AI is slowing down

https://www.wheresyoured.at/subprimeai/

He is extremely vague in his predictions and timelines, and yet still manages to miss.

His predictions timing sucks but he’s right in pointing out the insane numbers involved.

I think AI is a wonderful tool but I also think that there are many wonderful tools that if we bet our entire economy on would result in a catastrophe.

Personally, I see both parties making predictions.

Meanwhile, I still must labour. How many more yachts are needed before the earth becomes the utopia they keep selling everyone on? How many more communities must have their rights trampled against their expressed will?

Or do I need to scan my retinas and provide Alt-man a DNA sample for a handful of empty crypto currency first?

Either that he's HN mods's favorites or we're experiencing a special case of xkcd 1053[0]: there are always ten thousand people haven't realized how wrong Ed Zitron is.

At this point I don't think even Ed himself believes what he writes. It's just fan service for subscribers. And that is totally reasonable if we view blogging as a business.

[0]: https://xkcd.com/1053/

If this current building spree ends in massive solar and other power generation being overbuilt and cutting energy costs, we've had a really good outcome.

If you look at SpaceX plans and ambitions, they hope to deploy massive compute to orbit (multiple Terrawatts, hundreds of thousands of sats). If their ambitions even slightly materialise it would make ground based compute pale in comparison.

Whether or not they succeed in their plans is beside the point - the point is they know that terrestrial electric infra can't sustain the growth they need

The reset is prone to happen by other means.

Quoting Modi is a joke which one cannot even remotely relate w.r.t to AI and don't even feel sorry for saying that since that man blabbers on every stage about non-sensical / non-existent stuff! Watching his videos is the best timepass one can have!

Having said that, the infra and mindset is definitely not there in India to even remotely to innovate or compete in AI race!

Academia is a huge BS where every other person is a backstabber!

A lot of talent is there for sure, but all wants to work for some company or another since there is absolutely zero support for entrepreneurs . No real innovation.

All copy cats as they have proven with mobile and robotics. Just copying or masking Chinese products with the local brand names and reselling. That's all they are good at and that's the irony.

So far, nothing has come from that country which is a real innovation or ground breaking. The day it happens probably one can consider that they are good.

But otherwise, they are good at selling / reselling and scamming the world and nothing else! They cannot produce anything or whatever they produce is taken control by a handful of big corporates from the western region. That's a narcistic corporate monopoly!

Extremely bad tax structure, endless corruption and useless and unqualified ministers occupying worst portfolios, people are really struggling to survive!

Where will they innovate or compete in the global AI race?

Everyone at every level just want to scam and make money to surive that's all!

Period.

everyone is still fighting for market share so they are giving stuff away, but that doesnt mean people wouldnt be willing to pay for it if it wasnt free.

This is the big one. It's clear that AI can generate huge volumes of code by KLOC. It is not clear that spending a lot of money tokenmaxxing will eventually result in increased real revenue for software businesses, and eventually even an MBA has to look at a "money in vs money out" chart.

The fact that he isn't a deeply involved technical developer who knows the ins and outs and nuances of using LLM tools is the point, because the stated capabilities of LLMs are that they are trivial to use, extremely powerful, and getting so much better every month that you personally can replace developers without even trying as a completely non-technical person with basic writing skills.

Given the hype and extreme claims being made, the fact that he remains ignorant and gets practically no use out of LLMs immediately disproves those statements. The counterargument boiling down to "you're using it wrong" is actually just a further indictment of Sam Altman and his like, because it shouldn't be possible to use LLMs wrong!

The rest, well, the hype needs to die before anyone can make sane estimates of what LLM tech can do for us in various fields. Right now it's all a complete mess.

Very little new or ground-breaking (I struggle to think of things AI has produced that aren't themselves just more AI), but various previously-stable sites and services breaking.

I'm not talking about the quantity of code produced, but about actual user needs that are now resolved that would not have been before.

The main productivity gain will not come from existing software engineer, but from people that couldn't code at all before but are now able to do things by themselves. We are still very early.

Kind of a self-fulfilling prophecy.

What's not a problem, by the way. That's why people always recommend content creators to be themselves. If they try to be somebody else, they find their public is already busy following other people.

