I really respected Ed Zitron, but I feel like he's very much lost the plot on AI.
Scroll back not too far and he was publishing criticisms that no one wants to spend actual money AI. Anthropic has shattered all notions of that since then.
Then there was the idea that even if people want it, we have way too much GPU capacity to ever be saturated. Now almost all providers are hitting limits.
Now, its the next iteration that even if people want to spend money and GPU's are at capacity, its just never going to be profitable. This may or may not be true, especially with more capable open source models that can be served at cost. But at this point, he mostly just brings up anything possible to downplay AI
I said this in the last Ed Zitron article too, but it's more than just having an axe or grind or acting in bad faith (though those are both true as well). He's a completely standard example of audience capture: there's huge demand right now for "AI is a scam" takes, fulfilling that demand is how he makes his living, and he can't abandon it without losing his audience no matter what the facts on the ground do. All he can do is pivot explanations whenever the old ones get empirically falsified.
I don't understand his audience still being in denial about what is coming. There may not be a job apocalypse but there is a decent chance tough times are ahead. Eventually, his audience may turn into outright Luddites. If that happens I sort of hope they don't stop at data centers/AI and go for the whole project of the Internet.
The audience feels threatened. Reading anti-AI hot takes is comforting when you’re afraid it’s going to take your job.
There is a lot of hype right now about AGI destroying the economy, replacing workers, or even ending the world. Companies are embellishing as they run up to IPO. But there’s a lot of unhealthy counter-beliefs trying to take it the opposite extreme. Keeping up with AI news is about avoiding the hype monsters at either end of the spectrum.
I'm not really an AI-futurist or anything, I think the truth is between the extremes, but it seems like a lot of people who are ideologically against AI just move the goal posts whenever a new development is made. They also seem to operate under the assumption that whatever the current state of the technology is is as good as it will ever be. "it can't even do x today, so it'll never be good".
I agree that it’s not going to be profitable, when it comes to monopolistic profit. AI is increasingly commoditized and providers can’t set prices too far out of band with their competition, which includes local models, Chinese distillations, and established giants which can operate at a loss indefinitely. I haven’t seen any moat appear thus far, and we’re rapidly approaching the point where we will learn the bitter lesson again. As another comment said, we should draw a distinction between "AI is valuable" and "AI justifies its current investment levels."
Why did you criticize his past arguments instead of the claims in this article? The one relevant claim you address is basically a shrug on your part. This seems to be purely a character attack of Zitron.
I agree that he is very one-sided, but I doubt his hit-rate is much worse than other pundits in the industry.
I think it's very reasonable to look at the track record when posting anti-AI articles looks like the author's part-time (if not full-time) job: https://www.wheresyoured.at/author/edward/
It's the same idea. The crux of the argument is that the author has a history of bad predictions, so this must also be a bad prediction, or it's at least likely enough to be bad that we done need to invest further analysis into it.
I don't think that's necessarily a bad argument style (at this point it's by far the easiest way to argue that a Musk project won't work for example), but you have to be careful with it.
In this case, there are only two previous predictions being considered. Suppose the author would have been right 75% of the time given their available information; there was still a >6% chance of those predictions not working out. That's a pretty rough bound for ruling them out just on principle in a world where they do actually know a lot about how AI will progress. There isn't enough "track record" to confidently say much about the author's predictions.
Track record would matter if we would need to trust him. (E.g. he knows some hidden insider data which stays secret, while he shares only a conclusion without must justification)
Track record is not relevant if it is a prediction with all the arguments laid out in the open.
Well, I think he is probably right about this one. The costs are just too high and the spend is entirely too high. If the build out and demand is as advertised component prices will keep going up and costs will too offsetting any revenue gains and if they aren’t then they will never be able to justify the investment already made. Either way their entire business model involves a constant carousel of new investors either through private capital or by IPO and they need to keep that charade going for another five or more years or the whole thing explodes.
AI is a neat tool, but I think it becomes a race to the bottom. Who can provide the minimum viable product at the lowest price. And that price has to be pretty darn low for it to make sense for companies and essentially free for it to make sense for consumers.
A lot of the current AI economics seems to depend on three assumptions being true at once: 1. inference costs fall fast enough 2. usage grows into very large recurring revenue 3. customers don't cut once handed the bill
We should draw a distinction between "AI is valuable" and "AI justifies its current investment levels." There's real productivity value in AI, especially for things like search, boilerplate, tests, refactoring, etc...BUT that doesn't mean every enterprise should let token spend grow without strict telemetry, cost-attribution and outcome-based measurements.
The teams that win here will not be the ones using the Most AI, but the ones that treat it like any other expensive production dependency, which means measuring unit economics, cap runway usage, properly align models with tasks(not just Opus everything), and scale workflows with ROI in mind.
MSFT, GOOGL, META, AMZN guided ~$285B combined capex for 2025 — roughly matching their total net income. Every dollar of profit is being plowed back in, which only works if #1 and #2 both hold.
Uber is a good comparison because everyone was predicting the demise of ride sharing as soon as they tried to become profitable.
The subsidies went away gradually and the prices leveled out in a spot where the services are heavily used. Uber became profitable. Ride sharing is affordable.
I think our $20/month plans might become a little less generous and the $200/month plan won’t always allow non-stop vibe coding, but I don’t think the prices are going to rise so much that users are priced out. Like Uber, customers will grumble for a while and then adapt to the new normal.
The big difference is that compute hardware is getting better. I think we might overshoot with data center buildouts to the point that compute becomes cheap, while hardware improvements continue to lower the cost of serving models. Over time the same service becomes cheaper to operate, opposite of Uber where driver wages are creeping upward.
Places that have dollars and not euros. North America, usually, has phone bills that high. If you don't shop around and bring your own device, at least.
Correct, but people still largely don't use those plans. They walk into service provider store, get a "free" iphone, and then pay $70/mo until their next "free" phone in 2yrs.
"I know these facts, they just go to a different school. I'd bring you to them if your Mom would let you leave the neighborhood, but you're just a little boy".
I mean surely to make this claim, you aren't just making it up, surely you've done the research. In that case, what's so hard about sharing facts which you already know? I'm not asking you to put in a bunch of effort pulling financial statements and analyzing everything, I assume you've already done that because I doubt you'd make the claim otherwise.
I like writing my passion projects without AI. Is this so strange?
Using AI to write my software just takes all the fun out of it for me.
It feels like just reading a summary or recap instead of reading the actual full novel myself. Like it defeats the whole purpose of it. I write software because it's fun and it stimulates my mind and teaches me things and improves my skills.
> This is just how the VC game works. Cross-town Uber rides don't stay $5 forever.
Basically yes but there is a small difference I think. Things like Uber took an existing and proven business model. slapped an App on top and priced the competition out of the market. The winner takes it all.
With "AI" it's not yet clear if there will be any winner at all because it's not yet proven if the business model is viable at the "real" price. Think air taxis across town, 5$ a ride, will work at scale for sure, probably won't work for 500$.
Seeing as the physics and economics of SaaS LLMs are a lot different from branded taxis, and that LLM token prices are down 100x over the past 4 years, there is good reason to believe that analogy isn't exactly perfect. Price hikes in the near term wouldn't shock me (in fact they've kinda already happened) but in the long term I'm optimistic
Tokens are a commodity, so the price should drop over the long term as more and more efficient compute comes online. However, in the short term, these foundation models are worth paying for. So I think we will continue to see the price creep up as investors push OpenAI and Anthropic to drive revenue growth.
It's hard to imagine a bright future for either company. The more hopeful analog might be Coca Cola & Pepsi. Both have a commodity product, but due to distribution networks and brand, they command a price premium. But it doesn't seem much fun to provide a high-volume low-margin commodity.
