Computer Science  

Computer science has not only changed the way we conduct our lives, it has also created new jobs, and even helped preserve antiquity. Here are four concrete ways that computer science has changed the world.

Computer science has changed the world in ways that people couldn't have imagined just 20 or 30 years ago. Computers have not only changed the way we conduct our personal lives, they have also opened up jobs, created new jobs, and even helped preserve antiquity. Here are four concrete ways that computer science has changed the world.

Translation

The global economy dictates that documents be translated quickly. From the newest Harry Potter novel to the most pressing legal documents, translation bridges the gap between cultures. In the past, this painstaking process existed in the realm of language professionals. In the computer age, it still does, but the process is sped up considerably thanks to computer science, according to an article on the Wired website.

Specifically, a computer is able to scan patterns, words, and phrases between two languages faster than any human can. While translation will probably always require the aid of human translators, using computers helps language professionals more quickly spot and correct problems than they could have on their own.

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Sorting Information

Millions and millions of bits of information explode onto the Internet every day. Because of this, new jobs in networking, database management, and software creation exist today that didn't 20 years ago. For the person who wants to learn the skills to manage all this new information, a degree in computer science is practical.

Some of the fastest-growing jobs, including translation, forensic science, and statisticians rely on being able to process information quickly. The person who can create the software to help this process along and to help sort it in a meaningful way will find a position in tomorrow's new economy. Programs like an online master’s of computer science can help people break into a career in the tech industry.

Computing Scientific Probabilities

Much of the science world relies on using mathematics on a large scale. Being able to process the statistical probability of real-world problems like the spread of disease means scientists get answers more quickly to pressing problems. Computer science leads the charge in this endeavor. Aside from projecting outcomes, computer science has another use here. Scientists around the globe can more readily share information with their colleagues, allowing them to collaborate on big projects without ever leaving home.

Creative Commons

Documents, pictures, videos, and illustrations in the realm of the Creative Commons got a major boost from computer science. For example, one of the largest collections of public domain books is on the Project Gutenberg website. Novels like "Frankenstein," "Dracula," and "The Metamorphosis," along with some more obscure books are available free of charge on this online library. At the time of this writing, Project Gutenberg has transcribed and uploaded 50,000 classic and antique books for the public to enjoy. Other uses for this type of project include museum databases and online genealogy sites.

Computer science has given us more than just access to our daily emails. As the above examples show, it has changed the way we communicate, the way we catalogue information, the way we participate in the scientific process, and given us access to the most important ancient texts. Truly, not since the invention of the printing press has technology world changed so much.

By Anica Oaks

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 Machine Learning  

Deep learning start-up MetaMind has published details of a system that is more accurate than other language processing methods.  The company is developing technology designed to be capable of a range of different artificial-intelligence tasks.

Google and Facebook, are investing huge sums into the  research and development of improved artificial intelligence algorithms for processing language.

Around the world, various research groups are making steady progress toward improving a computer's language skills especially using recent advances in machine learning.

"The insight—and it’s almost trivial—is that every task in NLP is actually a question-and-answer task."

The most recent development in Natural Language Processing (NLP) comes from a start-up called MetaMind, which has developed a language recognition system that is more accurate than the leading systems available on the market.

MetaMind has published new research detailing how their neural networking system uses a kind of artificial short-term memory to answer a wide range of questions about a piece of natural language.

According to MetaMind, the system can answer everything from very specific queries about what the text describes to more general questions like “What’s the sentiment of the text?” or “What’s the French translation?” The research, due to appear next week at Arxiv.org, a popular online repository for academic papers, echoes similar research from Facebook and Google, but it takes this work at step further.

MetaMind was founded by Richard Socher, a prominent machine-learning expert who obtained his PhD from Stanford where he worked with Chris Manning and Andrew Ng. Socher tested his algorithms using a data set compiled by Facebook for measuring machine performance at routine comprehension tasks. MetaMind's software ended up outperforming Facebook's own algorithms.

The new technology is designed to be capable of different artificial-intelligence tasks including image classification and sentiment analysis. The work is indicative of ongoing success in giving machines more efficient learning and comprehension.

“The insight—and it’s almost trivial—is that every task in NLP is actually a question-and-answer task,” Socher told Wired.

A key to this progress is an approach known as deep learning, a relatively new field of artificial intelligence research that aims to perfect tasks such as face and language recognition.

"[MetaMind's] deep learning technology is going to have enormous impact in multiple industries …” says Marc Benioff, the CEO of Salesforce.

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The MetaMind system processes data using what Socher calls “episodic memory.” Like how Demis Hassabis describes DeepMind's algorithms, this is something akin to the way the brain treats short-term memory in the hippocampus. The system must “remember” one fact before determining what another is, based on the natural language data supplied.

“You can’t do transitive reasoning without episodic memory,” Socher says.

And, he explains, you can use much the same setup to do analyze sentiment or translate words into a new language. “One model—one dynamic memory network—can solve these very different problems,” he says.

MetaMind's founder says that his work has made significant progress toward more generalizable artificial intelligence. “This idea of adding memory components is something that’s in the air right now,” he says. “A lot of people are building different kinds of models, but our goal is to try to find one model that can perform lots of different tasks.”

In the talk below, Socher describes how deep learning algorithms can learn language.




SOURCE  MIT Technology Review

By 33rd Square

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 Machine Learning  

Skype Translator gives you the ability to speak another language without learning one. Simply set up a Skype video or voice call with someone who speaks another language and start talking. Translator is currently available in English and Spanish. More languages are coming soon.

After years of development, if Microsoft's Skype Translator lives up to the hype, this could be one of the most powerful communication technologies ever created.

The company recently previewed Skype Translator to two elementary school classes—one in Washington and one in Mexico City. A few rounds of “Mystery Classroom” was all it took for these students to discover the potential of translator to break down language barriers and bring people together.

The Skype Translator project offers near real-time translation of both spoken and written languages for participants in Skype conversations, making it possible for two people who speak completely different languages to talk with each other with virtually no barriers to understanding. The preview program starts with support for English and Spanish spoken translation, as well as over 40 languages for real-time text chat.

As of now, the translator is limited to users of Windows 8.1 software.

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With Skype Translator,  Microsoft invested in speech recognition, automatic translation and machine learning technologies for more than a decade, to develop this tool, and according to the company, Skype Translator is only "the most recent and visible example."

"This is just the beginning of a journey that will transform the way we communicate with people around the world. Our long-term goal for speech translation is to translate as many languages as possible on as many platforms as possible and deliver the best Skype Translator experience on each individual platform for our more than 300 million connected users."

By using machine learning, Skype Translator will get 'smarter' that the more it is used. By learning from the training data during this preview stage, along with all of its nuances, the software can learn to better recognize and translate the diversity of topics, accents and language variation of actual Skype Translator users.

According to Microsoft, "This is just the beginning of a journey that will transform the way we communicate with people around the world. Our long-term goal for speech translation is to translate as many languages as possible on as many platforms as possible and deliver the best Skype Translator experience on each individual platform for our more than 300 million connected users."

So far, the early tests look promising, and it will be interesting to see how it performs in real-world situations with more complex dialog.




SOURCE  Tech Crunch

By 33rd Square

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