The pace at which AI is moving these days is incredible. It's stressful to do research, because of the constant fear of getting scooped.
Whatever idea you started working on last week, a few other teams have probably been working on it for a month and are about to publish.
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I agree, one way to combat is to work on problems that needs new dataset ensuring u get the first stab at state of the art ;)
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(is the acceleration a direct outcome of more brains in the field, or is something else occurring?)
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it's rare to have such a speed in a field. I'd vote for the "many architectures, speedy feedback" bit
@fchollet
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did you partially start your open research platform to prevent people from unknowingly working on the same thing independently?
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my motivation is mainly to foster collaboration and to be able to draw attention to research projects I can't work on myself
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I find it somewhat relieving. If many people investigate the same idea, its harder for one interpretation to bias the field.
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so you mean only in universities labs it can work?
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Not necessarily. I've been buzzing around first use of DL in a relatively popular technical field for a year. (debug)
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Do you think the pace of *novel* research is fast, or, do you think that there's a lot of flag-planting in AI research?
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One thing that worries me (perhaps wrongly) about AI research is how so much of the "good stuff" is (just) preprints...
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