To recreate this strangeness, go to Google Translate, select English to Spanish, type in “Heath Ledger is dead”, hit translate, and bask in the glow of Google’s oddity (at least, for as long as it lasts until they possibly fix it).
(Thanks, Josh, for the story, which he found on 4chan)
When I was a kid in the 80s poking around on my ol’ Apple //c, I loved the Beagle Bros, a company that made great software and had a very unique style. Their combination of vintage wordcut artwork with hobbyist programming was great fun (here is a great example).
The Beagle Bros company logo depicted the founders as stylized 19th century figures:
My memory of the Beagle Bros was stirred recently when I came across this logo:
Is this company stealing from the iconography of the long-dormant Beagle Bros software empire? Or is this type of logo very common, and I’m just crazy? Wait, don’t answer that.
(by the way, check out the Beagle Bros online museum)
Posted in computing, crackbaby, meaningless, tech, toys
Another quick update to the Zodiac webtoy: now there are links to flip and rotate the ciphertext. This was a popular feature request that I finally got around to implementing. Enjoy!
I’ve finally made some more updates to the Zodiac webtoy! The biggest change is the addition of simple letter-frequency statistics.
Here is the list of noteworthy changes:
The webtoy seems to be getting much slower in Internet Explorer 6. I’ve not tested it in Internet Explorer 7. But it works pretty well in Firefox and Safari. I am afraid of all the horrible, horrible JavaScript code that I wrote – Please let me know of any problems you find! If you find the new version to be too crappy, you can still use the old version by clicking here.
Posted in computing, meaningless, tech, toys, zodiac
I enjoyed this brief glimpse of the underbelly of Apple’s product marketing. An interviewer asks a touchy question about iTunes acting as a monopoly, and Apple’s PR folks start to freak out:
Such is the ugly reality of companies attempting to control expectations.
From Microsoft’s Help and Support pages:
Computer Randomly Plays Classical Music
View products that this article applies to.
Article ID : 261186
Last Review : March 27, 2007
Revision : 3.3
This article was previously published under Q261186
SUMMARY
During normal operation or in Safe mode, your computer may play “Fur Elise” or “It’s a Small, Small World” seemingly at random. This is an indication sent to the PC speaker from the computer’s BIOS that the CPU fan is failing or has failed, or that the power supply voltages have drifted out of tolerance. This is a design feature of a detection circuit and system BIOSes developed by Award/Unicore from 1997 on.
Anyone remember the famous scene in 2001 when HAL the computer gets shut down?
[HAL’s shutdown]
HAL: I’m afraid. I’m afraid, Dave. Dave, my mind is going. I can feel it. I can feel it. My mind is going. There is no question about it. I can feel it. I can feel it. I can feel it. I’m a… fraid. Good afternoon, gentlemen. I am a HAL 9000 computer. I became operational at the H.A.L. plant in Urbana, Illinois on the 12th of January 1992. My instructor was Mr. Langley, and he taught me to sing a song. If you’d like to hear it I can sing it for you.
Dave Bowman: Yes, I’d like to hear it, HAL. Sing it for me.
HAL: It’s called “Daisy.”
[sings while slowing down]
HAL: Daisy, Daisy, give me your answer do. I’m half crazy all for the love of you. It won’t be a stylish marriage, I can’t afford a carriage. But you’ll look sweet upon the seat of a bicycle built for two.
This fortune I read today seems like a natural follow-up to my previous post:
This is the first numerical problem I ever did. It demonstrates the
power of computers:Enter lots of data on calorie & nutritive content of foods. Instruct
the thing to maximize a function describing nutritive content, with a
minimum level of each component, for fixed caloric content. The
results are that one should eat each day:1/2 chicken
1 egg
1 glass of skim milk
27 heads of lettuce.— Rev. Adrian Melott
All you have to do is help Netflix read people’s minds!
