Perfect Brains...

Two interesting studies publicized last week:



The first studies SuperAgers, defined as persons aged 80 and above, but with memories that are as sharp as those of healthy persons decades younger [http://www.kurzweilai.net/superager-brains-yield-new-clues-to-their-remarkable-memories]. Their unusual brain signature has three common components when compared with normal persons of similar ages: a thicker region of the cortex; significantly fewer tangles (a primary marker of Alzheimer’s disease), and a whopping supply of a specific neuron - von Economo - linked to higher social intelligence. It’s thought that these von Economo neurons play a critical role in the rapid transmission of behaviorally relevant information related to social interactions.



In the other [http://medicalxpress.com/news/2015-02-young-meditation-age-related-loss-gray.html], the scientists looked specifically at the association between age and gray matter. They compared 50 people who had mediated for years and 50 who didn't. People in both groups showed a loss of gray matter as they aged. But the researchers found among those who meditated, the volume of gray matter did not decline as much as it did among those who didn't. Accumulating scientific evidence that meditation has brain-altering capabilities might ultimately allow for an effective translation from research to practice, not only in the framework of healthy aging but also pathological aging.



So the question is what effect would have group meditation? Couldn't we preserve gray matter and increase number of von Economo neurons at the same time?

Define Google

Google updates search to show synonyms, translation http://www.androidauthority.com/google-updates-search-258608/

Anaphora and other 'deep' knowledge issues

http://m.newyorker.com/online/blogs/elements/2013/08/why-cant-my-computer-understand-me.html

The meaning behind words (Google)

 We’re on the cusp of deep learning for the masses. You can thank Google later — Tech News and Analysis: "word2vec. Google calls it “an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words.”"
...
"Kaggle’s Howard calls word2vec the “crown jewel” of natural language processing. “It’s the English language compressed down to a list of numbers,” he said.

Word2vec is designed to run on a system as small as a single multicore machine (Google tested its underlying techniques over days across more than 100 cores on its data center servers). Its creators have shown how it can recognize the similarities among words (e.g., the countries in Europe) as well as how they’re related to other words (e.g., countries and capitals). It’s able to decipher analogical relationships (e.g., short is to shortest as big is to biggest), word classes (e.g.,carnivore and cormorant both relate to animals) and “linguistic regularities” (e.g., “vector(‘king’) – vector(‘man’) + vector(‘woman’) is close to vector(‘queen’))."

Why Technology Is Key to Overcoming the Language Barrier

Why Technology Is Key to Overcoming the Language Barrier (Jonathan Lichtman, senior vice president of SAIC): "The two main approaches to machine translation are generally rule-based (RBMT) and statistical (SMT). RBMT uses manually programmed rules to translate one language to another. SMT involves the use of previously translated content to determine which words and phrases have the highest possibility of conveying the correct meaning. Both have advantages and disadvantages, but by combining the two approaches together in the same engine — a hybrid approach — language pairs can be developed faster and with less pre-translated “training” data.

That is an important leap in translation technology because it addresses two main barriers to the automation and accuracy of a language pair: not having enough translated data available and the constant evolving nature of language."

'via Blog this'

Lernout & Hauspie's Dragon Systems Purchase: a Horror Story Still Reverberating Today - NYTimes.com

We were all surprised when even Dragon Systems (like most NLP companies at that time) gave up and decided to sell to their biggest competitor, but as this article demonstrates, it wasn't that simple...

Goldman Sachs and a Sale Gone Horribly Awry - NYTimes.com: "The deal, the $580 million sale of a highflying technology company, Dragon Systems, had just been approved by its board and congratulations were being exchanged. But even then, at that moment of celebration, there was a sense that something was amiss.

The chief executive of Dragon had received a congratulatory bottle from the investment bankers representing the acquiring company, a Belgian competitor called Lernout & Hauspie. But he hadn’t heard from Dragon’s own bankers at Goldman Sachs."

'via Blog this'

Official google.org Blog: The Endangered Languages Project: Supporting language preservation through technology and collaboration

Official google.org Blog: The Endangered Languages Project: Supporting language preservation through technology and collaboration: " Endangered Languages Project, a website for people to find and share the most up-to-date and comprehensive information about endangered languages. Documenting the 3,000+ languages that are on the verge of extinction (about half of all languages in the world) is an important step in preserving cultural diversity, honoring the knowledge of our elders and empowering our youth. Technology can strengthen these efforts by helping people create high-quality recordings of their elders (often the last speakers of a language), connecting diaspora communities through social media and facilitating language learning."