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We provide low-latency (10-100 microsecond) machine learning algorithms that adapt over time to predict and control complex physical systems. Our technology is seamlessly integrated from the base hardware to low-level assembly code, all the way up to a high-level, easy-to-use user interface that runs within a web browser. An early prototype of this technology has proven capable of both predicting and controlling near chaotic, stability limit engine combustion in sub-millisecond real-time.