Important Editor’s Note: Heartbeat is sponsored by Fritz AI, one of the platforms covered in this post. The author of this post was paid for this content (we pay all contributors for all content); however, all information, research, and perspectives included are solely the author’s and do not include any editorial input/control from Heartbeat or Fritz AI

In the past few years we’ve seen many startups and even mature companies coming up with new mobile apps or features powered by machine learning and AI. These features require some heavy, real-time processing by neural networks.

The potential killers of these ML-powered experiences? Data roundtrips for inference, the cost of backend servers to support millions of devices, concerns surrounding user data privacy.

But luckily, there’s a way to solve these issues: Mobile Machine Learning. By performing machine learning inference on edge devices, developers and engineers can count on better performance, increased reliability, faster speeds, and less power/memory consumption.

That’s all well and good in theory, but what are the available tools to make it happen? Luckily, we have several wonderful capabilities for AI on the edge in terms of both hardware and software.

Both of the leading mobile OS makers have come forward with their own implementations for running ML models on their platforms. On top of that, there are a number of good solutions that help manage, customize, and protect TensorFlow Lite and Core ML models to make it easier for developers and engineering teams to integrate AI features in their apps. All of these libraries aim to provide better developer experiences while working on AI-powered apps.

As a mobile app developer, one has to make the critical decision of selecting one of the available libraries. This requires a detailed analysis of what all of these libraries are offering.

In order to make your decision easier and more data-driven, I’ve analyzed some of the basic aspects/features of these available libraries.

We’ll be looking at the following tools: