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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

#371

Post by crena »

GeekyBear wrote: post #319
HerbManic wrote: post #4

Earlier quoted context omitted.

Pretty much it. That said, they did try to appease the markets by announcing 'Apple Intelligence' so they didn't appear to be behind everyone. They did do the smart thing of not throwing too much capital behind it. Once the hype crumbles, they will be able to do something amazing with this tech. That will be a few years off but probably worth the wait.

Apple's Neural Engine and the CoreML framework to leverage it are almost a decade old now. Apple Intelligence was a rebrand, and Apple has made some unique decisions rolling it out. For instance, the new chatbot version of Siri's hallucinations were seen as unacceptable, so its release was delayed. Is a chatbot that provides false information regularly really an advancement? Apple chose not to do photorealistic gener…

That is definitely true, but some time ago Apple’s marketing team has also put out some pretty cringey commercials to the contrary. It’s wild how they seemed to be encouraging people to cheat and hide their ineptitudes, rather than just being honest about it.

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

#372

Post by dangus »

nl wrote: post #260
dangus wrote: post #254

Earlier quoted context omitted.

And if AI was making lots of money they’d break it out and proudly display it in their financials on its own.

They can't break it out because it is embedded in other services. But to quote: > Overall, we’re seeing our AI investments and infrastructure drive revenue and growth across the board. and > Revenue from AI solutions built by our partners increased nearly 300% year-over-year, and commitments from our top 15 software partners grew more than 16X year-over-year. https://blog.google/company-news/inside-google/message-ceo…

Revenue != Profit

Operating margin has been declining since approximately 3/2025 at Alphabet.

You think Google has no ability to tell us whether a traditional search makes more revenue than an AI Summary search? I think we would be naive to assume they don't know that.

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

#374

Post by Gigachad »

satvikpendem wrote: post #336
dwaite wrote: post #334

Earlier quoted context omitted.

Knowing the building heights around Chicago is not an OS feature. Even if Siri was perfect, they still aren't going to ship a wikipedia object graph on every phone. Likewise, the phone does not understand removing people from a photo. It is a feature specific to the photo app, and Siri allows you to wire in commands for the features in your app just fine and has for years. If Google decided for competitive reasons to…

> Hey Siri start the Chronometer / There is no contact named Chronometer in your phone Is what I was referring to, Siri often fails at even opening apps which is an OS feature. Regardless, even for your examples at a certain point an AI assistant not being able to do certain things while others can does become the fault of that AI.

Just ask for the timer. That's what it's called in iOS. I've never seen someone stuck on this before.

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

#375

Post by rk06 »

ebbi wrote: post #358

I think introducing the MacBook Neo now, at that price point, was a genius move. While they're playing the waiting game on AI, they're cementing the next generation into the Apple ecosystem and getting them to not sway towards whatever device(s) OpenAI is cooking up. The MacBook Neo feels like the iPod of this generation.

can it run windows?

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

#376

Post by rachel_rig »

10keane wrote: post #93

there are always three elements in the equations of business model: 1. marginal cost 2. marginal revenue 3. value created for llm providers, i always believe the key is to focus on high value problems such as coding or knowledge work, becaues of the high marginal cost of having new customers - the token burnt. and low marginal revenue if the problem is not valuable enough. in this sense no llm providers can scale lik…

[dead]

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

#377

Post by TeMPOraL »

jstummbillig wrote: post #323
dns_snek wrote: post #276

Earlier quoted context omitted.

We're not talking about writing assembly by hand here. If your software has a million daily users and wastes a minute of their day, that's about 9 work-years of labour wasted every single day. In a 5-year lifecycle that's about 10,000 years of human labour wasted. Yes, I had to quadruple-check this myself. Does it take 10,000 work-years of effort, per project, to train its developers to write reasonably performant co…

What world are you living in where the median piece of software has a million users? Or even a hundredth of that?

It's what many software companies dream of and aim for. But the same argument works with 10k users, or even 1k users.

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

#379

Post by dns_snek »

jstummbillig wrote: post #323
dns_snek wrote: post #276

Earlier quoted context omitted.

We're not talking about writing assembly by hand here. If your software has a million daily users and wastes a minute of their day, that's about 9 work-years of labour wasted every single day. In a 5-year lifecycle that's about 10,000 years of human labour wasted. Yes, I had to quadruple-check this myself. Does it take 10,000 work-years of effort, per project, to train its developers to write reasonably performant co…

What world are you living in where the median piece of software has a million users? Or even a hundredth of that?

I'm not talking about the median piece of software with 2 users and 0.1 developers (I made that up).

The ones that stick out are actively maintained, widely used, and well funded. It doesn't have to be a million active users, but they should be the first to get their act together.

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

#380

Post by shaz0x »

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…

Even Gemma 4 E2B is more useful than you'd think if you give it the right harness. I've been running it on Android via llama.rn and it handles function calling natively — the model outputs structured tool calls without any prompt engineering. Won't replace Opus for hard reasoning but for a mobile app that needs to pick a tool and run it, the cost math is hard to argue with. $0/query forever.
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