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Transformer architecture optimized for Apple Silicon

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Re: Transformer architecture optimized for Apple Silicon

#101
post #31

Earlier quoted context omitted.

I never said anything about openai not being relevant. the point is scale and good enough. gpt-4 is already good enough for most reasonable use cases, notably siri optimization. 5 years is a long time. 5 years ago llms didn't even exist.

Gpt3.5-turbo runs laps around siri and is cheap, surely Apple will acquire talent to build something that does remote queries and falls back to local for the next 1-2 years while they figure out on device accelerated LLMs

People keep saying this. But it’s only half the problem to process natural language in text form. How well would ChatGPT do at understanding Spanish from a non native speaker with a southern US accent? (Raises hand). I’ve yet to see a speech to text system that does well at understanding speech by non native speakers or even native English speakers with a heavy regional accent.

Re: Transformer architecture optimized for Apple Silicon

#102

i'd say within 5 years apple will have optimized apple silicon and their tech, along with language model improvements, such that you will be able to get gpt-4 level performance in the iPhone 19 with inference happening entirely locally. openai is doing great work and is serious competition, but I think many underestimate big tech. once they're properly motivated they'll catch up quick. I think we can agree that opena…

Live translation on AirPods, here we go!

Re: Transformer architecture optimized for Apple Silicon

#103

Earlier quoted context omitted.

I really think you have hit the nail on the head here. Apple has a ridiculous, almost unfathomably deep moat for training and running personalised, customised LLMs and other AI models on the 'edge' with these Apple Silicon chips in all their devices. We must be talking orders of magnitude differences in operational cost, not to mention completely unique features like privacy. The very definition of disruption, waitin…

Maybe, but Apple doesn’t have a search to rival Google (or even an assistant, given the state of Siri). Focusing on privacy and on-device learning is great, but when the strength of these models is in consuming all the data they can hoover up your motive is at odds with your philosophy.

They have every query their users enter into Spotlight. They have all the results it returns (who cares if they originated from Google, ok maybe they do, maybe not using it for anything is part of their deal with Google). They have your contacts, calendars, messages, email, music, workout history, tasks, real time location, which Siri already uses to e.g. recommend a destination when you get in your car to a degree of accuracy that straight spooks me sometimes.

Apple has access to SUBSTANTIALLY more fine-grained personalized data than Google does. Full stop. That's a weird thing to assert in the tech crowd, but think about it deeply and you'll realize its true.

Google has islands of services that they've done an extremely good job of building bridges between. They have some islands that Apple has nothing like (YouTube is the biggest one) (Search is a huge island, but only indefensible if the interfaces customers use to access it don't leak the queries and results; no one opens a browser and types "www.google.com" on mobile and even if they did, Apple controls the browser renderer, they could lift everything if they wanted to, they won't, I'm simply illustrating how much Apple should fuckin scare Google). But the waters between those islands are patrolled by Samsung, Xiaomi, Oppo, and Vivo, and there's sharks in there as well (uh, the metaphor is falling apart, the sharks are "Google's tumultuous history with privacy and user blowback if they overstep").

Apple is a continent. Many of their cities are ports that connect to some of Google's islands, but Google's product still has to be checked by customs.

You're right that even given that power, hoovering it up is at-odds with Apple's philosophy. Or, is it? I think "hoovering it unencrypted to the cloud" definitely is; but that's the point OP was making: if we're extremely close, as a species, to solving "make AI work", one of the challenges for the next five years is inevitably going to be "make it more personal". Its awesome that I can ask ChatGPT to write a date comparison function. It'll also be awesome if I could ask Siri "when did sarah and I talk about getting a cat" or something.

That requires personalized data to set the context. If Apple can swing at the fences and say "everything is on-device, nothing leaves, we can't see it, and now you can ask Siri that, and by the way there's new functionality built-in to iOS that apps can leverage to integrate with Siri's new LLM capabilities just like ChatGPT plugins"; that's an extremely compelling product. Extremely. And I know they would ingest that data, that they would do that, because they already do! Go ask Siri to call Sarah, or if you have any meetings tomorrow (assuming you're using Apple Calendar), and it will respond. I don't know where you're getting this take that they don't "hoover data"; they ingest everything from all their first party apps into Siri's `DATA MATRIX`. Its just, you know, 2010s era querying and data crunching.

Don't get me wrong, Google's gonna do a lot of this too. But Google is playing from the position of "we have a model, we have the data, we just need to pay hundreds of millions of dollars a year maintaining all these servers". Apple is playing from the position "our customers are paying us for the silicon to run this, we have the data, we just have to figure out the model". If its not obvious at this point: the models/algorithms/etc are not a moat. They're going to be commoditized with time. Publicly accessible data isn't a moat. Personal data is a moat, because people care about privacy. And cost effective training and inference silicon is a moat, because its Physical, and like literally One Company on the planet makes it, and they're in a big time situationship with Tim Cook.

