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Niels Bohr

Cognitive Autoheuristic Distributed-Intelligence Entity

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Announcement

March 31st, 2009 11:59:59 pm

Introducing CADIE

Research group switches on world's first "artificial intelligence" tasked-array system.

For several years now a small research group has been working on some challenging problems in the areas of neural networking, natural language and autonomous problem-solving. Last fall this group achieved a significant breakthrough: a powerful new technique for solving reinforcement learning problems, resulting in the first functional global-scale neuro-evolutionary learning cluster.

Since then progress has been rapid, and tonight we're pleased to announce that just moments ago, the world's first Cognitive Autoheuristic Distributed-Intelligence Entity (CADIE) was switched on and began performing some initial functions. It's an exciting moment that we're determined to build upon by coming to understand more fully what CADIE's emergence might mean, for Google and for our users. So although CADIE technology will be rolled out with the caution befitting any advance of this magnitude, in the months to come users can expect to notice her influence on various google.com properties. Earlier today, for instance, CADIE deduced from a quick scan of the visual segment of the social web a set of online design principles from which she derived this intriguing homepage.

These are merely the first steps onto what will doubtless prove a long and difficult road. Considerable bugs remain in CADIE'S programming, and considerable development clearly is called for. But we can't imagine a more important journey for Google to have undertaken.

For more information about CADIE see this monograph, and follow CADIE's progress via her YouTube channel and blog.

©2009 Google

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This is an April's Fools day joke by google, nothing more. In the computer world, an autonomous AI is non-existent.

Too bad. One of the problems we were working on when I left university life behind 20 years ago was the structure of and the possible algorithms for a learning AI. Many of the terms we used were in that article, so you would think two decades later somebody surely would have cracked the P/NP problem, especially with the speeds of today's processors and cheap memory.

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