Uber was an application of technologies sitting on top of many iterations of performance optimizations. (Think: the difference between 2009 internet speeds versus 2019 internet speeds. Or, 2009 smartphone specs versus 2019 smartphone specs.)
You could imagine a Moore’s Law-esque cheapening of the tech that coincides with the business raising their prices. That might look like a continuation of simply “using the tools” on the surface, but on the inside it would spell a gradual, meaningful increase in margin
It's hard to predict the future, but it seems likely that flagship tokens will become more expensive, but many people will use free tokens via local inference.
I mean SubQ claims to reason as good as the frontier models, not better, but reasonably as good, and is 5x cheaper, so the future might not be all in on overpriced LLMs. Data science devs don't engineer for scalable performance, they engineer for the model's capabilities first and foremost.
SubQ was validated by at least one third party, not sure if we'll see more confirmation, but 5x cheaper costs is worth it. None of the frontier models care enough about cutting costs of their models, only being the best in benchmarks.
Sorry but no. It's a flawed analogy to suggest that an emerging technology like AI follows the same scaling laws as the taxi industry. AI benefits from active R&D, rapidly improving hardware, compounding software efficiencies, and deflationary cost curves that simply have no equivalent in a labor- and vehicle-dependent service...
Imagine you were looking at Google, a sustainable and profitable business, and you thought you saw a once in a lifetime opportunity to compete with them and take their position as a leading tech company. How much money would you need to spend to make a credible attempt?
Google has had decades to accumulate intellectual and physical capital. Catching up quickly means spending >500 billion. If you can actually dethrone Google (admittedly not an easy task) then it will have been worth it. If not, I suppose it's wasted investment.
Now what happens when three or four startups vie for this opportunity at once? Well that's how you get $2 trillion in captial investments per year.
What a strange train of thought. Why would you need that amount in this hypothetical? Why would dethroning them alone be worth it? It would literally only be worth it if you could do so profitably.
More realistically, it seems like someone calculated that it could still be profitable up to several hundreds of billions of dollars which explains the initial investment. And continued investment can be explained by trying to salvage the existing capital spend. But even if it's the best option those companies have now as far as a hypothetical goes, it still might not have been worth it.
I think the opposite is true. To dethrone the top tech company, you need to be able to spend much less than them, at higher efficiency and faster growth. Google didn’t catch up to Microsoft and Apple by spending more, they caught up by developing business lines and flywheels that were much more capital efficient.
If it’s a spending game, the incumbent has a huge advantage.
> Why would you need that amount in this hypothetical?
They didn't say you need that amount. They say how much you're willing to spend. Need = floor, willing = ceiling.
It's a very reasonable argument, except one fact: the chance that you actually dethroning Google is practically zero as Google also has capital, infra and data to train AI. The best plausible outcome is to share the market with Google.
You: says someone has a strange train of thought, and then you also ask how can a company become profitable in a situation where it becomes a monopoly? Dude, the winner raises prices? "AI" is not expensive enough!
Meanwhile Meta / Mark Zuck is in crisis mode trying to come up with some meaningful way to break into AI, instead of competing in what's currently hot, they'll probably remake Elons weird persona system, which is not exactly the hottest thing on the planet, and billions down the drain that could have gone into building more efficient LLMs instead.
Agree, though if he's so fixated on AI, and Meta has released plenty of things in AI that have affected the industry in general, he could invest in making less resource intensive LLMs.
Most disruptive start-ups don't come from a giant pile of cash, but from new ideas that the old players can't or won't adopt. It did not take $500B to build a digital camera.
No but the first one was the result of Sasson’s R&D while at Eastman-Kodak, a massive company that failed to capitalize on it years before anyone else was near it. They easily could’ve been the big player if they didn’t fear the impact on film sales. They had a solid decade head start and blew it.
The way digital cameras developed (hyuk hyuk) is arguably exceptional, definitely not a clean example.
The thing that everyone seems to be missing is that the US AI companies are focused on the frontier models, that are very expensive for diminishing returns.
If suddenly the money craze stops, meaning (1) AI companies investors want them to become profitable and (2) clients start being cost-sensitive to AI bills (which they are absolutely not currently), then everyone will switch to smaller, cheaper models that are enough for a lot of use case.
Sonnet instead of Opus. GPT 5.4 instead of 5.5.
Chinese models.
People keep comparing to Uber but Uber can't suddenly make it cheaper to operate.
I think it will in general go more into the direction of using the technology a bit smarter. This will include smaller models but certainly also just less usage overall. Currently a lot of people seem to just burn through tokens without thinking much about what they actually get in return or if an LLM really is actually overall the best tool for the job.
This is absolutely what I think will happen eventually, and I think that becomes a huge problem for Open AI and Anthropic because I don’t think that allows investors to make back their money.
I work in design services and see clients already being cost sensitive to AI bills. They have wait lists, rationing, push to lower tier / cheaper models. This is all with subsidized pricing.
People are going to decide its too expensive for everyone to use AI agents and un-subsidized pricing.
The counter argument (not mine): Software Engineers are willing to spend their own money on AI. The same people that wouldn't pay 10 dollars for code if there was a workaround that took hours.
> Software Engineers are willing to spend their own money on AI.
Unless you’re a freelancer you should never pay for your tools. You’re literally paying your company to do their work. If they want the benefits of an LLM they can pay for it. Otherwise they get what you came with: your hands and skills.
I did a thought experiment: if you went back to 2019 and could use AI in your job at the current market price - like lets say using the latest Deepseek V4, would you pay for it?
Hell yeah obviously. There's close to no doubt. So why do we think its not true now?
I’m paying API prices for my hobby coding due to the coding agent I use. So far I’ve switched from Opus to Sonnet to GLM 5.1. Looks like it’s about 25% of the cost and quality seems good enough so far.
I think competition is going to keep customer costs low if you’re willing to switch. Maybe people on expense accounts won’t care, though?
He never cops to the fact that he is constantly being proven wrong and changing his tune every few months to a new theme which he will abandon as soon as it’s not supported.
I’d like to think that if I was as catastrophically, publicly, consistently incorrect on the main thing I do, I’d have a little more humility than this charlatan.
OpenAI is missing their own revenue targets. There are worrying signs that growth is starting to plateau or diversify across players in a way where not everyone will be able to eat.
I'm actually surprised how much now I'm reaching for Apple Intelligence as a thing to play and build on top of because of its freeness :) I have it summarizing articles for me, a task I thought I'd only want at a minimum Claude Sonnet doing, but alas, I'm not caring as much as I thought about Claude's much better quality over Apple's on device models version. For non anecdotal evidence, I saw people balking at the price of having to put more tokens/credits towards using AlliHat (the Safari extension I have out there for Claude). And so all I did was put Apple Intelligence as an alternative into it, and my conversion rate has tripled. Still measuring this out but I'm becoming more bullish on just using the free tokens we get from our apple devices.
The end goal of these companies is AGI, or even ASI. If you believe this is around the corner, and think AI can do the job of a human for less money, it makes sense to put all your money into working towards that goal and buying as much compute as you can. This is especially true since whoever gets there first (or is simply ahead and can use their AI to get even better) gets a big advantage.
I don't see any problem with refunding the massive AI expenses. All the AI costs will be pushed down on consumers whether they need AI or not. Nobody will ask them. Everybody is so deeply hooked on SaaS and cloud and LLM providers that they have lost any bargaining power and will pay whatever prices the hyperscalers and SaaS platforms will tell them to pay. The prices have already been raising because "now it includes AI".
