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I believe the goal of a research field should be to stop being primarily a research field, and instead move into the real world. Become an industry. Deep learning has achieved just that: academic research now represents less than 10-15% of users of deep learning.
This could be rephrased as: the true test of a scientific idea is contact with reality and impact on the world, not approval by other academics. And if academic debates are the only hurdle your ideas ever have to clear, it may be that you aren't doing science at all.
I'm not sure that this is a great metric for "doing science". e.g. for centuries orbital mechanics was an academy subject - we observed only, and didn't really do any orbital engineering until the 1950s. But it was still a rigorous science, because it was experimentally tested.
When will cosmology ever become an industry? The main goal of science is understanding and explaining the world.
@fchollet is conflating “science” with “engineering”. In his defense this is a common enough error of attribution. It stems partly from the term “computer science“, which seems to imply a thing that it often isn’t. What do most people with a CS degree do? Engineering
Absolutely! We get far too bogged down in this insular circle, that we forget to validate against the ultimate test: reality. We've seen many so-called SotA implementations struggle to find reproduced results when applied outwards.
Or possibly your work was always just engineering and now it’s moved into a more appropriate forum ;)
Would you rephrase again or maybe rollback to the previous version? It sounds worse now. Usually impact on the world takes time and isn't easy to predict. We would never have AI without physicists doing fundamental research more than 50yrs ago, pushing the boundaries of science.
But then by the same logic that was a successful research field as it led to (at least) AI applications?
I appreciate the general idea but there are some problems with it. E.g. Cryptography - underlying math came from pure mathematics (number theory, abstract algebra etc), Relativity (Non-euclidean geometry), Blockchain(number theory, abstract algebra), Computers (Turing machines)
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