Goto

Collaborating Authors

 Government


Filipinos losing jobs to artificial intelligence? Bam Aquino worried

#artificialintelligence

There seems to be no escaping a future where robots and artificial intelligence (AI) get to perform more and more jobs, as sci-fi films warn. But Sen. Bam Aquino is not too excited about reaching such technotopia, as he raised concerns about AI completely doing away with human intelligence and leaving thousands of Filipino workers jobless. Aquino, who chairs the Senate committee on science and technology, filed a resolution on Friday seeking an inquiry into the government's preparedness to address the negative effect of AI on the country's workforce. The Department of Science and Technology (DOST) has been tapped to develop an AI program in the Philippines to optimize mass production, particularly in the country's manufacturing sector. Artificial intelligence is defined as the capability of machines to imitate human cognitive functions in doing simple to complex tasks.


Artificial intelligence is coming for law firms

#artificialintelligence

French presidential candidate Emmanuel Macron's campaign said Friday it has been hacked -- 9GB of authentic and fake emails were posted Friday to Pastebin, a document-sharing site, from a user named EMLEAKS, according to Reuters. The campaign said this is "déjà vu" of the kind of "democratic destabilization" that took place in the U.S. last year. Why it matters: It's less than two days before the French presidential election comes to a close, and the way that works in France includes a ban on campaigning over the weekend. The hack came hours before the ban sets in. What to watch: The polls.


Singapore's artificial intelligence capabilities to get S$150m boost

#artificialintelligence

SINGAPORE: The National Research Foundation (NRF) will be investing up to S$150 million into a new national programme aimed at boosting Singapore's artificial intelligence (AI) capabilities over the next five years. Called AI.SG, the initiative will see Singapore-based research institutes partner AI start-ups and companies developing AI products to grow knowledge in the space, create tools and develop talent to power the country's AI efforts. This was announced by Minister for Communications and Information Yaacob Ibrahim at the opening of InnovFest Unbound event on Wednesday (May 3). "AI.SG will do three key things – first, address major challenges that affect both society and industry. Secondly, invest in deep capabilities to catch the next wave of scientific innovation. And finally, to grow AI innovation and adoption in companies - an initiative most pertinent to our business community," said Dr Yaacob.


Robotics, Artificial Intelligence Could Transform Society, But at What Cost?

#artificialintelligence

Some of the world's wealthiest and most influential leaders came to California this week for the Milken Institute Global Conference, a wide-ranging review of issues permeating economics and politics, with topics ranging from agriculture to mortgage markets to international trade and alliances, plus a long look at what the future will hold. Of the 4,000 VIPs who attended -- invitations are highly selective, and tickets topped out as high as $50,000 -- one of the most intriguing questions under discussion was one that almost no one could readily answer: What effect will robotics and artificial intelligence have on our lives and on the world's business, and how rapidly will this next technological revolution take place? The Milken Institute Global Conference, an annual event for the past 20 years, has grown steadily into a unique gathering: individuals with the capital, power and influence to move the world forward meet face-to-face with those whose expertise and creativity are reinventing industry, philanthropy and media. This year's meeting in Beverly Hills, California, amounted to a peer review of President Donald Trump's first 100 days in office. Four members of Trump's Cabinet took part.


What 'Hidden Figures' Can Teach Recruiters About AI

#artificialintelligence

In the recent film "Hidden Figures," a group of women known as "computers," help mastermind NASA's effort to put a man into space and eventually on the moon. Without their hard work and brilliance, America's famed "moonshot" might never have succeeded. By the end of the film, their roles have largely been replaced by a computer that is capable of making millions of calculations per second -- a feat that far surpasses their abilities. Instead of despairing that they might find themselves without a job, these women adapted: they learned computer programming, thereby ensuring their ongoing relevance despite the growing role of computers at NASA. The advent of artificial intelligence, deep learning, and automation has everyone from Elon Musk to Stephen Hawking worried about the consequences.


