The conversation about unconscious bias in artificial intelligence often focuses on algorithms that unintentionally cause disproportionate harm to entire swaths of society--those that wrongly predict black defendants will commit future crimes, for example, or facial-recognition technologies developed mainly by using photos of white men that do a poor job of identifying women and people with darker skin. But the problem could run much deeper than that. Society should be on guard for another twist: the possibility that nefarious actors could seek to attack artificial intelligence systems by deliberately introducing bias into them, smuggled inside the data that helps those systems learn. This could introduce a worrisome new dimension to cyberattacks, disinformation campaigns or the proliferation of fake news. According to a U.S. government study on big data and privacy, biased algorithms could make it easier to mask discriminatory lending, hiring or other unsavory business practices.
Important resources like minerals, oil and diamonds often go hand-in-hand with conflict and poor governance. But when it comes to one particular resource -- the most important resource of all -- many think a different theory will hold true. Often referred to as the water wars thesis, it suggests that growing water scarcity will drive violent conflict as access to water dries up for certain communities. Analysts worry that people, opportunistic politicians and powerful corporations will battle for dwindling water supply, inflaming tensions. In a new study, researchers tried to map out how water wars will emerge around the world and which countries are most likely to see water-related conflict in the coming decades.
This week's milestones in the history of technology include the coining of the term "artificial intelligence," the digitization of the Library of Congress, and the first penny paper. The first issue of Scientific American is published by Rufus Porter as a weekly broadsheet subtitled "The Advocate of Industry and Enterprise, and Journal of Mechanical and Other Improvements." In an era of rapid innovation, Scientific American founded the first branch of the U.S. Patent Agency, in 1850, to provide technical help and legal advice to inventors. A Washington, D.C., branch was added in 1859. By 1900 more than 100,000 inventions had been patented thanks to Scientific American.
A team of researchers from the University of Albany have developed a method of combating Deepfake videos, using machine learning techniques to search videos for digital "fingerprints" left behind when a video has been altered. One of the biggest concerns in the tech world over the past couple of years has been the rise of Deepfakes. Deepfakes are a type of fake video constructed by artificial intelligence algorithms run through deep neural networks, and the products of the deepfake technology are shockingly good – sometimes difficult to tell apart from a real, genuine video. AI researchers, ethicists, and political scientists are worried that the Deepfake technology will eventually be used to impact political elections, disseminating misinformation in a form more convincing than a fake news story. In order to provide some defense against the manipulation and misinformation that Deepfakes can cause, researchers from the University of Albany have created tools to assist in the detection of fake videos.
It's used internally and to me it's the perfect thickness of abstraction for DL research if you use TF. I write a lot of custom layers and while there are a few TF quirks you have to know, Sonnet has much less mental overhead than the TF.layers lib and is way more "hackable." I tried out all the other topper libs pretty extensively and Sonnet really stood out. The main issue with external adoption, is, well, that there is none _ . I tried looking up a DCGAN example in Sonnet and couldn't find an open source one...there are lots internally, though.
A community for discussion and news related to Natural Language Processing (NLP). Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora.
If you're looking for it, there is plenty of bad news in the tech world. From concerns about hacking and identity theft to a 2017 survey out of England that ranked Instagram as "worst for young people's mental health" compared to four other social platforms, it can be enough to make you want to become a Luddite. But the other side of the issue might be able to put a smile on your face: Tech companies and researchers are turning to AI and other software to try to solve just about any problem you can think of, from identifying fake news, to noticing if someone falls, to looking for ways to speed up the amount of time an MRI scan takes. Some companies are building software to help you change your thoughts for the better or even analyze a voice for signs of depression. For example, Woebot is a cute chatbot app designed to be an on-call emotional helper.
The Papago GoSafe S810 camera duo has more "safety" features than you can shake a stick at, including one I'd never even considered--stop sign recognition. It recognizes stop signs and pops the digital equivalent up on its display. Kind of fun, but as I'm wont to say: If you need this stuff, call a cab or wait for self-driving vehicles. Admonishment aside, the $170 S810 is more than just fancy features. It takes very, very good day and night video, and the rear camera, unlike some we've seen recently, actually captures enough detail to be useful.
Google's latest flagship smartphones -- the Pixel 3 and Pixel 3 XL -- are finally shipping to customers, and the reviews are unanimous: The rear camera and dual selfie cams are best in class. But as good as those cameras might be, they're a bit puzzling -- and sort of paradoxical. The original Pixel and Pixel XL have two cameras: one front and one rear. The Pixel 2 and Pixel 2 XL have two cameras: one front and one rear. And the Pixel 3 and Pixel 3 XL have three cameras: two front and one rear.