Mobile developers have a lot to gain from revolutionary changes that on-device machine learning can offer. This is because of the technology’s ability to bolster mobile applications—namely, allowing for smoother user experiences capable of leveraging powerful features, such as providing accurate location-based recommendations or instantaneously detecting plant diseases.

This rapid development of mobile machine learning has come about as a response to a number of common issues that classical machine learning has toiled with. In truth, the writing is on the wall. Future mobile apps will require faster processing speeds and lower latency.

You might be wondering why AI-first mobile applications can’t simply run inference in the cloud. For one, cloud technologies rely on central nodes (imagine a massive data center with large quantities of storage space and computing power). And such a centralized approach is incapable of handling processing speeds necessary to create smooth, ML-powered mobile experiences. Data must be processed on this centralized data center and then sent back down to the device. This takes time and money, and it’s hard to guarantee data privacy.

Having outlined these core benefits of mobile machine learning, let’s explore in more detail why, as a mobile app developer, you’ll want to keep your eyes peeled for the incoming on-device ML revolution.