Jun-18-2017


Google bets AI and human oversight will curb online extremism

#artificialintelligence

To start, it's pouring more energy into machine learning research that could improve its ability to automatically flag and remove terrorist videos while keeping innocently-posted clips (say, news reports) online. It's also expanding its counter-radicalization system, which shows anti-extremist ads to would-be terrorist recruits. Google plans to "greatly increase" the number of humans in its YouTube Trusted Flagger program, improving the chances that it'll catch terrorist material. Google wants to tackle those YouTube videos that are borderline, too -- if it spots videos with "inflammatory" religious or supremacist material, it'll put those clips behind a warning and prevent them from getting ad revenue, comments or viewing recommendations.


Google bets AI and human oversight will curb online extremism

#artificialintelligence

To start, it's pouring more energy into machine learning research that could improve its ability to automatically flag and remove terrorist videos while keeping innocently-posted clips (say, news reports) online. It's also expanding its counter-radicalization system, which shows anti-extremist ads to would-be terrorist recruits. Google plans to "greatly increase" the number of humans in its YouTube Trusted Flagger program, improving the chances that it'll catch terrorist material. Google wants to tackle those YouTube videos that are borderline, too -- if it spots videos with "inflammatory" religious or supremacist material, it'll put those clips behind a warning and prevent them from getting ad revenue, comments or viewing recommendations.


What does a world with 36% unemployment look like? A video game called 'Detroit: Become Human'

#artificialintelligence

Man has grappled with his place among machines since the days of John Henry and the steam engine at the turn of the twentieth century. Here at the turn of the twenty-first, it's not brawn the machines are replacing, but brains. Computational power is at an all-time high, and the threat of automation looms large across our economic horizon. And while many minds are pondering what comes next, one such mind made a video game about it. Detroit: Become Human is the latest release from visionary game developer David Cage, known for making games that are far more story-driven and impactful than almost anything else on the shelf, such as Beyond: Two Souls or Heavy Rain.


How Machine Learning Can Improve Healthcare, Medicine And Human Well-Being

#artificialintelligence

Investors hope for billion-dollar health-tech "unicorns". Amid such talk it is worth remembering that the biggest winners from digital health care will be the patients who receive better treatment, and those who avoid becoming patients at all.' – The Economist Machine learning and Artificial Intelligence (AI) continue to transform many aspects of our lives. The potential gains in healthcare are enormous. Although investment in digital healthcare start-ups has doubled since 2013, progress is slow, in part because of regulatory and cost hurdles. Machine learning in healthcare means that organisations can benefit from evolving technological capabilities.


The Next Big Opportunity for Tech Entrepreneurs? 'Smart' Homes

#artificialintelligence

The role of technology in the home has changed drastically in recent years. We've come a long way from the kitchen wall phone and desktop computer, in an era when smartphones, tablets and wearables dominate the scene. The newest wave comes from the internet of things (IoT), and today's offerings are raising the bar on what makes a device "smart." Increasingly, "smart" means safe, in terms of security and health. Joe Colistra, architect at the Center for Design Research at the University of Kansas, was recently profiled in The Atlantic on his vision for a smart home that safeguards occupants' well-being.


Keeping Our Human Edge In A Machine-Dominated World - Forbes Middle East

#artificialintelligence

Am I alone in thinking that it is a shame we can fix fewer things by ourselves these days? Personally, I always drew great satisfaction from fixing a broken piece of equipment. I enjoyed opening it – against the manufacturers' warnings – to discover how it actually worked, and then fix it using superglue or a paperclip. We are increasingly denied this feeling of being in control. It started with simple, loose parts being replaced by horrendously expensive integrated parts.


AI Apps All Set To Be The Game-Changers For Various Industries

#artificialintelligence

Technology has taken over the world, with every day ushering in innovations at various levels. Artificial intelligence is the tech buzzword of the current times as it is poised to take machine functionality to a new level. As the name suggests, AI is the capability of machines to mimic and even improve on the human brain's cognitive abilities. The technology capitalizes on the superior computational abilities of machines as they are well-equipped to handle huge amounts of data and use it for decision-making. With such extensive benefits, AI serves as a dependable technology for enterprises across industries.


Google bets AI and human oversight will curb online extremism

Engadget

Google is under a lot of pressure to stamp out extremists' online presences, and it's responding to that heat today. The internet giant has outlined four steps it's taking to flag and remove pro-terrorism content on its pages, particularly on YouTube. Technological improvements play a role, of course, but the company is also counting on a human element that will catch what its automated filters can't. To start, it's pouring more energy into machine learning research that could improve its ability to automatically flag and remove terrorist videos while keeping innocently-posted clips (say, news reports) online. It's also expanding its counter-radicalization system, which shows anti-extremist ads to would-be terrorist recruits.


[P] python-recsys (SVD) with implicit feedback rather than ratings (recommender systems). • r/MachineLearning

@machinelearnbot

Check out Crab if you haven't already. SVD will probably not work well off the bat, unless you have a way to mark "unmeasure/NA" pieces and avoid those in the SVD computation. Some sparse SVD implementations may have this, but I don't know any offhand in Python. You can still do 0/1 (2 score) rating with recommender systems, though if you have extra information (confidence) that can help. This 0/1 setup is really similar to "click through prediction", or CTR as well which is a huge field (and again, $$$ related) - check out some code that is awesome (I didn't write it, but learned a ton from it), also see the discussion in the old Kaggle competition I link to in that gist.


The steps in the machine learning workflow

@machinelearnbot

From medical diagnosis, speech, and handwriting recognition to automated trading and movie recommendations, machine learning techniques are being used to make critical business and life decisions every moment of the day. Each problem is unique, so it can be challenging to manage raw data, identify the right data to include in the model, train multiple types of models, and perform model assessments. Machine learning uses algorithms that learn from data to help make better decisions; however,it is not always obvious what the best machine learning algorithm is going to be for a particular problem. Luckily, information such as variable importance and model assessment tools can help us decide which machine learning techniques to apply. Examples of machine learning techniques include clustering, where objects are grouped into bins with similar traits; regression, where relationships among variables are estimated; and classification, where a trained model is used to predict a categorical response.