For the last 18 months, Jeff Jonas has been helping banks and government agencies track down criminals. As he puts it, he specialises in "hunting clever bad people". He may sound like a super sleuth, but he is in fact a computer programmer by training. Mr Jonas' startup Senzing has created software that helps global organisations comb through data to catch criminals faster than humans could ever manage. The company has been in "stealth mode" since it spun out of IBM in 2016, but it is has just publicly announced itself as open for business.

Ricardo Baeza-Yates ([email protected]) is Chief Technology Officer of NTENT, a search technology company based in Carlsbad, CA, USA, and Director of Computer Science Programs at Northeastern University, Silicon Valley campus, San Jose, CA, USA.

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The NITI Aayog on Wednesday entered into a partnership with technology company ABB India to work together towards realizing the government's ambitious vision of'Make in India' through advanced manufacturing technologies that incorporate the latest developments in robotics and Artificial Intelligence (AI). As per the statement of intent (SoI) signed on Wednesday, the NITI Aayog will work with ABB across various sectors to suggest solutions for digitalization, incorporating the Internet of Things (IoT) and AI technologies. Jointly, NITI Aayog and ABB will work with ministries, solicit feedback for areas critical to them and discuss solutions using industrial automation, and digitalization technologies. "We are looking forward to learning more about practical applications of future technologies such as AI and IoT, especially in streamlining governance and economic systems. "This collaboration, which will include cross-sectoral understanding of digitalization at ABB's world class centres, will be key in driving progress of key sectors in India," said NITI Aayog CEO Amitabh Kant.

NASA's Mars Curiosity rover is for the first time testing an improvised new percussive drilling technique intended to pound subsurface samples into powder in hopes of better understanding the shallow Martian subsurface. After a year's drilling hiatus, Curiosity is again back to drilling samples in rocks at the surface of Mars' Gale Crater. This self-portrait of NASA's Curiosity Mars rover shows the vehicle at the'Mojave' site, where its drill collected the mission's second taste of Mount Sharp. The scene combines dozens of images taken during January 2015 by the MAHLI camera at the... "If all goes well and we can continue drilling, the science team hopes to learn how the ancient climate at Gale crater, and the prospects for life there, changed over time," Ashwin Vasavada, the Curiosity Rover's project scientist, told me. Curiosity's drilling capability was knocked out of business in December 2016, when the motor that moves Curiosity's drill back and forth became unreliable, Vasavada told me.

National Transportation Safety Board investigators examine a driverless Uber SUV on March 20 that fatally struck a woman in Tempe, Ariz. The accident prompted Uber to suspend all road-testing of such autos in the Phoenix area, Pittsburgh, San... On the same day Uber said it's pulling the plug on autonomous vehicle tests in Arizona, Apple's on-again, off-again self-driving car initiative takes a step forward, a reminder that early-stage industries are nothing if not volatile. That may not be the case at Alphabet's Waymo, however, which looks to be on track with its robot ride-service plans. Uber's decision close its Tempe, Arizona, facility, where it tested Volvo XC90 SUVs outfitted with laser LiDAR sensors, cameras, radar and self-driving software, comes in the wake of a March crash in which one of those vehicles struck and killed a pedestrian as she crossed a dark suburban street. Governor Doug Ducey ordered Uber to stop testing indefinitely after the crash, and the National Transportation Safety Board is investigating.

Andy Dufresne, the wrongly convicted character in The Shawshank Redemption, provocatively asks the prison guard early in the film: "Do you trust your wife?" It's a dead serious question regarding avoiding taxes on a recent financial windfall that had come the guard's way, and leads to events that eventually win freedom for Andy. And it's also a dead serious question being asked today with respect to AI. At this point we all recognize that successful deployment of AI is going to come down to something much more fundamental than the technical aspects of algorithms, neural networks and machine learning. It's going to come down to trust. Do we trust the black box calculations of AI? Do we trust it to drive our cars, diagnose our illnesses, and manage our finances? We have the same issue of trust with objects, but with a different set of circumstances.

SAN FRANCISCO – Uber is pulling its self-driving cars out of Arizona, a reversal triggered by the recent death of woman who was run over by one of the ride-hailing service's robotic vehicles while crossing a darkened street in a Phoenix suburb. The decision announced Wednesday means Uber won't be bringing back its self-driving cars to the streets to Arizona, eliminating the jobs of about 300 people who served as backup drivers and performed other jobs connected to the vehicles. Uber had suspended testing of its self-driving vehicles in Arizona, Pittsburgh, San Francisco and Toronto while regulators investigated the cause of a March 18 crash that killed 49-year-old Elaine Herzberg in Tempe, Arizona. It marked the first death involving a fully autonomous vehicle, raising questions about the safety of computer-controlled cars being built by Uber and dozens of other companies, including Google spin-off Waymo. Uber still plans to build and test self-driving cars, which the San Francisco company considers to be critical to maintaining its early lead in the ride-hailing market.

Modern cyber security operations collect an enormous amount of logging and alerting data. While analysts have the ability to query and compute simple statistics and plots from their data, current analytical tools are too simple to admit deep understanding. To detect advanced and novel attacks, analysts turn to manual investigations. While commonplace, current investigations are time-consuming, intuition-based, and proving insufficient. Our hypothesis is that arming the analyst with easy-to-use data science tools will increase their work efficiency, provide them with the ability to resolve hypotheses with scientific inquiry of their data, and support their decisions with evidence over intuition. To this end, we present our work to build IDEAS (Interactive Data Exploration and Analysis System). We present three real-world use-cases that drive the system design from the algorithmic capabilities to the user interface. Finally, a modular and scalable software architecture is discussed along with plans for our pilot deployment with a security operation command.

Flood extent mapping plays a crucial role in addressing grand societal challenges such as disaster management, national water forecasting, as well as energy and food security. For example, during Hurricane Harvey floods in 2017, first responders needed to know where flood water was in order to plan rescue efforts. In national water forecasting, detailed flood extent maps can be used to calibrate and validate the NOAA National Water Model [15], which can forecast the flow of over 2.7 million rivers and streams through the entire continental U.S. [4]. In current practice, flood extent maps are mostly generated by flood forecasting models, whose accuracy is often unsatisfactory in high spatial details [4]. Other ways to generate flood maps involve sending field crew on the ground to record highwater marks, or visually interpreting earth observation imagery [2]. However, the process is both expensive and time consuming. With the large amount of high-resolution earth imagery being collected from satellites (e.g.,