| > "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. |
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.