Isn’t Apple potentially under a lot of pressure due to the DRAM prices as well as having to compete with AI for fab capacity? Before all the price hikes their products were already priced at the top of the market so I would assume that memory getting more expensive will impact their sales or margin quite a bit as they can’t subsidize hardware like AI companies do (they can of course eat into their own margins a bit which I think they already do). So not sure if what happens right now is great for them, if the memory market collapses it will of course be good.

Curious, why would Apple want to wait for "all this" to implode? They've had on-device silicon for AI for eons now (in AI-years), so they could have been executing their strategy, whatever it is, all this time, no?

My outsider take is that Apple leadership never really believed in the capability of GenAI, and hence kept pursuing their pre-LLM strategy. An interesting signal about how that's working out now is that their AI org leadership was overhauled recently.

Others are betting on AGI/almost AGI like system. It's a gamble because no one actually knows whether or when it will be possible to create it. But if their bets pay off, they could outcompete Apple. Basically, other companies are going all in on the next card, while Apple is holding back and waiting to see which cards are dealt.

Cell phones are commodities, so how does Apple maintain that cash flow? It's almost like there is more to it than that...

I just switched to iPhone and I have to say the UI is so bad. It will be my last.

No Apple was not sitting there and waiting as if its some grand plan. They tried their VR device which they don't even talk about now. They were late to AI and yes if the bubble bursts they will be at a better position but it's not some grand master strategy. Even inside apple there's been a lot of talk about how badly the company handled AI.

As for laughing all the way to the bank, I am sure memory manufacturers and Nvidia was definitely join them regardless of what happens.

Also comparing Apple (literally one of the largest companies in the world) to a company burning VC money makes no sense.

Here's an interview with the senior product manager of Apple Silicon that more-or-less says the same thing: https://www.macrumors.com/2026/07/06/apple-silicon-exec-expl...

> He also described a shift toward running AI locally rather than in the cloud – a move motivated by privacy, security, and the rising cost of inference as agents consume more tokens. However, Brooks envisions a hybrid future in which agents decide what runs on-device and what gets sent to the cloud.

And coupled with their efforts in auditably-private cloud computing, that's a strong pitch.

I generally agree. Xserve didn't work out for Apple and they dropped it pretty quickly--think I still have an A/UX coffee cup. Wasn't really in their DNA even if there was an argument before Linux took off. For better or worse, they're basically a client company and barely a software (OK and basically a software services) one--although they spend a fair bit on (roughly) user experience.

I don’t think they need to go all-in on anything related to AI.

> This leverages their core competencies, requires only modest investment, and will likely pay out no matter how the AI market eventually shakes out.

This looks more like a call or a small raise or whatever (I don’t play poker).

They've been investing in NPUs for a long long time. Since the first iPad Pro at least (2018). Apple Silicon is a natural fit for tensor/matrix operations due to unified memory, so if anything them going "all in" on that has been a nice side effect.

Just feels like the Apple press/podcast circuit just keep trying to spin ways to frame Apples fumble of the AI era as some sort of savvy move.

If they've gone all in on that, it looks even worse for Apple. Qualcomm's Hexagon has been a better NPU since the beginning. Now even Mediatek is better at it than Apple. Blogs like macrumors and daringfireball are notorious for not having any clue about what is going on in the broader industry.

Not really. Their new Siri is powered by Gemini.

Read a little more of what he's written before you praise him, so you don't end up looking as dumb as I did.

Ed may be right about some of his claims, but he is 100% a crank, and he makes so many incoherent claims I'd say that if he's right, it's in the nature of a broken clock.

There are good sources of well-argued AI skepticism, and then there's Ed Zitron.

Cal Newport is another great person to follow on this and I think he understands the CS fundamentals much better.

The entire internet is full of anti-AI discussion and a straight up disbelief in any chance of success.

Implying there is a "gushing torrent" of pro AI narrative is bizarrely out of touch. We both know this isn't true.

The vast majority of what I see out there is relentlessly negative about AI. It is kind of absurd to call this the "alternative" unless the implication is that the rest of AI skeptical writing is not "well-argued."

75% of comments on every article you read about AI on hacker news is talking about the bubble. But everyone thinks the bubble talk is contrarian.

