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allenanie authored Sep 3, 2024
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Trace is a new AutoDiff-like tool for training AI systems end-to-end with general feedback (like numerical rewards or losses, natural language text, compiler errors, etc.). Trace generalizes the back-propagation algorithm by capturing and propagating an AI system's execution trace. Trace is implemented as a PyTorch-like Python library. Users write Python code directly and can use Trace primitives to optimize certain parts, just like training neural networks!

[Project website](https://microsoft.github.io/Trace/) | [Documentation](https://microsoft.github.io/Trace/intro.html) | [Blogpost](https://www.microsoft.com/en-us/research/blog/tracing-the-path-to-self-adapting-ai-agents/)
[Paper](https://arxiv.org/abs/2406.16218) | [Project website](https://microsoft.github.io/Trace/) | [Documentation](https://microsoft.github.io/Trace/intro.html) | [Blogpost](https://www.microsoft.com/en-us/research/blog/tracing-the-path-to-self-adapting-ai-agents/)

![BlogPost](https://github.com/microsoft/Trace/blob/main/docs/images/MSR_blog_cover2.png?raw=true)

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