Monday, 25 July 2016
from Playful Technology Ltd
Saturday, 12 March 2016
Saturday, 27 February 2016
Thursday, 17 December 2015
As mentioned before, my interests in conlanging and Doctor Who don't overlap as much as I'd like, due to Tardis telepathically translating everything. This apparently goes for writing too - in The Impossible Planet the Doctor realises that they're in a particularly dangerous situation when they encounter a script that the Tardis can't translate.
However, something odd has been going on this season. Amidst the rumours of the Hybrid, the theme of Truth of Consequences, the story of Ashildr, and the build up to the death of Clara, there's been another, more subtle theme in the background. In Under the Lake / Before the Flood, the Fisher King scratches this on the wall of his hearse.
The Doctor can't read it, and has to get Cass to lip-read what the ghosts are saying before he can work out what it means. The reason that the Tardis can't translate it is that the writing is intended to plant a message in the mind of the reader. Also, in that story we have the use of British Sign Language, which the Tardis can't translate because The Doctor's forgotten it.
In The Zygon Invasion / The Zygon Inversion we see this where the Zygon rebels have been active.
Neither The Doctor, Clara nor the Tardis is present in these scenes, and whatever the poster says doesn't come into the story.
In this case it's not translated because what we're seeing has been hacked from the visual cortices of those who experienced the events, most of whom could read the script to start with. As in Under the Lake / Before the Flood, Ramussen's broadcast is meant to be a vector for mental malware.
Finally, in Face the Raven, we get this.
This is a bit of an oddity. It's the Aurebesh script from Star Wars, which is simply a cipher for the Roman alphabet (Star Wars never having cared about plausible languages). It says Delorean, which is presumably a Back to the Future reference. It looks like this is just an in-joke.
So, is this leading up to something? Might Doctor Who be about to start using conlangs? And if so, please can I make one?
Thursday, 22 October 2015
Tuesday, 21 July 2015
Earlier this year, I helped to organise the Sixth Language Creation Conference, which I did so that I could finally get to meet so that I could finally meet some of the friends I've made online over the past few years. Among these were John Quijada (who later wrote some very flattering things about me in the Language Creation Tribune) and David Peterson, of whom some of you may have heard.
Conlanging is not the only thing we have in common. We're all progressive rock fans, too, but while I have never managed to get a band together, John has composed an album's worth of material, and recorded it with David singing. Here's the first track.
The impressive thing here is that David is singing in Ithkuil. Ithkuil is John's conlang, and it's very complex. It has about twice as many sounds as English, and allows more complex combinations. Due to the great precision and concision of Ithkuil, the slightest mispronunciation would change the meaning. It must have taken David ages to learn to sing it.
Wednesday, 17 June 2015
A post on Data Community DC discusses Why You Should Not Build a Recommendation Engine. The main point is that recommendation engines need a lot of data to work properly, and you're unlikely to have that when you start out.
I know the feeling. In a previous job I created a recommendation engine for a business communication system. It used tags on the content and user behaviour to infer the topics that the user was most likely to be interested in, and recommend content accordingly. Unfortunately, my testbed was my employer's own instance of the product, and the company was a start-up that was too small to need its own product. I never really got a handle on how well it worked.
This brings me to Emily. Emily isn't a product. It's a personal portfolio project. I had an idea for a recommendation system that would infer users' interests from content they posted in blogs, and recommend similar content. The problem is, the content it recommends comes from the other users, so at its current early stage of operation, it doesn't have much to recommend. The more people use it, the better it will become, but what's the incentive to be an early adopter?
What I seem to have at the moment is a recommendation engine that needs somebody to recommend it.