Doesn't it follow naturally that there will come a point where science will practically be limited by the human lifespan? As in, there is so much one has to learn before being a productive researcher that there simply isn't enough time to learn it?
http://en.wikipedia.org/wiki/The_Structure_of_Scientific_Rev...
His finding was that science works by accretion of facts, except that over time, a number of facts that don't fit the established theory build up. Eventually, this reaches a crisis point where you realize that the current models are unable to explain reality, and then they get thrown out (a "paradigm shift") and everything needs to be figured out again from first principles. At this point, younger scientists have the advantage, because the "knowledge frontier" contracts back to nothing (almost...the new theory still has to account for old experimental results).
The last major paradigm shift in physics was a century ago, with the twin discoveries of relativity and quantum mechanics. You could probably argue that we're due for another one soon - the weight of evidence that our understanding of the universe is flawed has been building up, with unexplained results around dark matter/dark energy/cosmology and the failure of superstring theory to make accurate testable predictions. It's pretty likely that within our lifetime physics may become a hot place for brilliant 20-somethings again.
But in the meantime, most of the action has been in computing. The field of practical applications of computer science has been undergoing a paradigm shift approximately every 10 years (wasn't yesterday's top Hacker News story about that?), hence why we see so many young tech billionaires.
How much of that is done by Musk himself is debatable. One of my pet peeves about the Musk fan-club is that he tends to partner with some very brilliant engineers and then get all the credit for the work they do. However, people high up in his companies (more than one of them) have said that he involves himself very extensively in discovering the technology itself, and his bachelors and the first couple years of his Ph.D were both in physics, so it seems likely that he does at least know the science behind what his companies do.
Also, he dropped out of his Ph.D. on the first week. So it appears that he didn't learn too much physics in academia. Rocketry and electric cars don't involve too much advanced physics and he has top notch experts working for him in all the relevant fields.
It already happens and I think this is where AI and robotics play a big part. They will essentially evolve us in thinking as our lives will become too short to gain all the knowledge needed and they will pass the information better while connecting many more dots that can only be seen from a higher macro perspective from a longer life.
A 500 year old AI knowledge bank and study (evolving with time) will be no match for a 70-80 year life in the field. AI will be the great thinking age even though we won't be doing most of it. Yes we have this now with records and digital data but correlation will get more difficult and so much gets lost from age to age. Additionally, a single lifetime will be throttled with AI that can really match or exceed human capability. AI and smarter computers will be our turbo button on science.
We also have to keep in mind that once something has been discovered, it generally takes a lot less time to learn than it did for the person discovering it.
1) With more scientific advances we will hopefully be able to live longer 2) The better we understand a field, the more we can compress and simplify it and have an easier time teaching it. At least this appears to be the case in mathematics, where I can only imagine many years ago something like trigonometry was not well understood and the greatest mathematicians of the time did research to further our understanding of it, but now it's something we're expected to learn in high school. I can only imagine this will happen as well to the current topics of research as well.
Also, being better at predicting talent will help in the sense that more people will manage to reach the frontier of science. Having some strong driving force that forces children to take the necessary tests and follow their predictions will further increase that number.
However, neither would help to lengthen one's career substantially. The best one can win is 25% or so (20 years on a 80 year life span)