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Apple's On-Device and Server Foundation Models
- Marciakhan 2y ago[dead]
- wslh 2y agoIs it me or Apple is really moving fast? I don't think it is easy for a company of this size to concisely put a vision of AI in these short and crazy AI times. BTW, not an Apple fan but an Apple user.
- majestik 2y agoChatGPT came out November 2022 and it took Apple 18 months to announce Siri will integrate with it. Is that moving fast? Maybe, compared to what, Oracle?
- wmf 2y agoPeople thought Apple was behind but they were just working quietly.
- MacsHeadroom 2y agoGoogle had similar AI functionality on Pixels last year and Microsoft had like six AI CoPilot products before that. So I would not say Apple is moving fast. Most people expected this update 6 months ago.
- doctor_eval 2y agoSince when does Apple make major software update announcements at Christmas?
- azinman2 2y agoTake a look at the yearly OS cadence. iOS 17 only came out a few months before your 6 month expectation.
- simianparrot 2y agoI just hope all of this can be toggled off, I don't want it on my devices.
- dmix 2y agoThey said repeatedly in the video anything going over the wire is optional and user controllable.
- simianparrot 2y agoI don't want local AI either. These "smart" features are all noise to me.
- GaggiX 2y agoIt would be cool to understand when the system will use one or the other (the ~3 billion on-device model or the bigger one on Apple servers).
- swatcoder 2y agoConceivably, they don't have precise answers for that yet, and won't until after they see what real-world usage looks like. They built out a system that's ready to scale to deliver features that may not work on available hardware, but they're also incentivized to minimize actual reliance on that cloud stuff as it incurs per-use costs that local runs don't.
- GaggiX 2y agoYeah this is probably right. If it works well enough during real-world usage it will be using the on-device model, if not then there is the bigger one on the servers. There is also GPT-4o, so they have 3 different models to use depending on the task.
- aixpert 2y agoif you have ever used a 3 billion or 7 billion parameter model you know that they are really bad at text generation, so this will be done in the cloud
- kmeisthax 2y ago> We train our foundation models on licensed data, including data selected to enhance specific features, as well as publicly available data collected by our web-crawler, AppleBot. Web publishers have the option to opt out of the use of their web content for Apple Intelligence training with a data usage control. And, of course, nobody has known to opt-out by blocking AppleBot-Extended until after the announcement where they've already pirated shittons of data. In completely unrelated news, I just trained a new OS development AI on every OS Apple has ever written. Don't worry. There's an opt-out, Apple just needed to know to put these magic words in their installer image years ago. I'm sure Apple legal will be OK with this.
- mdhb 2y agoSo built on stolen data essentially.
- ytdytvhxgydvhh 2y agoWhat’s the problem with that? Reproducing copyrighted works in full is problematic obviously. But if I learned English by watching American movies, I didn’t steal the language from the movie studios, I learned it.
- asadotzler 2y agoYou're not a machine capable of acquiring that "learning" with zero effort and selling that learning to infinite buyers.
- bigyikes 2y agoDoes that imply I just stole your comment by reading it? No snark intended; I’m seriously asking. If the answer is “no” then where do you draw the line?
- deleted 2y ago[deleted]
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- ddxv 2y agoWill these smaller on device models lead to a crash in GPU prices?
- htrp 2y agoX to doubt.
- sooheon 2y agoPrices fall when supply outpaces demand -- this is adding more demand.
- jondwillis 2y agoNot in the short-to-medium-term. Try the local models out, they fall over pretty quickly, even if you have 64GB+ of VRAM.
- wkat4242 2y agoIt depends what you use them for. If you ask it for knowledge, like a comparison of vacuum cleaner models then yes, it's a hallucination fest. They just don't have the parameters for this level of detail. This is where ChatGPT is really king. But if you give them the data they need with RAG, they're not bad. Acting on commands, looking stuff up in provided context, summarising all perform pretty well. Which seems to be also what Apple is targeting to do with them.
