What’s on the menu for semantic technology this week? Two vendors in the foodie field are offering up some new treats.

From Nara, whose neural networking technology is behind a service to help users better personalize and curate their restaurant dining experiences (see how in our story here), comes a new feature that should make picking a restaurant for a group dinner an easier affair. It combines users’ “digital DNA” – the sum of what it learns of what each one likes and doesn’t like regarding dining venues – to serve up restaurant choices that should appeal to the entire group across its range of preferences.

“It’s a really fun way to start getting [the service] into social,” says Nara founder and CEO Tom Copeman.

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The NY Times reports today that Google acknowledged it had violated people’s privacy during its StreetView mapping project. Thirty-eight states had brought a case against Google on the grounds that the project resulted in people’s passwords and other personal information being unknowingly recorded by the search giant. Google has agreed to settle it by paying a $7 million fine as well as by becoming more aggressive in ensuring that its employees’ efforts don’t violate privacy and informing the public about how to avoid having their privacy compromised.

In its discussion of the settlement, the article brings up that the way now is paved for another privacy battle, this time over Google Glass. Concerns are that Google Glass eyewear also can be used to record photos, videos and audios of the wearer’s surroundings, without the permission of the individuals featured in those surroundings. With Google Glass, users can use their voice to input commands to take a picture or make a video, as well as to take steps less likely to compromise privacy, such as search for facts about landmarks or events.

How that privacy question plays out is yet to be seen. But concerns aren’t stoping the project – which was demonstrated at last week’s SXSW conference – from moving ahead. Google yesterday announced that the glasses will accommodate frames and lenses that match users’ eye prescriptions, for example.

Getting Google Glass to respond to voice commands and searches appears to leverage capabilities it has developed for its Voice Search App for Android, as well as its semantically-driven Knowledge Graph database of hundreds of millions of entities and billions of facts, and their relationships to each other.

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Early in the summer, The Semantic Web Blog introduced readers to Nara, an advanced neural networking service to automate, personalize and curate web dining experiences for users. (See that story here.)

The service is moving ahead with the launch today of its mobile version, as well as in other respects. “We’re now doing a full-on consumer launch of a polished product on both the web and mobile [platforms],” says CTO Nathan Wilson. “People really are clamoring for the mobile component, especially for this [dining] use case.” Versions for both the iPhone’s iOS and Android operating systems are available.

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John Markoff of the New York Times reports, “Inside Google’s secretive X laboratory, known for inventing self-driving cars and augmented reality glasses, a small group of researchers began working several years ago on a simulation of the human brain. There Google scientists created one of the largest neural networks for machine learning by connecting 16,000 computer processors, which they turned loose on the Internet to learn on its own. Presented with 10 million digital images found in YouTube videos, what did Google’s brain do? What millions of humans do with YouTube: looked for cats.” Read more

Dollars to donuts most folks haven’t ever found a place to eat courtesy of neural networking technology before. Generally, Internet searches for spots to have a bite come courtesy of friends’ Facebook recommendations, services like Yelp, and even some semantically-powered offerings such as BooRah, now an Intuit company.

But the collection of neuroscientists, computer scientists, astrophysicists, and creative artists behind Nara, launching into public beta today, have taken the advanced neural networking route to automate, personalize and curate web dining experiences for users – though there’s more to come on the future menu. President and CEO Tom Copeman says of the company, which in April secured $3.6 million of a $4.5 million equity offering, that its cutting-edge neural network and proprietary and patented algorithms and process for analyzing tons of web data, and personalizing it, including considering user feedback on the suggestions it offers, is creating a whole new category.

That is the pure-play digital lifestyle brand that “creates an emotional connection between us and the Web. We’re trying to change how people think about the web, and from sense of what it means to me, and makes sense to me, and how personal it is to me.”

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— TONY SHAW, OLIVER (OLLY) DOWNS

Tony Shaw: Hi Olly, so to get us started, could you give me a high-level overview of what Atigeo does?

Olly Downs: Absolutely. Atigeo’s platform, xPatterns, enables enterprises to derive insights from large, disparate sources of unstructured data. In doing so, we’ve taken two approaches toward how our platform is productized. The first approach is around aspects of our core technology, which allows us to build simple ontologies for domains of unstructured data and then act upon the understanding of the data – in response to queries or profiles of entities, for example. The second aspect of our product enables enterprises to provide customers the ability to access and manage their profile or persona.

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