“The search engine behemoth Google has transformed its strategy from ‘Mobile First’ into ‘AI First’, and released Google AI tools. Android app developers can utilize these tools to make high-end mobile applications for corporate clients. Here we go through a few major AI factors that can take the Android app development process to the next level. Let’s start with the most obvious feature.
“Apple, they write, stands out: its “Metal” API for iOS runs on a consistent chip platform and the GPUs in those chips are higher-performance, on average, “making Metal on iOS devices with GPUs an attractive target for efficient neural network inference.” Even then, however, the results of a “rigorous” examination of the speed of inference across six generations of Apple’s “A” series chips shows that within each generation of chip there is still “wide performance variability.”
“Programmability is a primary roadblock to using mobile co-processors/accelerators,” they write.
The newest version of Facebook’s “PyTorch” framework, unveiled this year at the company’s developer conference, is designed to “accelerate AI innovation by streamlining the process of transitioning models developed through research exploration into production scale with little transition overhead.” It also supports the “Open Neural Network Exchange,” or ONNX, specification backed by Microsoft and others.”