7 ms·

A look at Apple's technical approach to AI including core model performance etc.

196 points by xrayarx 2y ago

seydor 2y ago
a little cope for the fact that apple failed to present state of the art performance
- Closi 2y ago
  Apple seems to be betting that something polished which is “less than state of the art” will sell better than something less polished and more advanced. Technical capability is rarely more important than product market fit.
  - sigmoid10 2y ago
    The problem here is that for current AI systems, the state of the art is the one that has ironed out the most kinks. I.e. what you would expect from a polished product. That is basically ChatGPT with it's monstrous API that does tons of god knows what behind the scenes in addition to feeding text to an LLM, most of which was figured out by trial and error from user reports. There's no doubt that a modern LLM based Siri would be a much better product than the old one, but if they're not careful, they will fall into the same trap they did the last time introducing an assistant.
    - tomashubelbauer 2y ago
      Privacy is a part of the equation and while Apple could gather all the context off my phone's local data and give ChatGPT the whole thing to really give it the best shot and providing a useful and helpful answer, this would not be a polished product on all axes, mainly the responsiveness and privacy ones. The tradeoff of using local models for less than SoTA inferrence but with unbeatable privacy and latency seems right to me for Apple and what Apple customers want and expect.
    - Closi 2y ago
      I think this is still a tech-centric view rather than a product-oriented view. E.g. Apple generating emojis using a diffusion model is clearly less SOTA than other image models, but could be a really neat feature from a product/user perspective. Would a better diffusion model help? Maybe, but it probably changes the product less than all the UI and tight integration work they will have done. If I was to guess, I would guess many more emoji's will get created through this feature than images generated in Microsoft's 'Image Creator' in Paint (I could be wrong - just my gut feel).
      - viraptor 2y ago
        WhatsApp has integrated AI generated stickers almost a year ago. (https://www.theverge.com/2023/8/15/23832635/whatsapp-ai-generated-stickers-test-android-beta https://www.theverge.com/2023/8/15/23832635/whatsapp-ai-gene...) I'm not sure how much they're used globally, but there are people crazy about stickers and the quality of what I got was really decent already. There were already external apps available for this purpose for a while, so yeah, the interest is there.
        fennecbutt 2y ago
        Microsoft SwiftKey has also been doing this for quite a while (not quite that long) as well.
    - HarHarVeryFunny 2y ago
      The best AI experience right now isn't just using SOTA models, but using them in a way that plays to their strengths and avoids their weaknesses (hallucination, limited reasoning, etc). The way to minimize hallucination is to use LLMs to manipulate text (translate, summarize, query, reword, etc) rather than generate it out of thin air, and arguably Apple are doing this by integrating LLM use into the product and therefore controlling it's application, rather than just providing a chat interface that people are wont to use an hallucinating "search engine"/oracle.
  - andruby 2y ago
    Indeed. And that has always been Apple’s forte.
    - pjmlp 2y ago
      Not always, specially when Steve Jobs was away.
    - tomalbrc 2y ago
      Except for the dozens of products that were neither polished nor state of the art (maps, Siri, iOS 6/7, most of their Mac related software, etc)
- Hippocrates 2y ago
  Why does SOTA matter here? OpenAI has actually failed already to make something useful and mass-market. After all these years of pushing SOTA, it's still a website with a text box. Siri in its current form is more useful to me than ChatGPT 4. You simply don't need SOTA models for a lot of valuable features; you need context, annotation APIs, and the right platform and integrations to assist users where they already are (on their phones, in cars, in their IDE, etc). MSFT's GitHub copilot is a good example of getting it right. Apple relegated ChatGPT to a 3rd tier AI capability for "google answers", and "write me a poem" party tricks, and rightfully put it behind a privacy disclaimer. It looks barely better than the various ChatGPT shortcuts so many people have cobbled together. That part of the announcement stuck out like a sore thumb and looked to me like a huge L for OpenAI. The "partnership" was a nothingburger. Like someone at Apple agreed to it early on but then late in the project realized it wasn't needed at all. So much for SOTA.
  - nicce 2y ago
    > Why does SOTA matter here? OpenAI has actually failed already to make something useful and mass-market. It is mainly B2B market in reality. Look for the API capabilities: https://platform.openai.com/docs/introduction https://platform.openai.com/docs/introduction
  - infecto 2y ago
    I mostly agree with you. OpenAI is reportedly still doing great in terms of revenue, but Apple's implementation is magical if it performs as shown in the keynote. In my opinion, it's the best implementation of LLM/AI in a consumer device. It's amusing to think back to all the buzz around Humane's AI pin.
    - Hippocrates 2y ago
