Burn is an open-source AI infrastructure platform that enables efficient training and deployment of neural networks on various hardware, including cloud servers and edge devices. It features a dynamic computation graph, advanced JIT compiler, and supports both training and inference, making it suitable for AI researchers and engineers.
In the Data science & ML workbench space, Burn takes a focused approach. It focuses on simplifying and optimizing the process of training and deploying AI models across diverse hardware platforms. Burn is an open-source project aimed at AI researchers and machine learning engineers. The project is open source (Apache-2.0). The product ships for the web and the command line, and it can be self-hosted.
Burn first shipped in 2022. The project is developed in the open on GitHub with 15.4k stars and 237 commits in the last 90 days. Across PulseGate's embedding index, Burn has few near neighbours, marking it as relatively distinct. Among its 6 catalogued features are dynamic computation graphs, multi-platform support, and JIT compiler.
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