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>At the same time, the low barrier of entry and hype has resulted in a huge amount of people downloading Keras, copying a bunch of code, tuning a few parameters, and then putting their result on arXiv so they can put AI research on their resume. This has resulted in so much noise and low quality work that it really hurts the field.

I'm sorry but given that many papers in NeurIPS, ICML, etc are exactly what you described I find your criticism a bit lacking.

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The peer review system is so broken, especially with the number of submissions that the top journals get in ML now, that I don't even pay attention to what's accepted where anymore. It's all the same as arXiv to me. The best way to figure out what's useful and what's not is to wait and see which papers pass the test of time. But if you're an academic you don't necessarily have that luxury.

Well that definitely speaks more to the field in general and not necessarily to "beginners" who tune a pretrained model and post the results to arXiv. There's massive incentives to post papers with incremental progress when there's potentially billions of dollars of Grants and VC money for folks with their names on those papers.

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