      > It's amusing to think back to all the buzz around Humane's AI pin It certainly is. And the Rabbit R1. How in the world did people who supposedly know anything about AI think they could make that work as a standalone device detached from rich context. The sad thing is, rich context may not be possible outside of OS-level integration that is gate kept, but I still think they're idiots for trying.
- threeseed 2y ago
  It is best in class for a model that runs primarily on a mobile device.
throwaway4good 2y ago
The NVDIA stock has had a huge AI-related run over the past year while Apple has barely moved. This basically says that only a tiny bit of the AI will done on NVDIA hardware for the billions of Apple users. The market is not pricing that in.
- shdh 2y ago
  That's assuming Apple isn't training their models on Nvidia hardware. Inference is on Apples own silicon though.
  - mupuff1234 2y ago
    Looks liked they used Google TPUs https://www.reuters.com/technology/artificial-intelligence/how-apple-used-googles-help-train-its-ai-models-2024-06-11/ https://www.reuters.com/technology/artificial-intelligence/h...
- andruby 2y ago
  My opinion is that the market is treating Nvidia as the shovel sellers during a gold rush. If almost every business that wants to do AI needs to buy Nvidia hardware, their sales will go through the roof. That’s what the market is pricing into the Nvidia stock. It is very unlikely that Apple will sell their “server” hardware to other businesses in that way. Their advantage is the vertical integration, for themselves. While I am bullish on AAPL, I don’t expect it to have a run like Nvidia.
  - zarzavat 2y ago
    NVIDIA are not selling shovels, they are selling shovel-making machines to the shovel-sellers (the companies making foundation models). When the market is saturated with shovel-making machines, what then?
    - esmy 2y ago
      The last time I remember this happening, the shovel-making machines lost a lot of value and got amortised out to the second hand market. When the prevailing coin still mined on GPUs switched algorithms the bottom of GPU prices fell out on eBay. I expect at some point a) the training and the inference will move to even more specialised hardware and the current existing silicon go to either hobbyists or some other market that requires the current cards b) the way in which we do AI may fundamentally change in ways we can't predict, causing the required hardware to also change (move to FPGA or favouring some other aspect than VRAM) In both scenarios NVIDIA isn't the one who win, because the sudden influx lifts a secondary market nv don't profit from directly. I personally don't think they'll be able to sustain their current valuation past the current AI rush, and will compact back down to somewhere their levels pre-chatgpt. That said I'm just a guy on the Internet who wouldn't mind some beefy ex-datacentre gear if I could make it work for video editing workloads.
FL33TW00D 2y ago
I described this system word for word 2 years ago, glad to see it come to fruition on the only software stack integrated enough to do it. https://fleetwood.dev/posts/a-case-for-client-side-machine-learning https://fleetwood.dev/posts/a-case-for-client-side-machine-l...
- jimmySixDOF 2y ago
  If you described Speculative Decoding, 3bit Quantization, and Adapter based weight selection all two years ago then your AI Lab must be so sota /s
  - reqo 2y ago
    I am curious, what do you mean by "Adapter based weight selection"?
    - supriyo-biswas 2y ago
      That's apparently Apple's term for LoRA[1]. [1] https://arxiv.org/abs/2106.09685 https://arxiv.org/abs/2106.09685
      - jimmySixDOF 2y ago
        Sort of but Adapters allow for multiple weight adjustments (think loras) for specific skills so it is more like extra optimized mixture of experts or multi agent approach. They have a slide with adapters listed like summarization, prioritization, tone (happy, business, etc), editor, etc) -- this is not to be mixed up with Intents which is how on device apps publish their capabilities to the Intelligence system for real npu os level multi agent tool use.
- aitooltime 2y ago
  Thanks for posting the article. Some predictions in the article: 1. Partial client side execution of the models, then main model execution in cloud. (Example: text encoder for Stable Diffusion runs local, UNet runs cloud) 2. Local LoRAs for “dynamic ML” 3. WebGPU will be new standard to unlock models in the web Even though the article had some good calculations and overview, I am not sure word-for-word is how I would describe its relationship to the OP.
oldpersonintx 2y ago
[dead]
SebFender 2y ago
"Apple has demonstrated how meaningful AI interactions can be built into every corner of our digital life" Well not really. I haven't seen anything new here, unless you consider genmoji a killer app... The whole thing comes down to - your request may get sent to ChatGPT for advanced features. Better doesn't mean new.
- jb1991 2y ago
  If you didn’t see anything new in the announcement at all, maybe you didn’t actually see all the proposed features they are advertising? I’ve never seen a lot of stuff contained in one personal device or computer before. A single assistant that has access to finding connections throughout your life, emails, photos, etc.?
  - SebFender 2y ago
    Yes I did - but in 30 years attending and watching these I've learned a lot. As for Siri - been waiting for a decade for it to do something really useful - Let's hope this time it does.
- barkerja 2y ago
  > The whole thing comes down to - your request may get sent to ChatGPT for advanced features. If that was your takeaway from the keynote/SOTU, then I would suggest you go back and watch it again. That's not even remotely close to being accurate.
