On November 7, 2000, Hillary Rodham Clinton was elected to the United States Senate for the state of New York. Her election had several firsts - she was the first female Senator from New York and the only First Lady to run for public office. Clinton was sworn in on January 3, 2001 and she served as both a Senator and First Lady until January 20th.
Photograph of President William Jefferson Clinton, First Lady Hillary Rodham Clinton, and Chelsea Clinton Applauding during Election Night at the Grand Hyatt Hotel in New York, New York, 11/07/2000
In this cartoon from the 1907 off-year election, political cartoonist Clifford Berryman reminds us of how elections reflect the public mood and, thus, of the importance of voting. Illustrated here, William Jennings Bryan, William Randolph Hearst, and President Theodore Roosevelt anxiously calculate the impact of state and local elections on their political futures. The books scattered around the floor suggest that forecasting the consequences of an election is “infinitesimal calculus.” Bryan went on to run unsuccessfully for President the next year, and Hearst ran unsuccessfully for Mayor of New York City in 1909. Roosevelt did not run for reelection and instead went into temporary retirement after his term expired.
Figgerin’ on the Returns by Clifford K. Berryman, 11/7/1907, U.S. Senate Collection, U.S. National Archives (1693465)
From our friends at the Association of Centers for the Study of Congress and their new tumblr!
This is probably the most painful bug report I’ve ever read, describing in glorious technicolor the steps leading to Knight Capital’s $465m trading loss due to a software bug that struck late last year, effectively bankrupting the company.
The tale has all the hallmarks of technical debt in a…
To translate one language into another, find the linear transformation that maps one to the other. Simple, say a team of Google engineers
Computer science is changing the nature of the translation of words and sentences from one language to another. Anybody who has tried BabelFish or Google Translate will know that they provide useful translation services but ones that are far from perfect.
The basic idea is to compare a corpus of words in one language with the same corpus of words translated into another. Words and phrases that share similar statistical properties are considered equivalent.
The problem, of course, is that the initial translations rely on dictionaries that have to be compiled by human experts and this takes significant time and effort.
Now Tomas Mikolov and a couple of pals at Google in Mountain View have developed a technique that automatically generates dictionaries and phrase tables that convert one language into another.
The new technique does not rely on versions of the same document in different languages. Instead, it uses data mining techniques to model the structure of a single language and then compares this to the structure of another language.
“This method makes little assumption about the languages, so it can be used to extend and reﬁne dictionaries and translation tables for any language pairs,” they say.
The new approach is relatively straightforward. It relies on the notion that every language must describe a similar set of ideas, so the words that do this must also be similar. For example, most languages will have words for common animals such as cat, dog, cow and so on. And these words are probably used in the same way in sentences such as “a cat is an animal that is smaller than a dog.”
The same is true of numbers. The image above shows the vector representations of the numbers one to five in English and Spanish and demonstrates how similar they are.
This is an important clue. The new trick is to represent an entire language using the relationship between its words. The set of all the relationships, the so-called “language space”, can be thought of as a set of vectors that each point from one word to another. And in recent years, linguists have discovered that it is possible to handle these vectors mathematically. For example, the operation ‘king’ – ‘man’ + ‘woman’ results in a vector that is similar to ‘queen’.
It turns out that different languages share many similarities in this vector space. That means the process of converting one language into another is equivalent to finding the transformation that converts one vector space into the other.
This turns the problem of translation from one of linguistics into one of mathematics. So the problem for the Google team is to find a way of accurately mapping one vector space onto the other. For this they use a small bilingual dictionary compiled by human experts–comparing same corpus of words in two different languages gives them a ready-made linear transformation that does the trick.
Having identified this mapping, it is then a simple matter to apply it to the bigger language spaces. Mikolov and co say it works remarkably well. “Despite its simplicity, our method is surprisingly effective: we can achieve almost 90% precision@5 for translation of words between English and Spanish,” they say.
The method can be used to extend and refine existing dictionaries, and even to spot mistakes in them. Indeed, the Google team do exactly that with an English-Czech dictionary, finding numerous mistakes.
Finally, the team point out that since the technique makes few assumptions about the languages themselves, it can be used on argots that are entirely unrelated. So while Spanish and English have a common Indo-European history, Mikolov and co show that the new technique also works just as well for pairs of languages that are less closely related, such as English and Vietnamese.
That’s a useful step forward for the future of multilingual communication. But the team says this is just the beginning. “Clearly, there is still much to be explored,” they conclude.
Ref: arxiv.org/abs/1309.4168: Exploiting Similarities among Languages for Machine Translation
Hilary Hahn - Sibelius Violin Concerto (part 1) (by Oxy151268)
The ongoing crisis at the Fukushima No. 1 plant is a sign that the world needs to seriously rethink nuclear safety and consider possibly ending its dependence on atomic power, the former chairman of the U.S. Nuclear Regulatory Commission said Tuesday in Tokyo.
“When you look at what happened around the Fukushima Daiichi (No. 1) area, it’s simply unacceptable,” as tens of thousands of people have been unable to return to their homes due to radioactive contamination, said Gregory Jaczko, who served as the top U.S. nuclear regulatory official for nearly three years until July 2012.
Given that Japan is extremely prone to earthquakes and tsunami, among other disasters, using nuclear power poses serious risks unless some kind of new technology is created to completely eliminate the possibility of severe accidents, Jaczko told reporters at the Foreign Correspondents’ Club of Japan.
However, Jaczko also said that creating such zero-risk technology is next to impossible.
Instead, Jaczko said, he hopes Japan pours its resources and energy into coming up with ways to function without atomic power.
“I think the Japanese people have the ability to do that,” he said.
While Japan’s atomic watchdog, the Nuclear Regulation Authority, is now examining requests from utilities to restart reactors, Jaczko stressed the importance of getting the public actively involved in the process.
“There needs to be a thorough public debate and a public dialogue to ensure that those decisions” have received as much support from the public as possible, said Jaczko, who headed the NRC when the Fukushima crisis erupted on March 11, 2011.
As for the ongoing issue of tainted groundwater flowing into the ocean at the No. 1 plant, Jaczko expressed befuddlement that the issue has only recently come under the spotlight.
“This was known from the beginning that there would potentially be these contamination problems,” he said.
Americans are increasingly abandoning property ownership as investment increases in the rental sector
Claude Debussy - Clair de lune (by MissBrina13)