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We review the use of machine learning techniques in ultrafast dynamics in fiber-optics systems. We discuss how neural networks can be used to correlate the spectral and temporal characteristics of dissipative soliton lasers and predict nonlinear dynamics in optical fibers for a wide range of input conditions. We also show how machine learning algorithm allow for optimizing supercontinuum generation.