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University of Michigan
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BlazingAML delivers up to 333x speedups in anti-money laundering detection while maintaining state-of-the-art accuracy, by compiling high-level fuzzy pattern descriptions into optimized GPU code.
Masked diffusion models can finally achieve faster inference without sacrificing generation quality, thanks to a clever speculative decoding scheme.