  - SebFender 2y ago
    Good suggestion - I would recommend the same back.
- shepherdjerred 2y ago
  Did you watch the WWDC keynote? There are a lot of legitimately exciting features. There's a level of integration with AI and your OS/apps that is (as far as I know) unprecedented. One thing I really want is for Siri to be able to control my house with Home Assistant with natural language, e.g. "turn off all of the lights outside except for the balcony". The updates to Siri seem like it _could_ make this possible. I would _love_ to be proven wrong, so please do show me alternatives.
mk_stjames 2y ago
I think there is a mistake in the line: >This looks like 2 years after the release of GPT-4, Apple has approximately trained an original GPT-4 level model. GPT-4 was released just 15 months ago, on March 14, 2023. Two years ago we were just getting GPT-3.5.
- dmd 2y ago
  ⠀
  - rq1 2y ago
    So you mean one year ago?
- why_only_15 2y ago
  It's not two years after release, but it is two years after it was trained
  - bastawhiz 2y ago
    But that's not what they said, and Apple surely didn't train their model on the morning of the announcement
- natolambert 2y ago
  thx, you're right. I've fixed it!
cubefox 2y ago
This article really reads like it was written by an Apple fan rather than an objective observer.
- resource_waste 2y ago
  I wonder when the illusion is going to come crumbling down. As long as there are teenagers that are susceptible to peer pressure and don't know marketing tricks, I think it could last forever. Look how many other Veblen good companies have existed for hundreds of years. With Apple's cash and media, they can have rappers and celebs always using/mentioning their stuff.
  - acdha 2y ago
    > As long as there are teenagers that are susceptible to peer pressure and don't know marketing tricks, I think it could last forever. Consider also that you might have made a mistake in your analysis and there are factors involved other than celebrity endorsements – for example, wouldn’t it be interesting to know why Nokia, Google, Samsung, Sony, LG, etc. weren’t more successful thanks to their own endorsements? Your own peer pressure might be hindering your understanding of the market.
  - shepherdjerred 2y ago
    Which illusion?
    - theshackleford 2y ago
      The one they have invented for themselves.
cma 2y ago
All of Apple's investment in AI edge capability is almost totally undermined by their huge price discrimination on RAM, shipping 8GB laptops in 2024 and charging like $300-500 for 8GB more.
- talldayo 2y ago
  I don't know why you're being downvoted. Unless Apple users want to swap a multi-gig 3B model onto their 256gb SSD and chew through it's lifetime TBW, we should be campaigning for enough RAM to do normal stuff. Our SSDs deserve a break.
  - fennecbutt 2y ago
    Yup, idk why but Apple fans act weird, like brainwashed. You can argue "Hey Apple shouldn't charge so much ram, it's better for me, it's better for you, it's better for everyone" and then you get attacked for it (usually by claims that they use "suuuuper" special flash and ram chips bla bla super high performance bla).
mark_l_watson 2y ago
I think Apple’s approach to (more or less) private local AI, with short term reliance on OpenAI makes sense. When I listened to the Apple Developer’s presentations this week I always filtered everything said with “they are talking about proposed product updates, and some existing working functionality.” I have been enjoying running all of Apple’s beta iOS, iPadOS, and macOS beta releases this week, and there are nice features in Photos, Calendar, etc., but we need to wait to see what they release next fall. I am not an Apple developer, really, I did really well selling a Mac app in 1984, and a Mac app I wrote two years ago had pathetic sales. That said, I have been trying the beta Xcode with LLM code completions, etc., and I have been experimenting with MLX and Apple Silicon for a long while. Apple is definitely an interesting player in the AI product space!
ibaikov 2y ago
From Apple website: "Apple Intelligence analyzes whether [the request] can be processed on device. If it needs greater computational capacity, it can draw on Private Cloud Compute, which will send only the data that is relevant to the task to be processed on Apple silicon servers. When requests are routed to Private Cloud Compute, data is not stored or made accessible to Apple, and is only used to fulfill the user’s requests." Are there any more details on what exactly is being sent as context to the cloud? Do they send features extracted from an image on device or the full picture? Is it capable of only sending current pic or will on-device model select what it thinks is needed for context and many pictures and/or texts will be sent?
- sradman 2y ago
  There is also a technical blog post [1] on the architecture of Private Cloud Compute. I don't think that there are any details on the context being sent, just that any context is ephemeral, can't be traced back to you, and that the machine instances leverage Apple Silicon's Secure Boot and Secure Enclave. [1] https://security.apple.com/blog/private-cloud-compute/ https://security.apple.com/blog/private-cloud-compute/
  - ethbr1 2y ago
    Which, IMHO, is the right way to do it. Overly freezing the context guarantees at this early stage would be highly limiting. It makes more sense to invest in surrounding privacy infrastructure (PCC) to provide sane guarantees without strictly bounding context.
deleted 2y ago
[deleted]
la64710 2y ago
Nothing new , I guess that’s the point anyway,?

