Did Linux "win" over BSD? BSD is in every MAC for the last decade. In that regards I would say that BSD has "won" the desktop from Linux. Finally, I have to point out that, although Apple's advertisements call the Macintosh a 32-bit system, its MC68000 processor is generally regarded as a 16-bit processor (the limiting factor is its inability to deal with multiplicands greater than 16 bits). This is no different from the vendors of some other 68000-based microcomputers, but I hate to see Apple hyping a machine that easily stands on its own merits. . Improve Efficiency of Budgeting & Forecasting. Download a Free Trial AutoCAD. The collective or community effort to provide a public good — which is what freely revealed innovations are — has traditionally been explored in the literature on "collective action." However, behaviors seen in extant innovation communities fail to correspond to that literature at major points. In essence, innovation communities appear to be more robust with respect to recruiting and rewarding members than the literature would predict. The reason for this appears to be that innovation contributors obtain some private rewards that are not shared equally by free riders (those who take without contributing). For example, a product that a user-innovator develops and freely reveals might be perfectly suited to that user-innovator's requirements but less well suited to the requirements of free riders. Innovation communities thus illustrate a "private-collective" model of innovation incentive (von Hippel and von Krogh 2003). 18.8 Adapting Policy to User Innovation To address this question we developed a method for automatically generating neural network models that reproduce measured animal behaviors. Our modeling approach relies on Continuous-Time Recurrent Neural Networks (CTRNNs): dynamical systems that share important properties with biological neural circuits [ 19, 32]. These models are consequently more informative of in vivo circuit dynamics than other simple models like non-neuronal Markov [ 33, 34] and random walk schemes [ 12, 13]. We emphasize that the resulting neural networks are not intended to map directly onto the anatomy of Drosophila AS circuits. Instead they reveal emergent dynamics that represent theoretical predictions about in vivo circuit function. .