Computers and Languages

This short presentation provides an excellent video introduction to the basic principles and difficulties of machine translation. Two main methods of machine translation are discussed: Rule-based Translation and and Statistical Machine Translation. Each method poses particular difficulties. 1. Rule-based Translation uses lexical databases (dictionaries) and sets of linguistic rules to parse syntax, morphology and semantics. It's the semantic aspect that poses the greatest challenge. 2. Statistical Machine Translation analyses databases of books, documents and articles that have already been translated by humans, and uses these to identify correspondent language patterns. The quality of this method depends on the size of the database and the availability of samples for certain languages or styles of writing. The difficulties arise primarily with linguistic irregularities and shades of meaning. It seems that understanding language may be a unique facet of the human brain struct

In ' The charge of the chatbots: how do you tell who’s human online? ', published in the Observer newspaper November 18th 2018, Tim Adams reports on advances in artificial intelligence in the field of human-computer conversation. Some of the main points he makes are: 1. Advances in technology are creating chatbots that mimic human behaviour to a sophisticated extent:  “The ability of bots – a term which can describe any automated process present in a computer network – to mimic human online behaviour and language has developed sharply in the past three years.” 2. One dimension of the effectiveness of these entities is the human tendency to put our trust in other human voices: "these creations can exploit our tendency to ascribe trusted human characteristics to voices even if, on a rational level, we suspect that they are artificial. That psychology is as old as electronic communication itself." 3. The first such chatbot was developed in the USA in

John Naughton , writing in the Observer (18th November 2018) explains that the acronym CAPTCHA means 'Completely Automated Public Turing test to tell Computers and Humans Apart'.  In the Turing Test , a human interrogates two interlocutors - one human, one machine - and based on the interlocutors' responses, the human interrogator has to determine whether she is conversing with a machine or a human.  In other words, to what extent can a machine understand and utter human language patterns? Naughton argues, however, that the Turing Test has been turned on its head, and it is now machines asking we humans to prove that we are not machines.   He further explains that image-based CAPTCHA, like the one shown below, are being used to train machine-learning algorithms for driver-less cars. So we humans are training the machines, and as such we are being used as unpaid labour. Read the article online here

This track, by the amazing artist Moby, is great to listen to.  But not only that, the video conveys a disturbing message about human attachment to and uses of the mobile phone. The people in this video animation are blind to the suffering of a young woman; suffering that is caused by people having posted their phone-made film of her awkward dancing.  A crowd of people coldly film her suicidal plunge, and then walk away. At the end, the crowd walks blindly off the edge of a cliff, like lemmings; so fixated on their phones that they don’t look where they are going.  Are we all walking blindly off a precipice?  Are mobile phones killing our humanity?  Watch and decide for yourself. 

I've created this post simply to see if embedding the iframe tag is allowed. It seems to be. Here is an embedded exercise made with H5P , a brilliant online authoring platform.