Fritz makes it easy to build these experiences with an end-to-end mobile ML platform. Get started at

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6 Reviews5.0/5
Hey Hunters! Today, we’re excited to announce that Fritz’s mobile machine learning platform is open to everyone! The most compelling mobile experiences these days are powered by machine learning and for the past few months, we’ve had the privilege of working with some amazing developers building incredible apps that prove it. InstaSaber turns a piece of paper into a lightsaber, MDAcne tracks skin health over time, and PlantVillage helps farmers in Africa keep their crops healthy. We want to make it easy for anyone to build experiences like these and making Fritz available to everyone is just the start. Fritz offers APIs to solve common problems like image labeling and object detection. Everything runs directly on-device which means it works offline, at high frame-rates, and keeps sensitive data in the hands of users. Developers with custom models can use Fritz to manage and protect them. We support Core ML, TensorFlow Lite and TensorFlow Mobile. All ML features along with custom model support are available on both iOS and Android. Fritz is available for free at Looking for inspiration? Check out these great apps using Fritz: InstaSaber - Turn any piece of paper into a lightsaber, sound effects included. ( PlantVillage - Helping farmers in Africa detect and treat crop disease ( MDAcne - Track skin health over time. ( Heartbeat - Our open source iOS app to help you get started ( Need help getting started? Join Heartbeat, the largest developer community for mobile machine learning. Tutorials, guides, and inspiration. Join us on Slack! Thanks! - The Fritz Team
This is awesome. What additional benefits do I get over using Apple's Core ML? I know you mentioned in your post that you support Core ML, but what does that mean?
@derek_t_lo Thanks, great questions! You can think of Fritz as a management layer on top of model formats like Core ML and TensorFlow Mobile / Lite. With the Fritz SDK, you get analytics on how fast the model runs on every device so you can make sure your users are getting a consistent experience regardless of the device their own. We also protect models when they're deployed so its harder to reverse engineer and steal them. And when you're ready to release a new version of your model, you can push it to all of your users over-the-air, no app store review process required. If you're using Core ML in your app without Fritz, you're really in the dark about how everything is working for your users outside of manual testing.
This is really cool! Will definitely be sharing with my friends who are doing things with ML
I know that there is a bunch of frameworks like your. Why this one is better?