I was trying to decide on some Flutter side project to exercise some organizations and concepts from the framework and since AI is at hype I did some research and found out about Google Machine Learning kit which is a set of machine learning tools for different tasks such as face detection, text recognition, document digitalization, among other features (you should really check the link above). They're kinda plug... - Source: dev.to / over 1 year ago

The biggest difference between the two plugins is the SDK used to recognise the barcodes. The Capacitor Community Barcode Scanner plugin currently uses the ZXing decoder and the Capacitor ML Kit Barcode Scanning plugin uses the ML Kit from Google. Source: over 2 years ago

Assuming you're talking about leveraging the device's the device's Tensor Processing unit for machine learning then there then you're in luck because Google designed the TPU to work extremely well with the machine learning solutions developed by Google such as easy to use SDKs, robust runtimes and APIs ( e.g. - which you probably aren't going to need to touch). If you're a researcher there's plenty of lower level... Source: over 2 years ago

Google's ML Kit https://developers.google.com/ml-kit. Source: about 3 years ago

Thanks. The name of the ML package is "ML Kit". This one: https://developers.google.com/ml-kit. Source: over 3 years ago

On the machine learning side of AI, they have CoreML. You can drag-and-drop images into Xcode to train an image classifier. And run the models on device, so if solar flares destroy the cell phone network and terrorists bomb all the data centers, your phone could still tell you if it's a hot dog or not. https://developer.apple.com/machine-learning/ https://developer.apple.com/machine-learning/core-ml/... - Source: Hacker News / over 1 year ago

Apple has actually created ML chipsets, so AI can be executed natively, on-device. https://developer.apple.com/machine-learning/. - Source: Hacker News / over 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: over 2 years ago

> It’d be one thing if Apple actually worked on AI softwares a bit and made it readily available to developers. * Apple Silicon CPUs have a Neural Engine specifically made for fast ML-inference * Apple supports PyTorch (https://developer.apple.com/metal/pytorch/) * Apple has its own easily accessible machine-learning framework called Core-ML (https://developer.apple.com/machine-learning/) So it would be inaccurate... - Source: Hacker News / over 2 years ago

This is the developer documentation where they advertise the APIs - https://developer.apple.com/machine-learning/. Source: about 4 years ago