251–260 of 562 posts
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I thought the news of them using Apple Silicon rather than NVIDIA in their data centers was significant. Perhaps there is still hope of a relaunch of xserve; with the widespread use of Apple computers amongst developers Apple has a real chance of challenging NVIDIA's CUDA moat.
Not at Apple's price points.
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> For people interested in AI research, there's nothing new here. Was anyone expecting anything new? Apple has never been big on living at the cutting edge of technology exploring spaces that no one has explored before—from laptops to the iPhone to iPads to watches, every success they've had has come from taking tech that was already prototyped by many other companies and smoothing out the usability kinks to get it r…
Apple was first with 64 bit iPhone chips. Remember Qualcomm VP at the time claimed it was nothing. Apple Silicon for M1 was impressive for instant in low power high performance.
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The Steam Deck ships with 16 gigs of quad-channel LPDDR5 and it costs $400. Apple knows exaaaactly what they're doing with this sort of pricing. Can't forget about that cozy 256gb SSD either. An AI computer will need more than that, right?
RAM is literally the cheapest primary component in a laptop at going rate of 1-4usd/GB. I'd say that shipping 8GB base model in 2024 is clearly manipulation by Apple, i.e. planned obsolescence or a way to moat Apple software. Anyone who doesn't see this is just being delusional. Same way Apple and Samsung ship 128GB of storage when the production price between 128gb and 1tb is like 10$ (on a 1000$ device). Samsung ev…
I love that they use machinelearning.apple.com not ai.apple.com
For the majority of the keynote they explicitly avoided the word AI instead substituting the word Intelligence, then Apple Intelligence, and then towards the end they said AI and ChatGPT once or twice. I think they saw the response to all the AI shoveling and Microsoft Recall and executed a fantastic strategy to reposition themselves in industry discussions. I still have tons of reservations about privacy and what th…
AI will ultimately do all the 'development', and will replace all apps. The integrations are going to be a temporary measure. Only apps that will survive are the ones that control things that apple cannot control (ie. how Uber controls its fleet)
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Is steamdeck sold at cost? From what I know Apple has a rule that everything must be sold at 40% margins. That is prob the main reason.
As a consumer I really cannot be made to care why it's the case. This artificial price tiering is stupid and everyone has been calling it a scam for years. Apple clearly knows they're in the wrong, but continues because they know nobody can stop them.
“We utilize adapters, small neural network modules that can be plugged into various layers of the pre-trained model, to fine-tune our models for specific tasks.” This is huuuuge. I don’t see announcement of 3rd party training support yet, but I imagine/hope it’s planned. One of the hard things about local+private ML is I don’t want every app I download to need GBs of weights, and don’t want a delay when I open a new…
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" Don't be snarky. " https://news.ycombinator.com/newsguidelines.html
One day they're going to train a moderation bot on your account, and it's going to be amazing.
“We utilize adapters, small neural network modules that can be plugged into various layers of the pre-trained model, to fine-tune our models for specific tasks.” This is huuuuge. I don’t see announcement of 3rd party training support yet, but I imagine/hope it’s planned. One of the hard things about local+private ML is I don’t want every app I download to need GBs of weights, and don’t want a delay when I open a new…
With huge blobs of binary model weights, dynamic linking is cool again.
It is kind of ironic that languages that praise so much for going back to early linking models, have to resort for much heavier OS IPC for similar capabilities.
> For on-device inference, we use low-bit palletization, a critical optimization technique that achieves the necessary memory, power, and performance requirements. Did they go over the entire text with a thesaurus? I've never seen "palletization" be used as a viable synonym for "quantization" before, and I've read quite a few papers on LLM quantization
https://apple.github.io/coremltools/docs-guides/source/palet...
Though I'm not sure how warranted it really is, in both cases it's still pretty much the same idea of reducing the precision, just with different implementations
Edit: they even refer to it as LUT quantization on another page: https://apple.github.io/coremltools/docs-guides/source/quant...