- htrp 2y ago> Our foundation models are fine-tuned for users’ everyday activities, and can dynamically specialize themselves on-the-fly for the task at hand. We utilize adapters, small neural network modules that can be plugged into various layers of the pre-trained model, to fine-tune our models for specific tasks. For our models we adapt the attention matrices, the attention projection matrix, and the fully connected layers in the point-wise feedforward networks for a suitable set of the decoding layers of the transformer architecture. >We represent the values of the adapter parameters using 16 bits, and for the ~3 billion parameter on-device model, the parameters for a rank 16 adapter typically require 10s of megabytes. The adapter models can be dynamically loaded, temporarily cached in memory, and swapped — giving our foundation model the ability to specialize itself on the fly for the task at hand while efficiently managing memory and guaranteeing the operating system's responsiveness. This kind of sounds like Loras......
- karmasimida 2y agoI think it is just LoRA, you can call the LoRA weights as adapters
- cube2222 2y agoThe article explicitly states they’re Loras.
- alephxyz 2y agoThe A in LoRA stands for adapters
- GaggiX 2y agoLoRA stands for "Low Rank Adaptation" btw.
- advael 2y agoI'm disappointed that they make the fundamental claim that their cloud service is private with respect to user inputs passed through it and don't even a little bit talk about how that's accomplished. Even just an explanation of what guarantees they make and how would be much more interesting than explanations of their flavor of RLHF or whatever nonsense. I read the GAZELLE* paper when it came out and wondered what it would look like if a large-scale organization tried to deploy something like it. Of course, Apple will never give adequate details about security mechanisms or privacy guarantees. They are in the business of selling you security as something that must be handled by them and them alone, and that knowing how they do it would somehow be less secure (This is the opposite of how it actually works, but also Apple loves doublespeak, and 1984 allusions have been their brand since at least 1984). I view that, like any claim by a tech company that they are keeping your data secure in any context, as security theater. Vague promises are no promises at all. Put up or shut up. * https://arxiv.org/pdf/1801.05507 https://arxiv.org/pdf/1801.05507
- killingtime74 2y agoDon't they do it in this linked article? https://security.apple.com/blog/private-cloud-compute/ https://security.apple.com/blog/private-cloud-compute/
- advael 2y agoWoa, good catch! Maybe they're doing better about at least being concrete about it, though I still have to side-eye "Users control their devices" (Even with root on macbooks I don't have access to everything running on it). However, the section that promises to open-source the cloud software are impressive and if true gives them more credibility than I assumed. I would still look out for places where devices they do control could pass them keys in still-proprietary parts of the stack they're operating, as even if we can verify the cloud container OS in its entirety if there's a backchannel for keys that a hypervisor could use then that's still a backdoor, but they are at least seemingly making a real effort here
- threeseed 2y ago
- epipolar 2y agoIt would be interesting to see how these models impact battery life. I’ve tried a few local LLMs on my iPhone 15 Pro via the PrivateLLM app, and the battery charge plummets just after a few minutes of usage.
- urbandw311er 2y agoLikely they’ll be able to take advantage of the hardware neural engine and be far more power efficient. Apple has demonstrated this is something it takes pretty seriously.
- brcmthrowaway 2y agoSo iOS LLM Apps dont use the neural engine? Lol
- deleted 2y ago[deleted]
- renewiltord 2y agoProbably not. The CoreML LLM stuff only works on Macs AFAIK. Probably the phone app uses the GPU.
- hmottestad 2y agoIf they use Llama.cpp they probably run on the GPU. Apple hasn’t published much about their neural engine, so you kinda have to use it through CoreML. I assume they have some aces up their sleeves for running LLMs efficiently that haven’t told anyone yet.
- woadwarrior01 2y agoNone of the current iOS and macOS LLM Apps use the Neural Engine. They use the CPU and the GPU. nb: I'm the author of a fairly popular app in that category.
