Nobody knows, because we don't know how to do it yet. There could be a "big breakthrough" tomorrow that more or less finishes it out, or it could take 100 years, or - worst case - Penrose turns out to be right and it's not possible at all.
Also, are there useful books, courses or papers that go into general AI research?
Of course there are. See:
https://www.amazon.com/Engineering-General-Intelligence-Part...
https://www.amazon.com/Engineering-General-Intelligence-Part...
https://www.amazon.com/Artificial-General-Intelligence-Cogni...
https://www.amazon.com/Universal-Artificial-Intelligence-Alg...
https://www.amazon.com/How-Create-Mind-Thought-Revealed/dp/0...
https://www.amazon.com/Intelligence-Understanding-Creation-I...
https://www.amazon.com/Society-Mind-Marvin-Minsky/dp/0671657...
https://www.amazon.com/Unified-Theories-Cognition-William-Le...
https://www.amazon.com/Master-Algorithm-Ultimate-Learning-Ma...
https://www.amazon.com/Singularity-Near-Humans-Transcend-Bio...
https://www.amazon.com/Emotion-Machine-Commonsense-Artificia...
https://www.amazon.com/Physical-Universe-Oxford-Cognitive-Ar...
See also, the work on various "Cognitive Architectures", including SOAR, ACT-R, CLARION, etc,
https://en.wikipedia.org/wiki/Cognitive_architecture
"Neuvoevolution"
https://en.wikipedia.org/wiki/Neuroevolution
and "Biologically Inspired Computing"
https://en.wikipedia.org/wiki/Biologically_inspired_computin...
Reading wikipedia about history of the term, it sounds like term was popularized by this book: https://www.amazon.com/Artificial-General-Intelligence-Cogni... which says that general means "ability so solve variety of tasks in variety of domains", not "all tasks in all domains". So "always meant" is easily challengeable here.