The Netflix Prize is a contest that has been going on since October 2006. I didn’t hear about it until today. When you rate movies on the Netflix DVD rentals site, their proprietary Cinematch algorithm will predict which other movies you might like based on ratings that have been made by all Netflix users. It is very similar to Amazon’s “people who bought X also bought Y” feature. The Netflix Prize challenge is to come up with a new prediction system that is 10% more accurate than Cinematch. Whoever does this will get the top prize of $1,000,000. Netflix is also rewarding a periodic “progress prize” of $50,000 to people who can beat the last progress prize winner by 1%. The current progress prize winner, an AT&T Labs team named BellKor, has a technique that yields a prediction improvement of 8.5% over Cinematch. Read about their technique here. Their technique makes my brain hurt — it blends together 107 different results from a large ensemble of data mining models, including neighborhood-based models (k-NN), factorization models (such as Ridge regression), regressions based on Gaussian priors, restricted Boltzmann Machines, asymmetric factor models, and regression models (using principal components analysis for feature selection, and SVD vectors as predictor variables). Basically, they packed a data mining shotgun with as much shot as they could find, and pulled the trigger. That’s a hell of a lot of work for $50,000!
Figure 1: Oh, no! Data mining engineers found out that I like terrible movies!
By comparison, Netflix’s own Cinematch algorithm uses the following techniques, as quoted in their Netflix Prize FAQ:
How does Cinematch do it?
Straightforward statistical linear models with a lot of data conditioning. But a real-world system is much more than an algorithm, and Cinematch does a lot more than just optimize for RMSE. After all, we have a website to support. In production we have to worry about system scaling and performance, and we have additional sources to data we can use to guide our recommendations.
Netflix has begun a very interesting bounty hunt. As of today, 23021 teams from 164 different countries are clamoring for the cash. I love the idea of putting up public bounties for innovation – the X-Prize comes to mind, particularly the Google-sponsored lunar X prize.
Computer science professor Dr. Ryan Garlick of University of North Texas has a very interesting setup for his symbolic processing course this semester: Each student’s objective is to contribute towards cracking the unsolved 340-character Zodiac cipher.
From a UNT news article:
Cracking the cipher is a difficult task for more than one reason, which is why Garlick, along with his students, are currently developing several computer software techniques that will hopefully make the process far more feasible.
“There are just too many possible keys to look at them all,” Garlick said. “There are 63 different symbols, and each can represent 26 possible letters (we think), which is just too many possible combinations to evaluate them all.”
This is where the computer techniques they are fashioning will hopefully come in handy. Corey Rosemurgy, an Austin senior and computer science major in Garlick’s class, is currently developing a genetic algorithm to solve the cipher.
“The genetic algorithm that I am developing models itself after the inherent properties of biological evolution and the theory of survival of the fittest where only the strong survive,” Rosemurgy said.
I was very interested to discover this course, since I have been working on a similar approach since around March of this year. In my free time (what little there is), I’ve been running experiments using ECJ, a Java-based evolutionary computing framework. So far, my focus has been on trying to get the algorithm to solve Zodiac’s 408-character cipher, which has a known solution. Using a dictionary-oriented approach, the algorithm was able to find the correct solution using a limited 400-word dictionary. Now I am trying to improve this by adding more words to the dictionary used by the algorithm. The basic idea is to get this test case working well before attempting to have it solve the really difficult 340-character cipher. This has proven to be very difficult, because the search space (number of possible solutions) is extremely large, and there is exactly one correct solution. The needle is tiny, and the haystack is vast. Evolutionary computing methods tend to be better-suited for finding really good solutions, rather than the one best solution, so this approach is quite challenging (if not flawed).
I’m glad that many people are still working on this problem; it would be nice to finally find a solution. Still, there is still a strong possibility that there is no solution, and the cipher is just gibberish designed to keep people unnecessarily busy. If so, then the Zodiac killer succeeded beyond his wildest dreams.
More info:
article | course page (of interest here are the syllabus and powerpoint presentation) | google code page and code repository for zodiac decoder software (this is the repository of software used and developed by students in the course)
Another evil incarnation of “turduckenology” arose yesterday at work. From my virtual Windows XP instance running inside Parallels Desktop on my Mac, I needed to make a remote desktop connection to my Windows XP desktop, which is running a Virtual PC 2007 instance of a virtual machine that itself had a remote desktop connection over a VPN to a client machine on their network:
That’s me diving through the rabbit hole of *four* instances of Windows via my Mac, so I can install our software on a client’s machine. The horror!
What really bends my noodle during this is figuring out how to copy and paste all the way up and down the chain of Windows instances. And it’s really easy to lose track of which Windows XP you are in when you are clicking around – it’s easy to run the wrong program in the wrong place!
These are the kinds of memories that will preoccupy my demented dreams when I am an old man in a nursing home.