- jjtheblunt 2y ago
- cube2222 2y agoHalfway down the article contains some great charts with comparisons to other relevant models, like Mistral-7B for the on-device models, and both gpt-3.5 and 4 for the server-side models. They include data about the ratio of which outputs human graders preferred (for server side it’s better than 3.5, worse than 4). BUT, the interesting chart to me is „Human Evaluation of Output Harmfulness” which is much, much ”better„ than the other models. Both on-device and server-side. I wonder if that’s part of wanting to have gpt as the „level 3”. Making their own models much more cautious, and using OpenAI’s models in a way that makes it clear „it was ChatGPT that said this, not us”. Instruction following accuracy seems to be really good as well.
- crooked-v 2y agoI want to know what they consider "harmful". Is it going to refuse to operate for sex workers, murder mystery writers, or people who use knives?
- its_ethan 2y agoThe caption for the image gives a little more insight into "harmful" and one of the things it mentions is factuality - which is interesting, but doesn't reveal a whole lot unless they were to break it out by "type of harmful".
- hotdogscout 2y agoI bet it's the usual double standards the AI one percenters cater to. No sex because apparently it's harmful yet never explained why. No homophobia/transphobia if you're Christian but if you're Muslim it's fine.
- arthur_sav 2y agoThey'll inject whatever ideology / dogma is "the current thing" into this.
- HeatrayEnjoyer 2y ago[flagged]
- TheRoque 2y agoWhy isn't there a comparison with the Llama3 8b in the "benchmarks" ?
- hmottestad 2y agoMaybe it’s too new for them to have had time to include it in their studies?
- TheRoque 2y agoPhi-3-Mini, which is in the benchmarks, was released after Llama3 8b
- hmottestad 2y agoLlama 3 8B is really really good. Maybe it makes Apples models look bad? Or it could be a licensing thing where Apple can’t use Llama 3 at all, even just for benchmarking and comparison. The license for the Llama models was basically designed to stop Apple, Microsoft and Google from using it.
- teonimesic2 2y agoI believe it is because llama 3 8B beats it, which would make it look bad. The phi-3-mini version they used is the 4k which is 3.8B, while LLama 3 8B would be more comparable to phi-3 small (7B) which also considerably better than phi-3-mini. Likely both phi-3 small and llama 3 8B had too good results in comparison to Apple's to be added, since they did add other 7B models for comparison, but only when they won.
- mixtureoftakes 2y agollama 3 definitely beats it, but 99% of the users wont care which is actually a good thing... apple totally wins the ai market not by being sota but by sheer amount of devices which will be running their models, we're talking billions
- ra7 2y ago> Our foundation models are trained on Apple's AXLearn framework, an open-source project we released in 2023. It builds on top of JAX and XLA, and allows us to train the models with high efficiency and scalability on various training hardware and cloud platforms, including TPUs and both cloud and on-premise GPUs. Interesting that they’re using TPUs for training, in addition to GPUs. Is it both a technical decision (JAX and XLA) and a hedge against Nvidia?
- m-s-y 2y agoThey’d be silly not to hedge. Anyone, in fact, would be silly. It to hedge. On pretty much everything.
- anvuong 2y agoJax was built with TPUs in mind, so it's not surprising that they use TPUs
- gokuldas011011 2y ago"Use the best tool available"
- flakiness 2y agoThey hired people nearby. Conveniently there is a small town called Mountain View.
- Isuckatcode 2y ago>By fine-tuning only the adapter layers, the original parameters of the base pre-trained model remain unchanged, preserving the general knowledge of the model while tailoring the adapter layers to support specific tasks. From a ML noob (me) understanding of this, does this mean that the final matrix is regularly fine tuned instead of fine tuning the main model ? Is this similar to how chatGPT now remembers memory[1] ? [1] https://help.openai.com/en/articles/8590148-memory-faq https://help.openai.com/en/articles/8590148-memory-faq
- MacsHeadroom 2y agoChatGPT memory is just a database with everything you told it to remember. Low Rank Adaptors (LoRA) are a way of changing the function of a model by only having to load a delta for a tiny percentage of the weights rather than all the weights for an entirely new model. No fine-tuning is going to happen on Apple computers or phones at any point. They are just swapping out Apple's pre-made LoRAs so that they can store one LLM and dozens of LoRAs in a fraction of the space it would take to store dozens of LLMs.