Encapsulating models and approximate inference programs in probabilistic modules

arXiv.org Artificial Intelligence

This paper introduces the probabilistic module interface, which allows encapsulation of complex probabilistic models with latent variables alongside custom stochastic approximate inference machinery, and provides a platform-agnostic abstraction barrier separating the model internals from the host probabilistic inference system. The interface can be seen as a stochastic generalization of a standard simulation and density interface for probabilistic primitives. We show that sound approximate inference algorithms can be constructed for networks of probabilistic modules, and we demonstrate that the interface can be implemented using learned stochastic inference networks and MCMC and SMC approximate inference programs.


Measuring the non-asymptotic convergence of sequential Monte Carlo samplers using probabilistic programming

arXiv.org Machine Learning

A key limitation of sampling algorithms for approximate inference is that it is difficult to quantify their approximation error. Widely used sampling schemes, such as sequential importance sampling with resampling and Metropolis-Hastings, produce output samples drawn from a distribution that may be far from the target posterior distribution. This paper shows how to upper-bound the symmetric KL divergence between the output distribution of a broad class of sequential Monte Carlo (SMC) samplers and their target posterior distributions, subject to assumptions about the accuracy of a separate gold-standard sampler. The proposed method applies to samplers that combine multiple particles, multinomial resampling, and rejuvenation kernels. The experiments show the technique being used to estimate bounds on the divergence of SMC samplers for posterior inference in a Bayesian linear regression model and a Dirichlet process mixture model.


DeepDeath: Learning to Predict the Underlying Cause of Death with Big Data

arXiv.org Machine Learning

Multiple cause-of-death data provides a valuable source of information that can be used to enhance health standards by predicting health related trajectories in societies with large populations. These data are often available in large quantities across U.S. states and require Big Data techniques to uncover complex hidden patterns. We design two different classes of models suitable for large-scale analysis of mortality data, a Hadoop-based ensemble of random forests trained over N-grams, and the DeepDeath, a deep classifier based on the recurrent neural network (RNN). We apply both classes to the mortality data provided by the National Center for Health Statistics and show that while both perform significantly better than the random classifier, the deep model that utilizes long short-term memory networks (LSTMs), surpasses the N-gram based models and is capable of learning the temporal aspect of the data without a need for building ad-hoc, expert-driven features.


Silicon Valley jumps into biometric gold rush for Trump's 'other border wall'

PBS NewsHour

HOUSTON – An arriving passenger uses a biometric scanner at George H. W. Bush Intercontinental Airport February 1, 2008 in Houston, Texas. Under President Donald Trump, technology companies have started cashing in on a little-noticed government push to ramp up the use of biometric tools -- such as fingerprinting and iris scanners -- to track people who enter and exit the country. Silicon Valley firms that specialize in data collection are taking advantage of a provision tucked into Mr. Trump's executive order on immigration, which included his controversial travel ban, that called for the completion of a "Biometric Entry-Exit Tracking System" for screening travelers entering and leaving the United States. The tracking system was mandated in a 1996 immigration law passed by Congress but never fully implemented by Trump's past three predecessors. In Trump's first months in office, federal courts blocked the sections of his original and revised immigration orders that called for a temporary travel ban on visitors from seven majority Muslim countries.


Week in Review: Apple, Microsoft A.I. Investments, 'Reality Caucus' Xconomy

#artificialintelligence

Some 2,500 lightning strikes were recorded across Western Washington Thursday as powerful thunderstorms marched up the state, getting everyone's attention and lighting up social media with beautiful photographs, such as the one below. In tech news this week, we're tracking a new state-by-state jobs report from Apple, Microsoft Ventures' latest A.I. investments, Seattle's new broadband privacy rules, and Congresswoman Suzan DelBene's new caucuses on reality (virtual and augmented) and digital trade. This one is from a few shots layered, all the bolts are in the right place. CEO Tim Cook pledged a $1 billion investment in U.S. advanced manufacturing. In addition to direct employment, Apple counted 81,100 jobs in Washington connected to its App Store ecosystem.