There is little doubt that the Defense Department needs help from Silicon Valley's biggest companies as it pursues work on artificial intelligence. The question is whether the people who work at those companies are willing to cooperate. On Thursday, Robert O. Work, a former deputy secretary of defense, will announce that he is teaming up with the Center for a New American Security, an influential Washington think tank that specializes in national security, to create a task force of former government officials, academics and representatives from private industry. Their goal is to explore how the federal government should embrace A.I. technology and work better with big tech companies and other organizations. There is a growing sense of urgency to the question of what the United States is doing in artificial intelligence.

More than a year after entering the White House, President Trump still has not selected his top science and technology adviser, leaving unfilled a critical policy post that guides the administration on issues as varied as artificial intelligence, climate change and cancer research. While the White House maintains that it is unconstrained in its work -- and has staffed up to tackle such challenges as closing the country's Internet-access gaps -- the vacancy still troubles policy experts, who feel that Trump would be best served by someone who could double as an emissary to the academic and engineering worlds. "Symbolically, it signals science and technology is at the table in the administration's policymaking," said Kumar Garg, who was an innovation policy aide under President Barack Obama. "But also substantively, because the science adviser is the principal who gets invited to senior strategy meetings ... on critical topics like biosecurity, cybersecurity, [and] how do we make sure America remains competitive against China and Russia in emerging technology." Technically, the White House has two major science and technology posts.

Both industries see huge potential revenues in the market for autonomous vehicles, which could be available for wide use in just two years. But it remains unclear how many drivers will be ready to give up control, and many countries must still put laws in place to allow self-driving cars to hit the road.

NextGov: Discussions about the future of artificial intelligence with some technology novices--and experts--are often rife with references to "The Matrix" and "Terminator," but such romanticizing can stall agencies from adopting the technology, according to a top government scientist. "Do not be seduced into thinking [artificial intelligence] is different than any other IT application--it is not," said Alexander Kott, chief scientist at the Army Research Lab. "AI is not a magic dust."

Introverts are uniquely suited to disruption because they're comfortable playing where other people aren't

Stephen Hawking's fame was founded on the research he did on general relativity and black holes. But he often stepped outside his own field of research, using his recognition to highlight what he saw as the great challenges and existential threats for humanity in coming decades. His pronouncements drove headlines in the media, which sometimes proved controversial. Hawking was clearly troubled that we were putting all our eggs in one basket - that basket being Earth. For decades, Hawking had been calling for humans to begin the process of permanently settling other planets.

It was the last question of the night and it hushed the entire room. An entrepreneur expressed his aggravation about the FDA's antiquated regulatory environment for AI-enabled devices to Dr. Joel Stein of Columbia University. Stein a leader in rehabilitative robotic medicine, sympathized with the startup knowing full well that tomorrow's exoskeletons will rely heavily on machine intelligence. Nodding her head in agreement, Kate Merton of JLabs shared the sentiment. Her employer, Johnson & Johnson, is partnered with Google to revolutionize the operating room through embedded deep learning systems. To better understand the frustration expressed at RobotLab, a review of the policies of the Food & Drug Administration (FDA) relative to medical devices and software is required.

The European Robotics Forum 2018 (ERF2018), the most influential meeting of the robotics community in Europe, takes place in Tampere on 13-15 March 2018. ERF brings together over 900 leading scientists, companies, and policymakers for the largest robotics networking event in Europe. Under the theme "Robots and Us", the over 50 workshops cover current societal and technical themes, including human-robot-collaboration and how robotics can improve industrial productivity and service sector operations. During the opening the ERF2018, on 13 March, Juha Heikkilä, Head of unit, EC DG CNECT, explained that "the European Robotics Forum has been instrumental in breaking down silos and bringing together a strong, integrated robotics community in Europe. This year's theme, "Robots and Us", reflects the increasingly broad impact of robotics and allows discussing not just technology but also the all-important non-technological aspects of robotics."

Scientific fields such as insider-threat detection and highway-safety planning often lack sufficient amounts of time-series data to estimate statistical models for the purpose of scientific discovery. Moreover, the available limited data are quite noisy. This presents a major challenge when estimating time-series models that are robust to overfitting and have well-calibrated uncertainty estimates. Most of the current literature in these fields involve visualizing the time-series for noticeable structure and hard coding them into pre-specified parametric functions. This approach is associated with two limitations. First, given that such trends may not be easily noticeable in small data, it is difficult to explicitly incorporate expressive structure into the models during formulation. Second, it is difficult to know $\textit{a priori}$ the most appropriate functional form to use. To address these limitations, a nonparametric Bayesian approach was proposed to implicitly capture hidden structure from time series having limited data. The proposed model, a Gaussian process with a spectral mixture kernel, precludes the need to pre-specify a functional form and hard code trends, is robust to overfitting and has well-calibrated uncertainty estimates.

Atlanta was Georgia's only applicant and is considered a front runner, with an Amazon lobbyist visiting the city in December. Atlanta never disclosed the details of the proposal it submitted for HQ2, but it described it as'aggressive' in terms of incentives offered. City officials did not specify what the incentives were. 'On the city side alone, we put forth more incentives than we've ever put forward in the history of the city,' Mayor Kasim Reed said last year, adding that'nothing was left on the table.' Austin did not promise any financial incentives or city tax cuts with its proposal.