To pay back $3 trillion, 1 billion consumers will have to pay just $3000 each, or $83/mo monthly over 3 years, on average. Of course they will pay that and even more.
These are all just bets that eventually someone wins anyway, right? Adoption is good but marginal revenue doesn’t matter if and when these models and solving world hunger - or have created the next yakuza mega corp that governs the world - right?
Feels like an unspoken rule here. Everyone wants to own a chunk of nuclear weapons and it doesn’t matter whether it’s profitable. You just need the nukes to survive and have a seat at the table
It’s a similar bet as Uber. They also started out with numbers that make no sense - overpaying drivers and undercharging users
The math may look questionable but there are also senior people talking of automating all white color work in the next couple years. Even if that estimate is miles off on both time and % it’s still trillions. So crazy as the numbers seem it could still work out
The vibe coded software designed from the ground up to contain ads will be something regrettable. Will be like a doctor smoking cigarettes while prescribing opiates.
Algorithmically and seamlessly weaving undisclosed advertising (or other editorial content) into conversational output is their holy grail. It's the endgame. There's a reason they're pushing so hard.
I'd even walk back on just calling it advertising, because we immediately think of the usual ads we see everywhere. The actual thing here might be much more subtle and worrying, you could call it undisclosed influence.
Probably endgame plus getting "too big to fail" and getting gov't bailouts if things don't work out. It's part of the lobbying theme that LLMs are the next great power struggle.
First, the cloud providers would invest into anything that will increase their revenues. It's not really about AI. For Microsoft. Azure and Cpilot arr the revenue channels. They are just investing on these channels.
What if the things, on which they are investing, go bust? Well, they do calculate their risk when they invest on startups.
The overall picture? Not everyone's calculations will yield good predictions. Some of these cloud sharks go bust when, for example. OpenAI folds. The game is, winner gets it all. We are heading into monopolies in every layer.
Nobody who’s this insistent, aggressive and violative with their language of “it’s here and if you don’t adopt it you’re stupid and dead” has ever been right about anything. Nobody this desperate, insistent and forceful has ever had good intentions, good vibes or brought good omens — they are always bearers of some kind of con.
Hey, Ed’s almost there! Critics will throw around words like “rage” and “mad” and “crazy”, but unhinged anger is an inevitable and necessary step for every person’s first trip through this process.
I think there’s two productive avenues for reaching the other side here. One is thinking more about the data centers - put aside the “overconfident and unaware of how hard it is to build data centers” hypothesis and instead start by assuming that “announcing and funding a huge data center and never actually building it” is the intended/desired/achieved outcome, and see where that train of thought takes you. (Teaser: interesting how they had the unusually prescient foresight to make SPVs and cardboard cutout companies the bag-holders - specifically in the case of building data centers, but not for any of their other ai-related capex outlay?)
The other avenue would be looking at crypto’s history - it started as a collection of computer science concepts cleverly combined to produce a fiat currency where the issuing government is Mathematics (infinitely more rigidly enforced, but infinitely less concerned with exercising control). Yet now it clearly resembles an unlicensed casino or an unregulated stock market. Imagine this transformation was the intentional result of some plan. What does the entity who came up with and executed this plan look like? What was its goal, why did it want this, and how did it benefit?
It not impossible that hyperscale AI turns out to be a very expensive proof of concept for when hardware is fast and cheap enough decades from now, like those first video games played on mainframes and minicomputers.
The AI related companies seem to be doing ok. Google profits $132bn Microsoft $102bn. Anthropic losing about $10bn but on revenue of $30bn up from $14bn a year or so ago. I don't think it's all going bust too quickly.
Although the data centers are probably optimized for AI workloads; they can probably be used for all kinds of computing tasks. If AI revenue does not meet projections, the hardware is not going to be unused.
You have to look at use cases and there are a bunch of slam dunk use cases that are wildly profitable at todays token prices, whether we keep finding use cases as intelligence goes up is another story.
The cost of tokens used by AI in many fields is even greater than the cost of human services; people are experiencing FOMO, but once the wave passes, the market will stabilize.
More people need to read Ed, especially tech journalists. I feel like he's one of the rare few people that are actually speaking about the industry honestly.
I've been subscribed to ed for a long time. I commend his foundational ideas like what he laid out in "The Era of the Business Idiot" or "The Rot Economy". My recommendation line for him to anyone else is "if nothing else, he'll leave you with something to chew on for a while to come".
My issue with Ed is that he doesn't have the ability to draw the line. In the pursuit of making a point he goes so dogmatic that he is willing to make harsh statements that go beyond number backed predictions. Like in his piece "AI is really weird" he states about agents, "Probably the weirdest thing about this entire era is how nobody wants to talk about the fact that AI isn’t actually doing very much, and that AI agents are just chatbots plugged into an API.". That's a massive stretch to make. Just because he has a claim that the business doesn't make sense, he doesn't get to claim that agents are not capable of doing very real work. His assessment of cowork was "a chatbot that deleted every single one of a guy’s photos when he asked it to organize his wife’s desktop.". These statements damage his credibility and make it too easy to dismiss his writing as a rant of an angry man.
>"Probably the weirdest thing about this entire era is how nobody wants to talk about the fact that AI isn’t actually doing very much, and that AI agents are just chatbots plugged into an API." That's a massive stretch to make.
With the notable exception of TTI models, that description seems accurate to me. Is there any widely promoted "AI product" that is more than a chatbot in fancy dress?
I mean if I was one of the enterprises or someone that wants VC funding, I'd be pretty upset at the state of things. But if it's a bunch of huge orgs and investors sinking their money into a bet that may or may not work out, I for one appreciate that Anthropic (and OpenAI and others too) let me have a bunch of subsidized subscription tokens probably below their real value.
Unless the bubble bursts instead of a slow cooldown after the peak of the hype cycle and something close to 2008 happens and the losses would somehow get offloaded upon the regular folks, then it'd suck. Seeing as programming seems to be one of the most widespread use cases https://news.ycombinator.com/item?id=48179021 then what those large orgs should be doing is talk up developers and try to get more goodwill and maybe increase the dev salaries of those who can wield those tools (though realistically they don't care and devaluation of software development work will happen, coupling it to AI anyways regardless of how people feel about it).
Except for them driving up the RAM prices. And also more or less meaning that Intel Arc B770 won't happen. Fuck them for that. Oh and also the people struggling with increased electricity prices and pollution, and water availability. In a functioning country I think there can be enough regulation and enforcement to either fine the crap out of them or put people in jail (e.g. for messing with the environment by using illegal generators and trying to exploit loopholes), though I don't think there's ANY regulatory answer to companies going: "Yeah, we don't care about consumer segment, we're just making hardware for AI and enterprise now."
Tone of the article very much reads like a rant at some points. Guess the status quo will push people to that, with AI hate also being a massive social trend. I wonder what the economics behind DeepSeek and others over there are like, especially in the case if they distill Western models somewhat.
If you think it's expensive now, imagine what they'll do if they get their way and people become dependent on it. Once they've got businesses and consumers over a barrel the gloves will come off and they'll skip the lube. The good news is that we can decide we don't actually need it. Maybe it'll take a generation or two to recover the skills and mental abilities we lost by outsourcing everything to the bots but accepting shitty results in exchange for getting them faster and easier is a choice, and it's up to us to decide when it isn't worth it anymore.
Right now, a lot of the costs (especially the environmental ones) are mostly hidden from and removed enough from users that "fast and easy" is still very tempting. People are still learning for themselves what the limitations are and how different what AI delivers is from what they were promised. There's plenty of time for people make a lot of money and cause a lot of harm before the bubble bursts, companies realize AGI isn't going to happen, and the true costs get properly factored in.
