“We’re still in the early stages,” Page said on Google’s fourth-quarter 2012 earnings call. “We’re still at 1 percent of where we should be.”

Knowledge Graph is Google’s attempt to provide answers beyond simple keywords and queries. Answers, for instance, that an intelligent person or entity might provide and that demonstrate some degree of understanding of the concepts behind the questions.

In order to do that, Google has assembled a massive and growing “semantic network” of at least 570 million objects and 18 billion facts about and relationships between them, from sources such as the CIA World Factbook, Wikipedia, and Freebase, an entity graph of “people, places, and things” that is built the same way Wikipedia is: by interested volunteers.

Those facts about things like “Lamborghini Countach,” “bike,” or “cat” — and the connections between them =– are what Google hopes to use to improve search results and make searching more natural, similar in some ways to how Wolfram Alpha and Siri work, at least in their limited contexts. Ultimately, the Star Trek experience would be nice: simply asking computers natural questions.

That’s critical for Google, as Page acknowledged in a rare well-duh moment, saying that ”getting people correct answers is really important for our business.” But he also laid a finger on one of Google’s biggest challenges with Knowledge Graph: internationalization, saying that it was “hard work.”

However, if humanity ever develops something that approaches artificial intelligence, it’ll probably be from something like Google Knowledge Graph. Perhaps when Page and team are at something like 75 percent.

photo credit: Google

Semantifi is one of 70 companies chosen by VentureBeat to launch at the DEMO Fall 2010 event taking place this week in Silicon Valley. After our selection, the companies pay a fee to present. Our coverage of them remains objective.

Google and other popular search engines only search about 1 percent of the Web, according to research data from UC Berkeley. That just isn’t enough for deep-Web crawler Semantifi, which launched its new search engine at DEMO Fall 2010.

Semantifi offers users a way to search for specific data through a search engine powered by user-created apps. One example: searching for U.S. population numbers separated into age and gender. It uses the “deep Web,” where information is stored in databases and is not immediately accessible through traditional search engines that just search the text and images of websites. The technology to power Semantifi has been in development for 5 years.

Wolfram Research’s Wolfram Alpha, as well as some other data-powered search engines, also provide “answers” for searches on the Internet, such as a mathematical problem or what the national bird of Sweden is, but Semantifi offers users a chance to power the search with their own sets of data.

The Stamford, Conn.-based company is currently run by a team of 30, and has raised $3.5 million in one fundraising round in September 2008 from Connecticut Innovations and Launch Capital, as well as some individual investors.

Primal, a company leveraging semantic technology to automate online activities, today announced the launch of Pages for Publishers, a tool that aggregates similar themed content based from around the web into one page, at the DEMO conference.

The traditional way of collecting and publishing content to a website often takes large teams of people and large amounts of money. Primal’s Pages for Publishers helps businesses supplement their own content with material from around the Web, such as images, blogs, news or even book recommendations. Content is pulled in real time and automatically, which spares the user from a continuous process of finding, organizing, and publishing.

Primal first presented its technology at DEMO Spring 2009, and later expanded its Pages offering in June, as a demonstration of the technology for the business customers it’s now seeking to reach reach with Pages for Publishers.

Pages for Publishers can feed in existing, valuable and relevant content from around the web to build out a more quality experience for the audience. For example, an article about DEMO could instantly feature relevant photos from Flickr, news items streaming in from Yahoo News, a backgrounder from Wikipedia, and book recommendations from Amazon – giving visitors more reason to stay on our site for a longer period of time.

Other curation tools have emerged such as Curation Station and OneSpot as well as recently launched Curata from HiveFive.

The Canadian-based company offers the tool for free, but with ads, so if you want to get rid of them the company offers a transactional pricing model based on the size of your website.

http://c.brightcove.com/services/viewer/federated_f8/980795693

It’s taken another step toward solving that huge problem that all search engines face: how to understand the meaning of search phrases you type in. The two guys behind it are impressively scrappy, too. Google or some other large company might want to acquire them before they raise venture capital.

Why is Kngine noteworthy? Try typing into Kngine phrases like United States and China wheat production in last ten years” or  ”Who was the president of France between 1960 and 2000.” It returns nicely visual results that directly answer these queries. It does so because it understands the semantics of the phrases you typed in.

Google, by contrast, returns thousands of results for these queries, but you won’t easily find any results responding directly to these queries. Another ambitious engine, WolframAlpha, also stumbles on these queries, despite hiring a small army of experts to create databases for queries.

The same shortcoming goes for Bing, Microsoft’s search engine. Surprisingly, even Powerset, the semantic search engine bought by Microsoft two years ago having raised $12.5 million in venture capital, fails to come close to what Kngine offers in these examples.

Here’s the conundrum for the search industry to date: Google and other search engines rely mostly on understanding keywords, and they’ve had difficulty moving beyond them. Type in my name “Matt Marshall” into Google, for example, and you’ll get results for that name, but you’ll also get lots of results for “Matt,” and for “Marshall,” even if those have nothing to do with “Matt Marshall.” You have to put a quote around “Matt Marshall” if you really want to to look for the two names together. To be clear, Google is getting much smarter over time in the area of semantics. It’s done extensive research into this approach. But the search giant has recognized that so-called natural language search — getting a computer to understand the meaning of phrases — is very hard to do accurately across the board. For now, Google just isn’t set up very well for this sort of approach.

Kngine is just the latest in a long line of companies offering so-called semantic search. A host of companies have tried. The most ambitious was Powerset, but there was also Hakia, and since then several other flavors have also popped up. None have really cracked the nut. And Kngine’s founders say they recognize too that they have huge limits to what they can do.

For now, each of these startups have picked off small pieces of the semantic puzzle. Here’s how Kngine is trying to distinguish itself: Most of the other semantic search engines limit their index to so-called “structured data” so that they don’t get overwhelmed by the chaos caused by greater web’s millions of sites. For example, they draw their results from a limited number of sites such as Wikipedia and Freebase. Kngine, however, has expanded beyond those sources, and seeks to index structures information sources across the greater Web. It has so far indexed “several thousand” sites.

It then mixes a number of semantic approaches to understand your queries, and seeks to provide slick visual results in return. These include interactive charts (if you search “3G phones,” it gives you all phones that support 3G, or if you search “Jim Carrey movies,” you get a list of all Jim Carrey movies) and segmenting results (type in Apple, for example, and it lets you pick whether you mean Apple Inc., or the fruit).

Haytham ElFadeel, 23, and his brother Ashraf, 30, have worked on this for two years on this with no outside funding. Both are engineers who studied in Cairo. Haytham Fadeel says he studied natural language, and that’s the sole basis of the engine’s semantic abilities. The two have built and designed the site entirely themselves, running the site on about $1,000 a month, which is basically the cost of their servers, according to Fadeel. That’s also about how much they make on the ad revenue they’re getting from Google AdSense. They’re essentially break-even. They’re living with support from friends and family in Egypt, which Haytham says is an advantage because costs are so low there.
The traffic is small, but growing. They’ve hit 50,000 page views a month, up from 2,000 page views six months ago. But Haytham says he realizes the company needs to raise some capital to help it expand to the next step.

Next up is their November release, which will focus on improving answers, he says.

The video below shows more of what Kngine can do.

[youtube http://www.youtube.com/watch?v=VTwrtTNmgok&hl=en_US&fs=1&rel=0%5D