For the purposes of this discussion, we will take Google as a combination of a search engine and instantaneous results set across all web sites and blog resources worldwide. What about scale?The last numbers I saw (Feb 2010) estimated 750 million websites worldwide, plus more than 200 million blogs. There are of course other domains which Google also scans. Other figures suggest 25 billion indexed webpages (Netcraft March 2009), but that number will have grown a lot since then. Here, I use the term neural network not in the strict Artificial Intelligence sense, but in a more general sense. Now, consider the human brain as I understand it (a very simple model). It has a set of data inputs (visual, auditory, chemical - taste and smell, pressure - touch, thermal, inertial - the ear canals, that we know of) and a memory structure. Data input is stored in short term memory becoming information - i.e. brain processing adds context, then sorted and filtered and then moved to long term memory. The short and long term memory is in the form of junctions between brain cells known as synapses. More input on a given memory strengthens the relevant synapses - that is repeated exposure to a given input strengthens the particular memory. For example, the more we taste bananas, then the easier it is to 'recreate' the taste in our minds. We know that as we age, the more salient memories (stronger synapses from earlier in our lives) are easier to retrieve, short term memory becomes less efficient and recent (but long term) memories are difficult to retrieve. Sorry, where was I? Ah yes, I remember now. Our ability to build new synapses falls off with age in most people, and once we reach maturity we are unable to grow additional brain cells. Autonomic responses (e.g. breathing) use 'hard wired' memory in the hypothalamus which is a very primitive part of the brain structure which may be compared to 'read-only' memory in a computer. Now, let us consider Google. Google has a set of data inputs - primarily the bot/crawler data gathering channel, but also input about the access frequency of web pages which is gathered through use of its search engine by users (and which reputedly includes a link to the user, supposedly to enhance the 'user experience'. The data from these bots about a given web page - for example keyword relevance to content, the number of external links to the page and so on, is converted into Google's proprietary and secret page rank scores and provides a 'salience' for the analogous Google 'synapse'. The analogous Google synapse is simply (I assume as I am not privy to Google's design) a database row for the website/page with the aforementioned data items (including the page rank/scoring factors) in the columns, site map entries and site refresh rate and search history information. No doubt, there is lots more besides as they are avid data collectors. Of course the analogy with the human brain breaks down with time, as we would not expect the Google model to suffer from a capacity limitation or by a constraint imposed by 'technology' (as happens with the brain when we age and the synapse building processes become less efficient). One more point - it is beleived that 'a given memory' in the brain is actually distributed across a number of synapses. What makes this analogy interesting? Well, consider how we might wish to add to human brain capacity and extend its efficiency - we are getting into William Gibson territory now (he was the author who invented the term 'cyberspace'). Why plug additional memory chips into the brain, when all that is needed is a wireless chip connecting to Google? Google Translator - no problem, speak a new language instantly! Science fiction? I don't think it is that far away (less than 50 years I guess). The potential social consequences are quite frightening to consider. (c) 2010 Phil Marks
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