This link has been bookmarked by 46 people . It was first bookmarked on 30 Jul 2008, by Sean.
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22 Sep 08
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19 Sep 08
Thomas JamesA pretty good, if technically dense, read.
sciencefiction computerscience science technology Google singularity searchengine stories writing
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17 Sep 08
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21 Aug 08
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01 Aug 08
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31 Jul 08
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30 Jul 08
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When Ed examined the traffic, he realized that Google was doing more than mapping the digital universe. Google doesn't merely link or point to data. It moves data around. Data that are associated frequently by search requests are locally replicated—establishing physical proximity, in the real universe, that is manifested computationally as proximity in time. Google was more than a map. Google was becoming something else.
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How does one come to a new understanding? The standard essay or paper makes a discursive argument, decorated with analogies, to persuade the reader to arrive at the new insight.
The same thing can be accomplished—perhaps more agreeably, perhaps more persuasively—with a piece of fiction that shows what would drive a character to come to the new understanding. Tell us a story!
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Bigelow speculated from the very beginning about "the possibility of causing various elementary pieces of information situated in the cells of a large array (say, of memory) to enter into a computation process without explicitly generating a coordinate address in 'machine-space' for selecting them out of the array."
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“This ‘universality’ is probably necessary to organize or resist organization by other automata?”
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When Ed examined the traffic, he realized that Google was doing more than mapping the digital universe. Google doesn't merely link or point to data. It moves data around. Data that are associated frequently by search requests are locally replicated—establishing physical proximity, in the real universe, that is manifested computationally as proximity in time. Google was more than a map. Google was becoming something else.
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"Law of Requisite Variety": that any effective control system has to be as complex as the system it controls.
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Since, by diagonal argument in the scale of possible infinities, there will always be more questions than answers, it is better to start by collecting the answers, and then find the questions, rather than the other way around.
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whereas Google's hemispheres were unevenly distributed from moment to moment throughout a network that spanned the globe.
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As von Neumann explained in 1948: "A new, essentially logical, theory is called for in order to understand high-complication automata and, in particular, the central nervous system. It may be, however, that in this process logic will have to undergo a pseudomorphosis to neurology to a much greater extent than the reverse." Ulam had summed it up: “What makes you so sure that mathematical logic corresponds to the way we think?”
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For 400 years, we have been waiting for machines to begin to think.
"We've been asking the wrong question," he whispered under his breath.
They would start to dream first.
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Alan Turing's suggestion, to build a disorganized machine with the curiosity of a child, made more sense. Eventually, "interference would no longer be necessary, and the machine would have ‘grown up’." This was Google's approach. Harvest all the data in the world, rendering all available answers accessible to all possible questions, and then reinforce the meaningful associations while letting the meaningless ones die out. Since, by diagonal argument in the scale of possible infinities, there will always be more questions than answers, it is better to start by collecting the answers, and then find the questions, rather than the other way around.
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What if analog was not really over? What if the digital matrix had now become the substrate upon which new, analog structures were starting to grow? Pulse-frequency coding, whether in a nervous system or a probabilistic search-engine, is based on statistical accounting for what connects where, and how frequently connections are made between given points. PageRank for neurons is one way to describe the working architecture of the brain. As von Neumann explained in 1948: "A new, essentially logical, theory is called for in order to understand high-complication automata and, in particular, the central nervous system. It may be, however, that in this process logic will have to undergo a pseudomorphosis to neurology to a much greater extent than the reverse." Ulam had summed it up: “What makes you so sure that mathematical logic corresponds to the way we think?”
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15 Jul 08
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