We have polar opposite media bubbles. I see OG programmers all over my timeline either grieving the "end of software engineering" (a la Ryan Dahl) or extolling "automatic programming" (a la antirez).

They are not only useful it is obvious they are. If you don’t see it I really, really don’t know what to tell you. You can tell yourself I am bot or shill or whatever if that helps you sleep but .. just trying to help out another dev here. Wake the F up.

Except that in the process of the markets finding out, things will not go back to normal if everyone's retirement is tied to the market. And in the process of finding out, things will not go back to normal if the hype cycle disrupts traditional hiring/firing decisions.

If it's as bad as some of us believe, then when it falls apart, a lot of people get hurt as collateral damage.

The market eventually found out about Bear Stearns, but a lot of innocent people lost their homes in the process.

In some ways things that are both useful and harmful are the hardest to deal with. And this isn't just "prestige", it's the already-decaying post-truth infosphere and the already-overheating CO2 levels in the atmosphere.

AI is useful in cases where you can automatically catch errors. Programming is uniquely suitable for this, because we have already got all our machinery of type systems and CI tests to catch human errors. How useful it is in other cases depends on how cheap it is to catch errors and how much they cost - and whether the cost of errors is inflicted on other people.

People who are against AI don’t care if it’s useless, they care it’s harmful. And you can’t systematically cause harm then say “oops, our bad” and have everything return to how it was with a snap of the fingers. The consequences of harm don’t go away when the source does.

> I do think they're worried about what it'll do to their prestige

Why must this always be the argument? It was the same with cryptocurrencies and NFTs, there is a specific type of proponent who always accuses critics of secretly being pro the technology but publicly against it due to some ulterior motive. Most people aren’t selfish lying rat bastards who think like that.

And in that period where the markets are irrational people are losing their jobs, hardware is being priced out of consumer markets and the rich are trying to embed themselves so hard that we get to pay for it when the market corrects itself. I think your take is highly indicative that you live in a shrinking bubble unaffected by those things.

https://www.wheresyoured.at/oai_docs/

However, it needs to be said that he received those numbers. I personally have quite a few issues with him, but there's no reason to doubt his journalistic integrity. Because of that, I believe he reports truthfully on data he receives by informants.

Additionally, none of the frontier models actually publicly talks about inference costs in anything but broad, "let's just forget that"-like takes. Which does not exactly spark confidence.

I'm eagerly awaiting anthropic's public disclosure of their financial details. That should be rather interesting in any case and finally put the inference-discussion to rest.

1. What data?

2. Intuitions = vibes.

Vibes are bad when used against you, but good when used in your favor.

Come on :-)))

Judging by the announcements today about its integration into the OSes? They are offering useful things ChatGPT cannot offer unless they write an "everything app".

One can (maybe should) make the argument that this is the browser monopoly again, but given that the USA has seemingly no intention of ever litigating that question again even if the EU does, there are clearly features here that OpenAI is effectively locked out of offering.

OpenAI's commitment to privacy is absymal relative to the sensitivity of the data people are dumping onto the platform. The CEO also has a reputation for being untrustworthy.

The biggest threat to ChatGPT's moat may be a brilliant marketing campaign by Apple that really gets people thinking about what platform they want to be upload their secrets to.

If AI use via Apple represents 10% of the total that vaguely implies that the total AI market is worth around $10 billion per year (which admittedly seems a bit low), and if it is just 1% (which also seems low) then we get $100 billion per year upper-end estimate.

Which just is not enough to justify the current valuations of AI companies.

But not because anybody asked for that. It is part of the force feeding so execs can make this exact argument, and pretend that demand is there.

If you’re only giving even odds you’re not very confident in openAI at all. $15 billion is peanuts.

I just don't see how being the "premium" provider really works if much cheaper models are basically good enough.

I don't gamble. Though you might not be alone taking the bet:

https://www.notus.org/technology/trump-blindsided-ai-compani...

"OpenAI CEO Sam Altman pitched the idea of turning over shares in his company to Trump in early 2025 and discussed the matter again with senior officials in recent weeks"

I actively hate it when it brings in some nonsense it thinks it knows about me. I told it my income once in an attempt to use it to find the perfect rewards credit card mix. Now anytime I try to get it to search for a deal it brings up some nonsense about “as a high income individual you don’t worry about saving $X, you care more about reliability, so you don’t need to look for the lowest cost” or something similar.

