3 ms·

those where quite different projects, having to surmount lot of known unknowns. self driving is still fraught with unknowns unknowns. once the problem gets mapp

• majewsky 8y ago
  Smells like hindsight bias.
  • LoSboccacc 8y ago
    not really. both those indicated projects had all the required component worked out already, plus the physics at their basis where understood. there was a working reactor and the governing phenomena was well understood. it was mostly a refinement and tuning process to get it right. same with apollo, at that point nasa had been launching people in space for a decade, working out the docking procedures and capsule operations. contrast with deep neural network, there are no models to predict overfitting or undertraining beyond what training cross validation say. hardly the same situation. there's no model that can predict a network confidence and network output as a classifier is still very rough even before it gets converted into car commands (i.e. see Uber report) those cited project had a theoretical framework on which they were built upon. neural network are still rooted in 'tune them if they don't work' stage.