- ww520 2y agoThe base model is frozen. The smaller adaptor matrices which are finetuned with new data. During inference, the weights from the adaptor matrices "shadow" the weights in the base model. Since the adaptor matrices are much smaller, it's quite efficient to finetune them. The advantage of the adaptor matrices is you can have different sets of adaptor matrices for different tasks, all based of the base model.
- scosman 2y ago“We utilize adapters, small neural network modules that can be plugged into various layers of the pre-trained model, to fine-tune our models for specific tasks.” This is huuuuge. I don’t see announcement of 3rd party training support yet, but I imagine/hope it’s planned. One of the hard things about local+private ML is I don’t want every app I download to need GBs of weights, and don’t want a delay when I open a new app and all the memory swap happens. As an app developer I want the best model that runs on each HW model, not one lowest common denominator model for slowest HW I support. Apple has the chance to make this smooth: great models tuned to each chip, adapters for each use case, new use cases only have a few MB of weights (for a set of current base models), and base models can get better over time (new HW and improved models). Basically app thinning for models. Even if the base models aren’t SOTA to start, the developer experience is great and they can iterate. Server side is so much easier, but look forward to local+private taking over for a lot of use cases.
- dimtion 2y agoWith huge blobs of binary model weights, dynamic linking is cool again.
- inickt 2y agoWhich Apple has put some pretty large effort in the last few years to improve in iOS
- pjmlp 2y agoDynamic linking has always been cool for writing plugins. It is kind of ironic that languages that praise so much for going back to early linking models, have to resort for much heavier OS IPC for similar capabilities.
- rfoo 2y agoWhich languages? IIUC Go and Rust resort to OS IPC based plugin system mainly because they refused to have a stable ABI. On the other hand, at $DAYJOB we have a query engine written in C++ (which itself uses mostly static linking [1]) loading mostly static linked UDFs and ... it works. [1] Without glibc, but with libstdc++ / libgcc etc.
- buildbot 2y ago3.5B per weight with no quality loss is state of the art - that's an awesome optimization result (a mix of 2b and 4b weights).
- Hugsun 2y agoI would like to see their method compared quantitatively to the best llama.cpp methods. IQ3_S has a similar bpw and pretty high quality. I wonder if they didn't stretch the truth using the phrase "without loss in accuracy".
- vzaliva 2y agoI love that they use machinelearning.apple.com not ai.apple.com
- deleted 2y ago[deleted]
- andbberger 2y agoglad someone sane is in charge in cupertino
- xwolfi 2y agoYeah they probably were still working on the last buzzword
- tmpz22 2y agoFor the majority of the keynote they explicitly avoided the word AI instead substituting the word Intelligence, then Apple Intelligence, and then towards the end they said AI and ChatGPT once or twice. I think they saw the response to all the AI shoveling and Microsoft Recall and executed a fantastic strategy to reposition themselves in industry discussions. I still have tons of reservations about privacy and what this will all look like in a few years, but you really have to take your hat off to them. WWDC has been awesome and it makes me excited to develop for their platform in a way I haven't felt in a very, very, long time.
- worstspotgain 2y ago> executed a fantastic strategy to reposition themselves in industry discussions Just the usual marketing angle, IMO. It's not TV, it's HBO. No one is reluctant to use the word smartphone to include iPhones. I don't think anyone is going to use the Apple Intelligence moniker except in the same cases where they'd say iCloud instead of cloud services. It's also a little clunky. Maybe they could have gone with... xI? Too close to the Chinese Xi. iAI? Sounds like the Spanish "ay ay ay." Not an easy one I think. The number of person-hours spent on this must have been something.
