I suggest that the tacit assumption in the question---that all founders of A.I. were optimistic about the goal being reached very soon---is historically false.
Some were optimistic, but just as many were not, although they hoped that their work was a step to the eventual realization of this goal far in the future.
I'm not sure it has anything to do with the generation they were part of being particularly optimistic. Many scientists in the same generation, including many noted physiologists, were sceptical about such claims, yet worked to make contributions toward this goal.
Many researchers in the same generation denied that artificial intelligence in the sense of pure Turing Machines COULD EVER do ALL the work biological brains were doing. M. Lighthill, R. Gerard, N. Rashevsky (originator of inhibition in neural network models), R. Rosen, Popper, Penrose, Hayek, Lucas, Pribram, etc., etc.
E.g., in a paper (Church’s thesis and its relation to the concept of realizability in biology and physics) in 1962, Rosen, argued that most arbitrary neural networks are not computable. Which does not mean artificial intelligence is impossible, but that it requires other methods of physically realizing computation.
Most suggested schemes are neural networks conceptually, but require specialized physical systems to be realized, due to the number of simultaneous interconnections. Indeed, one can couple Turing machines in a particular way to make a "as-a-whole" noncomputable (hypercomputable) system. Such discussions were present at the same time as much of A.I. was being developed.
(This has been discussed by J. Copeland in the 1990's---and the one catch is that Turing computation is the only computation that has a universal computer. Most hypercomputation concepts lack universal realizations, but depend on their construction on what they can and cannot do, are more specialized.)
McCulluch and Pitts were students of Rashevsky for instance, and they published on related subjects all the way through the 1950's.