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iPhone Air

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Re: iPhone Air

#581

Post by CephalopodMD »

nakamoto_damacy wrote: post #465

I have an iPhone 13 mini, just replaced the battery. If you want my money, give me an iPhone 17 mini with small width and height, I don't care about it being thinner like the Air. Also, no AI ruining the image quality of the expensive camera. I saw examples of a consumer-grade digital camera vs an iPhone 16 and the latter introduced "hotdog skin" effect and other effects that made the photos look over-processed.

Also still rocking a 13 mini. There are dozens of us! Dozens!

(Also to those who say not enough people wanted a mini phone to be worth producing: I submit the case of Prego chunky pasta sauce. Not many people want a chunky pasta sauce, but you sell a whole lot more pasta sauce in total if you sell both regular and chunky pasta sauce. Malcolm Gladwell has a TED talk about this.)

Re: iPhone Air

#582

Post by AdventureMouse »

aurareturn wrote: post #58

It has A19 Pro. A19 Pro has matmul acceleration in its GPU, the equivalent of Nvidia's Tensor cores. This would make future Macs extremely viable for local LLMs. Currently, Macs have high memory bandwidth and high VRAM capacity but low prompt processing speeds. Give it a large context and it'll take forever before the first token is generated. If the M5 generation gets this GPU upgrade, which I don't see why not, the…

> If the M5 generation gets this GPU upgrade, which I don't see why not, then the era of viable local LLM inferencing is upon us.

I don't think local LLMs will ever be a thing except for very specific use cases.

Servers will always have way more compute power than edge nodes. As server power increases, people will expect more and more of the LLMs and edge node compute will stay irrelevant since their relative power will stay the same.

Re: iPhone Air

#583

Post by wfme »

OhMeadhbh wrote: post #580

My experience is "air" in an Apple product's name means battery life is measured in tens of minutes and the fan makes a horrible racket because the CPU is underpowered and intended for only short suprts of activity. That's fine for a laptop because you can keep it plugged in and use your other computer to do tasks that require CPU, but not appropriate for a mobile phone that you may want to operate untethered for hou…

Did you uhhhh read any of the announcement, or just jump straight to writing this comment?

The 17 Air reports 27 hours of video playback - the same as the 16 Pro.

Re: iPhone Air

#584

Post by roody15 »

A19 uses the 3nm process and its benchmarks look similiar to the A18. My two cents I would hold off to next version of the air/pro with the 2nm process and the A20 series chips.

Re: iPhone Air

#586

Post by turtlebits »

ManBeardPc wrote: post #328

I want an extra thick model instead, let’s call it iPhone Travel (or Ultra?). Just thick enough so the cameras are no longer sticking out. Give me an all-week battery instead of an all-day one. Slim down the power usage and give a power saver mode that actually does make a difference. Let me go on a weekend trip in nature or festival without having to carry extra hardware or having to look for public charging station…

Thick is easy. Get a battery case. I used to have one that allowed for swappable samsung batteries packs that was great.

Re: iPhone Air

#587

Post by [deleted] »

aurareturn wrote: post #58

It has A19 Pro. A19 Pro has matmul acceleration in its GPU, the equivalent of Nvidia's Tensor cores. This would make future Macs extremely viable for local LLMs. Currently, Macs have high memory bandwidth and high VRAM capacity but low prompt processing speeds. Give it a large context and it'll take forever before the first token is generated. If the M5 generation gets this GPU upgrade, which I don't see why not, the…

[deleted]

Re: iPhone Air

#588

Post by rowanG077 »

AdventureMouse wrote: post #582
aurareturn wrote: post #58

It has A19 Pro. A19 Pro has matmul acceleration in its GPU, the equivalent of Nvidia's Tensor cores. This would make future Macs extremely viable for local LLMs. Currently, Macs have high memory bandwidth and high VRAM capacity but low prompt processing speeds. Give it a large context and it'll take forever before the first token is generated. If the M5 generation gets this GPU upgrade, which I don't see why not, the…

> If the M5 generation gets this GPU upgrade, which I don't see why not, then the era of viable local LLM inferencing is upon us. I don't think local LLMs will ever be a thing except for very specific use cases. Servers will always have way more compute power than edge nodes. As server power increases, people will expect more and more of the LLMs and edge node compute will stay irrelevant since their relative power w…

That's assuming diminishing returns won't hit hard. If a 10x smaller local model is 95%(Whatever that means) as good as the remote model it makes sense to use local models most of the time. It remains to be seen if that will happen but it's certainly not unthinkable imp.

Re: iPhone Air

#590

Post by MPSimmons »

AdventureMouse wrote: post #582
aurareturn wrote: post #58

It has A19 Pro. A19 Pro has matmul acceleration in its GPU, the equivalent of Nvidia's Tensor cores. This would make future Macs extremely viable for local LLMs. Currently, Macs have high memory bandwidth and high VRAM capacity but low prompt processing speeds. Give it a large context and it'll take forever before the first token is generated. If the M5 generation gets this GPU upgrade, which I don't see why not, the…

> If the M5 generation gets this GPU upgrade, which I don't see why not, then the era of viable local LLM inferencing is upon us. I don't think local LLMs will ever be a thing except for very specific use cases. Servers will always have way more compute power than edge nodes. As server power increases, people will expect more and more of the LLMs and edge node compute will stay irrelevant since their relative power w…

The crux is how big the L is in the local LLMs. Depending on what it's used for, you can actually get really good performance on topically trained models when leveraged for their specific purpose.
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