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Apple picks Gemini to power Siri

cnbc.com

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Re: Apple picks Gemini to power Siri

#262
post #27
post #3

Guess I am not using Siri anymore… By the way, have any of you ever tried to delete and disabled Siri’s iCloud backup? You can’t do it.

Unless Apple is lying: On iPhone, Settings → iCloud → Storage → Siri → Disable and Delete Edit: Tried it. It works for me. Takes a minute though.

I have a current case open with Apple with this issue. It does not work. And I don’t believe you. I’m sorry I just don’t believe you because Apple says there is a technical problem preventing this. That does not just affect me. Because I also tried it on three other phones of three other friends of mine and it does not work.

Re: Apple picks Gemini to power Siri

#263

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…

It’s also a bet that the capex cost for training future models will be much lower than it is today. Why invest in it today if they already have the moat and dominant edge platform (with a loyal customer base upgrading hardware on 2-3 year cycles) for deploying whatever future commoditized training or inference workloads emerge by the time this Google deal expires?

Re: Apple picks Gemini to power Siri

#265

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…

this also addresses something else ...

apple to some users "are you leaving for android because of their ai assistant? don’t leave we are bringing it to iphone"

Re: Apple picks Gemini to power Siri

#267

I wonder if this will my original homepods interesting to talk to or if they won't provide this on older devices.

Not sure if that's too much of a crutch for you, but it's quite easy to create an "Ask Gemini" shortcut that calls a Cloud Function and returns a spoken response. I use this on my HomePods all the time, and it's working great.

How do you do this on a HomePod? I could definitely see Apple limiting this to newer hardware, as a way to bump sales.

Re: Apple picks Gemini to power Siri

#268
post #32

Earlier quoted context omitted.

I mean, Siri has been bad for what, 15 years now? It does seem like a bt of an outlier.

Gemini only replaced Google assistant on Android a few weeks ago. I gave up on Google assistant a few years ago, but I'd guess it wasn't a worthwhile upgrade from Siri.

Still using Google assistant after trying Gemini on my pixel about 6 months ago. It was not an assistant replacement, it couldn't even perform basic operations on my phone, it would just say something like, "I'm sorry, I'm just an LLM and I can't send text messages." Has that changed?

Re: Apple picks Gemini to power Siri

#269
post #13

Why they are constantly so bad at AI but so good at everything else?

Because their focus on user privacy makes it difficult for them to train at scale on users' data in the way that their competitors can. Ironically, this focus on privacy initially stemmed from fumbling the ball on Siri: recall that Apple never made privacy a core selling point until it was clear that Siri was years behind Google's equivalent, which Apple then retroactively tried to justify by claiming "we keep your d…

This is nonsense. You don't need Apple user data to build a good AI model, plenty of startups building base models have shown that. But even if you did it's nonsense as Apple has long had opt-in for providing data to train their machine learning models, and many of those models, like OCR or voice recognition, are excellent.
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