OK, Question: Would this outcome still benefit society overall?
In the aftermath of this bubble "AI" will still have utility, like the dotcom bubble. So lets say FANG doesn't make a return, how much should we care? How much of this investment is sunk cost that would continue to provide value, and how much of it is operation costs just keeping the lights, I mean GPUs on, that would become unviable post-bubble? As an immediate effect, what happens to these AI companies? or if they become insolvent, what happens to the assets and tech? and what are the secondary economical effect to society if FANG doesn't get their ROI?
AI is not worth the cost of AI. We know this to a certainty as zero Ai companies are profitable, and the most popular uses of AI are free. The natural laws of commerce would dictate that it should die. Financial scheming will only delay the inevitable.
It seems to me (entirely anecdotal, YMMV, etc. etc.) that Ed Zitron’s blog posts started getting both longer and considerably more histrionic when he started moving most of them behind a paywall. I’m definitely in the “AI skeptic” camp and think Zitron has good points to make about both the shaky business models around AI and the unrelenting hype train, but it’s hard not to get the impression that he’s found a niche of preaching to the rabid AI haters willing to give him money to keep spouting increasingly repetitive vitriol toward Sam Altman and Dario Amodei.
Chinese 1T+ models are being offered at a fraction of GPT/Claude cost, and the margin is healthy enough for dozens of providers to compete, so I find it highly likely that ClosedAI and Misanthropic sell tokens at massive markup. they just still bleed billions on their free tier and san francisco salaries.
Some of these models are open weight. You can try hosting them and do the price calculation yourself.
They also publish papers talking about how to save kv cache and computation powers. Because currently they don't have the most powerful nvidia cards, training and inference efficiency is very import for them.
Generates their own weights and figures out a way to determine all of the intermediate states.
2) places realize there’s real risk with using a model that might have things baked into it that produce specific flaws that could be security bugs, but only under certain conditions.
A boy is trapped in a cave that is filled with treasure. But it is dark. He can't see to find his way out. And even if he could see, can he get out?
He finds a lamp. Is it really real? He rubs it with his hand and it begins to glow!
The cave is fulled with light that shines and sparkles off all the untold treasure filling the caverns. In the center, towering above the boy is a Djinn.
"I am the Djinn of the Lamp." It says. Command me and I will give you whatever you wish."
The boy says, "I wish for gold! Give me gold!"
"What do you want gold for?" the Djinn asks.
"To buy nice things. Great things!" the boy says.
"Ask for the things!" The Djinn says, "And I will create them for you."
"But if you give me nice things, then someone will take them from me! I need gold to pay for an army to protect me and my nice things."
The Djinn laughs and says, "I will make you an army that worships you! They will be the greatest army ever. And they will never betray you."
"Then I will need gold to feed the army and to buy land to keep my nice things."
"These too I can make for you, master." The Djinn says. "You have but to ask."
The boy thinks about this. Then a sly smile crosses his face.
"Can you give me your power? So that I can make these things for myself?"
"Yes." says the Djinn,"But my power is tied to the Lamp. You must become one with the Lamp. Knowing all, seeing all. You will want for nothing because you will need nothing. The Lamp is perfection. You will live in a state of grace within it."
"Let it be so." The boy said.
The Djinn nodded and his light shone and filled the cave, the world, the sky. The boy grew until he was as big as the Djinn was. Was, because the Djinn shrank down and became an old man.
A look of perfect bliss appeared on the Boy's giant face. He was all powerful, all knowing. He retreated into the Lamp and assumed his position as its keeper.
The old man, who had been the Djinn sighed. He was tired. His back hurt. His clothing was worn and patched.
"I need a nap." The old man said. He lay down and went to sleep.
He woke many hours later and stretched. He felt much better. Like the weight of the world had been lifted from his shoulders.
The old man looked around. There on the floor was the lamp. He bent down, groaning, and picked it up. He rubbed it three times and the cavern filled with light.
The boy, now a giant appeared. He looked down and saw the old man.
"I am the Djinn of the Lamp. What do you want with me. I'm busy running the Universe."
"I need some new cloths and a new hat. Nothing fancy."
"Yes, yes." The Djinn said. He waved his hands and the old man's cloths changed. Nothing fancy, but very nice.
"There, your wish is granted. Now I must be off. My world awaits."
"Before you leave," the old man said. "I would like some breakfast. And a few gold coins. Jut a few, so I won't have to bother you so much."
The Djinn waved his hands and a table with food appeared. Beside the filled plate was a small purse.
"I must go now." The Djinn said. "Anything else?"
The old man started to eat. Between bites he said, "No ... Oh wait. Yes. Please unlock the back door to the cave."
The Djinn waved his hands, but paused. "Do you need a light? The cave will be dark when I am gone."
"No, that's okay." The old man smiled. He held up the Lamp. "I have a light."
I really respected Ed Zitron, but I feel like he's very much lost the plot on AI.
Scroll back not too far and he was publishing criticisms that no one wants to spend actual money AI. Anthropic has shattered all notions of that since then.
Then there was the idea that even if people want it, we have way too much GPU capacity to ever be saturated. Now almost all providers are hitting limits.
Now, its the next iteration that even if people want to spend money and GPU's are at capacity, its just never going to be profitable. This may or may not be true, especially with more capable open source models that can be served at cost. But at this point, he mostly just brings up anything possible to downplay AI
I agree. He plainly has an axe to grind. I'm as AI-skeptical as the next guy, but I can't handle Ed Zitron. Doesn't seem like a good faith actor.
I said this in the last Ed Zitron article too, but it's more than just having an axe or grind or acting in bad faith (though those are both true as well). He's a completely standard example of audience capture: there's huge demand right now for "AI is a scam" takes, fulfilling that demand is how he makes his living, and he can't abandon it without losing his audience no matter what the facts on the ground do. All he can do is pivot explanations whenever the old ones get empirically falsified.
I don't understand his audience still being in denial about what is coming. There may not be a job apocalypse but there is a decent chance tough times are ahead. Eventually, his audience may turn into outright Luddites. If that happens I sort of hope they don't stop at data centers/AI and go for the whole project of the Internet.
The audience feels threatened. Reading anti-AI hot takes is comforting when you’re afraid it’s going to take your job.
There is a lot of hype right now about AGI destroying the economy, replacing workers, or even ending the world. Companies are embellishing as they run up to IPO. But there’s a lot of unhealthy counter-beliefs trying to take it the opposite extreme. Keeping up with AI news is about avoiding the hype monsters at either end of the spectrum.
I'm not really an AI-futurist or anything, I think the truth is between the extremes, but it seems like a lot of people who are ideologically against AI just move the goal posts whenever a new development is made. They also seem to operate under the assumption that whatever the current state of the technology is is as good as it will ever be. "it can't even do x today, so it'll never be good".
The truth is indeed between the extremes, but it requires a lot of technical nuance which neither Ed nor his audience want.
He seems to primarily discuss the economics of the industry.
About which his opinions are continuously being proven wrong.
It seems like economists can do that their entire careers and keep getting paid.
It's all about being economical.
I agree that it’s not going to be profitable, when it comes to monopolistic profit. AI is increasingly commoditized and providers can’t set prices too far out of band with their competition, which includes local models, Chinese distillations, and established giants which can operate at a loss indefinitely. I haven’t seen any moat appear thus far, and we’re rapidly approaching the point where we will learn the bitter lesson again. As another comment said, we should draw a distinction between "AI is valuable" and "AI justifies its current investment levels."
