151–160 of 674 posts
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best inference silicon in the world generally or specialized to smaller models/edge?
Not even an Apple fan, but from what I've been testing with for my dev use case (only up to 14b) it absolutely rocks for general models.
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Gatekeeping - nobody else can be the default voice assistant or power Siri, so where does this leave eg OpenAI? The reason this is important is their DOJ antitrust case, about to start trial, has made this kind of conduct a cornerstone of their allegations that Apple is a monopoly. It also lends credence to the DOJ's allegation that Apple is insulated from competition - the result of failing to produce their own winn…
So because Apple chose not to spend money to develop it's own AI, it must be punished for then choosing to use another companies model? And the reason that this is an issue is because both companies are large? This feels a little squishy... At what size of each company does this stop being an antitrust issue? It always just feels like a vibe check, people cite market cap or marketshare numbers but there's no hard cri…
No they were already being sued for antitrust violations, it just mirrors what they are accused of doing to exploit their platform.
https://storage.courtlistener.com/recap/gov.uscourts.njd.544...
The writing was on the wall the moment Apple stopped trying to buy their way into the server-side training game like what three years ago? Apple has the best edge inference silicon in the world (neural engine), but they have effectively zero presence in a training datacenter. They simply do not have the TPU pods or the H100 clusters to train a frontier model like Gemini 2.5 or 3.0 from scratch without burning 10 year…
If nothing else, this was likely driven by Google being the most stable of the AI labs. Gemini is objectively a good model (whether it's #1 or #5 in ranking aside) so Apple can confidently deliver a good (enough) product. Also for Apple, they know their provider has ridiculously deep pockets, a good understanding and infrastructure in place for large enterprises, and a fairly diversified revenue stream. Going with An…
The writing was on the wall the moment Apple stopped trying to buy their way into the server-side training game like what three years ago? Apple has the best edge inference silicon in the world (neural engine), but they have effectively zero presence in a training datacenter. They simply do not have the TPU pods or the H100 clusters to train a frontier model like Gemini 2.5 or 3.0 from scratch without burning 10 year…
Could you elaborate a bit on why you've judged it as privacy theatre? I'm skeptical but uninformed, and I believe Mullvad are taking a similar approach.
They also were deceptive about iCloud encryption where they claimed that nobody but you can read your iCloud data. But then it came out after all their fanfare that if you do iCloud backups Apple CAN read your data. But they aren’t in a hurry to retract the lie they promoted.
Also if someone in another country messages you, if that country’s laws require that Apple provide the name, email, phone number, and content of the local users, guess what. Since they messaged you, now not only their name and information, but also your name and private information and message content is shared with that country’s government as well. By Apple. Do they tell you? No. Even if your own country respects privacy. Does Apple have a help article explaining this? No.
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It’ll be interesting to see how it plays out. The question is, what’s the moat? If all they have is scaling to drive better model performance, then the winner is just whoever has the lowest cost of capital.
This isn’t a mystery - it’s Google
Why they are constantly so bad at AI but so good at everything else?
There's no reason to think that Apple would have any more skill at making a frontier AI model as they do at making airplanes or growing soybeans. Not much overlap between consumer electronics design and expertise, data, training, and datacenters needed for AI.
Apple definitely has software expertise, maybe it's not as specialized into AI as it is about optimizing video or music editors, but to suggest they'd be at the same starting point as an agriculture endeavor feels dishonest.
Was this just a massive oversight at Apple? Were there not AI researchers at Apple sounding the alarm that they were way off with their technology and its capabilities? Wouldn't there be talk within the industry that this form of AI assistant would soon be looked at as useless?
Am I missing something?
If nothing else, this was likely driven by Google being the most stable of the AI labs. Gemini is objectively a good model (whether it's #1 or #5 in ranking aside) so Apple can confidently deliver a good (enough) product. Also for Apple, they know their provider has ridiculously deep pockets, a good understanding and infrastructure in place for large enterprises, and a fairly diversified revenue stream. Going with An…
Definitely. At at this point, Apple just needs to get anything out the door. It was nearly two years ago they sold a phone with features that still haven't shipped and the promise that Apple Intelligence would come in two months.
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The gov’t can force them to reveal any user’s data and slap them with a gag order so no one will ever know this happened.
All user data is E2E encrypted, so the government literally cannot force this. This has been the source of numerous disputes [0, 1] that either result in the device itself being cracked [0] (due to weak passwords or vulnerabilities in device-level protection) or governments attempting to ban E2E encryption altogether [1]. [0] https://en.wikipedia.org/wiki/Apple%E2%80%93FBI_encryption_d... [1] https://en.wikipedia.org…
Why did they change their wording from:
Nobody can read your data, not even Apple
to:
Apple cannot read your data.
You know why.