196 points by xrayarx 2y ago

seydor 2y ago

a little cope for the fact that apple failed to present state of the art performance

Closi 2y ago
Apple seems to be betting that something polished which is “less than state of the art” will sell better than something less polished and more advanced. Technical capability is rarely more important than product market fit.
- sigmoid10 2y ago
  The problem here is that for current AI systems, the state of the art is the one that has ironed out the most kinks. I.e. what you would expect from a polished product. That is basically ChatGPT with it's monstrous API that does tons of god knows what behind the scenes in addition to feeding text to an LLM, most of which was figured out by trial and error from user reports. There's no doubt that a modern LLM based Siri would be a much better product than the old one, but if they're not careful, they will fall into the same trap they did the last time introducing an assistant.
  - tomashubelbauer 2y ago
    Privacy is a part of the equation and while Apple could gather all the context off my phone's local data and give ChatGPT the whole thing to really give it the best shot and providing a useful and helpful answer, this would not be a polished product on all axes, mainly the responsiveness and privacy ones. The tradeoff of using local models for less than SoTA inferrence but with unbeatable privacy and latency seems right to me for Apple and what Apple customers want and expect.
  - Closi 2y ago
    I think this is still a tech-centric view rather than a product-oriented view. E.g. Apple generating emojis using a diffusion model is clearly less SOTA than other image models, but could be a really neat feature from a product/user perspective. Would a better diffusion model help? Maybe, but it probably changes the product less than all the UI and tight integration work they will have done. If I was to guess, I would guess many more emoji's will get created through this feature than images generated in Microsoft's 'Image Creator' in Paint (I could be wrong - just my gut feel).
    - viraptor 2y ago
      WhatsApp has integrated AI generated stickers almost a year ago. (https://www.theverge.com/2023/8/15/23832635/whatsapp-ai-generated-stickers-test-android-beta https://www.theverge.com/2023/8/15/23832635/whatsapp-ai-gene...) I'm not sure how much they're used globally, but there are people crazy about stickers and the quality of what I got was really decent already. There were already external apps available for this purpose for a while, so yeah, the interest is there.
      - fennecbutt 2y ago
        Microsoft SwiftKey has also been doing this for quite a while (not quite that long) as well.
  - HarHarVeryFunny 2y ago
    The best AI experience right now isn't just using SOTA models, but using them in a way that plays to their strengths and avoids their weaknesses (hallucination, limited reasoning, etc). The way to minimize hallucination is to use LLMs to manipulate text (translate, summarize, query, reword, etc) rather than generate it out of thin air, and arguably Apple are doing this by integrating LLM use into the product and therefore controlling it's application, rather than just providing a chat interface that people are wont to use an hallucinating "search engine"/oracle.
- andruby 2y ago
  Indeed. And that has always been Apple’s forte.
  - pjmlp 2y ago
    Not always, specially when Steve Jobs was away.
  - tomalbrc 2y ago
    Except for the dozens of products that were neither polished nor state of the art (maps, Siri, iOS 6/7, most of their Mac related software, etc)
Hippocrates 2y ago
