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Are you suggesting Apple plans to do AI without harvesting data, or with transparent privacy controls on data? There's literally nothing for machine learning to

Are you suggesting Apple plans to do AI without harvesting data, or with transparent privacy controls on data? There's literally nothing for machine learning to learn besides harvested data. It's like suggesting that a power company is trying the strategy of using no wires for delivering electricity to houses.. I'd be excited if Apple found a way to trustlessly aggregate data and perform homomorphic training of their ML models, but they seem to be laying off that flavor of talent..

simonh 8y ago
It's actually not that Apple isn't collecting data sets, but they're doing so at a more measured pace by thoroughly anonymising it using differential privacy. If the AI needs to use raw personal data in it's calculations, that is done on the user's device to keep that information private. This appears to be slowing them down compared to their competitors, but it's not clear how much as against them being a bit behind for other reasons.
- mda 8y ago
  Others also anonimyzes data using differential privacy, k anonymity etc. It is a common practice and enforced when working with private / PII data.
JimDabell 8y ago
> There's literally nothing for machine learning to learn besides harvested data. You can obtain training data from sources other than your customers. Apple have employees driving vans around with cameras and LIDAR.
mcintyre1994 8y ago
Is this what their differential privacy stuff is about? It's not trustless (not least because 100% of the data comes from a closed source OS they control) but they do seem to be trying to figure out a privacy-friendly way to harvest data to train ML models.
TheCoelacanth 8y ago
You seem to be equating AI and statistics-based ML. Statistics-based ML is certainly producing the most results of any AI technique right now, but it is not necessarily the only one that ever will.

simonh 8y ago

It's actually not that Apple isn't collecting data sets, but they're doing so at a more measured pace by thoroughly anonymising it using differential privacy. If the AI needs to use raw personal data in it's calculations, that is done on the user's device to keep that information private. This appears to be slowing them down compared to their competitors, but it's not clear how much as against them being a bit behind for other reasons.

mda 8y ago
Others also anonimyzes data using differential privacy, k anonymity etc. It is a common practice and enforced when working with private / PII data.

JimDabell 8y ago

> There's literally nothing for machine learning to learn besides harvested data. You can obtain training data from sources other than your customers. Apple have employees driving vans around with cameras and LIDAR.

mcintyre1994 8y ago

Is this what their differential privacy stuff is about? It's not trustless (not least because 100% of the data comes from a closed source OS they control) but they do seem to be trying to figure out a privacy-friendly way to harvest data to train ML models.

TheCoelacanth 8y ago

You seem to be equating AI and statistics-based ML. Statistics-based ML is certainly producing the most results of any AI technique right now, but it is not necessarily the only one that ever will.