Looking at the very pretty marketing page over at Apple's I can honestly say: I've not a single use case for this. I'm sure there's someone who has, but I have to jump through several mental hoops to even imagine how any of this might be barely helpful in very rare edge cases for me.
OpenAI and Apple Announce Partnership
321–330 of 343 posts
Re: OpenAI and Apple Announce Partnership
#322Earlier quoted context omitted.
> LLMs are not accurate, they aren't subject matter experts that'll be maybe within 5% error margin. The Gell Mann amnesia effect suggests people will have a very hard time noticing the difference. Even if the models never improve, they're more accurate than a lot of newspaper reporting. > People will gradually learn and discover anf the cost of keeping a model updated and running won't drastically reduce so we'll mo…
> …they’re more accurate than a lot of newspaper reporting. Is that when they’re cribbing straight out of the newspaper pages, or is this just a cynical snipe at the poor state of media that, not for nothing, tech companies have had a fair hand in kneecapping?
The criticism of the performance of newspapers goes back well before Lovelace and Babbage:
"""I will add, that the man who never looks into a newspaper is better informed than he who reads them; inasmuch as he who knows nothing is nearer to truth than he whose mind is filled with falsehoods & errors. He who reads nothing will still learn the great facts, and the details are all false."""
- Thomas Jefferson (not Mark Twain), 1807, https://www.snopes.com/fact-check/mark-twain-read-newspaper-...
Re: OpenAI and Apple Announce Partnership
#323Earlier quoted context omitted.
Why does a mobile app needs to beat a highly trained professional every single time in order to be useful? Is this standard applied to any other app?
Because it's taxation. Financial well being is at stack. We're even looking at a potential jail time for tax fraud, tax evasion and what not. My app is powered by GTPChatChat, the model beating all artificially curated benchmarks. Still wanna buy?
This is one of those "perfect is the enemy of good" situations. Sure, for things where you have a legal responsibility to get things perfectly right using an LLM as the full solution is probably a bad idea (although lots of accountants are using them to speed up processes already, they just check outputs). That isn't the case for 99% of task though. Something that's mostly accurate is good. People are happy with that, and they will buy it.
Re: OpenAI and Apple Announce Partnership
#324Earlier quoted context omitted.
cuda is x86. the only way from 100% market share is down. …though it took two solid decades to even make a dent in x86.
CUDA is also ARM: https://developer.nvidia.com/cuda-downloads?target_os=Linux
nono - I don't mean cuda works on x86. I mean cuda is x86 - for gpgpu workloads - as in a defacto standard.
Re: OpenAI and Apple Announce Partnership
#325Earlier quoted context omitted.
LLMs are not accurate, they aren't subject matter experts that'll be maybe within 5% error margin. You're asserting that the AI features will be removed in 3 to 5 years because they're not accurate enough today , but you actually need them to remain inaccurate in 3 years time for your prediction to be correct. That seems unlikely. I agree that people will start to realize the cost, but the accuracy will improve, so p…
My experience suggests that LLMs become not less accurate, but less helpful. Two years ago they output a solution for my query [1] right away, now they try to engage user to implement that thing. This is across the board, as far as I can see. These LLMs are not about helping anyone, their goals are engagement and mining data for that engagement. [1] The query is "implement blocked clause decomposition in haskell." Th…
> These LLMs are not about helping anyone, their goals are engagement and mining data for that engagement.
Wow, this is a really interesting idea! A sneaky play for LLM providers is to be helpful enough to still be used, but also sufficiently unhelpful that your users give you additional training data.
Re: OpenAI and Apple Announce Partnership
#326Earlier quoted context omitted.
This partnership is structured so that no data is logged or sent to OpenAI.
The partnership is structured so that Apple can legally defend including language in their marketing that says things like "users’ IP addresses are obscured." These corporations have proven time and time again that we need to read these statements with the worst possible interpretation. For example, when they say "requests are not stored by OpenAI," I have to wonder how they define "requests," and whether a request n…
> The partnership is structured so that Apple can legally defend including language in their marketing that says things like "users’ IP addresses are obscured." These corporations have proven time and time again that we need to read these statements with the worst possible interpretation.
What's the worst possible interpretation of Apple and CloudFlare's iCloud Private Relay?
Re: OpenAI and Apple Announce Partnership
#327GPT4o access is a handy feature, but, what I was hoping to hear about is an improvement in Siri's language "understanding." In today's WWDC presentation, there were a few small examples of Siri improvements, such as an ability to maintain context, e.g., 'Add her flight arrival time to my calendar,' wherein Siri knows who "her" refers to. In my day-to-day experience with Siri, it's clear Siri doesn't have the kind of…
being "English only" also indicates that in order to have GPT level comprehension you need to use the real thing.
Re: OpenAI and Apple Announce Partnership
#328I was surprised how little they are leaning on OpenAI. Most of the impressive integrations that actually look useful are on-device or in their private cloud. OpenAIs ChatGPT was relegated to a corner of Siri for answering "google queries", if you grant it permission. This seems like an L for OpenAI, not being a bigger part of the architecture (and I'm glad).
Agreed. The rumors beforehand made it sound Apple and OpenAI would practically be merging. This felt like a fig leaf so Apple could say you can access SOTA models from you iPhone. But for me personally, the deep integration with the ecosystem + semantic index are way way more interesting.
unfortunately Apple's own model is GPT 3.5 class which is way less intelligent than GPT 4
Re: OpenAI and Apple Announce Partnership
#329IMO this really feels like the Facebook / Twitter integration from early iOS. That only lasted a few years. Apple clearly thinks it needs a dedicated LLM service atm. But still thinks it is only supplemental as they handle a bunch of the core stuff without it. And require explicit user consent to use OpenAI. And Apple clearly views it as a partial commodity since they even said they plan to add others. Tough to bet a…
Ditto. They'll use it now while they stand to benefit and in 3 years they'll be lambasting OpenAI publicly for not being private enough with data and pretend that they never had anything to do with them.
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Re: OpenAI and Apple Announce Partnership
#330Earlier quoted context omitted.
Not that it matters anyways, since Apple refuses to sign Nvidia GPU drivers for MacOS in the first place. So if they own any Nvidia hardware themselves, then they also own more third-party hardware to support it.
Maybe this is way too science fiction, but what are the chances Apple's GPU/AI engine designs on Apple Silicon were a testbed for full sized, dedicated GPU dies that could compete with Nvidia's power in their own data centers?
Very low? I guess anything is possible, but the M1 through M4 GPUs weren't really anything to write home about. It more closely resembles AMD's raster-focused GPU compute in my opinion, which is certainly not a bad thing for mobile hardware.
Nvidia's GPUs are complex. They have a lot of dedicated, multipurpose acceleration hardware inside of them, and then they use CUDA to tie all those pieces together. Apple's GPUs are kinda the opposite way; they're extremely simple and optimized for low-power raster compute. Which isn't bad at all, for mobile! It just gimps them design-wise when they go up against purpose-built accelerators.
If we see Apple do custom Apple Silicon for the datacenter, it will be a pretty radically new design. The first thing they need is good networking; a full-size Nvidia cluster will use Mellanox Infiniband to connect dozens of servers at Tb/s speeds. So Apple would need a similar connectivity solution, at least to compete. The GPU would need to be bigger and probably higher-wattage, and the CPU should really emphasize core count over single-threaded performance. If they play their cards right there, they would have an Apple Silicon competitor to the Grace superchip and GB200 GPU.