The US leads the world in artificial intelligence technology. Decades of federal research funding, industrial and academic research, and streams of foreign talent have put America at the forefront of the current AI boom. Yet as AI aspirations have sprouted around the globe, the US government has lacked a high-level strategy to guide American investment and prepare for the technology's effects. More than a dozen countries have launched AI strategies in recent years, including China, France, Canada, and South Korea. Their plans include items like new research programs, AI-enhanced public services, and smarter weaponry.

In a dangerous AI "arms race," China is exporting killer drone weapons and pilotless aircraft with AK-47 rifles to combat zones in the Middle East, Asia, and Africa, U.K.'s The Sun reported. Nicknamed "slaughterbots" in the report, the stealth weapons can deploy a targeted strike from the air "without a human pressing the fire button," per The Sun, citing a report by the U.S.'s Center for a New American Security (CNAS). "Though many current generation drones are primarily remotely operated, Chinese officials generally expect drones and military robotics to feature ever more extensive AI and autonomous capabilities in the future," the think tank's Gregory C. Allen claims, per the report. "Chinese weapons manufacturers already are selling armed drones with significant amounts of combat autonomy." The report pointed to a "Blowfish A2 drone" advertised as having "full autonomy all the way up to targeted strikes," according to Allen.

There is a large and growing environmental problem that is not on this Earth--it's trash orbiting our planet in space. Space debris is a not only an economic risk that can affect every day modern living, but also it is an existential risk that jeopardizes the ability for scientists to research weather and climate changes that impact all living things on Earth. In early February 2019, researchers from Stanford University's Space Rendezvous Laboratory (SLAB) announced a plan to crowdsource artificial intelligence (AI) to solve the massive problem of orbiting space debris. Simone D'Amico, founder and director of the Stanford's Space Rendezvous Lab, is partnering with the European Space Agency (ESA) to create an AI system that will provide navigational guidance to a space "tow truck" in order to identify, fix or remove defunct, orbiting satellites that are above the atmosphere, yet doomed to orbit due to the gravitational pull of the Earth. How can artificial intelligence solve the problem of space debris?

Adversarial examples are perturbed inputs that are designed (from a deep learning network's (DLN) parameter gradients) to mislead the DLN during test time. Intuitively, constraining the dimensionality of inputs or parameters of a network reduces the 'space' in which adversarial examples exist. Guided by this intuition, we demonstrate that discretization greatly improves the robustness of DLNs against adversarial attacks. Specifically, discretizing the input space (or allowed pixel levels from 256 values or 8-bit to 4 values or 2-bit) extensively improves the adversarial robustness of DLNs for a substantial range of perturbations for minimal loss in test accuracy. Furthermore, we find that Binary Neural Networks (BNNs) and related variants are intrinsically more robust than their full precision counterparts in adversarial scenarios. Combining input discretization with BNNs furthers the robustness even waiving the need for adversarial training for certain magnitude of perturbation values. We evaluate the effect of discretization on MNIST, CIFAR10, CIFAR100 and Imagenet datasets. Across all datasets, we observe maximal adversarial resistance with 2-bit input discretization that incurs an adversarial accuracy loss of just ~1-2% as compared to clean test accuracy.

A deep learning model is proposed for predicting block-level parking occupancy in real time. The model leverages Graph-Convolutional Neural Networks (GCNN) to extract the spatial relations of traffic flow in large-scale networks, and utilizes Recurrent Neural Networks (RNN) with Long-Short Term Memory (LSTM) to capture the temporal features. In addition, the model is capable of taking multiple heterogeneously structured traffic data sources as input, such as parking meter transactions, traffic speed, and weather conditions. The model performance is evaluated through a case study in Pittsburgh downtown area. The proposed model outperforms other baseline methods including multi-layer LSTM and Lasso with an average testing MAPE of 12.0\% when predicting block-level parking occupancies 30 minutes in advance. The case study also shows that, in generally, the prediction model works better for business areas than for recreational locations. We found that incorporating traffic speed and weather information can significantly improve the prediction performance. Weather data is particularly useful for improving predicting accuracy in recreational areas.

One of the largest Tech Billionaire and CEO of Tesla & SpaceX, Elon Musk wants to establish a base on the planet Mars, and he had indicated the first resident on the planet which could be with the help of Artificial Intelligence. On the social media channel Twitter, Elon Musk tweeted what his thoughts were on the first Martian being an intelligent machine which is just rather than the human: so for that, he replied "30%". How the Elon came up with this percentage remains a mystery still, moreover many of the people are wondering what exactly is this "Artificial Intelligence" resident could look like, according to the report which has been revealed. "It's possible that it could be a rover-like bot that explores the planet, or a stationary device that makes observations and conducts experiments without human assistance," the Geek report added. As of now, the manned Mars Mission is entirely hypothetical.

The culture secretary Jeremy Wright is to question Tinder and Grindr about measures used to protect children after police records showed they are at risk of grooming and sexual exploitation on the dating apps. The Secretary of State for Digital, Culture, Media and Sport (DCMS) said he was "truly shocked" to discover the perpetrators of child sex offences had used online dating services. Mr Wright said: "I will be writing to these companies asking what measures they have in place to keep children safe from harm, including verifying their age. "If I'm not satisfied with their response, I reserve the right to take further action." Police have investigated more than 30 incidents of child rape since 2015 where victims were sexually exploited after evading age checks on dating apps, according to The Sunday Times. Dwain Chambers made his sprint comeback in the 60m event at the British Indoor Championships. The 40-year-old came in second during his heat with a time of 6.78 however after a ...

You've just received an email: The dream job in Japan is yours. You start making phone calls, looking up the rent on Tokyo apartments, and getting ready to make the career move of a lifetime. There's just one problem: Can your Siri get a visa? It's a potential roadblock that's less farfetched than you'd think. In November 2018, Maltese government minister Silvio Schembri announced an initiative to grapple with questions like how many robots to let into the country at one time and more.

WASHINGTON: The White House will take "executive action" in the coming weeks to make sure the United States keeps its research and development advantage in artificial intelligence, advanced manufacturing, quantum computing and next generation wireless networks, known as 5G, a White House official said on Wednesday. President Donald Trump discussed investing in what he called "industries of the future" as part of expanded infrastructure investment in his State of the Union address Tuesday evening. The White House, which held meetings last year to discuss these technologies, did not provide detail on what the actions might be. The Wall Street Journal reported the administration wanted to increase the government's role to quicken the pace of development. "Within the coming weeks we could expect to see executive action designed to preserve American R&D leadership," the official said.

These are just some of the questions being raised by lawmakers, civil libertarians, and privacy advocates in the wake of an ACLU report released last summer that claimed Amazon's facial recognition software, Rekognition, misidentified 28 members of congress as criminals. Rekognition is a general-purpose, application programming interface (API) developers can use to build applications that can detect and analyze scenes, objects, faces, and other items within images. The source of the controversy was a pilot program in which Amazon teamed up with the police departments of two cities, Orlando, Florida and Washington County, Oregon, to explore the use of facial recognition in law enforcement. In January 2019, the Daily Mail reported that the FBI has been testing Rekognition since early 2018. The Project on Government Oversight also revealed via a Freedom of Information Act request that Amazon had also pitched Rekognition to ICE in June 2018.