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We use artificial neural networks to parameterize the shape functions ininclusive semileptonic $B$ decays without charm. Our approach avoids theadoption of functional form models and allows for a straightforwardimplementation of all experimental and theoretical constraints on the shapefunctions. The results are used to extract $|V_{ub}|$ in the GGOU framework andcompared with the original GGOU paper and the latest HFAG results, finding goodagreement in both cases. The possible impact of future Belle-II data on the$M_X$ distribution is also discussed.

NNVub: a Neural Network Approach to $B\to X_u \ell \nu$