I don't, and that's the point, isn't it?

It's the keys to a substantial chunk of the kingdom for $1B a year. Literally they are getting, for a very small price, the right to distill their own models from Gemini.

Is there money in this for someone with a data centre? Possibly. Is there money in it for NVIDIA? Possibly.

But either way, that's not OpenAI or Anthropic, is it?

https://mlq.ai/news/openai-projects-over-280-billion-revenue...

"OpenAI projects revenue will be divided nearly equally between its consumer and enterprise business units by 2030"

That it is so absurdly ambitious and so likely to run up against reality strikes me as really indicative of the quality of the envelopes these calculations are being sketched on.

Even within the Fortune 5 of the US if be surprised if any of them are paying more than $1B annually currently in total.

And then you can take the parent context into account. If they can just equip users with a slightly more expensive Mac and call their Dell rep to order a few thousand DGX Spark to handle the rest... Why would they risk their trade secrets and intimate details flowing into models that may or may not be trustworthy long term?

Most large enterprise have been burned by SaaS over the years in some way. I can't imagine there aren't architects in the large organizations that are truly weighing how to effectively use AI. And beyond that we're seeing more and more progress in SLMs and orchestration agents which become easier to run at scale on-prem.

I don't think people will be doing business with the labs directly. "Enterprise AI" will be distilled down into purpose built products, with the model just basically being a generic commodity, and nearly irrelevant to the enterprises buying whatever these products are much like how I don't care if whatever SaaS was built in React, Vue, or some other framework as long as it works.

Ironically, for as much shit as they get about Copilot, Microsoft I think has the right idea for the long game they just suck at execution. Copilot is the tool, integrated into the rest of their enterprise stack, it doesn't care what the model is behind the scenes (they already offer you the ability to choose between different models).

That doesn't really bode well for the labs and their trillion dollar IPOs, because they are effectively reduced down to being a developer framework.

https://news.ycombinator.com/item?id=48451053

• He seems to think that the moment Nvidia release new hardware, all existing hardware becomes worthless. It doesn't and there are plenty of tokens being served by old GPUs. This makes all his calculations about how quickly datacenters have to pay off useless.

• All his numbers about costs, revenues etc are guesses or attempts to work backwards from off the cuff and frequently inconsistent comments by tech executives. They could easily be very far off.

• He doesn't seem to understand that datacenters have never been full of hardware on their opening day. A lot of his attacks revolve around this confusion - he learns that an opened datacenter isn't yet at full load or fully equipped with GPUs and thinks that means it's been delayed. I remember when Google first opened their facility in the Dalles, it took years for it to completely fill with machines.

That seems like a giant paucity of imagination. I can easily name a lot of areas where AI is already having a large impact and it's not hard to imagine the impact growing:

1. Customer service. Yes, we all like to laugh at the silly chatbot mistakes, linked list reversals and Instagram oopsies, but a lot of companies are putting a lot of effort (and spend) into AI for customer service.

2. The legal profession is already spending a lot on AI, and it will only grow. Again, we all like to read about hallucinated case citations, but those are solvable problems (honestly I felt they were more human problems than tech problems to begin with) and there are so many areas in research and document summarization that AI is really good at.

3. Radiology. There are lots of arguments over whether AI will "replace radiologists", but that's besides the point. The largest radiology groups in the country already use AI software to check for specific missed diagnoses, and the expected spend on AI will grow, a lot.

4. Enterprise knowledge management. Services like Glean are popular and growing.

I can easily go on.

He mixes estimated capex spend by like 3 different sources with actually commitments by the LLM providers.

He talks about how crazy it would be for ai providers to double revenue every year. But openai is doubling every 9 months and anthropic is doubling every 3.

It's obvious if AI consumption stops growing today those companies are in trouble, and if AI consumption keeps growing at current rates they'll be more than fine.

Most people expect growth rate to slow, just no one knows by how much. This will determine if there is an over build out or not.

What turned me off though was this paragraph:

> 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.

That's a very bold claim. Really anyone excited about generative AI dude? That's just an absurd claim, and makes it sound like he hasn't used an LLM since GPT 3.5. It's just the language is so hyperbolic and angry that it's giving me more rant vibes that really hurt the tone and damage the (many valid) claims he's trying to make.