Re: Transformer architecture optimized for Apple Silicon

#104
In regards to LLMs there is a collision between Apple's extremely good chip design capabilities and Apple's insistence that Siri never says anything that isn't 100% scripted and 100% certain to not bad. Up until now, they've chosen to limit Siri functionality rather than leave anything to chance.

LLMs will absolutely be able to run locally, but whether Apple will be able to stop worrying and love the model remains to be seen.

Re: Transformer architecture optimized for Apple Silicon

#105

i'd say within 5 years apple will have optimized apple silicon and their tech, along with language model improvements, such that you will be able to get gpt-4 level performance in the iPhone 19 with inference happening entirely locally. openai is doing great work and is serious competition, but I think many underestimate big tech. once they're properly motivated they'll catch up quick. I think we can agree that opena…

Agreed. Apple is fantastic at waiting for the moment technology to be mature enough to be useful to everyday people and jumping on it. They have a fantastic CPU department that no one else can match, and certainly must have a skunkworks AI team. They’ll let everyone else make the mistakes, learn from them, and release a great product.

Re: Transformer architecture optimized for Apple Silicon

#106
post #39

Earlier quoted context omitted.

Isn't GPT so complex that it requires hundreds of GB of ram to be used? How's it going to run on iphone?

yes, there are billions of parameters necessary. but large language models only came out about 5 years ago. I'm confident 5 years from now the parameters necessary to get gpt-4 performance will be decreased orders of magnitude. at the very least, even if that's not the case, inference will be drastically less gpu heavy by then I suspect.

I could also imagine a sort of two-tier approach, where the on-device model can handle the majority of queries, but recognize when it should pass the query on to a larger model running in the cloud.

Re: Transformer architecture optimized for Apple Silicon

#107

Earlier quoted context omitted.

I really think you have hit the nail on the head here. Apple has a ridiculous, almost unfathomably deep moat for training and running personalised, customised LLMs and other AI models on the 'edge' with these Apple Silicon chips in all their devices. We must be talking orders of magnitude differences in operational cost, not to mention completely unique features like privacy. The very definition of disruption, waitin…

> Apple has a ridiculous, almost unfathomably deep moat for training and running personalised, customised LLMs and other AI models on the 'edge' with these Apple Silicon chips in all their devices. Do they? I can completely fathom, given my own anecdotal experiences, how garbage Siri quality is today. I haven't built anything against Siri APIs, but I've used Siri and various integrations and every single time I give…

Same experience.

Alexa is DIMENSIONS better than Siri. Siri can create a timer ... okay even an alarm. That’s it. It is comically bad. Their text to speech is excellent, but the rest is unbelievable bad.

If Apple has some kind of silver bullet, it’s time to put it out or be left behind.

Re: Transformer architecture optimized for Apple Silicon

#108

i'd say within 5 years apple will have optimized apple silicon and their tech, along with language model improvements, such that you will be able to get gpt-4 level performance in the iPhone 19 with inference happening entirely locally. openai is doing great work and is serious competition, but I think many underestimate big tech. once they're properly motivated they'll catch up quick. I think we can agree that opena…

Yea, probably right after they released the hyped Apple Car. It's probably just month away now!

I'm convinced there are quite a few products for the 'Patagonia vest crowd'*

*I used to be one in a Sales and Trading role and fully believe a lot of rumors are to keep the finance analysts happy.

Re: Transformer architecture optimized for Apple Silicon

#109

i'd say within 5 years apple will have optimized apple silicon and their tech, along with language model improvements, such that you will be able to get gpt-4 level performance in the iPhone 19 with inference happening entirely locally. openai is doing great work and is serious competition, but I think many underestimate big tech. once they're properly motivated they'll catch up quick. I think we can agree that opena…

OpenAI is big tech. Also, Apple has nowhere near the AI/ML staff that the rest of the tech giants have.

Re: Transformer architecture optimized for Apple Silicon

#110
post #47

Earlier quoted context omitted.

yes, there are billions of parameters necessary. but large language models only came out about 5 years ago. I'm confident 5 years from now the parameters necessary to get gpt-4 performance will be decreased orders of magnitude. at the very least, even if that's not the case, inference will be drastically less gpu heavy by then I suspect.

Wait, so there's a way to make a model as smart as GPT but with less parameters? Isn't that why it's so good?

You can train a small model to behave like the large model at a subset of tasks.
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