Stephen Shankland of CNet recently reported, “Google updated its Hangouts app on Wednesday so the multipurpose communication tool can detect when people are trying to find each other and make it easier to connect. The updated app, available for Google’s Android mobile operating system first but submitted to Apple for approval on iOS, also lets people express themselves with stickers and video filter effects, Bradley Horowitz, vice president of product at Google, said at the LeWeb conference here.”
Posts Tagged ‘Google’
Daniela Hernandez of Wired recently wrote that Quoc Le “works on the Google Brain, the search giant’s foray into ‘deep learning,’ a form of artificial intelligence that processes data in ways that mimic the human brain—at least in some ways. Le was one of the main coders behind the widely publicized first-incaration of the Google Brain, a system that taught itself to recognize cats on YouTube images, and since then, the 32-year-old Vietnam-native has been instrumental in helping to build Google systems that recognize your spoken words on Android phones and automatically tag your photos on the web, both of which are powered by deep-learning technology.” Read more
Right before Thanksgiving The Semantic Web Blog gave readers a heads-up about how retailers use of semantic technology could help make the holiday shopping season brighter for consumers. This week, to help those still in need of finding something special for that someone special on his or her shopping list – i.e. friends, children and family with a taste for meaningful computing (or at least for the products that result from it) – we’ll take a look at some holiday gift buys that might fit the bill.
Ladies and gentlemen, start your shopping engines:
- Joining his artificial-intelligence inspired robot friends like Robosapien X and Roboraptor is MiP, which toymaker Wowwee calls a balancing multifunctional and autonomous robot powered by iOS or Android smartphones. The device includes GestureSense technology that lets it respond to the motions of hands or other objects, so that you can play games like Follow the Leader, and to mobile apps that let you drive him around, set him up in a boxing match, or play games like stacking objects.
The MIT Technology Review recently wrote, “Translating one language into another has always been a difficult task. But in recent years, Google has transformed this process by developing machine translation algorithms that change the nature of cross cultural communications through Google Translate. Now that company is using the same machine learning technique to translate pictures into words. The result is a system that automatically generates picture captions that accurately describe the content of images. That’s something that will be useful for search engines, for automated publishing and for helping the visually impaired navigate the web and, indeed, the wider world.” Read more
This past weekend the movie about British mathematician and computer scientist Alan Turing, The Imitation Game, had a successful debut. Turing, of course, created the Turing Test, which is a test of a machine’s ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. Fittingly enough, tonight is the end date for entries to Google’s Imitation Game Code Cracking Challenge, a test designed to determine whether it’s being taken by a human or computer and which has as its focus the film’s principal character, Alan Turing.
Judges this week will be evaluating entries this week, and should be contacting winners by week’s end, making their determinations based both on entrants submitting the correct codes and which entrants solved them the fastest. (The test went live in mid-November.)
Fun stuff, with prizes to include a screening of the movie in the winner’s hometown with 200 friends and signed-cast posters, but perhaps even more interesting is that come January, a group of scientists at the 2015 meeting of the Association for the Advancement of Artificial Intelligence, conduct a workshop to come up with a replacement of the original Turing Test. It’s aiming to create an annual or bi-annual Turing Championship, that might consist of up to five different challenging tasks, “with bragging rights given to the first programs to achieve human-level performance in each task,” according to a statement by workshop organizers Gary Marcus, Francesca Rossi and Manuela Veloso. Read more
Ben Woods of The Next Web reports, “Google has joined forces with the University of Oxford in the UK in order to better study the potential of artificial intelligence (AI) in the areas of image recognition and natural language processing. The hope is that by joining forces with an esteemed academic institution, the research will progress more rapidly than going it alone for its DeepMind project. In total, Google has hired seven individuals (who also happen to be world experts in deep learning for natural language understanding), three of which will remain as professors holding joint appointments at Oxford University.” Read more
Cade Metz of Wired recently wrote, “Deep learning can do many things. Tapping the power of hundreds or even thousands of computers, this new breed of artificial intelligence can help Facebook recognize people, words, and objects that appear in digital photos. It can help Google understand what you’re saying when you bark commands into an Android phone. And it can help Baidu boost the bottom line. The Chinese web giant now uses deep learning to target ads on its online services, and according to Andrew Ng—who helped launch the deep learning operation at Google and now oversees research and development at Baidu—the company has seen a notable increase in revenue as a result. ‘It’s used very successfully in advertising,’ he says, sitting inside the company’s U.S. R&D center in Sunnyvale, California. ‘We have not released revenue numbers on the specific impact, but it is significant’.” Read more
Jordan Novet of Venture Beat reports, “Many people know Google first and foremost as a search engine company. But really it’s a machine-learning company, using data to make predictions that get incorporated into applications like search and advertising without people even realizing it. Today Google is announcing in a blog post that people can now choose to apply its machine-learning savvy to Google Sheets, the company’s spreadsheet app, to make educated guesses and fill in blank cells. This applied use of machine learning follows Microsoft’s recent announcement of a cloud-based service for that purpose, Azure Machine Learning.” Read more
AlchemyAPI’s New Face Detection And Recognition API Boosts Entity Information Courtesy Of Its Knowledge Graph
AlchemyAPI has released its AlchemyVision Face Detection/Recognition API, which, in response to an image file or URI, returns the position, age, gender, and, in the case of celebrities, the identities of the people in the photo and connections to their web sites, DBpedia links and more.
According to founder and CEO Elliot Turner, it’s taking a different direction than Google and Baidu with its visual recognition technology. Those two vendors, he says in an email response to questions from The Semantic Web Blog, “use their visual recognition technology internally for their own competitive advantage. We are democratizing these technologies by providing them as an API and sharing them with the world’s software developers.”
The business case for those developers to leverage the Face Detection/Recognition API include that companies can use facial recognition for demographic profiling purposes, allowing them to understand age and gender characteristics of their audience based on profile images and sharing activity, Turner says.
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