> I don't think there are actually that many domains where you can't simulate them with enough knowledge and compute.
The problem is that you have to simulate them accurately enough and fast enough. A perfect simulation of physics will necessarily be orders of magnitude slower than physics. To accelerate it, you need to figure out which parts can be cut or approximated without derailing the model, and just that part will require a lot of back and forth with reality.
Success isn't guaranteed either. If a physical system does whatever it does optimally enough, fast simulation is just physically impossible. Furthermore, even simple chaotic systems require unrealistic precision in the initial parameters to be useful. Natural entities are fairly chaotic and also pretty darn efficient at what they do, so it's plausible that even the best possible simulation of a middle manager is a slower bottleneck than a real middle manager.
The problem is that you have to simulate them accurately enough and fast enough. A perfect simulation of physics will necessarily be orders of magnitude slower than physics. To accelerate it, you need to figure out which parts can be cut or approximated without derailing the model, and just that part will require a lot of back and forth with reality.
Success isn't guaranteed either. If a physical system does whatever it does optimally enough, fast simulation is just physically impossible. Furthermore, even simple chaotic systems require unrealistic precision in the initial parameters to be useful. Natural entities are fairly chaotic and also pretty darn efficient at what they do, so it's plausible that even the best possible simulation of a middle manager is a slower bottleneck than a real middle manager.