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Apple's accidental moat: How the "AI Loser" may end up winning

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Re: Apple's accidental moat: How the "AI Loser" may end up winning

#111

Post by russelldjimmy »

smt88 wrote: post #57
hapticmonkey wrote: post #13

Apple aren’t in the business of building chatbots to impress investors (other than some WWDC2024 vaporware they’d rather not talk about any more). They’re in the business of consumer hardware. Consumers want iPhones and (if Apple are right) some form of AR glasses in the next decade. That’s their focus. There’s a huge amount of machine learning and inference that’s required to get those to work. But it’s under the ho…

Consumers don't necessarily want iPhone. They don't want to be excluded from iMessage, which is a completely different motivation.

No one uses iMessage in my country. Yet iPhones are sought after. Some of us just really like iPhones for the experience - not everything is a conspiracy. People can have different tastes and are more free to choose than people on HN like to believe.

Re: Apple's accidental moat: How the "AI Loser" may end up winning

#112

Post by russelldjimmy »

camkego wrote: post #109
Maxion wrote: post #88

Earlier quoted context omitted.

iMessage is AFAIK only really a big thing in the US.

I totally buy this as someone located in the US, but what is everybody else using? It can’t be WhatsApp? Is everyone sending all their connection graphdata to Meta?

It’s WhatsApp. No one thinks about sending data to Meta. The world is much bigger than the HN bubble, where almost no one thinks about privacy implications.

Re: Apple's accidental moat: How the "AI Loser" may end up winning

#113

Post by bdavbdav »

smt88 wrote: post #57
hapticmonkey wrote: post #13

Apple aren’t in the business of building chatbots to impress investors (other than some WWDC2024 vaporware they’d rather not talk about any more). They’re in the business of consumer hardware. Consumers want iPhones and (if Apple are right) some form of AR glasses in the next decade. That’s their focus. There’s a huge amount of machine learning and inference that’s required to get those to work. But it’s under the ho…

Consumers don't necessarily want iPhone. They don't want to be excluded from iMessage, which is a completely different motivation.

US centric view, which I believe to be wrong. UK is predominantly WhatsApp, and the bulk of handsets sold are still iPhones.

Income is a much tighter correlation than messaging platform. Rack up those market shares by phone value and the scales tip even harder.

Re: Apple's accidental moat: How the "AI Loser" may end up winning

#114

Post by crote »

lern_too_spel wrote: post #33
m463 wrote: post #27

Earlier quoted context omitted.

Quietly they are doing things on-device. The OCR + copy/paste is genuine goodness - modestly functional.

That's also literally years behind the competition. https://www.androidpolice.com/2018/05/09/android-ps-new-rece...

The competition has also attached it to a toxic brand and heavily integrated it with actively user-hostile applications. It doesn't matter if your tech is years ahead when people expect using it will mean your image content info will be sold to anyone willing to pay a cent for it.

Re: Apple's accidental moat: How the "AI Loser" may end up winning

#115

Post by anjel »

socalgal2 wrote: post #56
grtteee wrote: post #2

This is the classic apple approach - wait to understand what the thing is capable of doing (aka let others make sunk investments), envision a solution that is way better than the competition and then architect a path to building a leapfrog product that builds a large lead.

Yea, they nailed that with the Newton, Apple Pippin, and the Apple Vision Pro

Apple learned to hang back from plowing the unsold Lisa's into a landfill.

Re: Apple's accidental moat: How the "AI Loser" may end up winning

#116

Post by russelldjimmy »

bigyabai wrote: post #106
rvz wrote: post #21

Apple never competed in the "AI race" in the first place, because they already knew they were already at the finish line. This was really unsurprising [0]. [0] https://news.ycombinator.com/item?id=40278371

> This is an obvious moat for Apple who can offer a cheaper alternative for training, inference AI server farms. According to Bloomberg, Apple's inference server farms are a flop: https://9to5mac.com/2026/03/02/some-apple-ai-servers-are-rep... the chips [...] are not powerful enough to run the latest frontier models like Gemini, which the new Siri will be based on

Go a little bit deeper than what the media directly wants you to think.

Re: Apple's accidental moat: How the "AI Loser" may end up winning

#117

Post by oasisaimlessly »

bdavbdav wrote: post #110
lern_too_spel wrote: post #33

Earlier quoted context omitted.

That's also literally years behind the competition. https://www.androidpolice.com/2018/05/09/android-ps-new-rece...

But everyone talks about it like it was Apple, and isn’t that what matters (to Apple)?

I've never heard anybody (mis)attribute that to Apple.

Re: Apple's accidental moat: How the "AI Loser" may end up winning

#118

Post by crote »

moondev wrote: post #91
codeptualize wrote: post #76

Earlier quoted context omitted.

I think their M chips are a good example. They ran on intel for so long, then did the impossible of changing architecture on Mac, even without much transition pain. Obviously that was built upon years of iPhone experience, but it shows they can lag behind, buy from other vendors, and still win when it becomes worth it to them.

How is changing the architecture of a platform that only you make hardware for doing the impossible? They could change the architecture again tonight, and start releasing new machines with it. The users will adopt because there is literally no other choice. Every machine they release will be fastest and most capable on the platform, because there is no other option

The hard part is doing so without completely ruining the existing app ecosystem. Rosetta 2 is genuinely impressive.

Re: Apple's accidental moat: How the "AI Loser" may end up winning

#120

Post by charcircuit »

blcknight wrote: post #105
amazingamazing wrote: post #22

Gemma4 in my view is good enough to do things similar to Gemini 2.5 flash, meaning if I point it code and ask for help and there is a problem with the code it’ll answer correctly in terms of suggestions but it’s not great at using all tools or one shooting things that require a lot of context or “expert knowledge” If a couple more iterations of this, say gemma6 is as good as current opus and runs completely locally o…

There is a cognitive ceiling for what you can do with smaller models. Animals with simpler neural pathways often outperform whatever think they are capable of but there's no substitute for scale. I don't think you'll ever get a 4B or 8B model equivalent to Opus 4.6. Maybe just for coding tasks but certainly not Opus' breadth.

I think you are underestimating the strength a small model can get from tool use. There may be no substitute for scale, but that scale can live outside of the model and be queried using tools.

In the worst case a smaller model could use a tool that involves a bigger model to do something.

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