Examples of 'hybrid intelligence' are Google Suggest, which instantly offers popular searches as you type a search query, and the 'did you mean?' feature in Google search, which corrects you when you misspell a query in the searchbar. The more you use it, the better the system gets.
Training computers to become seemingly more intelligent poses major hurdles for Google's engineers. "Computers don't train as efficiently as people do," Spector explains.
"Let's take the chess example. If a Kasparov was the educator, we could count on almost anything he says as being accurate. But if you tried to learn from a million chess players, you learn from my children as well, who play chess but they're 10 and eight. They'll be right sometimes and not right other times. There's noise in that, and some of the noise is spam. One also has to have careful regard for privacy issues."
By collecting enormous amounts of data, Google hopes to create a powerful database that eventually will understand the relationship between words (for example, 'a dog is an animal' and 'a dog has four legs').
The challenge is to try to establish these relationships automatically, using tons of information, instead of having experts teach the system. This database would then improve search results and language translations because it would have a better understanding of the meaning of the words.
There's also a lot of research around 'conceptual search'. "Let's take a video of a couple in front of the Empire State Building. We watch the video and it's clear they're on their honeymoon. But what is the video about? Is it about love or honeymoons, or is it about renting office space? It's a fundamentally challenging problem."
One example of conceptual search is Google Image Swirl, which was added to Labs in November. Enter a keyword and you get a list of 12 images; clicking on each one brings up a cluster of related pictures. Click on any of them to expand the 'wonder wheel' further.
Google notes that they're not just the most relevant images; the algorithm determines the most relevant group of images with similar appearance and meaning.
To improve the world's data, Google continues to focus on the importance of the open internet. Another Labs project, Google Fusion Tables facilitates data management in the cloud. It enables users to create tables, filter and aggregate data, merge it with other data sources and visualise it with Google Maps or the Google Visualisation API.
The data sets can then be published, shared or kept private and commented on by people around the world. "It's an example of open collaboration," Spector says.
"If it's public, we can crawl it to make it searchable and easily visible to people. We hired one of the best database researchers in the world, Alon Halevy, to lead it."
Google is aiming to make more information available more easily across multiple devices, whether it's images, videos, speech or maps, no matter which language we're using.
Spector calls the impact "totally transparent processing – it revolutionises the role of computation in day-today life. The computer can break down all these barriers to communication and knowledge. No matter what device we're using, we have access to things. We can do translations, there are books or government documents, and some day we hope to have medical records. Whatever you want, no matter where you are, you can find it."
First published in .net Issue 198
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