Is it though? He's more of a gushing torrent of anti-AI propaganda. He has an agenda too, it's just the opposite one.

I find it weird/funny you are getting so many hate responses towards Ed, still no counter-arguments at all. When asked why he is wrong, they vanish. From the outside it looks like a coordinated campaign to try to discredit him.

Happy to read why is he wrong, and change my mind, as long as the arguments provide the same level of analysis he provides.

Well hold on. "They" also thought tokenmaxxing was a good idea, until they didn't.

Whether companies pay will come down to the bottom line once the hype around the country club dies down a bit and for that it's still TBD on the actual product cost impact.

Sure, but what you're not taking into account is that $1500/month is subsidised by VC money.

If Uber were asked to pay full price, they'd either get the same value for significantly more outlay, or keep their outlay capped but get significantly fewer tokens.

This would, I'm sure you'd agree, change the ROI outcome.

Zitron is arguing that if we all pay the true cost once the subsidies go, we'll either stop paying for the value we get today, or we'll find AI to be less useful than we do today, and those businesses won't be sustainable, and then <pop> goes the bubble.

I enjoy keeping an eye on https://isaiprofitable.com to see just where we are overall. Interesting reading if you like to think about such things.

that $1.5k is ostensibly not coming out of productivity gains from the AI though.

it's coming out of the salary budget from what i've seen. i've seen a company both say "AI max. it's the future! don't be late" and then go on to increase limits to compensation across the board.

Very true and I don't think you can completely discount the end consumer market either. A large number of the people not currently paying for a subscription are becoming dependent on AI enabled search results. I imagine monetization of those users is in its infancy and will rival the search result ad business eventually

For me, the economics are the exact opposite. I'd pay $1000 for a good gaming VR headset, but not $4000 -- because gaming is just a hobby that isn't really worth that much to me. Gaming VR headsets have been around for well over a decade, I've "been there, done that", and it's just not something that's worth that much money to me. However, I have no problem paying $3500+ for something that creates a new category of productivity and entertainment experiences for me.

Besides that, I actually disagree that the Vision Pro is not good for gaming. It's not good for traditional VR gaming, but using apps like Portal it's phenomenal for, e.g., playing existing PS5 games on a massive virtual screen, which in many ways I actually enjoy more than VR gaming, which is far too limited in comparison.

It's the same decision-making process that tried to do a electric car for years, and canceled it after spending time and money. In that exact timeline, China made great electic cars and new brands, Tesla advanced and Spacex launched dozens or more rockets. Apple is so far from any big new tech, they and market don't even realize it.

Apple had more money and influence than combination of all of them, yet failed with car and VR. Why would anyone think they can't fail much much bigger with AI and LLMs ?

Same decision making process behind making a VR headset out of heavy materials like glass and aluminum

> I will never understand the decision-making process that led to "Let's build an awesome VR headset that can't do gaming".

FOMO, someone else being successful in VR (and now in glasses) is a nightmare scenario for Apple because it's not their platform. They've got a lot to fear from someone else owning the platform, having written the playbook on how that platform would be controlled and exploited at everyone else's expense.

Imagine if Apple doesn't make their glasses: Meta keeps selling truckloads of them, as they get more powerful the smartphone becomes an optional accessory and then an unnecessary one, eventually they become an alternative to a smartphone and an app platform for third party devs.

It's the same story with VR, Apple does nothing and risks Meta or Steam building a viable platform where people want to use software instead of on their iOS devices, until the hardware can replace iOS devices entirely. (although VR is certainly more of a moonshot)

Who said it can’t do gaming? All the regular graphics APIs are supported.

I think the manufacturing analogy is apt. If you consider both the need for minimal COGS and the large R&D expense, it’s kind of like… biomanufacturing. You spend a lot on R&D to develop your bug, which at the end of the day is just a very complicated sequence (DNA vs model parameters), and then you expend a ton of capex (or rent someone else’s capital equipment) to produce a relatively commoditized product (a drug, a protein, food…) at as large scale and low cost as you can.

But that also makes the case for government subsidization + bailout, if you accept it as a capability critical to national security, but one that may not be profitable to run within the US on its own merits.

> AVP wasn't released early (late, if anything), and it wasn't a dud because of Tim Cook's disinterest.

