It's not yet clear whether, with the rise of artificial intelligence, workforce automation will lead to an overall rise or drop in human job creation. That's the argument put forward by University of Geneva professor and tax lawyer Xavier Oberson. Oberson argues that as robots take over more and more jobs – particularly in the industry and service sectors – there will be a rise in unemployment and a corresponding drop in tax and social security receipts by governments all over the world. He believes that imposing a tax on work done by robots could help offset these losses. Logistically, he says this could be managed by creating a "legal entity" representing robots, just as is done today for corporations.

The Trump administration appears to be taking a hands-off approach to preparing for the future of automation and artificial intelligence, despite warnings from tech analysts who say AI is already here and helped guide policy measures enacted in the waning months of the Obama presidency. During a press event last week, Treasury Secretary Steven Mnuchin told reporters he's not concerned by the prospect of millions of Americans losing their jobs to artificial intelligence, saying he doesn't expect the technological shift to happen for a long time. "That is so far in the future, in terms of artificial intelligence taking over American jobs, we're like so far away from that, not even on my radar screen," Mnuchin said at an event hosted by news website Axios. "I think it's 50 or 100 more years." Although it's unclear whether Mnuchin's comments represent a formal administration position, the treasury secretary is traditionally one of the president's most influential economic advisers.

Job Requirements • Master's degree or equivalent work experience in machine learning • Strong hands on experience solving complex problems using unsupervised and supervised machine learning algorithms • Proficiency in feature selection and feature engineering • Strong experience with big data tools and techniques, like Hadoop and Spark • Broad knowledge of machine learning algorithms, with ability to select and apply appropriate algorithms to specific problem domains • Ability to collaborate with domain experts to efficiently and effectively identify and extract previously unfamiliar domain knowledge Preferred • Knowledge in Natural Language Processing, especially named entity recognition • Experience in problems associated with people-centric data, like name parsing, name comparison, address parsing etc. • Experience with frameworks and techniques in deep learning and deep neural networks • Experience with computer vision, particularly facial recognition and comparison About SureID SureID, Inc. integrates leading edge products and services into solutions that combine identity enrollment, authentication, background screening, and access management to make facilities, assets, and people safer and more secure. Using SureID's patented programs, highly secure facilities – such as military installations, government buildings, manufacturing and distribution sites, ports, and commercial builds – can increase security and streamline access for authorized personnel. SureID has a proven track record for successfully servicing government, military and commercial clients. The RAPIDGate Program already serves thousands of companies and hundreds of thousands of RAPIDGate badge-holders who enjoy streamlined access into Department of Defense and Homeland Security facilities. SureID is a privately-held company founded in November 2001 and headquartered in Hillsboro, OR.

Treasury Secretary Steve Mnuchin says artificial intelligence is "so far in the future" that it's "not even on my radar screen." He says we won't have to worry about how it affects the workforce for "50 or 100 more years." Steve Mnuchin is not concerned one bit with AI and automation. In fairness to Mnuchin, the question was specifically about artificial intelligence, not robots. It's a fine distinction, but an important one -- while robots that can perform repetitive tasks have been in wide industrial use for decades now, artificial intelligence is a class of software that can "learn" and let machines do more sophisticated jobs.

If you're a brand advertiser at a car company or a cereal maker, you may want to know when your product appears, unscripted, in hundreds of hours of TV shows or online videos. How to track that without watching all of it? An artificial intelligence startup has the answer. Matroid, founded by Stanford University adjunct professor Reza Zadeh, can scan video for all sorts of things like when President Donald Trump appears, or how often a man holding a gun is recorded. Users can easily write a filter--Matroid calls them detectors--of their own to find particular people or objects, or they can pick from a library of pre-programmed filters designed by the startup.

Treasury Secretary Steven Mnuchin says he's "not at all" worried about robots displacing American workers, and his definition of artificial intelligence comes from Star Wars. In an interview today with Axios' Mike Allen, Mnuchin said he was unconcerned about the effects of automation, both with physical machines and artificial intelligence. "In terms of artificial intelligence taking over American jobs, I think we're so far away from that that it's not even on my radar screen," he said in response to a question from Allen. "I think it's 50 or 100 more years." When pressed, Mnuchin said that he wasn't talking about things like self-driving cars, which he believes could run from coast to coast in the not-so-distant future.

If there's one thing that labor economists and leaders in Silicon Valley generally seem to agree on, it's that increasingly sophisticated technology is coming to replace American jobs. According to a new report from PricewaterhouseCoopers, 38 percent of U.S. jobs are at high risk of being replaced by automation in the next 15 years, compared with 30 percent of jobs in the U.K. and 21 percent in Japan. The United States, like the United Kingdom, is dominated by service jobs in sectors like manufacturing, transportation, finance, and food service, and U.S. jobs are particularly at risk because, according to PwC's chief U.K. economist John Hawksworth, the tasks American workers perform are just easier to automate. Still, the White House seems completely uninterested in the imminent threat facing U.S. employment and wages, choosing to cast blame instead on China and Mexico for the decline of U.S. manufacturing jobs. "We want products made by our workers in our factories stamped with those four magnificent words--made in the U.S.A.," President Donald Trump declared on a recent trip to a Boeing plant in South Carolina.

Both artificial intelligence and blockchain technology have made major advances in the past few years. Could they be combined to bring us the money of the future? Recently, many advances have been made in the field of artificial intelligence. In the past few years, we saw artificial intelligence beat one of the world's best players at Go, save drivers from car crashes, and predict the outcome of the US Presidential Election. Many companies, both established market leaders and new startups, have started to incorporate artificial intelligence into mainstream products.

NASA announced Friday that its OSIRIS-Rex spacecraft -- bound for the near-Earth asteroid Bennu -- had successfully scanned part of its surrounding space for Earth-Trojan asteroids. Although no such asteroids were discovered, the scan demonstrated that a key instrument on board the spacecraft was functioned much better than expected. "The Earth-Trojan Asteroid Search was a significant success for the OSIRIS-REx mission," OSIRIS-REx Principal Investigator Dante Lauretta from the University of Arizona, Tucson, said in a statement. "In this first practical exercise of the mission's science operations, the mission team learned so much about this spacecraft's capabilities and flight operations that we are now ahead of the game for when we get to Bennu." Scientists believe that Earth-Trojan asteroids exist in the Earth-Sun Lagrangian points L4 and L5, which are stable points 60 degrees in front and 60 degrees behind Earth in its orbit.

Even if you haven't had a chance to check out TensorFlow in detail, it's clear that your choice of platform has a big impact just as it does for other machine learning frameworks. The adventure from trial to production involves many intermediate destinations, from feature engineering to model-building to execution and real-time evaluation. Even a model with the most spectacular F1-score is only as good as how effectively you can put it to use helping customers. Questions arise such as: do you need to evaluate against data for offline or online analysis (or both)? Where does the preprocessed (or feature-engineered) data live on its way to TensorFlow? Is there a way to preserve data lineage as it moves through the various stages to support both security concerns as well as easy debugging?