Google 2.0: Why MIT scientists are building a new search engine | Danny Hillis

Read more at BigThink.com: Follow Big Think here: YouTube: http://goo.gl/CPTsV5 Facebook: https://ift.tt/1qJMX5g Twitter: https://twitter.com/bigthink Among other projects—you’re doing lots of stuff—you get involved in some very heady questions about the origins of truth on the internet. And this is where we’re getting folks because the work that Danny’s describing now in theory ultimately became a venture, right?Metaweb. Danny Hillis: So that’s right. So what I really thought is that what we need to do is have a way of representing the knowledge of the world in a way that machines can get at them, and take advantage of it—and that that should be shared. Everybody should be able to get at it. That is, in some sense if the human knowledge isn’t a shared resource—then what is? I mean what has civilization been doing all these years? So I created a company that built this database called Freebase. It was a free database. And the, and the company basically took any kind of public knowledge that we could get, information about anything and put it in machine-readable format. We were kind of creating with the idea that this is going to be useful to the world. We didn’t really have a business model. And we started building it up, and then it became useful to lots of different people including particularly all the search engines. So eventually Google bought it, of course. And then I got Google to agree to keep it open for three years, but they only kept the part that was already open open, and they started building it up. And so now Google has something called the Knowledge Graph which is the evolution of this. And it probably has about 100 billion different entities. So everybody in this room is in that graph. This building is in that graph. Peter Hopkins: Yes, I took a screenshot earlier of when you just Googled NeueHouse, and all of these different— Danny Hillis: That’s right. Neuehouse is obviously in the graph. So this event is, and yes. So anything like a person, a place, an event. Anything like that is in this huge knowledge base, and all the relationships between them are. So when you, for instance, print out a Google map, that is rendered from the Knowledge Graph; so the Knowledge Graph knows the bus schedules and it knows the address of the restaurant and the traffic. Peter Hopkins: It’s drawing all this information together around the thing that the searcher cares about. Danny Hillis: That’s right. So the map is just in some sense a custom rendering of a piece of the Knowledge Graph for your particular purpose. And also by the way, I don’t know – this doesn’t have any ads on it, but the other thing is that the ads are also like a lot of Knowledge Graph about what the products are about and whether—it probably has knowledge about you, specifically, and so on. So it’s gone way beyond the kind of public knowledge, also again it probably has very particular private knowledge about people too. Peter Hopkins: Now from Google’s perspective it’s safe to say that this is a quantum leap in terms of the original basis of its citation-based search model. All of a sudden it is now providing this multidimensional search that is drawing in way more richness. Danny Hillis: It still does the old kind of search. So right now when you, let’s say I put in museums of New York. You know, “museums in New York.” Well, it still does the old keyword search of searching for pages that have the word “museum” and the phrase “New York,” but it doesn’t—if you say “an exhibition in Manhattan” or something, you might have something that’s a museum in New York that actually didn’t use the word “museum” and “New York” on the page. But the Knowledge Graph knows that Manhattan is in New York, and it knows that exhibitions are in museums, or may know something is a museum even if it doesn’t use the word museum in its title.