There’s also the ML as a service (MLaaS) movement that lowers the barrier for common ML capabilities (eg image object detection and audio transcription). Basically, you use APIs. See: https://aws.amazon.com/machine-learning/. Source: almost 2 years ago

Do you have questions about Data Science and ML on AWS - https://aws.amazon.com/machine-learning/. Source: over 3 years ago

Apple has quite nice page with docs at the bottom: https://developer.apple.com/augmented-reality/. Source: about 1 year ago

Feels like you're grasping at straws to dismiss them. If you think lower weight, not-grainy MR, six years of a public AR SDK, far better computing units, and an existing high-quality software ecosystem are "not noticeable", I'm left wondering what you think is noticeable. Source: about 1 year ago

If you're looking to build a more advanced application, there are plenty of useful resources for all major technologies. For mobile apps, the best places to get started are docs for Google ARCore and Apple ARKit. Both platforms work with popular gaming engines like Unity and Unreal Engine. - Source: dev.to / over 2 years ago

ARKit is Apple's (A)ugmented (R)eality development (K)it. It takes the output from Unity and displays it in the goggles/headset the guy is wearing to see all this. Well, what a camera pointed at the display sees. Source: over 2 years ago

Google and Apple have already released their augmented reality development platforms, ARCore or ARKit, enabling the seamless integration of the digital and physical worlds. - Source: dev.to / almost 3 years ago