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Apple picks Gemini to power Siri

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Re: Apple picks Gemini to power Siri

#161

Post by margalabargala »

JohnMakin wrote: post #136
quitit wrote: post #63

This is a bit of a layer cake: 1. The first issue is that there is significant momentum in calling Siri bad, so even if Apple released a higher quality version it will still be labelled bad. It can enhance the user's life and make their device easier to use, but the overall press will be cherrypicked examples where it did something silly. 2. Basing Siri on Google's Gemini can help to alleviate some of that bad press,…

Siri is objectively bad though. It isn't some vendetta. I am disabled and there are at least 50 different things that I'd love siri to do that should be dead simple , yet it cannot. My favorite one was when I suffered a small but not serious fall, decided to test whether siri could be alerted to call 9-11 while being less than 6 feet away from me, absolutely could not understand let alone execute my request. It's a l…

I don't think the parent said that Siri wasn't bad, on the contrary it sounds like they agree.

Their point is that if Apple totally scraps the current, bad, product called "Siri" and replaces it with an entirely different, much better product that is also named "Siri" but shares nothing but the name, people's perceptions of the current bad Siri will taint their impressions of the new one.

Re: Apple picks Gemini to power Siri

#162

Post by potamic »

MontyCarloHall wrote: post #35
eimrine wrote: 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…

That's a poor justification. There are companies that sell you all kinds of labelled data. OpenAI, Anthropic didn't train on their own user data.

Re: Apple picks Gemini to power Siri

#163

Post by lamontcg »

blitzar wrote: post #134
concinds wrote: post #97

Earlier quoted context omitted.

An Apple-developed LLM would likely be worse than SOTA, even if they dumped billions on compute. They'll never attract as much talent as the others, especially given how poorly their AI org was run (reportedly). The weird secrecy will be a turnoff. The culture is worse and more bureaucratic. The past decade has shown that Apple is unwilling to fix these things. So I'm glad Apple was forced to overcome their Not-Inven…

Apple might have gotten very lucky here ... the money might be in finding uses, and selling physical products rather than burning piles of cash training models that are SOTA for 5 minutes before being yet another model in a crowded field. My money is still on Apple and Google to be the winners from LLMs.

And when the cost of training LLMs starts to come down to under $1B/yr, Apple can jump on board, having saved >$100B in not trying to chase after everyone else to try to get there first.

Re: Apple picks Gemini to power Siri

#165

Post by its_ethan »

benoau wrote: post #152
its_ethan wrote: post #144

Earlier quoted context omitted.

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…

> 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? 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...

So if it mirrors something they were already accused of (like you're saying), my questioning should be pretty easy to map onto that issue as well?

It's the line of thinking that I'm trying to dig into more, not the specifics of this case. Now it feels like you're saying "this is anti-trust because someone accused them of anti-trust before".

If that case was prosecuted and Apple was found guilty, I suppose you can point to it as precedent. But again, does it only serve as precedent when it's a deal between Apple and Google? Is it only a precedent when there's a case between two "large" companies?

Again this is all really squishy, if companies aren't allowed to outsource development of another feature once they pass some sense of "large", when does it apply? What about the $1T pharmaceutical company that wants to use AI modeling? They're a large technically component company, if Eli Lily partnered with Gemini would you be sitting here saying that they also are abusing a monopolistic position that prevents competition in the AI model space?

Re: Apple picks Gemini to power Siri

#166

Post by hmokiguess »

Fiveplus wrote: post #42

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…

I always think about this, can someone with more knowledge than me help me understand the fragility of these operations?

It sounds like the value of these very time-consuming, resource-intensive, and large scale operations is entirely self-contained in the weights produced at the end, right?

Given that we have a lot of other players enabling this in other ways, like Open Sourcing weights (West vs East AI race), and even leaks, this play by Apple sounds really smart and the only opportunity window they are giving away here is "first to market" right?

Is it safe to assume that eventually the weights will be out in the open for everyone?

Re: Apple picks Gemini to power Siri

#167

Post by raw_anon_1111 »

ChildOfChaos wrote: post #137
Fiveplus wrote: post #42

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…

The trouble is this seems to me like a short term fix, longer term, once the models are much better, Google can just lock out apple and take everything for themselves and leave Apple nowhere and even further behind.

Of course there is going to be an abstraction layer - this is like Software Engineering 101.

Google really could care less about Android being good. It is a client for Google search and Google services - just like the iPhone is a client for Google search and apps.

Re: Apple picks Gemini to power Siri

#168

Post by insin »

johnthuss wrote: post #4
gnabgib wrote: post #2

Related: Apple nears $1B Google deal for custom Gemini model to power Siri (71 points, 2 months ago, 47 comments) https://news.ycombinator.com/item?id=45826975

The biggest NEW thing here is that this isn't white-labeled. Apple is officially acknowledging Google as the model that will be powering Siri. That explicit acknowledgment is a pretty big deal. It will make it harder for Apple to switch to its own models later on.

They can also put "Google" in the forever-necessary disclaimer

Google AI can make mistakes

Re: Apple picks Gemini to power Siri

#169

Post by hadlock »

Fiveplus wrote: post #42

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…

Seems like the LLM landscape is still evolving, and training your own model provides no technical benefit as you can simply buy/lease one, without the overhead of additional eng staffing/datacenter build-out.

I can see a future where LLM research stalls and stagnates, at which point the ROI on building/maintaining their own commodity LLM might become tolerable. Apple has had Siri as a product/feature and they've proven for the better part of a decade that voice assistants are not something they're willing to build a proficiency in. My wife still has an apple iPhone for at least a decade now, and I've heard her use Siri perhaps twice in that time.

Re: Apple picks Gemini to power Siri

#170

Post by hadlock »

CharlesW wrote: post #140
Fiveplus wrote: post #42

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…

> I'm oversimplifying but this effectively turns the iPhone into a dumb terminal for Google's brain, wrapped in Apple's privacy theater. Setting aside the obligatory HN dig at the end, LLMs are now commodities and the least important component of the intelligence system Apple is building. The hidden-in-plain-sight thing Apple is doing is exposing all app data as context and all app capabilities as skills . (See App I…

> what their actual 5-, 10-, and 20-year plans are

Seems like they are waiting for the "slope of enlightenment" on the gartner hype curve to flatten out. Given you can just lease or buy a SOTA model from leading vendors there's no advantage to training your own right now. My guess is that the LLM/AI landscape will look entirely different by 2030 and any 5 year plan won't be in the same zip code, let alone playing field. Leasing an LLM from Google with a support contract seems like a pretty smart short term play as things continue to evolve over the next 2-3 years.

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