For example, if I give you the text 'the car is red', there is no watly to imagine the meaning of this phrase (in any sense of the word 'meaning') unless you have some understanding of what cars are, what red is, and what it means for a car to be red (which is somewhat different from what it means for an apple to be red, for example).

It is interesting that with enough statistical analysis you can begin to decipher certain parts of the true message without knowing the cipher key. But this only works for those parts where you have a large corpus of text talking about them, and there are many common human needs or experiences that do not have such a corpus. It is also very easy to capture answer/response pairs in the corpus and repeat them, seeming to have high accuracy, but in fact failing to generalize more than meets the eye.

For example, with enough compute power, you could build a machine that, for any query, would find the most similar such query in all of its training data, and respond with the continuation of that query (which could be an answer or a follow-up question). This could be quite impressive in conversation, while doing nothing to elucidate anything about human intelligence, and being wholly unable to adapt to any novel situation.