Russian President Vladimir Putin has offered the best insight yet at what shape the country's AI strategy will take. Putin ordered his government apparatus on February 27th to formulate a national artificial intelligence strategy by June 25th. With that date quickly approaching, the world is waiting to see Russia's AI plans. Back in September 2017, Putin famously said the nation which leads in AI "will become the ruler of the world." Understandably, Putin's comments generated fear of a cold war-like rush to militarise AI technology.

A team of innovation specialists at the Census Bureau is working to speed up the process for getting security authorizations--known as an authority to operate, or ATO--for new systems and applications. Among their potential solutions: Developing an artificial intelligence bot that offers wisdom from successful ATOs, akin to Microsoft's much-maligned Clippy office assistant. Security officials focused on the ATO process have long urged agencies to reuse authorizations for like-for-like systems. While leaders have said that is happening more often, program managers are often reticent to reuse an authorization that might not track exactly to the app they are standing up. But for a given security control, there is language and considerations for how the documentation is put together that can easily be borrowed from one authorization to the next, according to the Census FISMAtic project team.

Air Force researchers working with artificial intelligence code may soon have a platform that gives them secure access to educated end-users and outside developers, algorithms, mission data and computational hardware. Because the Defense Department's does not allow unvetted software or code on its networks, it's difficult for developers to experiment with cutting-edge tools. But the Air Force is looking to dismantle some of those barriers with its Air Force Cognitive Engine (ACE) software platform. "We're trying to create a software ecosystem to hook up the core infrastructures that are required for successful AI development -- that's people, algorithms, data and computational resources," said Maj. Michael Seal, director for the Air Force's Autonomy Capability Team 3, which leads the ACE program. The traditional DOD way, Seal said during the Defense Department's April 25 Lab Day, is for people to use the network they're told to use, use one that houses data from an amalgamation of sources and use whatever tools are approved and available.

The Health and Human Services Department awarded 57 spots on its Intelligent Automation/Artificial Intelligence, or IAAI, contract, a $49 million vehicle that officials hope one day will compete with the massive governmentwide acquisition contracts, or GWACs. The department awarded spots to 28 small business and 29 large vendors, according to data obtained by Nextgov. See the full list at the end of the article. The vendors will offer a "catalog of emerging technologies" centered around robotic process automation, or RPA, and general AI tools. "When we say'artificial intelligence,' we're using the term very broadly," Lori Ruderman, who leads the HHS Buy Smarter initiative and is a senior adviser at the Program Support Center, said in January in the middle of the solicitation process.

The altered video of Nancy Pelosi giving a speech at the Center for American Progress on May 22, which had been slowed down and pitch-shifted to make her seem drunk, catalyzed the return of the debate on deepfakes. Thanks to the voracious nature of social media, the altered video (technically not a deepfake as some claimed) was shared far and wide with many commenting on her apparent inebriation. "She always looks like she's a non-functioning alcoholic," one contributor to a Fox and Friends broadcast said on May 24, and the Former Mayor of New York Rudy Giuliani retweeted the video questioning Pelosi's "bizarre speech pattern." This seems like intentional use of doctored media for political purposes, a clear potential use of deepfake material--in Pelosi's speech she said President Trump's refusal to cooperate with congressional investigations amounted to a "cover-up"--and Donald Trump, Barack Obama, and Vladimir Putin have all been prominent targets of this technology before.

David Cameron has taken a job as chair of a US artificial intelligence firm's advisory board, it was announced on Friday. The former prime minister "will be responsible for curating and overseeing the strategic guidance" the board provides to Afiniti, the company said in a statement. The position represents one of Cameron's most prominent appointments since he stood down as prime minister in 2016. He has previously taken a number of roles at not-for-profit organisations and has a memoir, For the Record, due out later this year. Cameron said he was "delighted" to take the job working on "transforming the future of customer service and interpersonal communications".

Artificial Intelligence (AI) promises to drive growth of the United States economy, enhance our economic and national security, and improve our quality of life. The United States is the world leader in AI research and development (R&D) and deployment. Continued American leadership in AI is of paramount importance to maintaining the economic and national security of the United States and to shaping the global evolution of AI in a manner consistent with our Nation's values, policies, and priorities. The Federal Government plays an important role in facilitating AI R&D, promoting the trust of the American people in the development and deployment of AI-related technologies, training a workforce capable of using AI in their occupations, and protecting the American AI technology base from attempted acquisition by strategic competitors and adversarial nations. Maintaining American leadership in AI requires a concerted effort to promote advancements in technology and innovation, while protecting American technology, economic and national security, civil liberties, privacy, and American values and enhancing international and industry collaboration with foreign partners and allies. Artificial Intelligence will affect the missions of nearly all executive departments and agencies (agencies).

As the Central Intelligence Agency harnesses machine learning and artificial intelligence to better meet its mission, insiders are aggressively addressing issues around bias and ethics intrinsic to the emerging tech. "We at the agency have over 100 AI initiatives that we are working on and that's going to continue to be the case," Benjamin Huebner, the CIA's privacy and civil liberties officer said Friday at an event hosted by the Brookings Institution in Washington. "That's a big complicated issue that we are very much thinking about all the time." Huebner said collaborating with the intelligence agency's data scientists is one of his favorite parts of his job. His privacy team works directly with their tech-facing colleagues on projects around statistics, coding, and graphical representations.

Neural networks, although a powerful engine in supervised methods, often require expensive tuning efforts for optimized performance. Habitability classes are hard to discriminate, especially when attributes used as hard markers of separation are removed from the data set. The solution is approached from the point of investigating analytical properties of the proposed activation functions. The theory of ordinary differential equations and fixed point are exploited to justify the "lack of tuning efforts" to achieve optimal performance compared to traditional activation functions. Additionally, the relationship between the proposed activation functions and the more popular ones is established through extensive analytical and empirical evidence. Finally, the activation functions have been implemented in plain vanilla feed-forward neural network to classify exoplanets.

This paper is concerned with the robustness of VAEs to adversarial attacks. We highlight that conventional VAEs are brittle under attack but that methods recently introduced for disentanglement such as $\beta$-TCVAE (Chen et al., 2018) improve robustness, as demonstrated through a variety of previously proposed adversarial attacks (Tabacof et al. (2016); Gondim-Ribeiro et al. (2018); Kos et al.(2018)). This motivated us to develop Seatbelt-VAE, a new hierarchical disentangled VAE that is designed to be significantly more robust to adversarial attacks than existing approaches, while retaining high quality reconstructions.