Most models never get trained, but they exist in the ANN, because they share their weights with the trained models. Therefore, a single ANN represents many different models. However, his ANN's randomly shut of a substantial part (~50%) of the neurons during each learning iteration. If I understand correct, Hinton uses so many artificial neurons compared to the amount of learning data, that you would usually see an overfitting effect. I don't know much about artificial neural networks (ANN) and even less about natural ones, but I have the feeling that I learnt a lot from this video. ![]() Unfortunately, even though it was posted three times to HN Here is a GREAT talk by Geoffrey Hinton (the Prof running said lab) To know another language is to know another world. Beyond that I couldn't care less about race, job, creed, colour or any other bigoted perspective. Last, she needs to be able to play a musical instrument. She must either be able to ski or snowboard. Seconds, she needs to have spent a significant amount of time outside her own country. First, she needs to speak more than one language. ![]() To give you another perspective, I've always had a few deal-breakers I look for when meeting a girl I might otherwise be interested in. It's naturally dry in a way that English, for all it's adjectives, can never hope to be. What frustrates me is that no other language can do that, so I can't share that with my girlfriend, who is French. Insulting someone therefore consists of creatively stringing together colourful combinations of everyday words, mixing in the odd English, Malaysian or Zulu word, and then spoken with a religious fervour that cracks you up. Afrikaans is a modern language and has a relatively small vocabulary. There are subtler benefits - I speak three languages natively, and the part I love most about that is also the part that frustrates me most. A notable other is that you realize just how insanely silly, myopic and stupid nationalism is. Acceptance of religions, of gays, and of the Japanese seemingly chasing Americans around meeting rooms. This broadens one's mind, and that in turn leads to acceptance. Knowing - I chose that word specifically, as opposed to "speaking" - a language means knowing a culture. nathannecro in his comment below highlights an intellectual aspect. But just as riding horses is more a form of recreation these days than a basis for being employed, so too speaking another language will be a declining factor in seeking employment in the next decade. That's a broadening experience and an intellectual delight. ![]() It's still good for human beings to spend the time and effort to learn another human language (as so many HN participants have by learning English as a second language). The IBM Watson project is already targeted at becoming an expert system for medical diagnosis, and patient care markets will surely provide a lot of income for further development of software interpretation between human languages. This is often necessary, for example, for physician interviews of patients in emergency rooms or pharmacist consultations with patients buying prescribed drugs (where I last saw a posted notice on how to access such an interpretation service). Right now a lot of interpreters in the United States make a lot of part-time income from gigs that involve suddenly getting telephone calls and joining in to interpret a telephone conversation in two languages. We can't count on error-free machine interpretation between any pair of languages (human language is too ambiguous in many daily life cases for that), but if companies develop tested, validated software solutions for consecutive interpreting (what I usually did, and what is shown in the video) or simultaneous interpreting (the harder kind of interpreting in demand at the United Nations, where even in the best case it is not always done well), then those companies will be able to displace a lot of human professionals who rely on their language ability to make a living. EVERY time I've heard someone else interpreting English or Chinese into the other language, I have heard mistakes, and I am chagrined to remember mistakes that I made over the years. That's a reachable target with today's computer technology. The economics of the issue is that a machine interpreter just has to be as good as a human interpreter at the same cost. To someone who spent years learning Chinese as a second language, and then made my living for years as a Chinese-English interpreter, that was pretty impressive.
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