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One hypothesis is that these networks are tuned to carry the most positional information possible given their noise.","posed_since":"","precise":"For the Drosophila gap-gene network (hunchback, Kruppel, knirps, giant) driven by maternal gradients, maximize the mutual information $I(x; g)$ between position $x$ and expression vector $g$ at a fixed budget of molecules and the measured noise, and test whether the optimal network, with no parameters fitted to gap-gene profiles, predicts the measured profiles, the positional error of about $0.01\\,L$ ($L$ = egg length), and mutant phenotypes. Answer: yes or no for wild type and for mutants or other species.","problem_ref":null,"references":"","settled_by":"Parameter-free predictions of the optimized network compared with measured expression profiles in mutants and in other fly species.","status_note":"An optimization-based derivation (Sokolowski, Gregor, Bialek, Tkacik; arXiv 2302.05680, 2023) reproduced key features of the wild-type network; out-of-sample tests remain open.","title":"Are embryonic gene networks optimal encoders of 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