It's difficult to say whether e-dating has weakened or boosted the pickup line game. It probably depends on who you ask. To get to the bottom of it, we ventured on over to Reddit to check out the general state of cheesy one-liners to be deployed in an online dating setting. And the results are, well … the results kinda speak for themselves. But as far as we can tell, pickup lines, like cockroaches after an apocalyptic event, have survived the shift to online dating and are doing just fine.
Facebook executives took the decision to end research that would make the social media site less polarising for fears that it would unfairly target right-wing users, according to new reports. The company also knew that its recommendation algorithm exacerbated divisiveness, leaked internal research from 2016 appears to indicate. Building features to combat that would require the company to sacrifice engagement – and by extension, profit – according to a later document from 2018 which described the proposals as "antigrowth" and requiring "a moral stance." "Our algorithms exploit the human brain's attraction to divisiveness," a 2018 presentation warned, warning that if action was not taken Facebook would provide users "more and more divisive content in an effort to gain user attention & increase time on the platform." According to a report from the Wall Street Journal, in 2017 and 2018 Facebook conducted research through newly created "Integrity Teams" to tackle extremist content and a cross-jurisdictional task force dubbed "Common Ground."
Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A Utah man was arrested on Sunday after he called police claiming he had killed a woman he met on Tinder. Ethan Hunsaker, 24, surrendered to officers from the Layton Police Department and was charged with first-degree murder. He told police he had met the 25-year-old victim late Saturday night after connecting on the dating app.
Its impact is drastic and real: Youtube's AIdriven recommendation system would present sports videos for days if one happens to watch a live baseball game on the platform ; email writing becomes much faster with machine learning (ML) based auto-completion ; many businesses have adopted natural language processing based chatbots as part of their customer services . AI has also greatly advanced human capabilities in complex decision-making processes ranging from determining how to allocate security resources to protect airports  to games such as poker  and Go . All such tangible and stunning progress suggests that an "AI summer" is happening. As some put it, "AI is the new electricity" . Meanwhile, in the past decade, an emerging theme in the AI research community is the so-called "AI for social good" (AI4SG): researchers aim at developing AI methods and tools to address problems at the societal level and improve the wellbeing of the society.
"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.
Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.
If you ever get the creepy feeling you're being monitored when you use your computer, smartphone or smart speaker, our guest Geoffrey Fowler is here to tell you you are. Fowler writes a consumer-oriented technology column for The Washington Post. He's been investigating the ways our browsers and phone apps harvest personal information about us even while we're sleeping. And he discovered that Amazon had kept four years' worth of recorded audio from his home, captured by his Alexa smart speaker, including family conversations about medications and a friend doing a business transaction. Geoffrey Fowler joined the Post in 2017 after 16 years with the Wall Street Journal, writing about consumer technology, Silicon Valley, national affairs and China. He writes his technology column from San Francisco. He spoke with FRESH AIR's Dave Davies. You have a recent column. The headline is "I Found Your Data. It's For Sale." What kind of personal data did you find available for sale on the Internet? GEOFFREY FOWLER: I found all kinds of things that normal people would consider secrets and that corporations spend a lot of money - millions and millions of dollars - to try to keep out of the hands of their competitors and criminals. I found people's flight records. I found people's records from their doctors prescribing them medications. I found people's tax documents that they were - thought they were only sharing with their tax preparer. And they were available with one click. I could have opened them up and downloaded them. And where did this data come from?
Recommender systems are personalized information access applications; they are ubiquitous in today's online environment, and effective at finding items that meet user needs and tastes. As the reach of recommender systems has extended, it has become apparent that the single-minded focus on the user common to academic research has obscured other important aspects of recommendation outcomes. Properties such as fairness, balance, profitability, and reciprocity are not captured by typical metrics for recommender system evaluation. The concept of multistakeholder recommendation has emerged as a unifying framework for describing and understanding recommendation settings where the end user is not the sole focus. This article describes the origins of multistakeholder recommendation, and the landscape of system designs. It provides illustrative examples of current research, as well as outlining open questions and research directions for the field.
Amazon Alexa has been programmed to read the news headlines in the style of a newsreader. The popular voice assistant will now emphasise words, and mimic the intonation and pace of a TV anchor to present the news in a more natural way. Newsreader Alexa has been trained to read the daily bulletins when the user says'Alexa, what's the latest?' Amazon Alexa has been programmed to read the news headlines in the style of a newsreader. The virtual assistant already was able to read out the headlines but using the traditional robotic voice. Amazon conducted tests and found that people preferred hearing the news in this more realistic and listener friendly manner, compared to the robotic tone.
An Amazon customer got a grim message last year from Alexa, the virtual assistant in the company's smart speaker device: "Kill your foster parents." The user who heard the message from his Echo device wrote a harsh review on Amazon's website, Reuters reported - calling Alexa's utterance "a whole new level of creepy". An investigation found the bot had quoted from the social media site Reddit, known for harsh and sometimes abusive messages, people familiar with the investigation told Reuters. The odd command is one of many hiccups that have happened as Amazon tries to train its machine to act something like a human, engaging in casual conversations in response to its owner's questions or comments. The research is helping Alexa mimic human banter and talk about almost anything she finds on the internet.