Скачать или смотреть Deploying ML Models to Edge Devices with TensorFlow Lite and WebAssembly | Keyhole Software

When most people think of AI systems, they envision monstrous rooms filled with servers processing vast amounts of data. However, the landscape is changing as AI is increasingly running on devices like iPads and iPhones, even in low or no internet connectivity areas. This shift presents unique challenges compared to traditional AI setups. One standout tool in this evolution is TensorFlow Lite, which allows developers to create efficient AI models for edge devices. Unlike its heavier counterpart, TensorFlow, TensorFlow Lite is designed to operate within the constraints of limited computational power and battery life. It has proven successful across various platforms, including Flutter and React Native. As companies explore mobile applications, understanding the capabilities and limitations of on-device AI is crucial. If you're interested in discussing potential use cases for your mobile application, we offer free consultations to help you navigate this exciting frontier of technology. Read more at https://keyholesoftware.com/deploying...

#ai
#machinelearning
#tensorflow
#mobile
#technology

0:00 - Introduction to AI Systems
0:31 - AI on Devices
1:00 - Introduction to TensorFlow Lite
1:39 - Capabilities of TensorFlow Lite
2:39 - Comparison of AI Capabilities: Apple vs Google
3:25 - Consultation Services