Apple’s Photos ecosystem is privacy oriented and as a result some (now) baseline features require the use of local models.

The Foundation models keep a surprisingly decent set of data available for fast filtering by a local LLM.

I’ve found a slower, second pass, is needed by Qwen to clean it up. (I am running on the new Mac Mini m5 pro 64gb.)

I’ve run my own tests using a date range, a short description of a red cedar planter box build I did last year, and a set of known correct photos.

There is some cool stuff you can do without sending your family’s pics up to any of the frontier model providers.

Nvidia is also selling the shovle but they train their own LLM and by doing so they can fine tune their CUDA/Chip to have a better shovel than others.

Nvidia's own model does not have to beat OpenAI or any SOTA model. Nvidia just need to build up the in house expert and knowledge to make a better chip since hyperscalers and none hyperscaler like Meta is building their own AI chip now.

Apple can chose not to train their own model to learn how to sell a better shovel.

That's just BS cope. They tried and miserably failed - and still are failing badly. Remember, they were the ones to push for AI with "Siri". Many firings later and 2 CEOs later we are still exactly in square one. The fucking thing can't even get who I want to call, let alone set an alarm without touching my phone FFS.

Exactly my thought as I read it.

They make and sell the hardware that will actually make AI something everyone can used without needing to rely on OpenAI/Anthropic et al.

Apple has never had a moat, anyone else could have built this sort of hardware but they haven't.

So they don't care which model wins, because it will always move out to the edge of the network, and they own a large chunk of that edge.

apple is pretty well set up for this because they do all their hardware in house. if they wanted to, they could pivot in this direction. Ternus is also a hardware guy.