Dear Funko,

I am deeply saddened to find no Funko Pop figurines of Pinky, Froppy, or Ruby Roundhouse. How can I keep my office safe without them?


Well, when this comes out, I should be protected from any hostile force. Even idiot managers.

“Alexa, let there be light!”

I bit the bullet and started moving to LED lighting at home. While I’m generally opposed to the Internet of Things, a few people I have reason to trust spoke well of Philips Hue smart lighting (in particular, the fact that it gets updates), so I picked up a starter kit on Amazon and gave it a try.

After playing with it for a while, I picked up some White Ambiance flood lights at Home Depot to start replacing the mix of incandescents and fluorescents in my ceilings, and some more White ones for outside. I also added a wireless dimmer switch (for the stairs) and motion detector (for the garage), and set up the Amazon Alexa integration. I’ll probably add another motion detector and a few more switches before my parents come out in March, since they won’t be used to calling out the names I’ve given to each lighting area.

While planning out the number and type of lights I’d need, I realized I had a way to use my most peculiar Christmas present: an eBay gift card. Sure enough, a number of dealers with good histories have new-in-box Hue lights, so I ordered some floods and A19 bulbs.

The floods arrived yesterday, in new-looking packaging, but the seal on one of the boxes looked like it had been opened and resealed. Sure enough, both boxes contained Hyperikon LED bulbs rather than the promised Philips Hue, and no, they weren’t even smart bulbs.

I have done the seller the courtesy of assuming that this was not an act of deliberate fraud (by them; obviously someone’s a scammer), and requested a “wrong item” return, sending them pictures of the shady seal and the bulbs. If they haven’t responded appropriately in a few days, I’ll post their name and start the dispute process with eBay. Fortunately this only affects the family room, so as long as the other eBay seller doesn’t screw me, the rest of the place will be done.

…except for the bathroom lights, which have these stupid multi-globe-bulb fixtures that will need to be replaced; no way I’m buying 21 LED smartbulbs to light 2.5 baths. In fairness, though, I haven’t had a single one of them burn out in 18 years.

Is there any franchise they’ve missed?

Seriously, Funko: McDuck, Balrog, Blossom, Chibi Sailor Moon, Bulma, Faye, Jack, Joey Ramone, Bob Ross, Ted, Jaws, Kevin, and coming soon, Queen Elizabeth and Kurt Cobain.

I think the Bond Golden Girl figure is in poor taste, but I confess I’m a bit tempted by the Dark Willow.

Bathtime Buddies…

No, not the kind with cheesecake. Last month, Wonderduck stumbled across an onsen-themed set of rubber-duck capsule toys (which reminds me, “no, Amazon won’t ship it internationally, but I have a reshipping agent that I use, and I have some other stuff that needs handled that way as well; I just need to update my account with them, because we’re moving our office”).

In the comments, I linked to one of the many bucket-o-duckies products on Amazon Japan. Here’s what it looks like when someone puts them to good use:


Dubious capsule toys

Honestly, I’m not sure I’d want to put 5 bucks into this machine. エロ過ぎる = ero-sugiru = “too sexy”.


Now, if it dispensed pokemon balls containing horny monster girls… oh, wait, that’s an anime plot.

Duck Soap

A little something we stumbled across while heading for the Terry Fator show at The Mirage.

Great show, by the way.

And if you want some really good Italian food in Vegas, go to Nora’s.

Reasons to have an OpenBSD router at home, Amazon Wand Edition

Since the new Amazon Dash Wand is effectively free for Prime customers, and it gives you a home-automation controller, bar-code scanner, and a hand-held Alexa device that is not always listening, I ordered one.

When it arrived this morning, I followed the instructions, opened the Amazon app on my iPhone, and went through the setup process. Wifi Fail. Wifi Fail. Wifi Fail. “You should contact customer service”.

The first 20+-minute call went through a bunch of cookbook questions about who my Internet provider was, and how to change the channel on my router. I had a brief flashback to the Seventies, then realized their script assumed Comcast meant “all-in-one cable modem, router, and wireless access point”. I played along, knowing this would make no difference, and the call eventually ended in an RMA.

