There could be arguments about his thesis within this model, or there could be arguments about the model.
在这个模型中，或者关于这个模型本身，自然也存在着一些问题。
The discussion of Godel's theorem was, par excellence, one which accepted the model of a logical system.
比如说，对于任何形式系统而言，一个无法避免的问题就是哥德尔定理。
Alan discussed the validity of the model itself,
图灵对此做了一些讨论，
In particular, there was the fact that no physical machine could really be 'discrete': Strictly speaking there are no such machines.
比如说，在现实世界中，没有任何一台机器，能够做到真正的“离散”：严格说来，真正的离散机器是不存在的。
Everything really moves continuously.
现实世界中的任何事物都是连续的。
But there are many kinds of machine which can profitably be thought of as being discrete-state machines.
但是有一些机器，我们可以将之视为离散的。
For instance, in considering the switches for a lighting system, it is a convenient fiction that each switch must be definitely on or definitely off.
比如说，我们考虑电灯的开关，我们总是假设，它要么是开着的，要么是关着的。
There must be intermediate positions, but for most purposes we can forget about them.
很显然，开关还存在许多中间位置，但在一般情况下，我们都会忽略这些中间位置。
That 'forgetting about them' would be precisely the element of 'selecting certain details' necessary to the scientific method.
“忽略这些中间位置”，这就是科学方法所必须的“选择一些特定的细节”。
He conceded that the nervous system was itself continuous, and therefore certainly not a discrete-state machine.
图灵承认真正的神经系统是连续的，他写道：神经系统本身，肯定不是离散状态机。
A small error in the information about the size of a nervous impulse impinging on a neuron, may make a large difference to the size of the outgoing impulse.
神经脉冲冲击神经细胞时，任意微小的偏差，都有可能造成输出信号产生巨大的差别。
It may be argued that, this being so, one cannot expect to be able to mimic the behaviour of the nervous system with a discrete-state system.
有人认为，既然是这样，就不能用离散状态机来模拟神经系统的行为。