Personally, I interpret GP as we have already proven many of the true hypotheses that can be simply and easily formulated, based on the categories and concepts that we currently find intuitive.

And this shouldn't really be a surprise. Our cultures and societies have had thousands of years of evolution; our human instincts have had at least hundreds of thousands of years. In that time, both culture and instinct have picked up many true facts about the world that have helped us survive. A lot of science has been taking those facts and systematically investigating how far they hold.

So these both can be true: the more questions we ask, the more questions we have to answer, but also that many of the 'easy' hypotheses have been mined out, and any true advance in science will by necessity pull us further and further from the realm where our basic instincts and intuitions can usefully guide us.

Quantum mechanics being the prototypical example, of course.

> the more questions we ask, the more questions we have to answer, but also that many of the 'easy' hypotheses have been mined out.

Like a tree? The main branches are the most visible, and so the most tackled. The smaller branches are only realised when you're deep enough in it. That's where our age's advantage comes in, as we have many more qualified 'explorers' than before, but it also makes it all the more important that the foundational branches are solid.

But then again it may be closer to readjusting our lens. The big questions (of the natural kind, not innovation like AI) today still pertain what we take for granted, like quantum mechanics is making us question the nature of reality again. But much like the discovery of waves once threatened the credibility of light as particles, I'm optimistic that reconciliation can happen, and to ascend to another level ... but where can we stop? When can we say "This is it"?

Just musing..

My father used to illustrate the progress of science as an island in the Sea of Unknown. The more you expand the island by gaining new knowledge, the more you get into contact with the unknown.

But the things we realize we don't know are much harder to figure out, they take more resources (time, money, study participants, analysis, etc). That's the reason things are, and should be, slowing down.

We are, clearly, close to figuring out most of the easy stuff. For our current definition of "easy" based on the amount of work, computing power and strength of the mathematical tools that we consider normal.

When you can do multiple experiments and predict the results to 8+ digits of accuracy there is little room for improvement. Your theory also needs to predict the same 8+ digits for all existing experiments while being either simpler or allowing for some new prediction that's also accurate and in disagreement with existing theory.

There really are very few edge cases left for QM 2.0