Earlier quoted context omitted.
I wouldn't say that's true at all for traditional computer programs. They're doing explicitly what they are designed to do, there is no adaptation/learning.
How do you define adaptation and learning? What about say, an autoscaler which is programmed to just track the the load for every hour over the last week, and use the average of the last 7 days at 8am to pre-emptively auto-scale? Is that learning and adapting? Alternatively, neural networks are also just doing explicitly what they are designed to do… sure there is a larger computational graph with lots of operations,…
Adapting and learning means it chose to concentrate on packing the world into retrievable storage.
When do we not adapt and learn? When we ignore our inputs and do nothing with it (don’t store it, don’t retrieve it).
In the example you gave, those classical programs cannot concentrate, it’s a one and done.