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Emmy was once the world’s most advanced artificially intelligent composer, and because he’d managed to breathe a sort of life into her, he became a modern-day musical Dr. Frankenstein. She produced thousands of scores in the style of classical heavyweights, scores so impressive that classical music scholars failed to identify them as computer-created. Cope attracted praise from musicians and computer scientists, but his creation raised troubling questions: If a machine could write a Mozart sonata every bit as good as the originals, then what was so special about Mozart? And was there really any soul behind the great works, or were Beethoven and his ilk just clever mathematical manipulators of notes?

We asked the experts when they estimated AI would reach each of four milestones:

* passing the Turing test by carrying on a conversation well enough to pass as a human * solving problems as well as a third grade elementary school student * performing Nobel-quality scientific work * going beyond the human level to superhuman intelligence

We also asked how the timing of achieving these milestones would be affected by massive funding of $100 billion/year going into AGI R&D.

We also probed opinions on what the really intelligent AIs will look like — will they have physical bodies or will they just live in the computer and communicate with voice or text? And how can we get from here to there?

[W]e describe selected studies of experimental evolution with robots to illustrate how the process of natural selection can lead to the evolution of complex traits such as adaptive behaviours. Just a few hundred generations of selection are sufficient to allow robots to evolve collision-free movement, homing, sophisticated predator versus prey strategies, coadaptation of brains and bodies, cooperation, and even altruism. In all cases this occurred via selection in robots controlled by a simple neural network, which mutated randomly.

Andrew Carlson along with Prof. Tom Mitchell and other researchers at Carnegie Mellon University have developed an artificial intelligence language-learning program that never ends.

It simply continues to run and learn more of the English language every day.

The idea is that the Web contains so much information to be extracted, and has so much new information added each day, that an AI program can continuously mine it without its knowledge ever reaching a plateau.

Use past news events to enhance your program trading strategies. Thomson Reuters NewsScope Archive is a comprehensive, machine-readable archive of Reuters news that presents events exactly as they broke to the markets. Each release of information is timestamped to the millisecond and tagged with an array of metadata fields for easy machine consumption.

Jonathan Wilkins of iSEC Partners said the method had a total success rate of 17.5 percent against reCAPTCHA. The rate is significant because of the wide use of botnets by spammers and other miscreants. Even a modest-sized network of 10,000 infected machines with a success rate of 0.01 percent would yield 10 successes every second. That could translate into 864,000 new accounts every day, he said.

...

A Google spokesman said the data collected in the report was collected in early 2008 and didn't reflect enhancements made to reCAPTCHA since then.

A five-year research programme, called Project Indect, aims to develop computer programmes which act as "agents" to monitor and process information from web sites, discussion forums, file servers, peer-to-peer networks and even individual computers.

Its main objectives include the "automatic detection of threats and abnormal behaviour or violence".

Welcome! This is the home page for The Computational Beauty of Nature, affectionately known as ``The Fish and Chips Book.'' Here, you will find information about the book, source code for simulations involving fractals, chaos, complex systems, and adaptation, and a whole slew of goodies for people interested in multidisciplinary topics involving computers, philosophy, and science.

This portal is based on and replaces the NLG Resources Wiki run by ACL SIGGEN from November 2005 to February 2009.

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