I don't consider myself a deep learning expert by any means. There are still a lot more things I don't know than things I know (it's not even close). I've only been working with neural networks since 2009, which is a lot less than many of you.
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Consider that, not long ago, most AI experts knew for a fact that neural networks were a failed avenue. Consider that, in 2013, most of the top names in computer vision were saying that the nascent success of DL might be just a fluke. And remember the debates about local minima?
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In general, I'm also not a fan of the idea of an "expert". It makes it sound like there's some threshold of knowledge beyond which you know it all, you've made it (perhaps the threshold is when you reach full professorship). I don't think that's how it works.
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If someone tells you they're a top expert, a pioneer, the main thing they're an expert at is playing status games. The same people will probably also try to demean those they feel are in competition with them, because that's how status games work.
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As for me, I'm just someone who's been trying to learn as much as possible (not just about AI). That's how I'd define myself: someone who gets excited about stuff and learns about it. If there's an "expert threshold", I hope I never reach it.
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End of conversation
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i hope you do realize they ***lie intentionally*** to market themselves. [no, it's NOT ignorance].
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So in order to have the clear mental model that you are talking about, what things/concepts etc should one learn?
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What about more nice coffee break (or beer time) discussions at the conferences ?
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