10x Faster Inference on Edge Deployments (getpostslate.com)

PostSlate has announced significant advancements in edge deployment for machine learning with their new video editing tools that achieve 10x faster inference times. This development is crucial as it addresses the common challenges associated with cloud-based services, such as data control, latency, and cost. By prioritizing on-device machine learning, PostSlate enhances user experience while retaining creative control, crucial for video editing. The technical backbone of this advancement lies in the use of the ncnn inference framework, which leverages the Vulkan GPU for optimized performance across a diverse range of hardware, including AMD, Intel integrated graphics, and Apple Silicon. Benchmarks reveal drastic speed improvements, with certain models like ArcFace R50 achieving inference times of just 3 ms compared to 30 ms using ONNX on CPU. The transition to ncnn also results in a reduced model footprint, making it more efficient. While there are challenges in converting models and potential limitations for CPU-only users, the overall shift to on-device processing promises enhanced performance, quicker feedback for users, and the vital benefit of data privacy.