Could you please explain your comment? The link that you have provided explains that with the new Intel Xeon Scalable generation it is difficult to implement single-root PCI complex on typically available motherboards, while according to [1] "the new Intel® Xeon® W processors are based on the Intel® Xeon® Scalable processor microarchitecture". Therefore, Intel Xeon W would have the same problems for supporting single-root PCI complex as the Xeon Scalable mentioned in the link you have provided.
Yes, but as others have said, professional advancement typically depends on publishing in the expensive journals. And that's no accident, in that predatory for-profit publishers have targeted prestigious journals for acquisition. It's the same game that drug makers play with top-selling drugs.
Eventually, authors will migrate to the not-for-profit open access journals and platforms. But that will take time. Top-ranked PIs must lead the way, given that their reputations are well established, and they have tenure.
Self-driving cars are expected to take over the roads, however no programmer is able to write code that does this directly, without machine learning. However, programmers have built all kinds of software of great value, from operating systems to databases, desktop software and so on. Much of this software is open source and artificial systems can learn from it. Therefore, it could well be that, in the end, it would be easier to build artificial systems that learn to automatically develop such software than systems that autonomously drive cars, if the right methodologies are used. The author is right to say that neural program synthesis is the next big thing, and this also motivated me to switch my research to this field. If you have a PhD and are interested in working in neural program synthesis, please check out these available positions: http://rist.ro/job-a3
Ironically, on the right of this article there is a link to another article from the same source, entitled "Top of the bots: This AI isn't a cold, cruel killing machine – it's a pop music hit machine" [1]. Perhaps the link was also placed there by a machine learning / AI algorithm...
The machines showed in these videos seem suited for very large and expensive processing facilities, which probably are cost-effective because one supplies the consumption of millions to tens of millions of people. But how smaller producers can automatize their processing without owning or depending on these facilities? Would robots that cost of the order of tens of thousands euros / dollars, that automate more flexibly but slowly than the machines in the videos, be cost-effective for smaller producers? How big is the market for such robots?
TBH, I suck at the business sides of things so I'm not the best guy to ask, but my impression is that the market isn't s great as one might think considering how much for we all eat. There ought to be a lot of room for growth if the machines actually move out to the field. Most of them are sitting inside cleaning plants because they are delicate and expensive. Search for Buhler, Sortex, Allen, Satake, Selgron for some example companies in that space.
I have been using Keynote [1] for years, without ever losing information. I find that its tree data structure is extremely useful. It is an open-source desktop program. Unfortunately its development seems to have been put on hold. It would be great if developers would keep it updated (on Windows 8, there are some small UX glitches).
The linked webpage is the history of the Wikipedia article on Blueseed, where the former COO (apparently) commented an edit with this: "Blueseed is now dead in the water, and I can say so myself as the former COO. Will someone like Elon Musk fish it out?"
Epistemio allows rating publications as well as publishing post-publication peer reviews. Even though ratings and reviews may be anonymous, reviewers are authenticated, in order to prevent the kind of issues mentioned in the target article.
[1] https://www.intel.com/content/www/us/en/processors/xeon/xeon...