<http://schema.org/articleBody>
"Google has a confession to make: It does not understand you. If you ask it \u201Cthe 10 deepest lakes in the U.S,\u201D it will give you a very good result based on the keywords in the phrase and sites with significant authority on those words and even word groupings, but Google Fellow and SVP Amit Singhal says Google doesn\u2019t understand the question. \u201CWe cross our fingers and hope someone on the web has written about these things or topics.\u201D\nThe future of Google Search, though, could be a very different story. In an extensive conversation, Singhal, who has been in the search field for 20 years, outlined a developing vision for search that takes it beyond mere words and into the world of entities, attributes and the relationship between those entities. In other words, Google\u2019s future search engine will not only understand your lake question but know a lake is a body of water and tell you the depth, surface areas, temperatures and even salinities for each lake.\nTo understand where Google is going, however, you need to know where it\u2019s been.\nSearch, Singhal explained, started as a content-based, keyword index task that changed little in the latter half of the 20th century, until the arrival of the World Wide Web, that is. Suddenly search had a new friend: links. Google, Amit said, was the first to use links as \u201Crecommendation surrogates.\u201D In those early days, Google based its results on content links and the authority of those links. Over time, Google added  a host of signals about content, keywords and you to build an even better query result.\nEventually Google transitioned from examining keywords to meaning.  \u201CWe realized that the words \u2018New\u2019 and \u2018York\u2019 appearing next to each other suddenly changed the meaning of both those words.\u201D Google developed statistical heuristics that recognized that those two words appearing together is a new kind of word. However, Google really did not yet understand that New York is a city, with a population and particular location.\nStill, word sequences and the meaning they have is something, but not enough for Google or Singhal, who was recently elected to the National Academy of Engineering.\nBig Changes Coming\nGoogle now wants to transform words that appear on a page into entities that mean something and have related attributes.  It\u2019s what the human brain does naturally, but for computers, it\u2019s known as Artificial Intelligence. \nIt\u2019s a challenging task, but the work has already begun.  Google is \u201Cbuilding a huge, in-house understanding of what an entity is and a repository of what entities are in the world and what should you know about those entities,\u201D said Singhal.\n\nIn 2010, Google purchased Freebase, a community-built knowledge base packed with some 12 million canonical entities. Twelve million is a good start, but Google has, according to Singhal, invested dramatically to \u201Cbuild a huge knowledge graph of interconnected entities and their attributes.\u201D \nThe transition from a word-based index to this knowledge graph is a fundamental shift that will radically increase power and complexity. Singhal explained that the word index is essentially like the index you find at the back of a book: \u201CA knowledge base is huge compared to the word index and far more refined or advanced.\u201D\nRight now Google is, Singhal told me, building the infrastructure for the more algorithmically complex search of tomorrow, and that task, of course, does include more computers. All those computers are helping the search giant build out the knowledge graph, which now has \u201Cnorth of 200 million entities.\u201D What can you do with that kind of knowledge graph (or base)? \nInitially, you just take baby steps. Although evidence of this AI-like intelligence is beginning to show up in Google Search results, most people probably haven\u2019t even noticed it. \nKnowledge Graph at Work Today\nType \u201CMonet\u201D into Google Search, for instance, and, along with the standard results, you\u2019ll find a small area at the bottom: \u201CArtwork Searches for Claude Monet.\u201D In it are thumbnail results of the top five or six works by the master. Singhal says this is an indication that Google search is beginning to understand that Monet is a painter and that the most important thing about an artist is his greatest works.\nWhen I note that this does not seem wildly different or more exceptional that the traditional results above, Singhal cautioned me that judging the knowledge graph\u2019s power on this would be like judging an artist on work he did as a 12- or 24-month-old.\nIt could be seen as somewhat ironic that Google is addressing what has been a key criticism leveled at it by its chief search competitor, Microsoft Bing. The software giant ran a series of scathing commercials, which while never mentioning Google by name, depicted the search results most people get as comically lacking context. Most people understood that the criticism and joke was aimed at Google, and now Google is doing something about the quality of its results.\nWhen I asked Singhal if he had thought about Bing\u2019s criticism and realized that Bing has long advertised that its results focus more on useful answers instead of links, Singhal deflected, saying he couldn\u2019t comment on what Bing may or may not be doing.\nIt\u2019s also worth noting that millions of people now believe they already have AI search thanks to Apple\u2019s iPhone 4S and Siri, the intelligent assistant. It uses the information it can access on your phone and through the web to answer natural language questions. Whatever Google's Knowledge Graph can do, it clearly needs to go beyond Siri's brand of AI.\nPinpointing exactly how far you can take the\"search of the future,\" however, is somewhat difficult for Singhal. \"We\u2019re building the 'hadron collider.' What particles will come out of it, I can\u2019t predict right now,\" he said.\nOn the other hand, Singhal does admit that it is his dream to build the Star Trek computer. Like Siri, you could ask this computer, which appeared on the 1960s sci-fi TV show, virtually any question and get an intelligent answer. \u201CAll aspects of computing or AI improve when you have such an infrastructure in-house,\" said Singhal, referring to the massive knowledge graph Google is building. \"You can process query or question much better, and you get a step closer to building the Star Trek computer,\u201D he said.\nBeyond Search\nSpeaking of Star Trek, there is another frontier that might benefit from the power of Google\u2019s Knowledge Graph: Robotics. Singhal is, admittedly, no expert, but noted that robotics, which exists at the intersection of mechanical engineers and computing, struggles when it comes to language capabilities.  \u201CI believe we are laying the foundation for how robotics would incorporate language into the future of robot-human interaction,\u201D he said.\nIt\u2019s an exciting thought. Being a robot geek, I proceeded to paint a picture of the future that Singhal did not disagree with: Future robots with access to Google\u2019s entity-based search engine might be able to understand that the \u201Ctiny baby\u201D they\u2019re caring for (What? You wouldn\u2019t leave your baby with a robot?)  is small, fragile and always hungry. The robot might even know how to feed the baby because it would know the entity \u201Calways hungry\u201D has to be cross-referenced with the fact that it\u2019s a \u201Cbaby,\u201D which is also an entity in the knowledge graph, and includes attributes like \u201Cno solids.\u201D\nAs we talked, it occurred to me that while 200 million entities is a lot, the world of knowledge is vast. How many entities would it take for the Google\u2019s Knowledge Graph to know the answer to everything?  Singhal laughed and instead of pinpointing a number spun the question around:\n\u201CThe beauty of the human mind is that it can build things and decide things in ways we didn\u2019t think were possible, and I think the best answer I can give right now is that the human mind would keep creating knowledge and I see what we\u2019re building in our knowledge graph as a tool to aid the creation of more knowledge. It\u2019s an endless quantitative cycle of creativity.\u201D"^^<http://www.w3.org/2001/XMLSchema#string>
<http://mashable.com/2012/02/13/google-knowledge-graph-change-search/>