Forgot to say why this is important. Neural nets, especially recurrent neural nets (RNN), can do inflection and thus make reuse of Wikidata statements possible inside the text. A lot of languages have quite complex rules for inflection and agreement.
An alternative to RNN is finite state transfer (FSM). On Thu, Sep 26, 2019 at 3:03 PM John Erling Blad <[email protected]> wrote: > A project that could be really interesting is to make a Lua interface for > some of the new neural nets, especially based on the Tsetlin-engine. Sounds > nifty, but it is nothing more than a slight reformulation of an old > learning algorithm (type early 70th), where the old algorithm has problem > converging for bad training data (ie. not separable). What is really nice > is that a trained network is extremely efficient, as it is mostly just > bit-operations or add-operations. Which means we can make rather fancy > classifiers that run in the web servers, and thus without any delayed > update of the pages. > > The bad thing is that the training must be done offline, because that is > nowhere near lightweight. > > Ordinary classifiers seems to work well, that is equivalents to fully > connected layers. Also some types of convolutional layers. Some regressions > can be done, but the networks are binary in nature, and mapping to and from > linear scaling adds complexity. > > But running neural nets inside a PHP-based web server… I doubt we would > hit the 10 sec limit for a Lua module even if we added several such > networks. > > Ok, to much coffee today… > > John > _______________________________________________ Wikitech-l mailing list [email protected] https://lists.wikimedia.org/mailman/listinfo/wikitech-l
