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AI is slowing down

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Re: AI is slowing down

#301
post #239

Today Apple launched its revamped AI offering. Judging by several reports, Apple pays Google a mere billion dollars a year to operate it. Essentially just licensing the IP. Google are (allegedly) happy to turn over the right to operate and distill their models for only a billion a year. Consumer revenue is only a smallish share of the puzzle, but still: If you are a consumer and you have a Mac or an iPhone, what do y…

ChatGPT has >1B users globally a mere 3 years in. iPhone is at 1.5B mostly concentrated in rich areas.

Re: AI is slowing down

#302
post #72

Earlier quoted context omitted.

There is an observational study that was published in March 2026 that followed 4000 teams over 2 years. It shows, in my view, exactly that the productivity gains don't translate into economic value. Here is the report: https://www.faros.ai/blog/ai-acceleration-whiplash-takeaways And my commentary: https://unessays.substack.com/p/talk-is-cheap

If it was published in March 2026, even if the data was collected up to the day the study was published, 7/8ths of it would fail my “within the last six months” test. But I am looking forward to the results of future studies on this topic!

I get wanting to wait for more data. And thinking that LLMs have improved enough that this will change.

My view is that it's not really about how good the models are - it's about how we're using them. Understanding what you've built is an important part of value creation, and LLMs eliminate that.

Re: AI is slowing down

#303
post #239

Today Apple launched its revamped AI offering. Judging by several reports, Apple pays Google a mere billion dollars a year to operate it. Essentially just licensing the IP. Google are (allegedly) happy to turn over the right to operate and distill their models for only a billion a year. Consumer revenue is only a smallish share of the puzzle, but still: If you are a consumer and you have a Mac or an iPhone, what do y…

> If you are a consumer and you have a Mac or an iPhone, what do you need from AI that Apple's new offering won't provide?

I've been using Kagi Assistant for my AI needs, and have to say, Siri will probably replace it in the fall. The question will be, will I still want to keep Kagi for search, or will this new Siri get me where I need to be on all fronts? I need to start paying more attention to how often I actually use the search results vs just the AI summary.

There are things I didn't see Apple show and I wonder how Siri will handle it. One example would be basic coding. They mentioned LLMs in Xcode and Siri with the Shortcuts app and Safari Extensions, but I just had Kagi write up a webpage as a means to display a bunch of data it gave me. Gemini could also do this, so maybe it's not a problem for Siri, but it remains to be seen. There is also a question of what the experience will be like. ChatGPT, for example, handles writing up this code is a much nicer way than Kagi Assistant. Kagi feels more like the results I would have had from ChatGPT a couple years ago where it just dumps out the code in a block and any change is an entirely new code dump, meanwhile ChatGPT goes into a coding interface with a live editor. Going to Xcode feels like overkill, Siri will probably be not enough... so that's a gap in the market Apple may not serve. I assume there will be several things like this. The prosumer level of AI usage, if you will.

Re: AI is slowing down

#304

Earlier quoted context omitted.

Not sure where I heard this, but I'm reminded of a story about someone predicting the dotcom crash early, circa 1998. For 2 years they were demonstrably crazy, and missed out on massive stock market gains. Then they were right. (And yes, tech slowly bounced back after that.) Predicting the timing of such a thing is notoriously difficult. I don't think being wrong about timing 2 years ago means there won't be a correc…

I'm open-minded to arguments about AI being a financial bubble and a bad business. 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.

I guess one of Zitron's arguments is that the utility you see today is based on subsidized costs, that if you had to pay more it might not be worth the tradeoff to you.

So the claim is the cost isn't coming down enough to make it make sense for a lot of uses in the long term. When I hear that next to the most wild claims, some by influential people, that the entire white collar workforce is going to be replaced very shortly, it's a bit of a useful reality check.

