Ever since the election, talking heads have discussed how "fake news" could have tipped the election to Donald Trump by disseminating false stories favorable to him or unfavorable to Hillary Clinton. Social media users can spread these fake new stories far and wide, creating an aura of credibility which can make fake stories hard to distinguish from the truth. Social media websites like Facebook have begun to cooperate with human fact checkers to track fake news websites and notify users that a story is likely false, but it is impossible to trace every single news story as they pop up. There is just too much information on the internet for any human mind to process. So maybe an artificial intelligence (AI) can perform better. Facebook along with researchers and hackers are examining whether artificial intelligence and big data can help track down fake news stories faster than humans can.

Public Sector Agencies Must Adopt Emerging Technologies Like Machine Learning and Artificial Intelligence to Effectively Compete for Talent, Accenture Report Finds ARLINGTON, Va.; Feb. 2, 2017 – Public sector agencies must adopt emerging technologies – including machine learning, artificial intelligence and biometrics – to attract and retain more technically adept employees. This approach is critical to addressing a widening skills gap and strong competition from a better financed private sector, a new report from Accenture (NYSE: ACN) shows. The report, Emerging Technologies in Public Service, examines the adoption of emerging technologies across agencies with the most direct interaction with citizens or the greatest responsibility for citizen-facing services: health and social services, policing/justice, revenue, border services, administration and pensions / social security. As part of the report, Accenture surveyed nearly 800 public service technology professionals across nine countries to identify emerging technologies being implemented or piloted. These technologies include advanced analytics/ predictive modeling, the Internet of Things, intelligent process automation, video analytics, biometrics/ identity analytics, machine learning, and natural language processing/ generation.

Today in Entertainment: Samantha Bee urges viewers to push back against Trump; 'Sharknado 5' news Major award shows such as the Grammys and the Oscars are right around the corner, but much of the arts and entertainment world is spending more time reacting to the new presidency of Donald Trump and his recent executive order on immigration. This visa-holding college kid is who Trump's travel ban is keeping out Entertainment in January: Oprah to join '60 Minutes'; AFI supports Asghar Farhadi This visa-holding college kid is who Trump's travel ban is keeping out Entertainment in January: Oprah to join '60 Minutes'; AFI supports Asghar Farhadi Blockbusters were the play of the day for the Super Bowl as sequels in the "Fast and Furious," "Pirates of the Caribbean" and "Guardians of the Galaxy" franchises made their mark during the Big Game.

Dlib is a modern C toolkit containing machine learning algorithms and tools for creating complex software in C to solve real world problems. That will build all the examples. Before you can run the Python example programs you must compile dlib. Note that on windows your compiler might put the test executable in a subfolder called Release. If that's the case then you have to go to that folder before running the test.

The use of Bayesian methods in large-scale data settings is attractive because of the rich hierarchical models, uncertainty quantification, and prior specification they provide. Standard Bayesian inference algorithms are computationally expensive, however, making their direct application to large datasets difficult or infeasible. Recent work on scaling Bayesian inference has focused on modifying the underlying algorithms to, for example, use only a random data subsample at each iteration. We leverage the insight that data is often redundant to instead obtain a weighted subset of the data (called a coreset) that is much smaller than the original dataset. We can then use this small coreset in any number of existing posterior inference algorithms without modification. In this paper, we develop an efficient coreset construction algorithm for Bayesian logistic regression models. We provide theoretical guarantees on the size and approximation quality of the coreset -- both for fixed, known datasets, and in expectation for a wide class of data generative models. Crucially, the proposed approach also permits efficient construction of the coreset in both streaming and parallel settings, with minimal additional effort. We demonstrate the efficacy of our approach on a number of synthetic and real-world datasets, and find that, in practice, the size of the coreset is independent of the original dataset size. Furthermore, constructing the coreset takes a negligible amount of time compared to that required to run MCMC on it.

As we are in the beginning of tax season, millions of Americans are eager to learn what this tax season holds for them. For many Americans tax season is officially their Christmas -- a big refund is what they are anticipating. For others, they just want to break even so they do not owe any money to the IRS. Wherever you fall along these lines, you want to make sure that your taxes are accurately being prepared to ensure that you experience no issues with the IRS. H&R Block has introduced a new partnership with IBM Watson to bring its customers a new and improved tax preparation experience.

Public sector agencies must adopt emerging technologies – including machine learning, artificial intelligence, and biometrics – to attract and retain more technically adept employees, a new report from Accenture recommends. It said this is critical to addressing a widening skills gap and strong competition from a better financed private sector. According to the report, "Emerging Technologies in Public Service," the need to attract technically proficient employees is becoming even more urgent as the existing workforce continues to age, creating an irrevocable loss of institutional knowledge unless action is taken now. The report emphasized that hiring and developing people with the necessary skills, including the need for emerging technology specialists, is one of the top three challenges across all industries and countries today," the report noted. "The very concept of work is being redefined as different generations enter and exit the workforce in a rapidly changing technological landscape," said Terry Hemken, who leads Accenture's Health & Public Service Analytics Insights for Government business. "Government leaders must make every effort to reskill their people to be relevant in the future and ready to adapt to change." Survey respondents said emerging technologies will augment existing roles rather than replace them. Automating tasks, whether through artificial intelligence, machine learning or other technologies, frees up employees to focus on activities that are more critical and more closely aligned with citizen needs, according to the research. In fact, eight in 10 respondents said that implementing emerging technologies will improve job satisfaction and can aid staff retention, partly by automating certain repetitive tasks and making others more aligned with citizens' direct needs. Nearly 60 percent of respondents also said that being able to implement projects using emerging technologies would require significant investment in reskilling existing staff. "Responsive and responsible leaders must ensure that their people are relevant and adaptable to keep pace with technology," Hemken said. "Creating the future workforce now is the responsibility of the very highest levels of an organization.

'The National Highway Traffic Safety Admnnistration, under the U.S. Department of Transportation, has issued its' official report on the crash of a Tesla so-called "Auto-pilot" vehicle which crashed into a big rig last summer. "Problem Description: The Automatic Emergency Braking (AEB) or Autopilot systems may not function as designed, increasing the risk of a crash."'

Comparing the World Economic Forum at Davos and President Donald Trump's inaugural speech last week is like a rare observation of two parallel universes colliding. One is a gathering of the world's economic, banking and technology elite. The other was a speech wrapped in doses of hyperbole- a pugilistic, nationalistic call to arms against the elite that painted an unbearable American dystopia. At Davos, the talk of artificial intelligence was dominated not by business benefits and lucrative efficiencies, but the consequences for the humans caught on the wrong side of technological progress. They are only now starting to consider the changes they are inflicting upon the world.

Chess enthusiasts watch World Chess champion Garry Kasparov on a television monitor as he holds his head in his hands at the start of the sixth and final match 11 May 1997 against IBM's Deep Blue computer in New York. Kasparov lost this match in just 19 moves giving overall victory to Deep Blue with a score of 2.5-3.5 (STAN HONDA/AFP/Getty Images) This week's milestones in the history of technology include the invention of the integrated circuit, the first singing telegram, and the first widely-publicized triumph of the machines over humans. Jack Kilby of Texas Instruments (TI) files for a patent on the integrated circuit. For this invention he received the 2000 Nobel Prize for Physics. The notion of an integrated circuit was there.