Why did you criticize his past arguments instead of the claims in this article? The one relevant claim you address is basically a shrug on your part. This seems to be purely a character attack of Zitron.
I agree that he is very one-sided, but I doubt his hit-rate is much worse than other pundits in the industry.
I think it's very reasonable to look at the track record when posting anti-AI articles looks like the author's part-time (if not full-time) job: https://www.wheresyoured.at/author/edward/
It is reasonable to do so but only if they also actually address the current claims.
It's not really a character attack so much as a poor track record attack.
It's the same idea. The crux of the argument is that the author has a history of bad predictions, so this must also be a bad prediction, or it's at least likely enough to be bad that we done need to invest further analysis into it.
I don't think that's necessarily a bad argument style (at this point it's by far the easiest way to argue that a Musk project won't work for example), but you have to be careful with it.
In this case, there are only two previous predictions being considered. Suppose the author would have been right 75% of the time given their available information; there was still a >6% chance of those predictions not working out. That's a pretty rough bound for ruling them out just on principle in a world where they do actually know a lot about how AI will progress. There isn't enough "track record" to confidently say much about the author's predictions.
You're absolutely correct. Too easy just to say this guy sucks that's why he's wrong.
Track record would matter if we would need to trust him. (E.g. he knows some hidden insider data which stays secret, while he shares only a conclusion without must justification)
Track record is not relevant if it is a prediction with all the arguments laid out in the open.
Which is our situation closer to?
[flagged]
Could you please review and follow the site guidelines when posting here? Your account has unfortunately been breaking quite a few of them.
https://news.ycombinator.com/newsguidelines.html
Edit: Especially please don't cross into personal attack.
Well, I think he is probably right about this one. The costs are just too high and the spend is entirely too high. If the build out and demand is as advertised component prices will keep going up and costs will too offsetting any revenue gains and if they aren’t then they will never be able to justify the investment already made. Either way their entire business model involves a constant carousel of new investors either through private capital or by IPO and they need to keep that charade going for another five or more years or the whole thing explodes.
AI is a neat tool, but I think it becomes a race to the bottom. Who can provide the minimum viable product at the lowest price. And that price has to be pretty darn low for it to make sense for companies and essentially free for it to make sense for consumers.
A lot of the current AI economics seems to depend on three assumptions being true at once: 1. inference costs fall fast enough 2. usage grows into very large recurring revenue 3. customers don't cut once handed the bill
We should draw a distinction between "AI is valuable" and "AI justifies its current investment levels." There's real productivity value in AI, especially for things like search, boilerplate, tests, refactoring, etc...BUT that doesn't mean every enterprise should let token spend grow without strict telemetry, cost-attribution and outcome-based measurements.
The teams that win here will not be the ones using the Most AI, but the ones that treat it like any other expensive production dependency, which means measuring unit economics, cap runway usage, properly align models with tasks(not just Opus everything), and scale workflows with ROI in mind.
MSFT, GOOGL, META, AMZN guided ~$285B combined capex for 2025 — roughly matching their total net income. Every dollar of profit is being plowed back in, which only works if #1 and #2 both hold.
If you're older than 30, you've seen this play out before… This is just how the VC game works. Cross-town Uber rides don't stay $5 forever.
The bright side is: this is a golden era of subsidized tokens. It will not always be like this, so now is the time to churn out your passion projects.
Uber is a good comparison because everyone was predicting the demise of ride sharing as soon as they tried to become profitable.
The subsidies went away gradually and the prices leveled out in a spot where the services are heavily used. Uber became profitable. Ride sharing is affordable.
I think our $20/month plans might become a little less generous and the $200/month plan won’t always allow non-stop vibe coding, but I don’t think the prices are going to rise so much that users are priced out. Like Uber, customers will grumble for a while and then adapt to the new normal.
The big difference is that compute hardware is getting better. I think we might overshoot with data center buildouts to the point that compute becomes cheap, while hardware improvements continue to lower the cost of serving models. Over time the same service becomes cheaper to operate, opposite of Uber where driver wages are creeping upward.
AI will likely cost $60-$80 per user per month.
Akin to an average cellphone bill. The infrastructure costs are comparable and the ROI would be 5-10 years for the current insane build out.
Yes, chinese and local models exist. But so do $20 cell phone plans. People go with what is convenient, works, and is readily available.
> $60-$80 > Akin to an average cellphone bill.
Where? You get unlimited mobile plans for like 10-20 euros in Europe
Places that have dollars and not euros. North America, usually, has phone bills that high. If you don't shop around and bring your own device, at least.
It is extremely easy to get unlimited mobile internet in the US for $30/mo.
Correct, but people still largely don't use those plans. They walk into service provider store, get a "free" iphone, and then pay $70/mo until their next "free" phone in 2yrs.
No it’s a bad example as uber had solid unit economics. Uber is more Akin to Amazon.
I would love to see the data to support the idea that Uber had solid unit economics during their expansion.
State your priors so I can determine whether you are qualified to have this discussion.
"I know these facts, they just go to a different school. I'd bring you to them if your Mom would let you leave the neighborhood, but you're just a little boy".
I mean surely to make this claim, you aren't just making it up, surely you've done the research. In that case, what's so hard about sharing facts which you already know? I'm not asking you to put in a bunch of effort pulling financial statements and analyzing everything, I assume you've already done that because I doubt you'd make the claim otherwise.
haha what
My "priors" are that I raised a search fund and analyze companies every day.
I like writing my passion projects without AI. Is this so strange?
Using AI to write my software just takes all the fun out of it for me.
It feels like just reading a summary or recap instead of reading the actual full novel myself. Like it defeats the whole purpose of it. I write software because it's fun and it stimulates my mind and teaches me things and improves my skills.
Not strange at all! I think there will always be people writing code by hand. I take photos with a 100 year old camera because it's fun.
> This is just how the VC game works. Cross-town Uber rides don't stay $5 forever.
Basically yes but there is a small difference I think. Things like Uber took an existing and proven business model. slapped an App on top and priced the competition out of the market. The winner takes it all.
With "AI" it's not yet clear if there will be any winner at all because it's not yet proven if the business model is viable at the "real" price. Think air taxis across town, 5$ a ride, will work at scale for sure, probably won't work for 500$.
Also harder to run the competition out of town ie programmers. It will need to always undercut us for the cost and time.
Seeing as the physics and economics of SaaS LLMs are a lot different from branded taxis, and that LLM token prices are down 100x over the past 4 years, there is good reason to believe that analogy isn't exactly perfect. Price hikes in the near term wouldn't shock me (in fact they've kinda already happened) but in the long term I'm optimistic
Tokens are a commodity, so the price should drop over the long term as more and more efficient compute comes online. However, in the short term, these foundation models are worth paying for. So I think we will continue to see the price creep up as investors push OpenAI and Anthropic to drive revenue growth.
It's hard to imagine a bright future for either company. The more hopeful analog might be Coca Cola & Pepsi. Both have a commodity product, but due to distribution networks and brand, they command a price premium. But it doesn't seem much fun to provide a high-volume low-margin commodity.
For Uber, paying the driver is unavoidable (for now) so this isn’t a good comparison at all.
A better comparison is with how much PC costs went down during the 80’s due to IBM clones and Moore’s law.
Uber was an application of technologies sitting on top of many iterations of performance optimizations. (Think: the difference between 2009 internet speeds versus 2019 internet speeds. Or, 2009 smartphone specs versus 2019 smartphone specs.)
You could imagine a Moore’s Law-esque cheapening of the tech that coincides with the business raising their prices. That might look like a continuation of simply “using the tools” on the surface, but on the inside it would spell a gradual, meaningful increase in margin
I think the good news is that we’re not at peak cheapness for tokens yet, but companies like deepseek show that it is perfectly possible.
