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Aber eine Maschine kann doch nicht denken! - Ist das ein Erfahrungssatz? Nein. Wir sagen nur vom Mensch, und was ihm, ähnlich ist, es denke. (PI 360)

 

But surely a machine cannot think! - But is that an empirical statement? No. We say only of a human being and what is like one that it thinks. (PI 360)

Und so können wir durch die vielen, vielen anderen Gruppen von Spielen gehen. Ähnlichkeiten auftauchen und verschwinden sehen. Und das Ergebnis dieser Betrachtung lautet nun: Wir sehen ein kompliziertes Netz von Ähnlichkeiten, die einander übergreifen und kreuzen. Ähnlichkeiten im Großen und Kleinen. (PI 66)

 

And we can go through the many, many other groups of games in the same way, can see how similarities crop up and disappear. And the upshot of these considerations is: we see a complicated network of similarities overlapping and criss-crossing: similarities in the large and in the small. (PI 66)

Aber eine Maschine kann doch nicht denken! - Ist das ein Erfahrungssatz? Nein. Wir sagen nur vom Mensch, und was ihm, ähnlich ist, es denke. (PI 360)

 

But surely a machine cannot think! - But is that an empirical statement? No. We say only of a human being and what is like one that it thinks. (PI 360)

Und so können wir durch die vielen, vielen anderen Gruppen von Spielen gehen. Ähnlichkeiten auftauchen und verschwinden sehen. Und das Ergebnis dieser Betrachtung lautet nun: Wir sehen ein kompliziertes Netz von Ähnlichkeiten, die einander übergreifen und kreuzen. Ähnlichkeiten im Großen und Kleinen. (PI 66)

 

And we can go through the many, many other groups of games in the same way, can see how similarities crop up and disappear. And the upshot of these considerations is: we see a complicated network of similarities overlapping and criss-crossing: similarities in the large and in the small. (PI 66)

Aber eine Maschine kann doch nicht denken! - Ist das ein Erfahrungssatz? Nein. Wir sagen nur vom Mensch, und was ihm, ähnlich ist, es denke. (PI 360)

But surely a machine cannot think! - But is that an empirical statement? No. We say only of a human being and what is like one that it thinks. (PI 360)

Und so können wir durch die vielen, vielen anderen Gruppen von Spielen gehen. Ähnlichkeiten auftauchen und verschwinden sehen. Und das Ergebnis dieser Betrachtung lautet nun: Wir sehen ein kompliziertes Netz von Ähnlichkeiten, die einander übergreifen und kreuzen. Ähnlichkeiten im Großen und Kleinen. (PI 66)

And we can go through the many, many other groups of games in the same way, can see how similarities crop up and disappear. And the upshot of these considerations is: we see a complicated network of similarities overlapping and criss-crossing: similarities in the large and in the small. (PI 66)

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The answers to your questions are not going to be completely settled because they rely on specific theories of philosophy of language and language's relation to philosophy of mind. One very interesting thing to note before any explanations, however, is that Wittgenstein himself did not believe that machines could think. Additionally, he believes thinking "is centered around the human being; thus decidedly anthropocentric" as Obermeier points out. From Philosophical Investigations:

Aber eine Maschine kann doch nicht denken! - Ist das ein Erfahrungssatz? Nein. Wir sagen nur vom Mensch, und was ihm, ähnlich ist, es denke. (PI 360)

But surely a machine cannot think! - But is that an empirical statement? No. We say only of a human being and what is like one that it thinks. (PI 360)

He feels that we know a priori that machines cannot think because thinking is only something humans, or things like humans, do. He believes it would be a categorical mistake to think that machines can think. To that extent, it would most likely be the case that he would reject arguments for or against his theories of language and thought based off of artificial intelligence programs. However, one of the difficulties in his philosophy is that he was cryptic even to the people close to him and nobody knows for sure what he would or would not agree with. Maybe he would be so impressed with AI programs today that he would have a complete change of mind on his ideas, much the same way he changed his mind on the Tractatus; at this moment, we don't know what he would think and all we are left with is what he wrote.

Central to later Wittgenstein is his idea that meaning is use. The idea employed in family resemblance in relation to meaning being use is the idea that we cannot write down a perfect definition of game, however we can still know perfectly well when someone is referring to a game and when they are not. He argues that even though, to use his example, "game" can be used and understood in language, there is not one complete definition of the word.

Und so können wir durch die vielen, vielen anderen Gruppen von Spielen gehen. Ähnlichkeiten auftauchen und verschwinden sehen. Und das Ergebnis dieser Betrachtung lautet nun: Wir sehen ein kompliziertes Netz von Ähnlichkeiten, die einander übergreifen und kreuzen. Ähnlichkeiten im Großen und Kleinen. (PI 66)

And we can go through the many, many other groups of games in the same way, can see how similarities crop up and disappear. And the upshot of these considerations is: we see a complicated network of similarities overlapping and criss-crossing: similarities in the large and in the small. (PI 66)

To Wittgenstein, the problem does not boil down to epistemology. He believes that there absolutely does not exist a concrete definition; he does not believe that one exists but some people may just be ignorant to it. This view is based off of his theory that meaning is use. The word "game" derives its meaning from how people use it and people use it in such a way that it cannot be pinned down by one definition, instead its uses exhibit a family resemblance. From the SEP:

So different is this new perspective that Wittgenstein repeats: “Don’t think, but look!” (PI 66); and such looking is done vis a vis particular cases, not generalizations. In giving the meaning of a word, any explanatory generalization should be replaced by a description of use.

This view of language is in sharp contrast with theories such as the canonical Fregean/Russellian theory of meaning. Generally, Fregean/Russellian theories of meaning hold central the idea that propositions hold meaning and are somehow semantically related to the world. The idea that language, propositions, and definitions are well defined in central to this view. Even Wittgenstein shared this idea in his early days in the Tractatus:

  1. What is the case—a fact—is the existence of states of affairs.
  2. A logical picture of facts is a thought.
  3. A thought is a proposition with a sense.

Ultimately, philosophers who subscribe to semantic theories of meaning would argue that Wittgenstein is wrong when he says that no boundaries can be formed. Inevitably they run into problems such as the Sorites paradox. These questions are still central questions in the philosophy of language and they do not yet have any answers with full consensus. What is clear, however, is that Wittgenstein believed that there are some words that cannot have a clear logical boundary condition (his example is "game") and philosophers on the other side of the theory of meaning, such as Davidson believe that we can.

The Sorites paradox poses one great example of words that seem to have no clear boundary condition and as such it is a central place where this discussion comes to light. From the SEP:

A challenge posed for the epistemic theorist's response is that on such a view the commonly supposed connection between meaning and use appears to be severed. While the margin-for-error principle discussed in Williamson (1994) might serve to explain how we could be ignorant of the postulated sharp boundaries were they to exist, it might be thought that since our use of vague terms does not draw sharp boundaries they could not possess them given the generally accepted connection between meaning and use.

As stated, he did not believe that machines could think. However if we extend his ideas to a philosopher who does believe that machines can think, she would argue that there exist some decision boundaries which a machine could never perfectly recognize, such as the decision boundary between games and non-games. Those philosophers who reject meaning as use would argue that a sufficiently strong AI program would always be able to find a decision boundary if the meaning of the criterion is well defined.

(The translation and source text I used for PI is Wiley-Blackwell 4th edition)