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I think there is one company very well placed to do this, Apple. Their revenue is driven by hardware sales, rather than advertising, and they have committed to

I think there is one company very well placed to do this, Apple. Their revenue is driven by hardware sales, rather than advertising, and they have committed to some level of "privacy" focussed design (although obviously there are criticisms). On top of that their hardware is looking almost like it was design for exactly these use cases. Apple silicone with its unified memory architecture, GPU and Neural cores is very well placed for local LLMs. Apple have a history of doing stuff locally, on the hardware they designed, that other companies have offloaded to the cloud. They are looking for "the next big thing" that lets them sell hardware. Some people thinks that's going to be their VR/AR headset, I don't. It's going to be local AI running privately on your device. Putting the AI in the cloud doesn't help with hardware sales. My only hesitation is that they have such a crap spell checker, surly you would solve first...

synctext 3y ago
> Apple silicone with its unified memory architecture, GPU and Neural cores is very well placed for local LLMs. Yes, university research from 2011 already showed a privacy focused design to machine learning[1]. But will this be private or public like Wikipedia, Bitcoin and Bittorrent? > Effectively an extension to your own brain. Correct. After 1996 fantasy/visionary publications about this, we now know roughly how to do this. Most difficult problem is who should own it, no corporation in control is desired. That means full decentralisation, federated learning is not enough. But fully decentralised learning is hard. Try to apply machine learning in permissionless, byzantine, unsupervised, decentralised, adversarial, continuous learning context. See my lab at Delft University focused for a decade already on "The Global Brain"[2]. With 2.3 million download and crowd-sourcing, we might get there.. [1] "Gossip Learning with Linear Models on Fully Distributed Data", 2011, https://arxiv.org/abs/1109.1396 https://arxiv.org/abs/1109.1396 [2] The Global Brain - the roadmap, https://github.com/Tribler/tribler/issues/7064 https://github.com/Tribler/tribler/issues/7064
tinus_hn 3y ago
I think Apple will be hesitant to release an AI on their platforms that can be made to say unpredictably bad things. For now as far as I have seen there’s only censoring and that’ll only lead to a game of people trying to work around it.
fsflover 3y ago
> Apple have a history of doing stuff locally, on the hardware they designed, that other companies have offloaded to the cloud. Looking at how they promote using iCloud on iDevices, I doubt that.
- mrtranscendence 3y ago
  I don't think iCloud is a great example, because there's a definite value add in having your files synced between multiple devices and your computer. A better example might be Siri, which does basically nothing without an internet connection.
  - fsflover 3y ago
    iCloud provides a lot of value, because storage is extremely expensive on all iDevices, and you can't upgrade it. Also Syncthing can be used for a synchronization between devices, if you control them.
triggerity 3y ago
Pretty every Google, Microsoft, Amazon, Samsung and apple can do that. Everyone has a huge motivation to get this solved. But because all of them also have their cloud storage and every customer is trusting their company I'm pretty sure most will not use local ai. Until when suddenly in 10 years we have hardware chips like gpt-8 hardware version or something.

synctext 3y ago

> Apple silicone with its unified memory architecture, GPU and Neural cores is very well placed for local LLMs. Yes, university research from 2011 already showed a privacy focused design to machine learning[1]. But will this be private or public like Wikipedia, Bitcoin and Bittorrent? > Effectively an extension to your own brain. Correct. After 1996 fantasy/visionary publications about this, we now know roughly how to do this. Most difficult problem is who should own it, no corporation in control is desired. That means full decentralisation, federated learning is not enough. But fully decentralised learning is hard. Try to apply machine learning in permissionless, byzantine, unsupervised, decentralised, adversarial, continuous learning context. See my lab at Delft University focused for a decade already on "The Global Brain"[2]. With 2.3 million download and crowd-sourcing, we might get there.. [1] "Gossip Learning with Linear Models on Fully Distributed Data", 2011, https://arxiv.org/abs/1109.1396 https://arxiv.org/abs/1109.1396 [2] The Global Brain - the roadmap, https://github.com/Tribler/tribler/issues/7064 https://github.com/Tribler/tribler/issues/7064

tinus_hn 3y ago

I think Apple will be hesitant to release an AI on their platforms that can be made to say unpredictably bad things. For now as far as I have seen there’s only censoring and that’ll only lead to a game of people trying to work around it.

fsflover 3y ago

> Apple have a history of doing stuff locally, on the hardware they designed, that other companies have offloaded to the cloud. Looking at how they promote using iCloud on iDevices, I doubt that.

mrtranscendence 3y ago
I don't think iCloud is a great example, because there's a definite value add in having your files synced between multiple devices and your computer. A better example might be Siri, which does basically nothing without an internet connection.
- fsflover 3y ago
  iCloud provides a lot of value, because storage is extremely expensive on all iDevices, and you can't upgrade it. Also Syncthing can be used for a synchronization between devices, if you control them.

triggerity 3y ago

Pretty every Google, Microsoft, Amazon, Samsung and apple can do that. Everyone has a huge motivation to get this solved. But because all of them also have their cloud storage and every customer is trusting their company I'm pretty sure most will not use local ai. Until when suddenly in 10 years we have hardware chips like gpt-8 hardware version or something.