Re: AI is slowing down

#305

Whats a bit wild to me is Google's only selling point for their Pixel phones are increasingly Gemini. Now that you can get Gemini, operated by Apple (with the Apple privacy features that come along with that), why would you ever consider going Android/Pixel (outside of running GrapheneOS, but I'm talking regular consumers here)? Google isn't even making anything on the deal with Apple. They pay $20B/year to be the de…

I switched from iPhone to Pixel after I couldn't stand Liquid Glass and found myself using Gemini more than I expected.

If you're in the Google ecosystem like Gmail and Calendar, it is exceptionally refreshing to be able to use an assistant that uses that ecosystem, instead of iOS requiring you to use Mail or its own Calendar app.

I don't think there's any real gap between Pixel and iPhone on the things that matter: UX jank, battery life, camera. Even the messaging issue in the US has closed with encrytped RCS support between them launching. So now it's just an ecosystem question, which might be why Gemini is mentioned so much with Pixel.

Re: AI is slowing down

#307
post #205

Earlier quoted context omitted.

Every day people here debate whether or not there are any actual productivity gains from LLM, and it's only in the limited context of software development. While I understand that this place obviously skews heavily towards the software industry, the notion that LLMs are anywhere near as useful in other industries is hubristic (at best).

Perhaps they aren't, but not currently viable !== always unviable.

Is it really worth it to cause a global economical collapse and harm society well-being to an unimaginable degree just to find out if it is viable?

Why cant it naturally grow and prove it's worth?

Re: AI is slowing down

#308
post #232

Earlier quoted context omitted.

Agreed. Phrases like "journalists are currently gooning over OpenAI and Anthropic" really put me off. It's a poor attempt at modern muckraking; cheeky yet offering little substance.

He's just a Brit, writing in a style we write in. Sweary, comical, red-top. The Register did it for years.

I'm not a Brit, but I do enjoy British culture, including writing. I haven't been able to read any of Ed's rants to the end despite generally being on the cautious side towards LLMs

Re: AI is slowing down

#309

Earlier quoted context omitted.

I don't read Ed Zitron, aside from when he appears here on Hacker News, and I also find his tone to be over-the-top. I think we might agree on that much. These articles are lengthy but, to my understanding, Ed's idea is... * AI companies have committed to purchasing X amount of compute * Data centers are being constructed to meet this demand, they'll need to charge amount Y * AI companies do not have sufficient reven…

Not the OP but Zitron makes clear errors: • 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 frequentl…

> 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.

Agreed, but I'd argue that Ed doesn't have much else to work with. I'd like to see journalists take this tack and start asking these executives to either back up their statements or back down from them. They should be held accountable for their statements.

Even if we dial down these numbers by a magnitude they are still insanely large and the AI companies do not seem to be making enough money to balance things out.

> 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.

I agree that older hardware from Nvidia doesn't become worthless when Nvidia releases new, more powerful hardware. I have to point out that it certainly loses a great deal of value and that's not nothing.

> 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.

Is that really the case? I mean, I read about the build out of these data centers being delayed all of the time. I read this last week and it seems roughly in line with Ed's ravings:

> A JPMorgan analysis last month found that more than 60% of data-center capacity planned for completion in 2027 isn’t yet under construction, and another 7% is delayed.[0]

[0]: https://www.msn.com/en-us/news/technology/america-s-data-cen...

Re: AI is slowing down

#310

One of the "smells" that gives away a quacky ranter is they speak in impassioned, "Why doesn't everyone understand this?" tones, but in fact their argument just doesn't flow. If Zitron's argument were as solid as he keeps saying it is, you would read it and understand it and see that it is solid. He would begin somewhere–statistics on AI demand, say–and then walk the calculations carefully over to the next step–maybe…

I don't read Ed Zitron, aside from when he appears here on Hacker News, and I also find his tone to be over-the-top. I think we might agree on that much. These articles are lengthy but, to my understanding, Ed's idea is... * AI companies have committed to purchasing X amount of compute * Data centers are being constructed to meet this demand, they'll need to charge amount Y * AI companies do not have sufficient reven…

I don't know if Ed is far off the mark. But this article does nothing to help illuminate it.

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.

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