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OK, but in this sort of race, publishing your very latest internal techniques lets everyone else instantly catch up. If these techniques are commercially valua
by gojomo 12y ago
OK, but in this sort of race, publishing your very latest internal techniques lets everyone else instantly catch up.
If these techniques are commercially valuable and in current use – and I believe they are! – then no leading company, or even member of the leading pack, would want to do a current-best reveal. They all have competitive reasons to do only carefully vetted, incremental reveals of somewhat-older work.
- gwern 12y agoYou can publish papers without giving away all the details necessary to make it work. Sad but true. For example, submitted to HN sometime ago was the blog of a dude trying to make Deepmind's 'neural turing machine' work; he was having a hella time because the published paper seems to be unclear or skip over a number of crucial points. Or more historically, the German chemical giants made an art of filing patents on all their key techniques, to gain IP protection, but leaving out enough crucial details that when the USA gleefully seized their IP rights during WWI, the American companies discovered they couldn't make the processes work.
- gojomo 12y agoIndeed, and if that's also happening with the deep-learning papers here, then it's another mechanism in support of my main point: what's published is often, by motivated choice, behind what's being done internally. (And not just, "time it takes to write up" behind.) Given that intent, there's no way to deduce from the pattern of new claimed results whether what's being revealed is a merely a few months, or many years, behind.