It's customary to use OSF (https://osf.io/) on papers this "groundbreaking," as it encourages scientists to validate and replicate the work.
It's also weird that at this stage there are not validation checks in place, exactly like those the author performed. There was so much talk of needing this post-"replication crisis."
I don't think it's "customary" to use OSF in machine learning. At least I had never heard of it. It looks great though, I'm glad other fields are figuring this out. Hopefully it will be taken up by the ML field too.
Really? Perhaps it was just my department (interdisciplinary). We were strongly encouraged to put our work up for review via OSF, including ML. This promotes transparency, collaboration, and verifiable replication.
Why? You can't trust "peer review" from a journal or a conference alone for the verified stamp of "correctness." Why? Bias and ego; humans are human. So, open it up to the hive, encourage people to swarm.
It's also weird that at this stage there are not validation checks in place, exactly like those the author performed. There was so much talk of needing this post-"replication crisis."