- ndgold 2y agoAbsolutely awesome amount of content in these two pages. This was not expected. It is appreciated. I can’t wait to use the server model on a Mac to spin up my own cloud optimized for the Apple stack.
- solarkraft 2y agoWhat makes you think you'll get that model? Edit: I see they're committing to publishing the OS images running on their inference servers (https://security.apple.com/blog/private-cloud-compute/ https://security.apple.com/blog/private-cloud-compute/). Would be cool if that allowed people to run their own.
- msephton 2y agoApparently they will in a VM but it seems perhaps only security researchers?
- rekoil 2y ago> Would be cool if that allowed people to run their own. Oh my god that would be absolutely amazing!
- whazor 2y agoIt would be much cooler if enterprises can swap to their custom models in their own clouds.
- titaniumtown 2y agoDid it mentioned being able to spin up the server model locally? I must've missed that part in the article.
- theshrike79 2y agoThey didn't but I'll bet it's coming in the next 5 years. Most likely integrated with an Apple TV or a similar thing. Enough local LLM processing power to handle a family's data all in-house.
- ksec 2y agoI hope, this could mean Apple will push the baseline of ALL Macs to have higher than 8GB of Memory. While I wish we all get 16GB M4 as baseline. Apple being Apple may only give us 12GB, and charges extra $100 for the 16GB option. It will still be a lot better than 8GB though.
- talldayo 2y agoThe Steam Deck ships with 16 gigs of quad-channel LPDDR5 and it costs $400. Apple knows exaaaactly what they're doing with this sort of pricing. Can't forget about that cozy 256gb SSD either. An AI computer will need more than that, right?
- zer0zzz 2y agoIs steamdeck sold at cost? From what I know Apple has a rule that everything must be sold at 40% margins. That is prob the main reason.
- makeitdouble 2y ago> From what I know Apple has a rule that everything must be sold at 40% margins. As for all rules, it's a rule except when it's not. On the top of my head Apple TV [0] had a 20% predicted margin presumably because they wanted to actually sell them. Otherwise 40% margin is usually calculated against the BOM, which doesn't mean 40% of actual profit when the product is sold. In that respect we have no idea of the actual margin on a macbook air for instance, it could be 10% when including their operating costs and marketing, or it could 60% if they negociated prices way below the estimated BOM for instance. It's just to say: Apple sells at 8Gb because they want to, at the end of the day nothing is stopping them to play with their margin or the product price. [0] https://www.reuters.com/article/idUSN06424767/ https://www.reuters.com/article/idUSN06424767/
- talldayo 2y agoAs a consumer I really cannot be made to care why it's the case. This artificial price tiering is stupid and everyone has been calling it a scam for years. Apple clearly knows they're in the wrong, but continues because they know nobody can stop them.
- shreezus 2y agoThis is great, however Apple needs to be explicit on what it, and what isn't relayed to third party services, and provide the ability to opt-out if desired. It's one thing to run inference on-device, and another to send your data through OpenAI's APIs. The partnership details are not entirely clear to me as a user.
- frizlab 2y agoThey are? Did you watch the keynote? They talked about it at length.
- tsunamifury 2y ago[flagged]
- frizlab 2y agoThey told explicitly there are three things. On device AI for queries that can be done on device, private cloud compute for those that can’t and opt in ChatGPT(-4o) support for more general queries. Cloud compute queries only use the data for answering the queries and are run on an OS where storage is not available along other privacy measures. The builds of the OS will be public and auditable by security researchers. I think it’s plenty details for a non-tech keynote. The tech details are in the session and SotU.
- tsunamifury 2y ago[flagged]
- deleted 2y ago[deleted]
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- TillE 2y agoIt's literally the prompt you just gave it, that's what they're sending to ChatGPT, nothing else. None of the features that sift through your data are touching OpenAI.
- superkuh 2y agoThe "Human Evaluation of Output Harmfulness" section confirms what I've perceived: Mistral-7B is the best of the small models in terms of minimizing false positive refusals. With the refusal vector abliteration stuff this is less of an issue but a good base is still important.
