me*dia*or

Since its publication back in November 2009 the UK government's Digital Economy Bill has caused torrents of criticism from the general public, to ISPs, artists and net neutrality defenders. Recently, BT's Chief Exec Ian Livingstone has expressed his opposition to the bill in a letter he sent to the Financial Times newspaper in which he talks about the urgent need to have the bill modified before becoming a law.

The boss of BT thinks that plans to cut off the alleged file sharers from the internet just go against natural justice and the measures that should be taken against piracy should focus on fines and certain proceeds that would solve the problem.

Major other internet players such as Google and Facebook but also broadband providers including Virgin and Orange have joined the cause and inked their name on the letter.

With respect to the clause empowering ISPs to block file-sharing websites which we talked about last week, many have warned already about the risk it represents for the UK's reputation for online business.

President Obama today spoke to the Export-Import Bank's annual conference and in the process lauded the Anti-Counterfeiting Trade Agreement, and gave a strong endorsement to aggressive IP enforcement.

What’s more, we’re going to aggressively protect our intellectual property. Our single greatest asset is the innovation and the ingenuity and creativity of the American people. It is essential to our prosperity and it will only become more so in this century. But it’s only a competitive advantage if our companies know that someone else can’t just steal that idea and duplicate it with cheaper inputs and labor. There’s nothing wrong with other people using our technologies, we welcome it –- we just want to make sure that it’s licensed, and that American businesses are getting paid appropriately. That’s why USTR is using the full arsenal of tools available to crack down on practices that blatantly harm our businesses, and that includes negotiating proper protections and enforcing our existing agreements, and moving forward on new agreements, including the proposed Anti-Counterfeiting Trade Agreement.

This may be the strongest pro-IP statement I've seen from Obama himself. But it should come as little surprise; here's what the Obama campaign said about the candidate's views on international IP enforcement:

Protect American Intellectual Property Abroad: The Motion Picture Association of America estimates that in 2005, more than nine of every 10 DVDs sold in China were illegal copies. The U.S. Trade Representative said 80 percent of all counterfeit products seized at U.S. borders still come from China. Barack Obama and Joe Biden will work to ensure intellectual property is protected in foreign markets, and promote greater cooperation on international standards that allow our technologies to compete everywhere.

So far, at least, all signs are that Obama is seeking to fulfill his campaign pledge.

(h/t Tech Daily Dose)

[via the newly minted Utne Tumblr! Strangely fitting format for Utne, actually.]

Tagged: bobby skinner, music, theremin, utne, utne tumblr, video, youtube

Just a heads up…

Pearl Jam will be returning to Saturday Night Live THIS upcoming Saturday night, March 13, to push some tunes off of their latest release Backspacer.

Eric did a cool post on Pearl Jam and their SNL history a couple of years ago, but here’s an updated look at their SNL performances.

1992

“Alive”

“Porch”

1994 (The year they somehow how got to perform 3, not the traditional 2 songs)

“Daughter”

“Not For” (Actually live take, not rehearsal!)

“Rearviewmirror”

Pearl Jam – Rearviewmirror – (SNL)
Uploaded by melkome. – Explore more music videos.

2006

“World Wide Suicide”

The band also debuted “Severed Hand”, but a video of that is hard to come by. I did, however, manage to find promos for that episode.

In other Pearl Jam news, the band just announced a mini US tour for May, in addition to their May 1 headlining slot at the New Orleans Jazz & Heritage Foundation Festival.

Here be dates:
May 3rd Kansas City, MO Sprint Center
May 4th St. Louis, MO Scottrade Center
May 6th Columbus, OH Nationwide Arena
May 7th Noblesville, IN Verizon Wireless Music Center
May 9th Cleveland, OH Quicken Loans Arena
May 10th Buffalo, NY HSBC Arena
May 13th Bristow, VA Jiffy Lube Live
May 15th Hartford, CT XL Center
May 17th Boston, MA TD Garden
May 18th TBD
May 20th New York, NY Madison Square Garden
May 21st New York, NY Madison Square Garden

Post from: Evolvor Media

This week we wrote about Google's Translate application and how it could eventually change the way people communicate, overcoming the language barriers that have long separated human populations. Franz Josef Och leads the machine translation (MT) team at Google, and has been the driving force behind much of the company's progress on the technology. The following is an edited transcript of a recent interview with Och.

How often do you add new languages to Google Translate?

Since October 2007, about every quarter or two, we've added a significant new number of languages. With each of those launches, we were also able to improve quality. So that in the last 2 1/2 years, we've reached 52 different languages, and I think we've made very nice strides in making the translation technology much better.