Really tried to read through this all the way, but man I'm just not in love with this guy. I feel like the frustration is clouding his judgement. This line is another one with a fact that isn't really grounded:

> so, you know, they only need to grow by 496% by the end of 2029!

Which isn't wrong, but also Anthropic's revenue increased from $1 billion in Dec. 2024 to $47 billion May of 2026. Which of course doesn't guarantee that it will continue to grow at that scale, but it's clear that there is a strong demand for what they are creating.

Idk, not really sure what my point is here. There are just so many facts and numbers quoted in here... It's a bit exhausting to refute a piece like this, when parts are genuinely correct, and parts are maybe subconciously exaggerated due to some emotional leaking into the argument.

- His own objectivity - he consistently throws shade (rightfully) at the pro-AI side being financially 'required' to hold a certain world view, but is completely blind to his own claim to fame effecting him similarly.

- He consistently claims AI can't be made to work, and tries to prove this by calculating with the bubble prices. Its like saying tulips could never be profitable in the middle of the mania because ships were too expensive as proven by their current price to use for shipping tulips.

Add in the semi regular instance downplaying AI's usefulness contradicting my own experience and I mostly dont bother reading him anymore.

Its not like I'll be surprised that shit hits the fan, and he's not going to call the 'when' any better than wallstreetbets or an octopus.

I scrolled down a bit to read. A popup took up my screen, asking me to subscribe, having read essentially nothing at this point.

I just left. Life is too short.

Hype cycles never last forever, but that doesn't mean all the value has been tapped by any means. The fact that modern GPUs can solve ridiculously complex high dimensional functions is a superpower in every possible field of research.

That being said, AI seems kind of miraculous sometimes.

Similar to cars. So enticing that we make everything else in the world worse in order to maximize the profit, make it indispensable, subsidize it, and make the dependency on it irreversible.

And it's not even something to blame individual people for.

Driving away from all the other cars to spend a weekend feels like freedom.

Using AI to answer a question feels like a "bicycle for the mind".

But in fact it's more like a car. It requires massive resources and creates perverse incentives, and the result is ineffective and corrupt.

Both cars and AI are amazing technology and extremely useful, but using them is not an individual responsibility. It requires societal subsidy.

Where did all the stock gains go before AI?

FAANG / MAG-7.

Was everything from 2012-2020 fake, too?

Infrastructure doesn't produce value overnight. How long did it take the Interstate System to provide measurable value? I asked Gemini. Supposedly increased national productivity by 25% over 39 years[1]. But if you drove on a newly finished interstate in 1959, you saw the same cars just moving a lot faster.

That's what we're seeing right now. People can produce an incredible amount of stuff really quickly with AI. Is it directly connected to measurable productivity across the entire economy? No, because, realizing a mass productivity increase from infrastructure takes time.

[1] - https://www.richmondfed.org/publications/research/econ_focus...

The question is, is AI leading to massive productivity gains in companies that implement it? AI productivity gains take time to diffuse, but so far companies in the S&P 500 are seeing very high growth. YOY earnings growth rate for the S&P 500 is 21.7% https://advantage.factset.com/hubfs/Website/Resources%20Sect...

I mean, do you know what the value of those stocks would be if AI didn't exist. Maybe they would be much more negative. Maybe we would be in a recession. Without a control this type of analysis is meaningless.

And that is even assuming that AI productivity gains are happening now instead of 5-10 years from now.

But does it also not mean that they will make less money given that there is already brutal competition for that lower tier from openrouter, Deepseek, Amazon, etc.?

You can't on the one hand say "customers are beginning to understand they can spend less" and on the other hand suggest that this is good for forecasts of revenue.

Could you share what tells about it? I.e. where he was wrong about it?

EDIT: In fact, parent comment has a link to some numbers.

[EDIT: Most] people don't want to go through the numbers. Ok. But there's a history here. When people don't want to see the numbers, certain kinds of things tend to happen.

Have a muck about with what Qwen 3.6 or Gemma 4 can do and you'll see. I mean this as an illustration but Qwen just isn't as far behind as I expected, and compared to the data centre hardware it will run on a potato.

The frontier models are losing their undeniable edge over that which is unmetered.