- revscat 2y ago> With this set of optimizations, on iPhone 15 Pro we are able to reach time-to-first-token latency of about 0.6 millisecond per prompt token, and a generation rate of 30 tokens per second. Notably, this performance is attained before employing token speculation techniques, from which we see further enhancement on the token generation rate. This seems impressive. Is it, really? I don’t know enough about the subject to judge.
- bastawhiz 2y agoFor a phone running locally, that's pretty fast. The bigger question is how good the output is. Fast garbage isn't useful, so we'll have to wait to see what it actually ends up looking like outside of demos.
- rishabhjain1198 2y agoFor people interested in AI research, there's nothing new here. IMO they should do a better job of referencing existing papers and techniques. The way they wrote about "adaptors" can make it seem like it's something novel, but it's actually just re-iterating vanilla LoRA. It was enough to convince one of the top-voted HackerNews comments that this was a "huge development". Benchmarks are nice though.
- kfrzcode 2y ago"AI for the rest of us."
- wkat4242 2y agoExcept Apple isn't really for the rest of us. Outside of America and a handful wealthy western countries it's for the top 5-20% earners only.
- throwaway2037 2y agoJapan and Taiwan are both more than 50% iOS. Ref: https://worldpopulationreview.com/country-rankings/iphone-market-share-by-country https://worldpopulationreview.com/country-rankings/iphone-ma...
- jahewson 2y agoApproximately 33% of all smartphones in the world are iPhones.
- theshrike79 2y ago
- ofou 2y agoQuite interesting this was released right after multiple rants from Elon sparked debates on X. "If Apple integrates OpenAI at the OS level, then Apple devices will be banned at my companies. That is an unacceptable security violation." Replying to Tim Cook: "Don’t want it. Either stop this creepy spyware or all Apple devices will be banned from the premises of my companies." "It’s patently absurd that Apple isn’t smart enough to make their own AI, yet is somehow capable of ensuring that OpenAI will protect your security & privacy! Apple has no clue what’s actually going on once they hand your data over to OpenAI. They’re selling you down the river." https://x.com/elonmusk/status/1800269249912381773 https://x.com/elonmusk/status/1800269249912381773 https://x.com/elonmusk/status/1800266437677768765 https://x.com/elonmusk/status/1800266437677768765 https://x.com/elonmusk/status/1800265431078551973 https://x.com/elonmusk/status/1800265431078551973
- kanwisher 2y agoApple made their own AI models, only in certain cases it will ask if you want to send it to OpenAI. Presumably other ai companies later can integrate into API. But this is very privacy safe, if you use an iPhone already it already indexes all your photos and OCRs them for easy searching, on device ...
- hehdhdjehehegwv 2y agoThe WWDC show got on my nerves with the corpspeak, but this is pretty cool stuff. I’ve been trying to make smaller more efficient models in my own work. I hope Apple publish some actual papers.
- gepardi 2y agoYeah it was close to “infomercial” levels of cheesy.
- visarga 2y agoThey use synthetic data in pretraining and teacher models in RLHF, that means they use models trained on copyrighted data to make derivative models, is that sitting ok with copyright owners?
- deleted 2y ago[deleted]
- miven 2y ago> For on-device inference, we use low-bit palletization, a critical optimization technique that achieves the necessary memory, power, and performance requirements. Did they go over the entire text with a thesaurus? I've never seen "palletization" be used as a viable synonym for "quantization" before, and I've read quite a few papers on LLM quantization
- bagrow 2y agohttps://apple.github.io/coremltools/docs-guides/source/palettization-overview.html https://apple.github.io/coremltools/docs-guides/source/palet...
- miven 2y agoHuh, generally whenever I saw the lookup table approach in literature it was also referred to as quantization, guess they wanted to disambiguate the two methods Though I'm not sure how warranted it really is, in both cases it's still pretty much the same idea of reducing the precision, just with different implementations Edit: they even refer to it as LUT quantization on another page: https://apple.github.io/coremltools/docs-guides/source/quantization-neural-network.html https://apple.github.io/coremltools/docs-guides/source/quant...