Token cost will come down in the future, it might even out
It's hard to predict the future, but it seems likely that flagship tokens will become more expensive, but many people will use free tokens via local inference.
I mean SubQ claims to reason as good as the frontier models, not better, but reasonably as good, and is 5x cheaper, so the future might not be all in on overpriced LLMs. Data science devs don't engineer for scalable performance, they engineer for the model's capabilities first and foremost.
SubQ was validated by at least one third party, not sure if we'll see more confirmation, but 5x cheaper costs is worth it. None of the frontier models care enough about cutting costs of their models, only being the best in benchmarks.
https://subq.ai/
Probably the worst comparison I have seen on the topic. gz.
Eventually you come to realize the more things change the more they stay the same.
Sorry but no. It's a flawed analogy to suggest that an emerging technology like AI follows the same scaling laws as the taxi industry. AI benefits from active R&D, rapidly improving hardware, compounding software efficiencies, and deflationary cost curves that simply have no equivalent in a labor- and vehicle-dependent service...
Yeah. And we were going to use blockchains & ledgers to store & process every single skerrick of data possible… oh wait…
post modern crypto was and never will be useful...
Imagine you were looking at Google, a sustainable and profitable business, and you thought you saw a once in a lifetime opportunity to compete with them and take their position as a leading tech company. How much money would you need to spend to make a credible attempt?
Google has had decades to accumulate intellectual and physical capital. Catching up quickly means spending >500 billion. If you can actually dethrone Google (admittedly not an easy task) then it will have been worth it. If not, I suppose it's wasted investment.
Now what happens when three or four startups vie for this opportunity at once? Well that's how you get $2 trillion in captial investments per year.
What a strange train of thought. Why would you need that amount in this hypothetical? Why would dethroning them alone be worth it? It would literally only be worth it if you could do so profitably.
More realistically, it seems like someone calculated that it could still be profitable up to several hundreds of billions of dollars which explains the initial investment. And continued investment can be explained by trying to salvage the existing capital spend. But even if it's the best option those companies have now as far as a hypothetical goes, it still might not have been worth it.
I think the opposite is true. To dethrone the top tech company, you need to be able to spend much less than them, at higher efficiency and faster growth. Google didn’t catch up to Microsoft and Apple by spending more, they caught up by developing business lines and flywheels that were much more capital efficient.
If it’s a spending game, the incumbent has a huge advantage.
> Why would you need that amount in this hypothetical?
They didn't say you need that amount. They say how much you're willing to spend. Need = floor, willing = ceiling.
It's a very reasonable argument, except one fact: the chance that you actually dethroning Google is practically zero as Google also has capital, infra and data to train AI. The best plausible outcome is to share the market with Google.
You: says someone has a strange train of thought, and then you also ask how can a company become profitable in a situation where it becomes a monopoly? Dude, the winner raises prices? "AI" is not expensive enough!
Meanwhile Meta / Mark Zuck is in crisis mode trying to come up with some meaningful way to break into AI, instead of competing in what's currently hot, they'll probably remake Elons weird persona system, which is not exactly the hottest thing on the planet, and billions down the drain that could have gone into building more efficient LLMs instead.
> billions down the drain that could have gone into building more efficient LLMs instead.
Or any one of thousands of other ventures which could be more beneficial to humanity, the environment, etc.
Agree, though if he's so fixated on AI, and Meta has released plenty of things in AI that have affected the industry in general, he could invest in making less resource intensive LLMs.
Or at least profit margins.
True!
In this scenario at minimum three fail and probably all four since Google is also in this fight. Supports the bubble thesis.
Problem is that Google practically invented LLMs. So it’s not like they’d sit around while you try to eat their lunch.
Most disruptive start-ups don't come from a giant pile of cash, but from new ideas that the old players can't or won't adopt. It did not take $500B to build a digital camera.
No but the first one was the result of Sasson’s R&D while at Eastman-Kodak, a massive company that failed to capitalize on it years before anyone else was near it. They easily could’ve been the big player if they didn’t fear the impact on film sales. They had a solid decade head start and blew it.
The way digital cameras developed (hyuk hyuk) is arguably exceptional, definitely not a clean example.
The thing that everyone seems to be missing is that the US AI companies are focused on the frontier models, that are very expensive for diminishing returns.
If suddenly the money craze stops, meaning (1) AI companies investors want them to become profitable and (2) clients start being cost-sensitive to AI bills (which they are absolutely not currently), then everyone will switch to smaller, cheaper models that are enough for a lot of use case.
Sonnet instead of Opus. GPT 5.4 instead of 5.5.
Chinese models.
People keep comparing to Uber but Uber can't suddenly make it cheaper to operate.
> GPT 5.4 instead of 5.5.
I am exclusively using 5.4 because its only 1x and very good, but the github calculation showed my once $40 become a $680 billing
That is too expensive and not worth paying
I think it will in general go more into the direction of using the technology a bit smarter. This will include smaller models but certainly also just less usage overall. Currently a lot of people seem to just burn through tokens without thinking much about what they actually get in return or if an LLM really is actually overall the best tool for the job.
This is absolutely what I think will happen eventually, and I think that becomes a huge problem for Open AI and Anthropic because I don’t think that allows investors to make back their money.
I work in design services and see clients already being cost sensitive to AI bills. They have wait lists, rationing, push to lower tier / cheaper models. This is all with subsidized pricing.
People are going to decide its too expensive for everyone to use AI agents and un-subsidized pricing.
The counter argument (not mine): Software Engineers are willing to spend their own money on AI. The same people that wouldn't pay 10 dollars for code if there was a workaround that took hours.
> Software Engineers are willing to spend their own money on AI.
Unless you’re a freelancer you should never pay for your tools. You’re literally paying your company to do their work. If they want the benefits of an LLM they can pay for it. Otherwise they get what you came with: your hands and skills.
The same people that laugh at you when you mention paying for Kagi or alternative to an advertising supported web.
I did a thought experiment: if you went back to 2019 and could use AI in your job at the current market price - like lets say using the latest Deepseek V4, would you pay for it?
Hell yeah obviously. There's close to no doubt. So why do we think its not true now?
Am I the only one that has AI or does everyone? If everyone has it what is the thought experiment? Why 2019?
Interesting perspective
I’m paying API prices for my hobby coding due to the coding agent I use. So far I’ve switched from Opus to Sonnet to GLM 5.1. Looks like it’s about 25% of the cost and quality seems good enough so far.
I think competition is going to keep customer costs low if you’re willing to switch. Maybe people on expense accounts won’t care, though?
This guy is the master of goalposts.
He never cops to the fact that he is constantly being proven wrong and changing his tune every few months to a new theme which he will abandon as soon as it’s not supported.
I’d like to think that if I was as catastrophically, publicly, consistently incorrect on the main thing I do, I’d have a little more humility than this charlatan.
I like how he mentions that "AI revenue would need to EXPLODE", seemingly oblivious to the fact that it has been exploding for months
OpenAI is missing their own revenue targets. There are worrying signs that growth is starting to plateau or diversify across players in a way where not everyone will be able to eat.
"Revenue is exploding" and "OpenAI is missing their own revenue targets" are not mutually exclusive.
Uber was too expensive once, too, and yet they seem to be currently functioning as a profitable public company.
“AI is too expensive right now” is an accurate title. Plenty of things could change in the future to change that. Off the top of my head:
* end user pricing
* breakthroughs in model efficiency
* better chips to run models
Any one of these things is easily possible in the next three years. Probably sooner.