Why does SOTA matter here? OpenAI has actually failed already to make something useful and mass-market. After all these years of pushing SOTA, it's still a website with a text box. Siri in its current form is more useful to me than ChatGPT 4. You simply don't need SOTA models for a lot of valuable features; you need context, annotation APIs, and the right platform and integrations to assist users where they already are (on their phones, in cars, in their IDE, etc). MSFT's GitHub copilot is a good example of getting it right. Apple relegated ChatGPT to a 3rd tier AI capability for "google answers", and "write me a poem" party tricks, and rightfully put it behind a privacy disclaimer. It looks barely better than the various ChatGPT shortcuts so many people have cobbled together. That part of the announcement stuck out like a sore thumb and looked to me like a huge L for OpenAI. The "partnership" was a nothingburger. Like someone at Apple agreed to it early on but then late in the project realized it wasn't needed at all. So much for SOTA.
- nicce 2y ago
  > Why does SOTA matter here? OpenAI has actually failed already to make something useful and mass-market. It is mainly B2B market in reality. Look for the API capabilities: https://platform.openai.com/docs/introduction https://platform.openai.com/docs/introduction
- infecto 2y ago
  I mostly agree with you. OpenAI is reportedly still doing great in terms of revenue, but Apple's implementation is magical if it performs as shown in the keynote. In my opinion, it's the best implementation of LLM/AI in a consumer device. It's amusing to think back to all the buzz around Humane's AI pin.
  - Hippocrates 2y ago
    > It's amusing to think back to all the buzz around Humane's AI pin It certainly is. And the Rabbit R1. How in the world did people who supposedly know anything about AI think they could make that work as a standalone device detached from rich context. The sad thing is, rich context may not be possible outside of OS-level integration that is gate kept, but I still think they're idiots for trying.
threeseed 2y ago
It is best in class for a model that runs primarily on a mobile device.

throwaway4good 2y ago

The NVDIA stock has had a huge AI-related run over the past year while Apple has barely moved. This basically says that only a tiny bit of the AI will done on NVDIA hardware for the billions of Apple users. The market is not pricing that in.

shdh 2y ago
That's assuming Apple isn't training their models on Nvidia hardware. Inference is on Apples own silicon though.
- mupuff1234 2y ago
  Looks liked they used Google TPUs https://www.reuters.com/technology/artificial-intelligence/how-apple-used-googles-help-train-its-ai-models-2024-06-11/ https://www.reuters.com/technology/artificial-intelligence/h...
andruby 2y ago
My opinion is that the market is treating Nvidia as the shovel sellers during a gold rush. If almost every business that wants to do AI needs to buy Nvidia hardware, their sales will go through the roof. That’s what the market is pricing into the Nvidia stock. It is very unlikely that Apple will sell their “server” hardware to other businesses in that way. Their advantage is the vertical integration, for themselves. While I am bullish on AAPL, I don’t expect it to have a run like Nvidia.
- zarzavat 2y ago
  NVIDIA are not selling shovels, they are selling shovel-making machines to the shovel-sellers (the companies making foundation models). When the market is saturated with shovel-making machines, what then?
  - esmy 2y ago
    The last time I remember this happening, the shovel-making machines lost a lot of value and got amortised out to the second hand market. When the prevailing coin still mined on GPUs switched algorithms the bottom of GPU prices fell out on eBay. I expect at some point a) the training and the inference will move to even more specialised hardware and the current existing silicon go to either hobbyists or some other market that requires the current cards b) the way in which we do AI may fundamentally change in ways we can't predict, causing the required hardware to also change (move to FPGA or favouring some other aspect than VRAM) In both scenarios NVIDIA isn't the one who win, because the sudden influx lifts a secondary market nv don't profit from directly. I personally don't think they'll be able to sustain their current valuation past the current AI rush, and will compact back down to somewhere their levels pre-chatgpt. That said I'm just a guy on the Internet who wouldn't mind some beefy ex-datacentre gear if I could make it work for video editing workloads.