- astrange 2y agoJust "quantization" is poor wording for that. Quantization means dropping the low bits. Sounds like it was confused with "vector quantization" which does involve lookup tables (codebooks). But "palletization" is fine too.
- elcritch 2y agoHuh, it’s PNG for AI weights.
- fudged71 2y ago404
- rvaish 2y agoEasel on iMessage has had this experience plus more for a while, including multiplayer, where you can have two people in one scene together with photorealistic imagery: https://apps.apple.com/us/app/easel-ai/id6448734086 https://apps.apple.com/us/app/easel-ai/id6448734086
- dingclancy 2y agoIt’s interesting that a sub-ChatGPT 3.5 class model can do a lot of things on-device if you marry it with a good platform and feed it personal context. GPT-4o, living on the browser, is not as compelling as a product compared to what Apple Intelligence can do on the iPhone with a less capable model.
- aixpert 2y agotheir 3 billion parameter model can't do shit, Only some basic grammar check style rewrite and maybe summarization
- pertymcpert 2y agoHave you tried it much?
- PHGamer 2y agoit would have been nice if they allowed you to build your own apple AI system (i refused to redefine apples AI as just AI :-p ) using clusters of mac minis and mac pros. but of course they still want that data for themselves like google does. its secure against everyone but apple and the NSA probably lol.
- IOT_Apprentice 2y agoWhat is stopping you from doing that? Nothing. Start cooking
- pudwallabee 2y ago[dead]
- Hugsun 2y agoThe benchmarks are very interesting. Unfortunately, the writing benchmarks seem to be poorly constructed. It looks like there are tasks no model can achieve and others that almost all models pass, i.e. every model gets around 9.0.
- orbital-decay 2y ago> 2. Represent our users: We build deeply personal products with the goal of representing users around the globe authentically. We work continuously to avoid perpetuating stereotypes and systemic biases across our AI tools and models. How do they represent users around the globe authentically while being located in Cupertino, CA? (more of a rhetorical question really)
- esskay 2y agoYou mean the person on the other side of the planet doesn't know about Philz Coffee down on Stevens Creek Blvd, or that there's a cool park a 2 minute walk away from Apple HQ?! It does baffle me how California centric they are with many of their announcements, and even some features.
- rekoil 2y agoThe Maps stuff always gets me. Yeah sure it looks pretty, but almost none of what makes it a usable product is available to me in Sweden.
- boxed 2y agoI wish I could have one keyboard on my iPhone and could type both Swedish and English with it. These are the basics they can't get right, and I don't see why. They clearly have bilingual people working over there, why is this so bad?
- cloogshicer 2y ago[flagged]
- blue_light_man 2y agoLanguage is mostly used for conditioning people into doing things. People will continue using language to manipulate you into giving your time or money to them. You cannot change others from trying to manipulate you. You can only change yourself and stop taking language seriously.
- dig1 2y agoReminds me on this [1] from George Carlin. [1] https://www.youtube.com/watch?v=isMm2vF4uFs https://www.youtube.com/watch?v=isMm2vF4uFs
- moray 2y agoThank you, I didn't know this bit. I always believed that great comedians are also the best communicators
- boxed 2y agoTo me censorship implies human speech being curtailed.
- internetter 2y agoI censor my poor APIs so they don’t leak the bcrypt key when you GET /user/:id
- madeofpalk 2y agoIt's censorship in the way that HN disallowing editorialising the submission title is censorship. Technically true, I guess, but not super helpful.
- lnenad 2y agoBut it is not safety if you forbid talking about sex, if you want to learn about certain things which could be missused. Same as banning murder in video games. Same as banning books that deal with these topics. It's definitely closer to censorship than safety.