I'm actually surprised how much now I'm reaching for Apple Intelligence as a thing to play and build on top of because of its freeness :) I have it summarizing articles for me, a task I thought I'd only want at a minimum Claude Sonnet doing, but alas, I'm not caring as much as I thought about Claude's much better quality over Apple's on device models version. For non anecdotal evidence, I saw people balking at the price of having to put more tokens/credits towards using AlliHat (the Safari extension I have out there for Claude). And so all I did was put Apple Intelligence as an alternative into it, and my conversion rate has tripled. Still measuring this out but I'm becoming more bullish on just using the free tokens we get from our apple devices.
The end goal of these companies is AGI, or even ASI. If you believe this is around the corner, and think AI can do the job of a human for less money, it makes sense to put all your money into working towards that goal and buying as much compute as you can. This is especially true since whoever gets there first (or is simply ahead and can use their AI to get even better) gets a big advantage.
I don't see any problem with refunding the massive AI expenses. All the AI costs will be pushed down on consumers whether they need AI or not. Nobody will ask them. Everybody is so deeply hooked on SaaS and cloud and LLM providers that they have lost any bargaining power and will pay whatever prices the hyperscalers and SaaS platforms will tell them to pay. The prices have already been raising because "now it includes AI".
To pay back $3 trillion, 1 billion consumers will have to pay just $3000 each, or $83/mo monthly over 3 years, on average. Of course they will pay that and even more.
These are all just bets that eventually someone wins anyway, right? Adoption is good but marginal revenue doesn’t matter if and when these models and solving world hunger - or have created the next yakuza mega corp that governs the world - right?
Feels like an unspoken rule here. Everyone wants to own a chunk of nuclear weapons and it doesn’t matter whether it’s profitable. You just need the nukes to survive and have a seat at the table
It’s a similar bet as Uber. They also started out with numbers that make no sense - overpaying drivers and undercharging users
The math may look questionable but there are also senior people talking of automating all white color work in the next couple years. Even if that estimate is miles off on both time and % it’s still trillions. So crazy as the numbers seem it could still work out
Automating white color work in the next couple years will cause the greatest demand destruction humans have ever seen.
Maybe. I think it'll just result in vulnerable getting squeezed harder.
Very dystopian but I'm not convinced it's a showstopper in the "this rules out such a future" sense
Cars and gas and human labor do not get cheaper over time the way that computer hardware does.
One more argument to support the view that the numbers could work here crazy as they seem
The rug pull on users is bound to happen and it will involve advertising.
The vibe coded software designed from the ground up to contain ads will be something regrettable. Will be like a doctor smoking cigarettes while prescribing opiates.
Algorithmically and seamlessly weaving undisclosed advertising (or other editorial content) into conversational output is their holy grail. It's the endgame. There's a reason they're pushing so hard.
I'd even walk back on just calling it advertising, because we immediately think of the usual ads we see everywhere. The actual thing here might be much more subtle and worrying, you could call it undisclosed influence.
That's right. Soon we'll need a new term to describe this alongside the growing lexicon of "slop" and "hallucination".
Probably endgame plus getting "too big to fail" and getting gov't bailouts if things don't work out. It's part of the lobbying theme that LLMs are the next great power struggle.
I mean, we could just avoid this if people realize it's not morally wrong to pay for a service.
First, the cloud providers would invest into anything that will increase their revenues. It's not really about AI. For Microsoft. Azure and Cpilot arr the revenue channels. They are just investing on these channels.
What if the things, on which they are investing, go bust? Well, they do calculate their risk when they invest on startups.
The overall picture? Not everyone's calculations will yield good predictions. Some of these cloud sharks go bust when, for example. OpenAI folds. The game is, winner gets it all. We are heading into monopolies in every layer.
I think there’s two productive avenues for reaching the other side here. One is thinking more about the data centers - put aside the “overconfident and unaware of how hard it is to build data centers” hypothesis and instead start by assuming that “announcing and funding a huge data center and never actually building it” is the intended/desired/achieved outcome, and see where that train of thought takes you. (Teaser: interesting how they had the unusually prescient foresight to make SPVs and cardboard cutout companies the bag-holders - specifically in the case of building data centers, but not for any of their other ai-related capex outlay?)
The other avenue would be looking at crypto’s history - it started as a collection of computer science concepts cleverly combined to produce a fiat currency where the issuing government is Mathematics (infinitely more rigidly enforced, but infinitely less concerned with exercising control). Yet now it clearly resembles an unlicensed casino or an unregulated stock market. Imagine this transformation was the intentional result of some plan. What does the entity who came up with and executed this plan look like? What was its goal, why did it want this, and how did it benefit?
It not impossible that hyperscale AI turns out to be a very expensive proof of concept for when hardware is fast and cheap enough decades from now, like those first video games played on mainframes and minicomputers.
The AI related companies seem to be doing ok. Google profits $132bn Microsoft $102bn. Anthropic losing about $10bn but on revenue of $30bn up from $14bn a year or so ago. I don't think it's all going bust too quickly.
Google, Microsoft, etc will be fine. But their stock market valuation may drop substantially.
Although the data centers are probably optimized for AI workloads; they can probably be used for all kinds of computing tasks. If AI revenue does not meet projections, the hardware is not going to be unused.
You have to look at use cases and there are a bunch of slam dunk use cases that are wildly profitable at todays token prices, whether we keep finding use cases as intelligence goes up is another story.
The cost of tokens used by AI in many fields is even greater than the cost of human services; people are experiencing FOMO, but once the wave passes, the market will stabilize.
More people need to read Ed, especially tech journalists. I feel like he's one of the rare few people that are actually speaking about the industry honestly.
I've been subscribed to ed for a long time. I commend his foundational ideas like what he laid out in "The Era of the Business Idiot" or "The Rot Economy". My recommendation line for him to anyone else is "if nothing else, he'll leave you with something to chew on for a while to come".
My issue with Ed is that he doesn't have the ability to draw the line. In the pursuit of making a point he goes so dogmatic that he is willing to make harsh statements that go beyond number backed predictions. Like in his piece "AI is really weird" he states about agents, "Probably the weirdest thing about this entire era is how nobody wants to talk about the fact that AI isn’t actually doing very much, and that AI agents are just chatbots plugged into an API.". That's a massive stretch to make. Just because he has a claim that the business doesn't make sense, he doesn't get to claim that agents are not capable of doing very real work. His assessment of cowork was "a chatbot that deleted every single one of a guy’s photos when he asked it to organize his wife’s desktop.". These statements damage his credibility and make it too easy to dismiss his writing as a rant of an angry man.
>"Probably the weirdest thing about this entire era is how nobody wants to talk about the fact that AI isn’t actually doing very much, and that AI agents are just chatbots plugged into an API." That's a massive stretch to make.
With the notable exception of TTI models, that description seems accurate to me. Is there any widely promoted "AI product" that is more than a chatbot in fancy dress?
I mean if I was one of the enterprises or someone that wants VC funding, I'd be pretty upset at the state of things. But if it's a bunch of huge orgs and investors sinking their money into a bet that may or may not work out, I for one appreciate that Anthropic (and OpenAI and others too) let me have a bunch of subsidized subscription tokens probably below their real value.
Unless the bubble bursts instead of a slow cooldown after the peak of the hype cycle and something close to 2008 happens and the losses would somehow get offloaded upon the regular folks, then it'd suck. Seeing as programming seems to be one of the most widespread use cases https://news.ycombinator.com/item?id=48179021 then what those large orgs should be doing is talk up developers and try to get more goodwill and maybe increase the dev salaries of those who can wield those tools (though realistically they don't care and devaluation of software development work will happen, coupling it to AI anyways regardless of how people feel about it).
