
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  jollyllama
  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 ExistenceIs 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 [1] https://fred.stlouisfed.org/series/PAYEMS
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  dkobia
  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.
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  zachthewf
  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/ from March 2024) arguing that AI is failing, is a waste of money, is bad, will never work, etc.
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  adamtaylor_13
  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.
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  dsign
  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.
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  vb-8448
  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.
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  simonw
  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"?
• Havoc
  >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
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  Kim_Bruning
  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.
• tencentshill
  All the top comments are commenting on the author. And now I add this metacommentary. Probably good it was flagged.
• ilaksh
  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.
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  ElFitz
  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.
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  paulbjensen
  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?
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  swader999
  I think we need to see Open AI's and/or Anthropic's S1's to really know the state of it all.
• yalogin
  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?
• bazaah
  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.
• atleastoptimal
  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
  Funny I just read an article on how it was actually speeding up.
• pxeger1
  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.
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  Animats
  There are real issues on the money front. The big AI companies have a financial model that assumes a huge increase in demand in the next year or two. Otherwise the bubble pops."Anthropic, OpenAI and every other AI company deliberately obfuscated these costs because they knew that the second a user actually had to pay for the fuckups of an AI model they’d scream like they were being stung to death by bees."So some of the growth was purchased by underpricing, subsidizing the customers with venture capital. Uber did that, and eventually got out of it by raising prices and squeezing the drivers.The "fuckup" problem is real. 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. You could use small, inexpensive models on small problems, and only use big models when the small models failed. Most customer service bots fit that model. Needing ever-larger models to fix the noise problem is not cost-effective.
• binyu
  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.
• real_winidi
  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?
• stephc_int13
  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.
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  qaq
  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 ?
• tossandthrow
  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.
• titzer
  > 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.
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  bilater
  every week I see this guy on HN. only forum where ppl still buy this c**
• ofcourseyoudo
  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 fieldAll 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.
• gnarbarian
  if you think AI is slowing down, you may not be smart enough to tell the difference anymore.
• anon
  undefined
• zuzululu
  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.
• RigelKentaurus
  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.
• jillesvangurp
  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.
• SubiculumCode
  I stopped as soon as the popup hit.
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  brindleth
  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.
• josefritzishere
  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.
• kachoio
  Bbut.. Elon said we are all going to be billionaires
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  feverzsj
  I predict the bubble is going to pop right after the midterm election.
• micromacrofoot
  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
  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.
• dwaltrip
  I'm so sick of people who peddle outrage for a living.
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  1vuio0pswjnm7
  "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 sayBut not HN commenters
• kingofbits
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• brianwmunz
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• voxleone
  [flagged]
• Kiro
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  bpodgursky
  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.
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  simianwords
  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.
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  aogaili
  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.
• ainch
  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/