FL33TW00D 2y ago

I described this system word for word 2 years ago, glad to see it come to fruition on the only software stack integrated enough to do it. https://fleetwood.dev/posts/a-case-for-client-side-machine-learning https://fleetwood.dev/posts/a-case-for-client-side-machine-l...

jimmySixDOF 2y ago
If you described Speculative Decoding, 3bit Quantization, and Adapter based weight selection all two years ago then your AI Lab must be so sota /s
- reqo 2y ago
  I am curious, what do you mean by "Adapter based weight selection"?
  - supriyo-biswas 2y ago
    That's apparently Apple's term for LoRA[1]. [1] https://arxiv.org/abs/2106.09685 https://arxiv.org/abs/2106.09685
    - jimmySixDOF 2y ago
      Sort of but Adapters allow for multiple weight adjustments (think loras) for specific skills so it is more like extra optimized mixture of experts or multi agent approach. They have a slide with adapters listed like summarization, prioritization, tone (happy, business, etc), editor, etc) -- this is not to be mixed up with Intents which is how on device apps publish their capabilities to the Intelligence system for real npu os level multi agent tool use.
aitooltime 2y ago
Thanks for posting the article. Some predictions in the article: 1. Partial client side execution of the models, then main model execution in cloud. (Example: text encoder for Stable Diffusion runs local, UNet runs cloud) 2. Local LoRAs for “dynamic ML” 3. WebGPU will be new standard to unlock models in the web Even though the article had some good calculations and overview, I am not sure word-for-word is how I would describe its relationship to the OP.

oldpersonintx 2y ago

[dead]

SebFender 2y ago

"Apple has demonstrated how meaningful AI interactions can be built into every corner of our digital life" Well not really. I haven't seen anything new here, unless you consider genmoji a killer app... The whole thing comes down to - your request may get sent to ChatGPT for advanced features. Better doesn't mean new.

jb1991 2y ago
If you didn’t see anything new in the announcement at all, maybe you didn’t actually see all the proposed features they are advertising? I’ve never seen a lot of stuff contained in one personal device or computer before. A single assistant that has access to finding connections throughout your life, emails, photos, etc.?
- SebFender 2y ago
  Yes I did - but in 30 years attending and watching these I've learned a lot. As for Siri - been waiting for a decade for it to do something really useful - Let's hope this time it does.
barkerja 2y ago
> The whole thing comes down to - your request may get sent to ChatGPT for advanced features. If that was your takeaway from the keynote/SOTU, then I would suggest you go back and watch it again. That's not even remotely close to being accurate.
- SebFender 2y ago
  Good suggestion - I would recommend the same back.
shepherdjerred 2y ago
Did you watch the WWDC keynote? There are a lot of legitimately exciting features. There's a level of integration with AI and your OS/apps that is (as far as I know) unprecedented. One thing I really want is for Siri to be able to control my house with Home Assistant with natural language, e.g. "turn off all of the lights outside except for the balcony". The updates to Siri seem like it _could_ make this possible. I would _love_ to be proven wrong, so please do show me alternatives.

mk_stjames 2y ago

I think there is a mistake in the line: >This looks like 2 years after the release of GPT-4, Apple has approximately trained an original GPT-4 level model. GPT-4 was released just 15 months ago, on March 14, 2023. Two years ago we were just getting GPT-3.5.