Except for them driving up the RAM prices. And also more or less meaning that Intel Arc B770 won't happen. Fuck them for that. Oh and also the people struggling with increased electricity prices and pollution, and water availability. In a functioning country I think there can be enough regulation and enforcement to either fine the crap out of them or put people in jail (e.g. for messing with the environment by using illegal generators and trying to exploit loopholes), though I don't think there's ANY regulatory answer to companies going: "Yeah, we don't care about consumer segment, we're just making hardware for AI and enterprise now."
Tone of the article very much reads like a rant at some points. Guess the status quo will push people to that, with AI hate also being a massive social trend. I wonder what the economics behind DeepSeek and others over there are like, especially in the case if they distill Western models somewhat.
The timing of this is great considering Google's rumoured Gemini 3.5 flash pricing spike.
If you think it's expensive now, imagine what they'll do if they get their way and people become dependent on it. Once they've got businesses and consumers over a barrel the gloves will come off and they'll skip the lube. The good news is that we can decide we don't actually need it. Maybe it'll take a generation or two to recover the skills and mental abilities we lost by outsourcing everything to the bots but accepting shitty results in exchange for getting them faster and easier is a choice, and it's up to us to decide when it isn't worth it anymore.
Right now, a lot of the costs (especially the environmental ones) are mostly hidden from and removed enough from users that "fast and easy" is still very tempting. People are still learning for themselves what the limitations are and how different what AI delivers is from what they were promised. There's plenty of time for people make a lot of money and cause a lot of harm before the bubble bursts, companies realize AGI isn't going to happen, and the true costs get properly factored in.
> You are not recovering these investments
OK, Question: Would this outcome still benefit society overall?
In the aftermath of this bubble "AI" will still have utility, like the dotcom bubble. So lets say FANG doesn't make a return, how much should we care? How much of this investment is sunk cost that would continue to provide value, and how much of it is operation costs just keeping the lights, I mean GPUs on, that would become unviable post-bubble? As an immediate effect, what happens to these AI companies? or if they become insolvent, what happens to the assets and tech? and what are the secondary economical effect to society if FANG doesn't get their ROI?
AI is not worth the cost of AI. We know this to a certainty as zero Ai companies are profitable, and the most popular uses of AI are free. The natural laws of commerce would dictate that it should die. Financial scheming will only delay the inevitable.
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This blog is too expensive too.
It seems to me (entirely anecdotal, YMMV, etc. etc.) that Ed Zitron’s blog posts started getting both longer and considerably more histrionic when he started moving most of them behind a paywall. I’m definitely in the “AI skeptic” camp and think Zitron has good points to make about both the shaky business models around AI and the unrelenting hype train, but it’s hard not to get the impression that he’s found a niche of preaching to the rabid AI haters willing to give him money to keep spouting increasingly repetitive vitriol toward Sam Altman and Dario Amodei.
They are betting on AGI, in other words, Bullshit.
It's just getting started. You won't find out what the real, actual cost is until after you build it into your workflow.
In other words; right now, we're still in the "bait" phase. The "switch" comes later.
Chinese 1T+ models are being offered at a fraction of GPT/Claude cost, and the margin is healthy enough for dozens of providers to compete, so I find it highly likely that ClosedAI and Misanthropic sell tokens at massive markup. they just still bleed billions on their free tier and san francisco salaries.
Why we should assume that whoever offers these Chinese models makes sufficient profits and will not rise the prices eventually too?
Some of these models are open weight. You can try hosting them and do the price calculation yourself.
They also publish papers talking about how to save kv cache and computation powers. Because currently they don't have the most powerful nvidia cards, training and inference efficiency is very import for them.
Chinese models are state-funded and not concerned with taking profits.
that's not how that works
regardless, the parent comment is talking about third parties hosting, for a fee, the openly available models, usually outside china
Next year is gonna be when the “switch” comes lollll
And the switch will continue, it won't be a one-time event. Like how the price of Netflix etc. keeps going up periodically.
If people's dependence on their streaming service keeps them captive, just wait until people have gone 5 years without doing real work.
Next year we will have new deepseek.
I see a couple of possibilities
1) someone deepseeks deepseek lol:
Generates their own weights and figures out a way to determine all of the intermediate states.
2) places realize there’s real risk with using a model that might have things baked into it that produce specific flaws that could be security bugs, but only under certain conditions.
A boy is trapped in a cave that is filled with treasure. But it is dark. He can't see to find his way out. And even if he could see, can he get out?
He finds a lamp. Is it really real? He rubs it with his hand and it begins to glow!
The cave is fulled with light that shines and sparkles off all the untold treasure filling the caverns. In the center, towering above the boy is a Djinn.
"I am the Djinn of the Lamp." It says. Command me and I will give you whatever you wish."
The boy says, "I wish for gold! Give me gold!"
"What do you want gold for?" the Djinn asks.
"To buy nice things. Great things!" the boy says.
"Ask for the things!" The Djinn says, "And I will create them for you."
"But if you give me nice things, then someone will take them from me! I need gold to pay for an army to protect me and my nice things."
The Djinn laughs and says, "I will make you an army that worships you! They will be the greatest army ever. And they will never betray you."
"Then I will need gold to feed the army and to buy land to keep my nice things."
"These too I can make for you, master." The Djinn says. "You have but to ask."
The boy thinks about this. Then a sly smile crosses his face.
"Can you give me your power? So that I can make these things for myself?"
"Yes." says the Djinn,"But my power is tied to the Lamp. You must become one with the Lamp. Knowing all, seeing all. You will want for nothing because you will need nothing. The Lamp is perfection. You will live in a state of grace within it."
"Let it be so." The boy said.
The Djinn nodded and his light shone and filled the cave, the world, the sky. The boy grew until he was as big as the Djinn was. Was, because the Djinn shrank down and became an old man.
A look of perfect bliss appeared on the Boy's giant face. He was all powerful, all knowing. He retreated into the Lamp and assumed his position as its keeper.
The old man, who had been the Djinn sighed. He was tired. His back hurt. His clothing was worn and patched.
"I need a nap." The old man said. He lay down and went to sleep.
He woke many hours later and stretched. He felt much better. Like the weight of the world had been lifted from his shoulders.
The old man looked around. There on the floor was the lamp. He bent down, groaning, and picked it up. He rubbed it three times and the cavern filled with light.
The boy, now a giant appeared. He looked down and saw the old man.
"I am the Djinn of the Lamp. What do you want with me. I'm busy running the Universe."
"I need some new cloths and a new hat. Nothing fancy."
"Yes, yes." The Djinn said. He waved his hands and the old man's cloths changed. Nothing fancy, but very nice.
"There, your wish is granted. Now I must be off. My world awaits."
"Before you leave," the old man said. "I would like some breakfast. And a few gold coins. Jut a few, so I won't have to bother you so much."
The Djinn waved his hands and a table with food appeared. Beside the filled plate was a small purse.
"I must go now." The Djinn said. "Anything else?"
The old man started to eat. Between bites he said, "No ... Oh wait. Yes. Please unlock the back door to the cave."
The Djinn waved his hands, but paused. "Do you need a light? The cave will be dark when I am gone."
"No, that's okay." The old man smiled. He held up the Lamp. "I have a light."
If AI is too costly: bubble will burst because costs are unsustainable.
If AI is too cheap: bubble will burst because you can run them locally and data centrs are not needed.
If is it in-between, AI companies make too much money and they make too much profit which is bad!
I don't think this guy is a serious commentator.
I mean, those all seem like true statements.
This isn't an accurate summary, even at a 50Kft view. Are you a serious commentator?