I was curious to see if it really was a wireless problem, so I logged into the OpenBSD router, checked the DHCP logs, and found an entry for a new Amazon MAC address. I fired up tcpdump and went through the setup again, and sure enough, the device got DHCP, connected to the Internet for DNS, connected to an Amazon server, and then started trying to talk to a public (non-Amazon) NTP server to set its date and time.

It failed every time. Annoyingly, it wasn’t even looking in DNS for its NTP server; the addresses were hardcoded in either the build or the config it had downloaded.

So, armed with the knowledge that the hardware was fine, I tried to get back through to customer service with this knowledge. An hour later, after two different people tried to debug phone app, wireless and bluetooth problems (including telling me to turn on GPS on my phone!), I finally got someone to twiddle the right bits so it could connect to servers that were up, and then cancel the RMA.

Now I have a Dash Wand. Ho, ho, ho.

Corpus Fun

I’m pretty sure “futanari” is not Dutch. Also “gmail”, “iphone”, “http”, “cialis”, and “jackalope”. “bewerkstelligen”, on the other hand, fits right in.

For my new random word generator, I’ve been supplementing and replacing the small language samples from Chris Pound’s site. The old ones do a pretty good job, but the new generator has built-in caching of the parsed source files, so it’s possible to use much larger samples, which gives a broader range of language-flavored words. 5,000 distinct words seems to be the perfect size for most languages.

Project Gutenberg has material in a few non-English languages, and it’s easy to grab an entire chapter of a book. Early Indo-European Online has some terrific samples, most of them easily extracted. But what looked like a gold mine was Deltacorpus: 107 different languages, all extracted with the same software and tagged for part-of-speech. And the range of languages is terrific: Korean, Yiddish, Serbian, Afrikaans, Frisian, Low Saxon, Swedish, Catalan, Haitian Creole, Irish, Kurdish, Nepali, Uzbek, Mongol, etc, each with around 900,000 terms. The PoS-tagging even made it easy to strip out things that were not native words, and generate a decent-sized random subset.

Then I tried them out in the generator, and started to see anomolies: “jpg” is not generally found in a natural language, getting a plausible Japanese name out of a Finnish data set is highly unlikely, etc. There were a number of oddballs like this, even in languages that I had to run through a romanizer, like Korean and Yiddish.

So I opened up the corpus files and started searching through them, and found a lot of things like this:

437 바로가기    PROPN   
438 =   PUNCT   
439 http    VERB    
440 :   PUNCT   
441 /   PUNCT   
442 /   PUNCT   
443 www NOUN    
444 .   PUNCT   
445 shoop   NOUN    
446 .   PUNCT   
447 co  NOUN    
448 .   PUNCT   
449 kr  INTJ    
450 /   PUNCT   
451 shop    PROPN   
452 /   PUNCT   
453 goods   NOUN    
454 /   PUNCT   
455 goods_list  NOUN    
456 .   PUNCT   
457 php NOUN    
458 ?   DET 
459 category    NOUN    
460 =   PUNCT   
461 001014  NUM 

1   우리의  ADP 
2   예제에서    NOUN    
3   content X   
4   div에   NOUN    
5   float   VERB    
6   :   PUNCT   
7   left    VERB    
8   ;   PUNCT   

Their corpus-extraction script was treating HTML as plain text, and the pages they chose to scan included gaming forums and technology review sites. Eventually I might knock together a script to decruft the original sources, but for now I’m just excluding the obvious ones and skimming through the output looking for words that don’t belong. This is generally pretty easy, because most of them are obvious in a sorted list:


Missing some of them isn’t a big problem, because the generator uses weighted-random selection for each token, and if a start token only appears once, it won’t be selected often, and there are few possible transitions. Still worth cleaning up, since they become more likely when you mix multiple language sources together.

“Need a clue, take a clue,
 got a clue, leave a clue”