I think (correct me if I am wrong) machine learning (and a lot of other fields within CS) is the first field that has completely shattered the closed journal type system in Academia. I work in an interdisciplinary field with an ML focus, and many non-ML faculty and collaborators are just so surprised hearing how the machine learning community generally approaches publications.
There is no need whatsoever for the ML field to go back. I also feel the cat is out of the bag for ML, and there is no turning back into a system that Nature promotes even if they are trying to.
There are already big names in this list and it was a a tenth (~30) only a few hours ago when I signed. Yoshua Bengio, Jeff Dean, Yann LeCun, Ian Goodfellow, ... Even if it only represents their personal opinion, like herd immunity I'm certain this will prevent widespread adoption.
When I started in NLP as an undergrad, almost all the papers I cared about were free to read from the ACL Anthology. As I shifted into broader machine learning, arXiv became my new home. Nature's closed Machine Intelligence would be a step back. I am glad that researchers and scientists want to keep research open and accessible.
P.S. It's already weird that Nature has DeepMind papers. At least in that case DeepMind have a formalized agreement / enough clout that they can host the paper themselves but even the hint of ambiguity can kill knowledge propagation at many institutions. An example would be "Mastering the Game of Go without Human Knowledge"[0] / "Mastering the game of Go with deep neural networks and tree search"[1].
>It's already weird that Nature has DeepMind papers.
Nature (the multidisciplinary journal) is a special case.
If you get article published in Nature you are not killing the knowledge propagation, you are enhancing it to the scientific community at large. It has maintained so much prestige that getting published there is type of signaling that still has value.
The old way of scientific publishing is going to shrink to almost nothing, but there is room for a handful of high-impact, high prestige publications like Nature to keep going. They would work like compendiums of best research in science.
You don't need special clout for most journals (including Nature) in order to self publish. The Nature license [1] allows it directly, as do journals such as Science.
The main thing is that they typically don't allow you to publish it outside of your website. I also don't know what the terms of this new journal are going to be.
Nature does have an "Open Access" option in their policy:
"Authors wishing to publish open access retrospectively should contact the individual journal editorial office, and will need to sign a new open access licence to publish form (LTP) and pay the journal's article processing charge."
However, they don't disclose how much money it costs to convert one's work to open access, and whether this option is available for all Nature journals, the main Nature journal, or just the specialized subject journals, such as Nature Machine Intelligence.
"As I shifted into broader machine learning, arXiv became my new home."
Similarly, when I researched machine learning topics for my master thesis (around 2001), citeseer.org proved to be an absolute treasure trove. I did not check out anything beyond machine learning and general computer science topics, but for these at least open access papers have quite a bit of tradition by now.
Some big names signed there. Sounds like a death sentence for this journal, despite the prestigious pedigree. Either it will wither or become a second-rate trashcan.
I do notice no Google names, though. Google has tended to favor Nature in the past, e.g. AlphaGo went there instead of to an open-access ML journal. Of course regular Nature has an established level of prestige that this new Nature spinoff doesn't yet. So it'll be interesting to see which way they go on it.
There is no need whatsoever for the ML field to go back. I also feel the cat is out of the bag for ML, and there is no turning back into a system that Nature promotes even if they are trying to.