The recent release of LiteRT, previously TensorFlow Lite, incorporates a novel API aimed at simplifying on-device machine learning inference. With significant enhancements like GPU acceleration through MLDrift and support for Qualcomm's NPU, the update allows models to run up to 25 times faster than traditional CPUs while consuming significantly less power. By collaborating with Qualcomm and MediaTek, LiteRT also allows for seamless integration of NPU accelerators, improving deployment for various AI applications, including vision, audio, and natural language processing. Developers can now easily specify their target backend, ensuring straightforward access to advanced features.
LiteRT, previously TensorFlow Lite, enhances on-device ML inference by simplifying GPU and NPU integration, achieving up to 25x speed improvements and lower power usage.
The latest LiteRT release equips developers with unified APIs that eliminate the need for vendor-specific SDKs, making AI model acceleration easier and more accessible.
With MLDrift, LiteRT introduces advanced GPU acceleration, optimizing data transfer and computation for significant performance increases in CNN and Transformer models over prior versions.
By partnering with Qualcomm and MediaTek, LiteRT ensures a standardized approach to leverage NPU accelerators, providing easier deployment of AI models across various applications.
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