Depends on what you mean by early.

WAs it released before the market was proven? yes.

Was the whole user experience up to scratch before it was released? no.

As someone who worked on the Quest pro/3 ecosystem, We were shitting our selves, because we knew that apple would only release something when the user experience was right.

Oculus just shat out features as and when performance cycles needed juicing.

Sure the UX was good, but it was less good than I expected. The headset was bulky and surprisingly off balance. It wasn't an all day wearable (i mean the quest pro was actually comfortable by comparison)

The resolution wasn't that great and the only thing you could do with it was either look like a twat recording video or have spreadsheets pasted everywhere. I was expecting an OS where we could put things on work tops, create augmentations to my room, decorate or be creative. Instead we got OSX XR.

Tim Cook was probably mostly disinterested because it didn't seem like a real business opportunity. Wherever AVP fell on the VR/AR spectrum, VR (while having other opportunities) was mostly a niche for high-end gamers and AR, whatever the possibilities in some future idealized form with fashionable glasses that give you lots of information about what/who you're looking at is a long way from reality.

Agree. Apple Vision Pro was a dud because the whole VR category is a dud.

People are starting to kinda hate tech. People don't seem to be looking for yet another "smart manacle". Time to move on.

I'm of the opinion that the market will need to expand, horizontally. That's what's happening, with low-cost LLMs. I already know lots of "regular folks" that are totally hooked on LLMs (mostly ChatGPT, at the "regular mensch" level). They usually use the free tier, but a lot of them are doing the $20/month Pro tier.

If anyone is in my age group, they remember when ATMs were free. It was the "heroin dealer" business model. It worked out well (for the banks). The Chinese did it with manufacturing.

Getting people hooked on subsidized junk, is an age-old (and highly effective) business model.

Think of all the shops that will soon be composed of people that simply can't even get out of bed, if their LLM is not available. If the LLM dealer starts raising the price, there's no choice. I suspect many of the valuations are taking this into account.

> "Junk is the ideal product... the ultimate merchandise. No sales talk necessary. The client will crawl through a sewer and beg to buy."

-William Burroughs

Also enterprises have to pay per-token.

Just to counterpoint the adjacent replier. I have claude, chatgpt, and gemini subs and rarely even use even close to 50%. I code c++ everyday. But im not full in on agentic workflows which is probably why. I mostly do fairly targeted things to my various code bases.

I max out Claude Code and Codex subs both every week without fail and I’m doing a lot of work but it’s not insane.

Interestingly, that METR study has updated data for 2026 that shows a speed up, although they admit that the data may not be reliable because of changed pay rate for participation, but this quote is telling:

> The primary reason is that we have observed a significant increase in developers choosing not to participate in the study because they do not wish to work without AI, which likely biases downwards our estimate of AI-assisted speedup.

So compared to just last year, they had a hard time finding participants because too many didn't want to work without AI.

I stopped reading at maybe 25% into the article. It's obvious garbage.

He selectively quotes the max theoretical enterprise pricing equivalent of fully using the private subscription. Did SemiAnalysis not also claim a very high margin?

He throws in doubt about the providers having decent margins, which he claims is made up by "AI boosters" rather than leaked financials and open-weight pricing.

Then next he talks about "the real cost" of inference as if it was in any way realistic that labs price the enterprise plans near cost, like he seems to imply.

Then next he claims AI is actually slowing developers down and there isn't much difference between the models.

It just seems delusional.

Welcome to Ed Zitron. There is a reason this man doesn't heavily short the same companies he criticizes. Be wary of anyone that won't put their money where their mouth is.

I don't know if his final analysis is right or wrong, but if he believes this, he's completely clueless (about this aspect at least).

Edit: to be clear, I am talking about Ed’s contention that AI coding isn’t net productive.

> I do think the valuations are quite and they would need to meet the reality, but don’t think there’s gonna be a crash or we’d ever go back to pre-AI era. It would more or less would be a correction to valuations.

Something to consider: would your description also apply to the dot-com boom of the late 1990s? The internet was real, the ideas for internet business were real, and we were not going to the previous reality. But the valuations weren't quite right and a "correction" happened at some point.