And even putting aside my optimism for the smaller open weights models, there's a huge amount of scope for the larger, hosted open weights models that are only just behind the cutting edge and which cost, what, 1/25th of the price on opencode go, openrouter etc.

Commodification is coming, and with it slimmer profit margins; it's hard to see them making anywhere near the kind of money they need to in a commodified market.

Do you think it's not slowing? Do I miss anything really important?

My understanding is that we have now is incremental improvement on thinking models which appeared more than a year ago. Of course, a breakthrough might happen, but I don't see one yet.

Old WSB saying: The market can remain irrational for (far) longer than one can remain solvent.

And unfortunately, a lot of the market on the "buyer" side has been acting irrationally. When you see CEOs telling their employees that they don't care about token cost, only about "how much AI do you use" because that is what the stock market wants to hear - that's when you know we're all getting cooked, the question is how long it takes until the bubble bursts.

I think the surest sign of productivity gains is the sheer volume of adoption. If you look beyond headlines, adoption is just incredible. Of course adoption does not necessarily point to productivity gains, but if this was some sort of FOMO or smoke and mirrors you would not see this much retention and this feverish a pace of adoption. You would not see a large segment of the profession using coding agents exclusively. All of these companies track productivity, again with imperfect proxies, yet everything points to a pretty consistent picture. Same with benchmarks, again a lot of crappy benchmarks but a lot of high quality ones too and a very diverse collection of tasks and capabilities they probe.

LoC: people argue it’s not what’s important

PRs/day: same as LoC

Getting projects done faster: oh but what about the quality.

Solve the technical problems and actually be more productive, the social systems build around the old way of doing things will hole you back.

Finish a PR in 10 minutes doesn’t matter if you’re waiting days for a human review.

Why should someone pick Opus 4.8 when Qwen3.7 Plus produces similar results for about 1/20th the cost.

That sort of pricing disparity is across the board. But further it's becoming more and more apparent that they are doing more with less parameters. That's what's giving the local models their super powers.

The way you make a viable service that eats 300bn annually is to have enough demand to service that. Anthropic underbought compute. That tells you something.

* robotics (need to close data gap and release first viable product to get a data flywheel)

* conversational ai (no one is ready for this and we’re getting closer and closer to natural speech. The quality still isn’t good enough but it’ll be soon).

* other agentic use cases, openclaw adoption was crazy and that had a ton of barriers to entry

* ai products, like the one OpenAI is working on with Johnny Ive

Anyone thinking it’s unreasonable to hit whatever revenue requirements is just not that aware of what’s happening. Not to mention were capacity constrained already!! This is barely speculation at this point.

Extreme ignorance?

I think it's a poor number to build an "AI is slowing down" narrative around.

While this seems to be allowed because the current ToS don't seem to explicitly forbid it, I'd be surprised if this loophole stayed open for long... Why would they even distinguish between business and (much cheaper) individual plans if companies can work around it by telling employees to just pay for the latter themselves?

They were right about all of that but it took 15-20 years and the companies involved grew 100x in that timefold, eventually reaching trillion-dollar valuations that would've seemed insane in 2007.

There is a tremendous amount of money to be made in destroying society.

So, it stands to reason that it wasn't a prediction, but a lucky guess (unless the alleged predictor has a history of correct predictions).

I'm not open-minded to arguments about utility, given that I personally witnessed LLMs evolve from interesting but useless toys to insanely helpful tools I use every day.

But from the article I linked back in March 2024:

"Generative AI models are expensive and compute-intensive without providing obvious, tangible mass-market use cases. Murati and Altman's futures depend heavily on keeping the world believing that development and improvement of their models' capabilities will continue a rapacious pace of progress that has unquestionably slowed, with OpenAI admitting that GPT-4 may be worse on some tasks.

As I've written before, hallucinations are a feature not a bug. These models do not "know" anything. They are mathematical behemoths generating a best guess based on training data and labeling, and thus do not "know" what you are asking it to do. You simply cannot fix them. Hallucinations are not going away."

