The daughter of the woman killed by an Uber self-driving vehicle in Arizona has retained a personal injury lawyer, underlying the potential high stakes of the first fatality caused by an autonomous vehicle. The law firm of Bellah Perez in Glendale, Arizona, said in a statement it was representing the daughter of Elaine Herzberg, who died on Sunday night after being hit by the Uber self-driving SUV in the Phoenix suburb of Tempe. The firm did not name her but DailyMail.com'As

The increasing scale and sophistication of cyberattacks has led to the adoption of machine learning based classification techniques, at the core of cybersecurity systems. These techniques promise scale and accuracy, which traditional rule or signature based methods cannot. However, classifiers operating in adversarial domains are vulnerable to evasion attacks by an adversary, who is capable of learning the behavior of the system by employing intelligently crafted probes. Classification accuracy in such domains provides a false sense of security, as detection can easily be evaded by carefully perturbing the input samples. In this paper, a generic data driven framework is presented, to analyze the vulnerability of classification systems to black box probing based attacks. The framework uses an exploration exploitation based strategy, to understand an adversary's point of view of the attack defense cycle. The adversary assumes a black box model of the defender's classifier and can launch indiscriminate attacks on it, without information of the defender's model type, training data or the domain of application. Experimental evaluation on 10 real world datasets demonstrates that even models having high perceived accuracy (>90%), by a defender, can be effectively circumvented with a high evasion rate (>95%, on average). The detailed attack algorithms, adversarial model and empirical evaluation, serve.

The randomized experiment is an important tool for inferring the causal impact of an intervention. The recent literature on statistical learning methods for heterogeneous treatment effects demonstrates the utility of estimating the marginal conditional average treatment effect (MCATE), i.e., the average treatment effect for a subpopulation of respondents who share a particular subset of covariates. However, each proposed method makes its own set of restrictive assumptions about the intervention's effects, the underlying data generating processes, and which subpopulations (MCATEs) to explicitly estimate. Moreover, the majority of the literature provides no mechanism to identify which subpopulations are the most affected--beyond manual inspection--and provides little guarantee on the correctness of the identified subpopulations. Therefore, we propose Treatment Effect Subset Scan (TESS), a new method for discovering which subpopulation in a randomized experiment is most significantly affected by a treatment. We frame this challenge as a pattern detection problem where we maximize a nonparametric scan statistic (measurement of distributional divergence) over subpopulations, while being parsimonious in which specific subpopulations to evaluate. Furthermore, we identify the subpopulation which experiences the largest distributional change as a result of the intervention, while making minimal assumptions about the intervention's effects or the underlying data generating process. In addition to the algorithm, we demonstrate that the asymptotic Type I and II error can be controlled, and provide sufficient conditions for detection consistency---i.e., exact identification of the affected subpopulation. Finally, we validate the efficacy of the method by discovering heterogeneous treatment effects in simulations and in real-world data from a well-known program evaluation study.

Hurricanes are cyclones circulating about a defined center whose closed wind speeds exceed 75 mph originating over tropical and subtropical waters. At landfall, hurricanes can result in severe disasters. The accuracy of predicting their trajectory paths is critical to reduce economic loss and save human lives. Given the complexity and nonlinearity of weather data, a recurrent neural network (RNN) could be beneficial in modeling hurricane behavior. We propose the application of a fully connected RNN to predict the trajectory of hurricanes. We employed the RNN over a fine grid to reduce typical truncation errors. We utilized their latitude, longitude, wind speed, and pressure publicly provided by the National Hurricane Center (NOAA) to predict the trajectory of a hurricane at 6-hour intervals.

Athens, Greece - Propped up on the radiator next to a battered door is a half-charred plaque that welcomes visitors to the office of the Afghan Community in Greece. The door, also burned, hangs loosely from the hinges. Inside, a wooden desk is collapsed in front of a soot-blackened wall, a shattered computer monitor toppled sideways on the ground next to it. Far-right attackers waited until office workers left for their lunch break on Thursday to break into the Afghan Community in Greece's single-room workspace, and smash computers, speakers and framed photos on the wall, before dousing the office in gasoline and setting it ablaze. "It is good that no one was here, otherwise we would have had victims," Yonous Muhammadi, former president of the Afghan Community in Greece and head of the Greek Forum of Refugees, tells Al Jazeera.

US software giant Mozilla and Germany's Commerzbank have both said they will pull advertising from Facebook over the Cambridge Analytica affair. The social network has been under fire all week over revelations that the political consultancy harvested private data from the Facebook profiles of 50m Americans and handed it on to the Donald Trump campaign for use in the micro-targeting of swing voters during the 2016 US presidential election. Facebook CEO Mark Zuckerberg has since apologised and volunteered to testify before Congress, conceding: "We made mistakes". Chief operating officer Sheryl Sandberg said the site would be "open to regulation" as it seeks to rebuild public trust over the handling of users' information and accusations that Russian bots were engaged in the spread of "fake news" and misinformation across its pages in a bid to sway the race for the White House. Writing in a blog post, Mozilla CEO Denelle Dixon said the company was "pressing pause" on its Facebook advertising.

The US Army wants to develop small drones to automatically spot, identify and target vehicles and people. It may allow faster responses to threats, but it could also be a step towards autonomous drones that attack targets without human oversight. The project will use machine-learning algorithms, such as neural networks, to equip drones as small as consumer quadcopters with artificial intelligence.

NASA's famous Curiosity Mars rover has achieved a major milestone and completed 2,000 days, aka sols, on the red planet. The robotic car-sized rover landed on the Martian landscape in August 2012 and has been devoted toward making critical finds for the space agency ever since. It has driven nearly 12 miles inside the Gale crater, diving into the history of the planet and understanding how it evolved over several billion years. Throughout its journey from the landing site to the current location on Mount Sharp of the crater, Curiosity made a number of discoveries. However, the biggest find continues to be the discovery of a riverbed that first indicated that liquid water flowed on the surface of the planet.

PRNEWSWIRE: The report "Artificial Intelligence in Military Market by Offering (Software, Hardware, Services), Technology (Learning & Intelligence, Advanced Computing, AI Systems), Application (Information Processing, Cyber Security), Platform, Region – Global Forecast to 2025", published by …

DaThe first thing many of us think about when it comes to the future relationship between artificial intelligence (AI) and cybersecurity is Skynet--the fictional neural net-based group mind from the "Terminator" movie franchise. But at least one security professional (with a somewhat rosier view) suggested that AI must be understood across a broader landscape, regarding how it will influence cybersecurity and how IT can use AI to plan for future security technology purchases. Click here to view original webpage at securityintelligence.com