- mFixman 2y agoHas anybody here improved their day-to-day workflow with any kind of "implicit" generative AI rather than explicitly talking to an LLM? So far all attempts seem to be building an universal Clippy. In my experience, all kinds of forced autocomplete and other suggestions have been worse than useless.
- mavamaarten 2y agoGitHub Copilot works well in my experience. It does bad suggestions at times, but also really spot-on ones. Other than that, AI for me is meme/image generation and a semi-useful chatbot.
- Blackstrat 2y agoI haven't seen anything indicating whether these features can be disabled. I'm not interested in adding a further invasion of privacy to my phone. I don't want some elaborate parlor trick helping me write. I've spent some time with ChatGPT and while it was somewhat novel, I wasn't overly impressed. Much of it was rudimentary and often wrong. And I wasn't overly impressed with some of the code that it generated. Reliance on such tools reminds me of an Asimov SF tale.
- hbn 2y agoI'd certainly expect you'd to be able to at the very least disable the stuff that does outgoing network requests. As for the stuff that's local to your device, how is your privacy being invaded? It's your device's OS looking at data on the device it's running on, as it's always done.
- anshumankmr 2y agoAs someone who has been dabbling with Prompt Engineering and now fine tuning some models (working on a use case where we may have to fine tune one of the Mistral's 7B instruct models), I want to know what kind of skillsets I need to really have so that I can join this team (or a similar team building these sort of things)
- BerthaDouglas34 2y ago[dead]
- koolala 2y agoaiPhone
- deldelaney 2y agoI need to resurrect by tiny old Motorola Flip Phone without internet connection. Maybe a phone should be just a phone. I don't need AI in my pants.
- dharma1 2y agodo they mention how big the models are? Last I saw was 3gb - I just bought a 8gb m4 iPad and keep thinking I should have gone for the 16gb one
- Jayakumark 2y agoThe model is not opensource. Also now we are stuck with walled garden for models thats deeply integrated at OS or Browser level. 1. Apple Models not open - so we cannot run Android, also not on Desktop Chrome or Edge. 2. Microsoft Phi3 - Can run inside iOS ,but on Android only as an APP but not on OS level or no supported APIs. Can run on Desktop Edge not chrome. 3. Google GEmini nano - Can only run inside Android and Desktop Chrome not Edge, not on iOS as weights are not open. So we cannot get a similar answer from LLM as its different models, you cannot across ecosystem.
- w10-1 2y agoI think we as tech people lost the forest for the trees. Apple (unwisely I think) is allowing UI's to just generate responses. The wow-neat! experience will wear off quickly. Then even as a miss rate of 0.1%, there will be thousands - millions - of cringe-worthy examples that sully the Apple brand for quality. It will be impossible to create quality filter good enough, and there will be no way to back these features out of the OS. For targeted use-cases (like coding and editing), this will be useful. But these features may be what finally makes contempt for Apple go mainstream, and that would be a shame. Internally at Apple, they likely discussed how much to limit the rollout and control usage. I think they decided to bake it into API's more to maintain developer mindshare than to keep users happy. The one feature that could flip that script is interacting with Siri/AI in order to get things done. The frustration with knowing what you want but not how or whether it can be done drives a lot of tech angst. If this only meant ordinary people could use their existing phones to their full extent, it would be a huge win.
- s3p 2y ago"that sully the Apple brand for quality." OK. No one remembers Apple Maps, the CSAM scanning, the crush ad, etc? Companies do embarrassing stuff all the time. At least they're trying.
- scottyah 2y agoI agree, they're joining in on the slippery slope auto-correct, home assistants, and Self Driving. I think it's been awhile since consumers have trusted or relied on consumer tech. Browsing the web from a phone can only be described as adversarial. Scrolling down a top google result recipe site is almost impossible. Texts don't always send and you can't keep up with all the cloud backup offerings that it's hard to tell if your photos are actually being saved. The current political and media scene is often described as post-truth, where accuracy isn't the biggest driving factor. It seems that computation is headed that way as well.