When people talk about AI crash, that's what they mean. Not that AI is a hoax, but that the correction could be quite violent and have effects on the broader economy.

> [local, but for] extremely niche or higher intelligence tasks

Access to a centralized copy of the web/literature/media, scraped and indexed/integrated, seems another non-local center of gravity. Versus a local model's last minute reaching out to "manually" search and browse.

Also mass parallelism for large ensembles. Perhaps unless/until we get those local models as 10k+ tok/s chips. Local can follow frontier because frontier is still sort of "expensive rack local". If STOA becomes massive burst-parallel ensembles, that following may get harder.

> but don’t think there’s gonna be a crash […]. It would more or less would be a correction to valuations. [...] The future of AI would be on-device models which are as powerful as current frontier models […]

That’s the crash… that’s pretty much exactly Ed Zitron’s thesis

> As an example I use Claude code heavily for every day development and Opus 4.8 was already good enough for my use cases and never used Fable.

I think the flaw in this logic is thinking about how AI is currently used only. Yes, Opus is good enough for the task you are asking it to do, but that doesn't mean that is all you will ever need.

As AI gets better and better, it will open up new use cases that require the better performance.

The money being poured into AI infrastructure means there is a market for new ways of doing things that take 1/1000 of the power or are 1000x faster, or both.

And there are many such moonshot startups.

AI on GPUs is an efficient as gaming on CPUs.

All that math where perfect precision is not required means that you can’t tell do things in different ways.

Why is on-device AI the future? What is your reasoning behind this? Look at the proportion of things we compute on someone else’s computer relative to what we compute on our own device. Why would this change for LLMs?

How's it "quite short sighted"? Are you saying the math _does_ make sense? if so, how?

The validity and permanence of a technology has literally nothing to do with how irresponsible people have been while placing speculative bets on it.

In this case, it’s really irresponsible.

Thats great but this is like when 3g came out. Sure it was the future, but it was half baked, impersonal, expensive, unreliable and required a culture shift to be adopted.

Onboard decent LLM performance thats _power efficient_ is at least two/three hardware generations away. (assuming linear performance)

but, the valuations, with debt trade and private credit obscuring exposure is a recipe for disaster.

Seriously, you should try Fable. It picks up on subtleties that Opus misses.

???

LOL WHAT.

Actually the right framing is Apple hedged the risk by maintaining good relations with China. They did not need to take any of the risk.

In my experience Sonnet is actually pretty good at coding tasks, at least with Go.

Isn't Anthrophic's "recent turn to profitability" just one specific quarter according to non-GAAP practices? How real is that?

I've never heard a compelling thesis for why this is a bubble that will pop. From my perspective AI adoption is just getting started, and every organization I see that starts on the journey only ramps up tokens dramatically. Even just sticking with current model capabilities we have years of business automation, personal automation, and so much more to saturate data centers. As the models improve that only makes more sense. Rather than Apple watching anything burn I think they are going to end up looking like nitwits who missed the boat.

Unpredictable AWS bills are a supply-side problem. He's talking about consumer behavior, and consumers of software do not expect a metered service.

But most consumer's aren't paying per token for access to models, so unless that changes and the labs start charging API pricing to everyone, it's kind of a moot point.

Enterprise certainly wouldn't fit. This argument seems to be targeted at the consumer market, which Apple deals in. Consumers are not paying varying Disney+ subscription prices based on how much they watch. So many points are still interesting. Though, I'm not convinced the consumer market is the primary target for AI firms.

It's fascinating that you simultaneously argue that margins will expand... while posting about personal behavior all of which points toward commoditization and intense price competition.

Doesn't sound like you've read any of Zitron's analysis

I think Ed's argument is that given the infra investment the revenue won't be enough to pay back the original investors. In fact cheaper models make this worse for them. Who cares about the investors? Well it turns out the infra was financed in large part by debt that was securitized and a bunch of regarded investors that bought the debt looking for higher returns will be taking a huge haircut when the bubble pops. The amount of securitized debt is roughly the same as the mortgage backed securities back on 2007, ergo the prediction is a big recession.

What's unclear to me is if this is a systemic issue that's going to cause credit to freeze up but imo the opacity of the shadow banking "system" does not help here. If you see one cockroach, etc.