Google made a valiant push for its Smart Glasses (shown above) starting in 2013 and “went back to the lab” by 2015 due to a lack of market traction, among other issues. As we all know, it’s rarely the first concept of a product that goes mainstream. The iPod was preceded by countless deprecated mp3-players. Prior to the current state of navigation, handheld GPS devices were common, but Smartphones eliminated the need for separate clunky devices. Thus, we cannot expect the first version of a product to have a high likelihood of success.
Augmented Reality (AR) has come a long way since 2015. The most obvious platform for widespread AR success is the Mobile phone. Most people are more likely to forget their keys or wallet than their Smartphone. Again, what device has replaced most other devices and has the widest variety of use cases? Smartphones. In a world top-heavy with developers, Google and Apple are taking full advantage of the Mobile AR scene with their respective developer environments, ARCore and ARKit. …
Harness machine learning algorithms on AWS to build out reliable time series models
In the world of machine learning, failing fast is crucial. When considering AWS’s DeepAR, a recurrent neural-network (RNN) time series algorithm, there are several questions to ask when sizing up the ability to fail fast: