271–280 of 674 posts
This is the sad state of Apple right now. It is ridiculous that they basically had unlimited access to TSMC and achieved nothing in AI. Management is a joke.
Google release hints at this being more than just Siri: > Apple and Google have entered into a multi-year collaboration under which the next generation of Apple Foundation Models will be based on Google's Gemini models and cloud technology. These models will help power future Apple Intelligence features, including a more personalized Siri coming this year. ... https://blog.google/company-news/inside-google/company-an…
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It's pretty clear they tried their best to miss or reinterpret the points I made so they could talk about something else.
I'm sorry for whatever cynicism leads you to believe this. I don't believe there is an "astroturfer" problem with siri, and that is mostly what I was responding to. Sorry you missed that.
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…
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…
So I'm glad Apple is not trying to get too much into a bidding war. As for how well orgs are run, Meta has its issues as well (cf the fiasco with its eponymous product), while Google steadily seems to erode its core products.
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It's a very low baseline with Siri, so almost anything would be an improvement.
Ollama! Why didn’t they just run Ollama and a public model! They’ve kept the last 10 years with a Siri who doesn’t know any contact named Chronometer only to require the best in class LLM?
I was in the map search, so I just said "Costco" and it said "I can't help with that right now, please try again later" or something of the sort. I tried a couple more times until I changed up to saying "Navigate me to Costco" where it finally did the search in the textbox and found it for me.
Obviously this isn't the same thing as Gemini but the experience with Android Auto becomes more and more garbage as time passes and I'm concerned that now we're going to have 2 google product voice assistants.
Also, tbh, Gemini was great a month ago but since then it's become total garbage. Maybe it passes benchmarks or whatever but interacting with it is awful. It takes more time to interact with than to just do stuff yourself at this point.
I tried Google Maps AI last night and, wow. The experience was about as garbage as you can imagine.
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 e…
A lot of the hype in LLM economics is driven by speculation that eventually training these LLMs is going to lead to AGI and the first to get there will reap huge benefits.
So if you believe that, being "first to market" is a pretty big deal.
But in the real world there's no reason to believe LLMs lead to AGI, and given the fairly lock-step nature of the competition, there's also not really a reason to believe that even if LLMs did somehow lead to AGI that the same result wouldn't be achieved by everyone currently building "State of the Art" models at roughly the same time (like within days/months of each other).
So... yeah, what Apple is doing is actually pretty smart, and I'm not particularly an Apple fan.
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> 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 fie…
This is the key. The real issue is that you don’t need superhuman intelligence in a phone AI assistant. You don’t need it most of the time in fact. Current SOTA models do a decent job of approximating college grad level human intelligence let’s say 85% of the time which is helpful and cool but clearly could be better. But the pace at which the models are getting smart is accelerating AND they are getting more energy…
OpenAI had it , they had the foot in the door with their integration last year with Siri. But they dropped that ball and many other balls.
Apple has seemingly confirmed that the Gemini models will run under their Private Cloud Compute and so presumably Google would not have access to Siri data. https://daringfireball.net/linked/2026/01/12/apple-google-fo...
Neither Apple's nor Google's announcement says Siri will use Gemini models. Both announcements say, word for word, "Google’s technology provides the most capable foundation for Apple Foundation Models". I don't know what that means, but Apple and Google's marketing teams must have crafted that awkward wording carefully to satisfy some contractual nuance.
"Apple Intelligence will continue to run on Apple devices and Private Cloud Compute, while maintaining Apple's industry-leading privacy standards."