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'Three black teenagers': anger as Google image search shows police mugshots

The Guardian

A simple Google image search highlighted on Twitter has been said to highlight the pervasiveness of racial bias and media profiling. "Three black teenagers" was a trending search on Google on Thursday after a US high school student pointed out the stark difference in results for "three black teenagers" and "three white teenagers". Kabir Alli of Virginia posted a clip to Twitter of himself carrying out a straightforward search of "three black teenagers", which overwhelmingly turns up prisoners' mugshots. He and others erupt in laughter when the result for "three white teenagers" show stock photos of smiling, wholesome-looking young people. The tweet has been retweeted by more than 60,100 users and favourited nearly 55,500 times since it was posted on Tuesday – but Alli's video was later reposted by World Star Hip Hop, an entertainment website with an enormous following on social media.


Google says sorry for racist auto-tag in photo app

The Guardian

Google has apologized after its new photo app labelled two black people as "gorillas". The photo service, launched in May, automatically tags uploaded pictures using its own artificial intelligence software. My friend's not a gorilla," Jacky Alciné tweeted on Sunday after a photo of him and a friend was mislabelled as "gorillas" by the app. Shortly after, Alciné was contacted by Yonatan Zunger, the chief architect of social at Google. "Big thanks for helping us fix this: it makes a real difference," Zunger tweeted to Alciné. He went on to say that problems in image recognition can be caused by obscured faces and "different contrast processing needed for different skin tones and lighting". "We used to have a problem with people (of all races) being tagged as dogs, for similar reasons," he said. "We're also working on longer-term fixes around both linguistics (words to be careful about in photos of people) and image recognition itself (e.g., better recognition of dark-skinned faces).


DeepText AI: Is a smarter Facebook a scary Facebook?

#artificialintelligence

Facebook already knows a lot about you, but the social network is about to get a whole lot smarter. The company has unveiled the DeepText Artificial Intelligence (AI) engine which is designed to understand the context and sentiment behind the written word. It relies on a technique called deep learning, which attempts to reduce the gap between computers and humans, when it comes to understanding the meaning behind human language. Facebook is using neural network architectures, including convolutional and recurrent neural nets, and can perform word-level and character-level based learning. This comes at a time when Google has just announced their artificial intelligence based messaging apps, Allo and Duo.


Apple Announces Changes for App Store

#artificialintelligence

Apple announced a revamped App Store this week that will allow developers to advertise as consumers search for new apps. Developers will also receive a bigger cut of the revenue from subscription apps, and Apple has said it has already sped up its process to approve apps before they are put on sale. But developers and analysts fear it will not help end the steady decline of individual app sales. The old slogan "There's an app for that" may have become truer than the individual who first coined it imagined - today there are over 1.9 million apps, according to analytics firm App Annie. "The app space has grown out of control," said Vint Cerf, one of the inventors of the internet, to a San Francisco conference on the future of the web Wednesday.



Spotify Plots Path to Profit with Machine Learning Tactics

#artificialintelligence

STOCKHOLM (Reuters) – Spotify is a household name, with more paying users than any other music-streaming service in the world. But it doesn't make a penny. Those 30 million paid subscribers help it rake in almost half the revenues in the global industry. But most of the money goes to record labels and artists, while the privately owned Swedish company faces growing competition from Apple with its deep pockets and massive iPhone user base. To reduce its dependence on labels and stand apart from rivals, Spotify is broadening beyond its music library.


The FBI is Making An AI to Track and Sort People By Their Tattoos

#artificialintelligence

The Federal Bureau of Investigation (FBI) teamed-up with the National Institute of Standards and Technology (NIST) to create a unique piece of technology capable of recognizing tattoos. Since 2014, the tandem has already been able to compile a database of 15,000 tattoos, giving them the foundation for developing recognition algorithms. Researchers from the Imaging wing of the NIST developed the idea of tracking tattoos for four reasons. First, one out of every five adults in the US has a tattoo. Second, tattoos provide distinguishing marks that serve as a form of identification.


Siemens Is Building An Army Of Collaborative Spider Robot Factory Workers

#artificialintelligence

In the 1936 film Modern Times, Charlie Chaplin plays a factory worker whose only job is to tighten two bolts--again and again, all day, until he finally goes mad. That model is reaching its own breaking point, says German industrial giant Siemens, because it's too clunky to keep up with market demands. "We're going to see more complex products that consumers or different industries want us to manufacture," says Livio Dalloro, head of research for Siemens Corporate Technology. "The costs to bring [an assembly line] up and then essentially bring this down, when you are going to be switching to a different product, are pretty high." In other words, the costs of reconfiguring a traditional production line for a new product get in the way of being able to quickly iterate on product design.


Customer tracking and AI robots top Domino's digital innovations list

#artificialintelligence

Tracking consumers in real-time, zero-click ordering and delivering pizzas via artificially intelligent robots are just some of the latest innovations underway at Domino's. The pizza retailer today launched the first in a proposed series of tech innovation events, under the brand'Abacus', showcasing the way digital and technology is being harnessed by the business. Ten innovations were detailed, some of which will be available from next week, while others will be rolled out over the coming 12-24 months.All stemmed from the theme'time is the enemy of food' and showed the power of harnessing data analytics not only for operational process improvements, but also for tailoring customer experiences and interaction. The first of these is On-Time Cooking, an extension of the GPS Driver Tracker capabilities Domino's has been providing for the last 10 years aimed at shortening the time between cooking a pizza and when customers pick up their order. Domino's A/NZ managing director, Don Meij, said that until now, stores haven't known exactly when a customer will arrive, running the risk of pizzas sitting on the rack for 10 or 20 minutes longer than they should.


Can you apply machine learning to machine learning? #SparkSummit

#artificialintelligence

As the Spark Summit 2016 event continues in San Francisco this week, attendees are getting to learn about the latest uses for Spark in the tech world, as well as getting exclusive glimpses of its effect on future developments. Christopher Cuong T. Nguyen, cofounder and CEO of Arimo, Inc., joined cohosts John Walls and George Gilbert (@ggilbert41) of theCUBE, from the SiliconANGLE Media team, during Spark Summit to discuss what his company is doing with Spark to create more effective and powerful work environments, along with the importance of keeping things accessible for all users. Nguyen, who described himself as "a very early adopter of Spark," was confident in his company's investment in Spark, saying, "If you are familiar with technology evolution, and then you understand architecture, and you have a sense of timing, then [an investment in Spark is] actually not a very risky bet." He also provided a deeper look at their motivations for using Spark specifically. "The information asymmetry that we had looking at Spark is that we looked at a whole bunch of different compute architectures, specifically in memory, and … we knew that what had to happen is that you need to have what's called a distributed dataset that exists outside of the compute cycle," he said.