January 23, 2013
Soramimi (‘mishearing’; [feigned] ‘deafness’) and Soramimi kashi (‘misheard lyrics’) are Japanese terms for homophonic translation of song lyrics, that is, interpreting lyrics in one language as similar-sounding lyrics in another language. A bilingual soramimi word play contrasts with a monolingual mondegreen (mishearing a phrase as a result of near-homophony, in a way that gives it a new meaning).
And example of Soramimi kashi is the Moldovan band O-Zone’s song ‘Dragostea din tei’ (named from the words in the opening of the song), known on the web as the ‘Numa Numa’ song. The refrain of the original song (in Romanian) is: ‘Vrei să pleci dar nu mă, nu mă iei…’ (‘You want to leave but you don’t want, don’t want to take me…’) A soramimi version, from the Japanese flash animation ‘Maiyahi,’ translates these words as: ‘Bei sa, beishu ka, nomanoma-yei!’ (‘Rice, is it, rice wine, drink it drink it yeah!’)
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January 23, 2013
A mondegreen [mon-di-green] is the mishearing or misinterpretation of a phrase as a result of near-homophony, in a way that gives it a new meaning. It most commonly is applied to a line in a poem or a lyric in a song. American writer Sylvia Wright coined the term in her essay ‘The Death of Lady Mondegreen,’ published in ‘Harper’s Magazine’ in 1954. The phenomenon is not limited to English, with examples cited by Fyodor Dostoyevsky, in the Hebrew song ‘Háva Nagíla’ (‘Let’s Be Happy’), and in Bollywood movies.
A closely related category is ‘soramimi’—songs that produce unintended meanings when homophonically translated to another language. The unintentionally incorrect use of similar-sounding words or phrases in speaking is a malapropism. If there is a connection in meaning, it can be called an ‘eggcorn.’ If a person stubbornly sticks to a mispronunciation after being corrected, that can be described as ‘mumpsimus.’
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January 23, 2013
Second Variety is an influential short story by Philip K. Dick first published in ‘Space Science Fiction’ magazine in 1953. A nuclear war between the Soviet Union and the West has reduced much of the world to a barren wasteland.
The war continues however among the scattered remains of humanity. The Western forces have recently developed ‘claws,’ which are autonomous self-replicating robots to fight on their side. It is one of Dick’s many stories in which nuclear war has rendered the Earth’s surface uninhabitable. The story was adapted to the movie ‘Screamers’ in 1995.
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January 23, 2013
‘The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary’ is an essay by Eric S. Raymond on software engineering methods, based on his observations of the Linux kernel development process and his experiences managing an open source project, fetchmail. It examines the struggle between top-down and bottom-up design. It was first presented by the author at the Linux Kongress in 1997 in Germany and was published as part of a book of the same name in 1999.
The essay contrasts two different free software development models: the Cathedral model, in which source code is available with each software release, but code developed between releases is restricted to an exclusive group of software developers. And, the Bazaar model, in which the code is developed over the Internet in view of the public. Raymond credits Linus Torvalds, leader of the Linux kernel project, as the inventor of this process. Raymond also provides anecdotal accounts of his own implementation of this model for the Fetchmail project.
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January 23, 2013
Neat and scruffy are labels for two different types of artificial intelligence research. ‘Neats’ consider that solutions should be elegant, clear and provably correct. ‘Scruffies’ believe that intelligence is too complicated (or computationally intractable) to be solved with the sorts of homogeneous system such neat requirements usually mandate. Much success in AI came from combining neat and scruffy approaches. For example, there are many cognitive models matching human psychological data built in cognitive architectures Soar and ACT-R.
Both of these systems have formal representations and execution systems, but the rules put into the systems to create the models are generated ad hoc. The distinction was originally made by AI theorist Roger Schank in the mid-1970s to characterize the difference between his work on natural language processing (which represented commonsense knowledge in the form of large amorphous semantic networks) from the work of John McCarthy, Allen Newell, Herbert A. Simon, Robert Kowalski and others whose work was based on logic and formal extensions of logic.
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January 23, 2013
Moravec’s paradox is the discovery by artificial intelligence and robotics researchers that, contrary to traditional assumptions, high-level reasoning requires very little computation, but low-level sensorimotor skills require enormous computational resources.
The principle was articulated by Hans Moravec, Rodney Brooks, Marvin Minsky and others in the 1980s. As Moravec writes, ‘it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.’
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January 23, 2013
The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not real intelligence. Technology journalist Pamela McCorduck writes: ‘It’s part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was chorus of critics to say, ‘that’s not thinking.”
AI researcher Rodney Brooks complains: ‘Every time we figure out a piece of it, it stops being magical; we say, Oh, that’s just a computation.’ As soon as AI successfully solves a problem, the problem is no longer a part of AI. McCorduck calls it an ‘odd paradox,’ that ‘practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful in, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the ‘failures,’ the tough nuts that couldn’t yet be cracked.’
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