dmd 2y ago
⠀
- rq1 2y ago
  So you mean one year ago?
why_only_15 2y ago
It's not two years after release, but it is two years after it was trained
- bastawhiz 2y ago
  But that's not what they said, and Apple surely didn't train their model on the morning of the announcement
natolambert 2y ago
thx, you're right. I've fixed it!

cubefox 2y ago

This article really reads like it was written by an Apple fan rather than an objective observer.

resource_waste 2y ago
I wonder when the illusion is going to come crumbling down. As long as there are teenagers that are susceptible to peer pressure and don't know marketing tricks, I think it could last forever. Look how many other Veblen good companies have existed for hundreds of years. With Apple's cash and media, they can have rappers and celebs always using/mentioning their stuff.
- acdha 2y ago
  > As long as there are teenagers that are susceptible to peer pressure and don't know marketing tricks, I think it could last forever. Consider also that you might have made a mistake in your analysis and there are factors involved other than celebrity endorsements – for example, wouldn’t it be interesting to know why Nokia, Google, Samsung, Sony, LG, etc. weren’t more successful thanks to their own endorsements? Your own peer pressure might be hindering your understanding of the market.
- shepherdjerred 2y ago
  Which illusion?
  - theshackleford 2y ago
    The one they have invented for themselves.

cma 2y ago

All of Apple's investment in AI edge capability is almost totally undermined by their huge price discrimination on RAM, shipping 8GB laptops in 2024 and charging like $300-500 for 8GB more.

talldayo 2y ago
I don't know why you're being downvoted. Unless Apple users want to swap a multi-gig 3B model onto their 256gb SSD and chew through it's lifetime TBW, we should be campaigning for enough RAM to do normal stuff. Our SSDs deserve a break.
- fennecbutt 2y ago
  Yup, idk why but Apple fans act weird, like brainwashed. You can argue "Hey Apple shouldn't charge so much ram, it's better for me, it's better for you, it's better for everyone" and then you get attacked for it (usually by claims that they use "suuuuper" special flash and ram chips bla bla super high performance bla).

mark_l_watson 2y ago

I think Apple’s approach to (more or less) private local AI, with short term reliance on OpenAI makes sense. When I listened to the Apple Developer’s presentations this week I always filtered everything said with “they are talking about proposed product updates, and some existing working functionality.” I have been enjoying running all of Apple’s beta iOS, iPadOS, and macOS beta releases this week, and there are nice features in Photos, Calendar, etc., but we need to wait to see what they release next fall. I am not an Apple developer, really, I did really well selling a Mac app in 1984, and a Mac app I wrote two years ago had pathetic sales. That said, I have been trying the beta Xcode with LLM code completions, etc., and I have been experimenting with MLX and Apple Silicon for a long while. Apple is definitely an interesting player in the AI product space!

ibaikov 2y ago

From Apple website: "Apple Intelligence analyzes whether [the request] can be processed on device. If it needs greater computational capacity, it can draw on Private Cloud Compute, which will send only the data that is relevant to the task to be processed on Apple silicon servers. When requests are routed to Private Cloud Compute, data is not stored or made accessible to Apple, and is only used to fulfill the user’s requests." Are there any more details on what exactly is being sent as context to the cloud? Do they send features extracted from an image on device or the full picture? Is it capable of only sending current pic or will on-device model select what it thinks is needed for context and many pictures and/or texts will be sent?

sradman 2y ago
There is also a technical blog post [1] on the architecture of Private Cloud Compute. I don't think that there are any details on the context being sent, just that any context is ephemeral, can't be traced back to you, and that the machine instances leverage Apple Silicon's Secure Boot and Secure Enclave. [1] https://security.apple.com/blog/private-cloud-compute/ https://security.apple.com/blog/private-cloud-compute/
- ethbr1 2y ago
  Which, IMHO, is the right way to do it. Overly freezing the context guarantees at this early stage would be highly limiting. It makes more sense to invest in surrounding privacy infrastructure (PCC) to provide sane guarantees without strictly bounding context.

deleted 2y ago

[deleted]

la64710 2y ago

Nothing new , I guess that’s the point anyway,?