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.
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and yet, the way AI researchers share code on GitHub does not support practice: very few make a usable API and do other than show how to replicate their paper test results. It’s an exercise to the reader to implement ‘classify’/‘predict’/‘generate’ for new data.
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This is a personal project that I hope can be improved collaboratively to spread best-practices in sciences relying on numerical analysis. https://github.com/nathanshammah/scikit-project … it tries to pick up guidelines and insight from the Python ecosystem (
@EuroSciPy@GaelVaroquaux@mybinderteam...)
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When will we be able to say the same thing ("an industry, not a research field") about neuroscience? It's frightening that it will happen.
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While I dont particularly agree with
@fchollet, certainly there are industry uses of neuroscience already. Medicine being a low hanging fruit there - Show replies
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This is so insightful. True for most fields...get in the real world, because people want the push forward in innovation in your field. They need it.
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Some research can be directly applied to real world and some can not. The latter can turn out to be more impactful in long run. If you don't see possible applications of your research, it doesn't mean you have to spend your time trying to find one. Maybe, it is not possible yet.
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I think you are completely wrong on this.
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It seems to me that a goal of a research field is to discover the unknown in that field. The applicability of it in the industrial world moves a part of it in industry because it becomes profitable "now". For many, research is not about profit; it's about understanding.
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I disagree. Research should be primarily aimed on widenning the knowledge about the universe & humanity.
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