If you’ve been following my recent posts on Metaduck, you know I spend my days building infrastructure for AI agents and wrangling LLMs into production. As software engineers, we’re used to treating neural networks as massive, static mathematical graphs powered by backpropagation and matrix multiplication running on beefy GPUs (e.g. with PyTorch or similar).
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RE# started as a research project to combine multiple things - first we wanted to bring boolean operators back from the 1964 paper where they originated, then we wanted to extend the .NET NonBacktracking engine, which was, the way i see it, being held back by backwards compatibility (i.e., a safe drop-in replacement for the PCRE existing engine, which meant that it had to support the same features and semantics). we wanted to break free from those limitations and see how far we can push the new engine without worrying about compatibility.