MonkeyLearn: MonkeyLearn is a powerful AI tool that automates text tagging in Google Sheets, eliminating manual and repetitive tasks. It is 100 times faster than human processing, significantly saving time, and 50 times more cost-effective. With MonkeyLearn, users can ensure consistent tagging criteria without errors, enabling efficient analysis of spreadsheets and faster insights from data. It offers direct... Source: about 1 year ago

For your reference, Apple's pages for Machine Learning for Developers and for their research. The Apple Neural Engine was custom designed to work better with their proprietary machine learning programs -- and they've been opening up access to developers by extending support / compatibility for TensorFlow and PyTorch. They've also got CoreML, CreateML, and various APIs they are making to allow more use of their... Source: about 1 year ago

We even host annual poster sessions of those PhD intern’s work while at our company, and it’ll give you an idea of the caliber of work. It may not be as great as Nvidia, Stryker, Waymo, or Tesla (which are not part of MAANG but I believe are far more ahead in CV), but it’s worth of considering. Source: about 1 year ago

They have something for ML: https://machinelearning.apple.com. - Source: Hacker News / about 2 years ago

They're more subtle about it, I think. https://machinelearning.apple.com/ Some of the papers are pretty good. I don't disagree with your sentiment in aggregate, though. Source: about 2 years ago

Siri is not where it needs to be because Apple refuses to mine user data to enrich it. They also are very hesitant to allow researchers to publish their breakthroughs which makes recruitment very hard. Although this is changing https://machinelearning.apple.com/. - Source: Hacker News / about 2 years ago