> "appears to have found that that the AI/ML organization built at Apple struggled to manifest its work into successful product wins despite the massive financial investment"
I would contest this statement very vigorously. Siri has been a disappointment but nearly every single Apple product has a load-bearing reliance on an AI/ML feature.
I'm continually frustrated by the (relatively recent, since LLMs) tic where just because a ML model isn't conversing with you or otherwise making its presence impossible to ignore, that it isn't delivering a massive amount of value. It is frustrating from laypeople, it is extra frustrating from industry insiders.
Just a few examples off the top of my head:
- AirPods with ANC and spatial audio. Both headline features of these products that are 100% AI/ML.
- Watch with heart arrhythmia detection, automatic workout detection, fall detection, etc. All are headline features (some literally life-saving) and are 100% AI/ML.
- iPhones have high-profile features that are 100% AI/ML: automatic car crash detection. Others are more subtle but IMO substantial differentiators - such as automatic image enhancements out-of-camera.
Again, I know in the age of ChatGPT we seem to have twisted ideas of what ML is, but "AI/ML" is not synonymous with LLM.
1) This appears to be what Apple has concluded by the action they're taking and implied by the premise of the article, versus my personal opinion.
2) The examples given may have been produced by AI/ML-based technologies developed at Apple, but may not have been the work of Apple's AI/ML Organization. Many "groups" (divisions) within Apple have their own teams using AI/Machine Learning (e.g. AI/ML Org coexisting with AI/machine-learning work and teams in TDG/VPG, SPG (special projects group: the one previously working on a car), etc.
I would contest this statement very vigorously. Siri has been a disappointment but nearly every single Apple product has a load-bearing reliance on an AI/ML feature.
I'm continually frustrated by the (relatively recent, since LLMs) tic where just because a ML model isn't conversing with you or otherwise making its presence impossible to ignore, that it isn't delivering a massive amount of value. It is frustrating from laypeople, it is extra frustrating from industry insiders.
Just a few examples off the top of my head:
- AirPods with ANC and spatial audio. Both headline features of these products that are 100% AI/ML.
- Watch with heart arrhythmia detection, automatic workout detection, fall detection, etc. All are headline features (some literally life-saving) and are 100% AI/ML.
- iPhones have high-profile features that are 100% AI/ML: automatic car crash detection. Others are more subtle but IMO substantial differentiators - such as automatic image enhancements out-of-camera.
Again, I know in the age of ChatGPT we seem to have twisted ideas of what ML is, but "AI/ML" is not synonymous with LLM.