The last language we added was Haitian Creole. I myself am quite surprised that we can build MT technologies for very small languages. If you'd asked me three years ago, when would you have Haitian Creole, or Yiddish, or Icelandic, I would've said that with statistical machine translation (SMT), the challenge is how much data you have, so probably quite some time -- if it ever works. But now, thanks to the Internet and the availability of data there -- along with the improvement in algorithms -- we can build MT systems for those small languages and make them work reasonably well.

How is it possible to make the system work for a language like Yiddish, where there's not much text out there to train the machine with?

What made it possible is that Yiddish is very similar to German, and has a lot of similarities to loan-words from Hebrew and Polish. For those languages, we have large amounts of training data. So what we do is learn a lot of stuff from those other languages and then apply that to Yiddish.
How did Google figure out so early that it was going to be important to be able to translate the Web?

The language barrier is really a very big problem for communication. That's especially true for someone who speaks a language where just a small percentage of the information out there is available in that language. A language like Arabic -- where 1% of the information on the Web is in Arabic -- those people would have very limited access to information out there. The idea is, can we with the help of technology and machine translation -- can we break down the language barrier? So that anyone can access any information -- any text out there -- independent of the language.

When I joined Google, I actually talked to Larry [Page] about that on the phone, because I was concerned about why Google would do MT -- it's a search engine company. He emphasized that it's really core to the mission of Google, and not just a side thing where if times get hard, then MT will [fall by the wayside]. But people are very serious at Google about the mission and trying to achieve it.

It's now important in areas like search, where we now have the idea of cross-lingual translated search. If you have a question about something, you should be able to type a query in, and if the answer is in a Web page in a completely different language, you should be able to find that and understand the information there.

How close are you to making that a reality?

It's a hard question. In some sense, I believe we've made progress, and this is an exciting time for MT in the research community at large, but also here at Google. MT gets a lot more traction, more people are using it and it gets integrated into many different products. But on the other hand, there's obviously still a lot of work ahead of us. What we're doing is working on the core quality of machine translation.

So I feel my job is relatively safe. For quite a few years, there will be things still to be improved. Now, while the MT is pretty good for some of the big languages, like Portuguese and Spanish, for the small languages there's still a lot to be done so we can get similar translation quality. It will be a never-ending kind of improvement.

When you train the translator, you've got to get so-called parallel data sets, where every document occurs in at least two languages. Where do you get all of those translations from?

When we started, there were standard test sets provided by the Linguistic Data Consortium, which provides data for research and academic institutes. Then there are places like the United Nations, which have all their documents translated into the six official languages of the United Nations. And there's a vast pool of documents available there in the database, which has been very useful because the translation quality has been very good.

But then otherwise, it's kind of 'the Web.' Where all the documents that are on the Web that are translated contribute to learning translation for our algorithms. On the Web, the quality of the translation might not always be so good, so it's a very interesting and challenging research problem in itself to find all the translations and learn from the potentially noisy translations out there.

Our algorithms basically mine everything that's out there.

So it's sort of analogous to the way Google's Web crawler spiders Web pages?

It's similar. While the Web crawler is mining the whole Web and indexing it, then for the translation crawler is the subset of documents that include translations. The challenge is to find which texts are translated into another language -- and where to find the corresponding translation.

Do you use the data from Google Books as a source of translated data?

That's obviously a very interesting data source because a lot of books have been translated into many different languages. And especially for small languages where there's not that much Web content out there, there are actually books. But that area has its own interesting challenges, with OCR quality being an issue -- especially if you want small unusual languages. But we've started adding books too into the mix of data.

The Android version of Google Translate allows the user to speak to the application, and have his or her words translated. How does that part work?

The way we are doing speech recognition and MT are conceptually rather similar. Both of them learn from large amounts of data. For MT, we need to mine those translations, but for speech recognition, what you need is a speech signal that you tape somehow, and then the transcription. The more of the transcribed speech you have, the better the speech recognition quality.

You have similar learning algorithms. In translation we learn the correlation in how words relate from source to target language. In speech recognition, they would learn how certain phonemes would get pronounced.

Is it just short step from here to real time, speech-to-speech translation, a la "Star Trek's" universal translator?

To really do the integrated speech-to-speech translation, where you can have a phone call with someone and it would interpreted live? I believe that based on the technology that we have, and the improvement rate we have in the core quality of MT and speech recognition, that it should be possible to do that in the not-too-distant future.

Here's a short demonstration of the Google Translate app for Android:

-- David Sarno