“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

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Google’s search engine chief Amit Singhal dreams of a day when, like Captain Kirk, you can just ask your computer a question and get a complex, detailed answer.

One step in that direction: Google is starting to roll out its new Knowledge Graph globally. Google announced Knowledge Graph a while ago; it treats your search queries as whole entities rather than just strings of letters, and it serves much better results in a much prettier interface that “normal” Google search.

For most of us, these changes aren’t that big of a deal; this is just the latest in a long string of incremental changes that Google is making to its search technology. Still, any time a giant like Google shifts its center of gravity a little, it has the potential to throw a big part of the world off balance.

Another big part of Google web search becoming more universal is a few feature: Search results can now include your Gmail messages and multimedia. You can sign up now to get early access. If you like Google Search Plus Your World, you’ll likely find this new feature quite useful as well. Also, this latest Google search field trial will include personalized, enhanced flight-tracking features, so you can more quickly see you’re going to be stuck in Newark for a few hours.

I spent some time with Singhal today as part of a press event where Google showed off its latest updates. He and I have something in common: We are united in our deep love for Star Trek. Specifically, we both want to bring the fascinating technologies of science fiction (and Star Trek in particular) to reality. The Enterprise computer operated on a deep understanding of human meaning, not a human understanding of machine-friendly keywords.

“To build the search engine I dream of, we need to make it truly universal,” Singhal says, “so you can do things that are not possible today.”

To that end, the company is also announcing voice-based search for iOS devices. Your searches are verbal and use natural language, and the app talks back to you, giving you verbal results in (more or less) natural language. It’s a lot like the Android voice search features the company showed off at Google I/O a couple months ago.

What Google is showing off today are a few baby steps, Singhal said, but they’re steps toward previously impossible goals like speech recognition, natural language processing, and true artificial intelligence.

Singhal says we’re not there yet, but just before his talk started, he, Google search guru Matt Cutts, and I were reminiscing about the “good” old days of AltaVista, Lycos, InfoSeek, and HotBot. My first real job involved doing search work at a startup in early 1999; Google wasn’t really a thing at that point, certainly not in sleepy central Virginia. And the search process pre-Google was excruciating, slow, and wildly unrepresentative of the web that existed at the time.

Those reminiscences stand in sharp contrast both to the future Singhal is envisioning and to the present state of web search. Over the past 13 years, we’ve come a lot closer Singhal’s goal of intelligent, human-friendly search, and we’re all excited about where search will go next.

Jack Menzel is one of the Googlers working on making the search engine smarter.

“We can use our understanding of the world to help you with more complicated tasks,” he says. He tells an anecdote about a road trip from the San Francisco Bay Area to Cedar Point, an amusement park in Ohio. Menzel needed some convincing to get in the car for such a long trip, and he puled up a Google search for “Cedar Point” to illustrate his point. In old-school web search, you’d see a list of links for the amusement park; you’d have to click through and copy/paste the names of rides into new searches to get more information on each one. But with Google’s new Knowledge Graph, the search engine’s newest “brain” rolled out a couple months ago, Google returns a map, contact information, specific rides in the park, images and videos, and a lot more — all on the first page of results, all arranged in pretty carousels, scannable boxes, and other information design elements infinitely better for humans than a list of links.

It’s not quite the Enterprise computer, but it’s getting closer. As Menzel told me during the Knowledge Graph launch, “Computers don’t really understand what people are talking about. To a computer, it’s just a string of letters.” Knowledge Graph treats queries as objects rather than strings, and it’s one of Google’s attempts to get closer to human-friendly, artificially intelligent search.

The other big part of Google’s web search evolution is speed. “Do you remember how slow it used to be?” Cutts muses. The Internet was slower, and our connections were slower 13 years ago. We’ve all been accelerating on every front, but Google has an institutional preference for lightning speed. It’s pushing and shoving the web to speed-focused standards, superspeedy Internet, speed-tweaked programming languages. Google is like a stupid teenager with his first car, with only one question on his mind: “How fast can this thing go?”

The bigger the dataset gets and the more we turn to Google for web search, the more urgent the need for speed becomes. Right now, the web has around 30 trillion unique URLs. Google crawls 20 billion pages every day, and we humans use Google to conduct 100 billion searches every month.

That kind of activity requires speed on every level of hardware, software, and even design. Today’s announcements, from the Gmail addition to search to the vocal search app, are all engineered to avoid wasting a millisecond more of your time, to get your head out of your devices, to make partaking in life simpler, to free up your brain for solving bigger problems than finding a movie tonight or finding an email you got last week.

“I dreamt all those dreams as a child,” Singhal says. “Thanks to all the wonderful research and the engineers at Google, we are so much closer to my dream of building the Star Trek computer.”

We know that Google’s still a business, and its primary goal is getting more users, selling more advertising, and making more money. But if it can move us a few more inches closer to Star Trek in that process, that’s okay with me.

Image courtesy of alpahspirit, Shutterstock

Google’s “search by image” feature just got a little bit smarter. The search engine can now better detect image subjects and give you lots of new related content.

Search by image allows you to upload a photo to Google and use it as a “search term,” as opposed to regular keywords. In the past, Google has been able to detect what is in many photos, but only on a very base level. For instance, if you uploaded a picture of a flower, it would return search results for flowers. But now Google is integrating its Knowledge Graph into “search by image.” Now when you upload that same image, Google will see not just a flower, but a Birds of Paradise flower, and will give you information about its origins.

Google introduced the knowledge graph in May. It allows Google’s search algorithm to detect context in search terms, as opposed to just face value definitions. Google gives the example of the Taj Mahal. When you’re searching for the Taj Mahal, you may mean the building, the musician, or the casino. The Knowledge Graph can detect which one you’re referencing and provide you search results based on the other two categories if it guesses wrong.

This is a big step for image recognition in search. One of the most frustrating aspects of life in this Internet-ruled world is the inability to get an answer. Much of that frustration stems from having the wrong keywords, not being able to describe well enough what you’re looking for. The “search by image” option takes care of that.

Along with the integration of the Knowledge Graph, Google also says it has improved its ability to guess the subject matter of an image. It also says it will provide more than just websites that include the same image; it will return news stories and other non-photo content related to the image in the search results.

Birds of Paradise image via Shutterstock