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by MarkMMullin
2397 days ago
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The 'problem' with modern science is that a large finite amount of stuff has been discovered, and new discoveries are most often built on that stuff. I splash around in the backwaters of machine learning, however I have to pick my targets carefully and maintain a very tight focus - the defined knowledge base has already grown to more than anyone can ingest in detail. Given the amount of knowledge that has to be absorbed to achieve mastery in a scientific discipline, and the fact that knowledge base keeps growing, it takes longer and longer to lay a foundation for just understanding what the hell people are talking about. Now, there are opportunities, for example the use of genetic algorithms as part of ML solutions, because for any 'real' researcher, GA's aren't the cool kid in the opinions of reviewers or funding agents. It's easier when you are the PI and the funding authority, even if the budget is quite a bit smaller |
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Faraday had no formal training, but his natural intuition, interest, and tenacity made him standout.
Newton was a brilliant, paranoid asshole.
Instead funding goes to credentialed career scientists whose greatest ability is self-promotion, fund raising, and stringing-along the public.
As an example: The next big particle accelerator sucks up billions; while alternative approaches to QM never get any attention because it’s a guaranteed way to kill a career and become a pariah.
So nobody is available to even try to create the theoretical framework at the investment of a few million.