Since then:

- hallucinations are dramatically less of a problem

- several mass market use cases have emerged, most notably coding

- rate of progress has increased

> I believe that artificial intelligence has three quarters to prove itself before the apocalypse comes, and when it does, it will be that much worse, savaging the revenues of the biggest companies in tech. Once usage drops, so will the remarkable amounts of revenue that have flowed into big tech, and so will acres of data centers sit unused, the cloud equivalent of the massive overhiring we saw in post-lockdown Silicon Valley.

We have seen 8 quarters since. Has any of that come to pass?

One other thing that’s working against the model makers is the hardware is getting better and the models are getting smaller and more capable. I don’t think we’re going back to the mainframe days. Local will be the endgame.

Is Ed right? Probably because in the end it’s unsustainable the companies left will be the companies that have income coming from somewhere else and there’s one large tech company that isn’t even participating in the boondoggle unless you count $1 billion dollars a year as participating ultimately there is no moat in AI model making.

Nvidia and Microsoft trying to introduce another Arm processor in a laptop of all things won’t change the tide either.

It is literally judging the book by it's author, which is an extremely rationale judgement to make.

It entirely depends on the situation. Background NPCs that just have conversations among themselves would be a great use of LLMs to make the world feel more immersive. Obviously you never want to directly engage the player with LLM generated writing.

I do have other sources of information and I probably agree in general that AI companies are doing pretty shady financial shenanigans. I even think it's possible that openai is in real trouble. But I don't extrapolate that into "AI is useless", which is what he does.

Someone else separately linked Ed’s 2024 claims [1] that:

A. AI revenue had about already maxed out.

B. AI's output accuracy was already about as high as it would ever be

C. AI users were already declining or was as high as it would ever be.

So we have 3 2024 claims about whether AI was already the biggest/best it would ever be, and whether AI usage was even already shrinking. All ended up being the opposite of true.

Have you looked at whether Ed’s previous claims that went against popular AI views and are testable ended up being true or not?

Does it matter whether an author’s claims like that are true or not for whether you will continue consuming them?

If straightforward claims like the above are so easily disprovable, what makes you believe that he isn't cherry-picking other stats in order to spread misinformation or disinformation, as the individual stats he points to might even be completely true, but if they are cherry-picked, they may be more misleading than elucidative?

If someone has a multi-year history of frequently spreading false claims, should we trust their predictions about future events more than other sources?

[1] https://news.ycombinator.com/item?id=48447549

Start at 1:07:00 in their announcement video. Craig is absolutely talking about "Apple Intelligence" as a whole in this segment.

Pragmatically, of course they'd need to add metering to any cloud available APIs that rely on large models. There's no way they will eat the cost of serving unlimited access to a cloud LLM to end users if they won't eat the cost of an image generation model.

MacBooks have a lot of memory and a lot of FLOPs. They mostly sit unused all day. Yes, the excess energy use will be higher than a GPU in a datacenter doing the same work, but you have to generate an absurd amount of tokens before the dollar-efficiency catches up with the MacBook.

"I believe that artificial intelligence has three quarters to prove itself before the apocalypse comes, and when it does, it will be that much worse, savaging the revenues of the biggest companies in tech. Once usage drops, so will the remarkable amounts of revenue that have flowed into big tech, and so will acres of data centers sit unused, the cloud equivalent of the massive overhiring we saw in post-lockdown Silicon Valley."

Ed Zitron. Mar 18, 2024

Don't want to ruin it but go read some old posts from the author about AI, the tone is the same and he is very much wrong.

I’m not attacking the piece. I’m not saying it’s right. I’m not saying it’s wrong.

What I’m saying is, the tone made it hard for me to judge the arguments fairly, despite finding some of them convincing. And as much as I dislike it, persuasion does partly depend on how an argument is made.

"Some people say the Sun sets at East, other people say it sets at West. The truth, of course, is certainly on the middle."

Usually does when you decide what constitutes extreme.

Obviously, you can agree with one thing and not with other. And he can be right in one thing and not the other. But, if you listen to what he is saying, he is absolutely saying the technology is not significant.

That’s really the only way the math works - outright displacement of labour

If I were to make a prediction, it's that ultimately these cheaper models are going end up eating their lunch. I don't think they'll make back the money they've invested and once that reality hits investors, those two companies are sunk.

That, however, is not the end of AI. Nor will it be the end of Nvidia/micron/etc. It will more just be a localized bubble pop that doesn't eliminate the product from the market.