American police departments near the United States-Mexico border are paying hundreds of thousands of dollars for an unproven and secretive technology that uses AI-generated online personas designed to interact with and collect intelligence on "college protesters," "radicalized" political activists, and suspected drug and human traffickers, according to internal documents, contracts, and communications that 404 Media obtained via public records requests. This article is copublished in partnership with 404 Media. Massive Blue, the New York–based company that is selling police departments this technology, calls its product Overwatch, which it markets as an "AI-powered force multiplier for public safety" that "deploys lifelike virtual agents, which infiltrate and engage criminal networks across various channels." According to a presentation obtained by 404 Media, Massive Blue is offering cops these virtual personas that can be deployed across the internet with the express purpose of interacting with suspects over text messages and social media. The technology--which as of last summer had not led to any known arrests--demonstrates the types of social media monitoring and undercover tools private companies are pitching to police and border agents.

Achieving unified multi-robot coordination and motion planning in complex environments is a challenging problem. In this paper, we present a hierarchical approach to long-range coordination, which we call Stratified Topological Autonomy for Long-Range Coordination (STALC). In particular, we look at the problem of minimizing visibility to observers and maximizing safety with a multi-robot team navigating through a hazardous environment. At its core, our approach relies on the notion of a dynamic topological graph, where the edge weights vary dynamically based on the locations of the robots in the graph. To create this dynamic topological graph, we evaluate the visibility of the robot team from a discrete set of observer locations (both adversarial and friendly), and construct a topological graph whose edge weights depend on both adversary position and robot team configuration. We then impose temporal constraints on the evolution of those edge weights based on robot team state and use Mixed-Integer Programming (MIP) to generate optimal multirobot plans through the graph. The visibility information also informs the lower layers of the autonomy stack to plan minimal visibility paths through the environment for the team of robots. Our approach presents methods to reduce the computational complexity for a team of robots that interact and coordinate across the team to accomplish a common goal. We demonstrate our approach in simulated and hardware experiments in forested and urban environments.

Planning for multi-robot teams in complex environments is a challenging problem, especially when these teams must coordinate to accomplish a common objective. In general, optimal solutions to these planning problems are computationally intractable, since the decision space grows exponentially with the number of robots. In this paper, we present a novel approach for multi-robot planning on topological graphs using mixed-integer programming. Central to our approach is the notion of a dynamic topological graph, where edge weights vary dynamically based on the locations of the robots in the graph. We construct this graph using the critical features of the planning problem and the relationships between robots; we then leverage mixed-integer programming to minimize a shared cost that depends on the paths of all robots through the graph. To improve computational tractability, we formulated our optimization problem with a fully convex relaxation and designed our decision space around eliminating the exponential dependence on the number of robots. We test our approach on a multi-robot reconnaissance scenario, where robots must coordinate to minimize detectability and maximize safety while gathering information. We demonstrate that our approach is able to scale to a series of representative scenarios and is capable of computing optimal coordinated strategic behaviors for autonomous multi-robot teams in seconds.

Microsoft bosses are slated to meet with Jeremy Hunt this week as Britain attempts to stop the company from purchasing the publisher of Call of Duty. The tech firm launched a bid to acquire video game Activision Blizzard, but British antitrust regulators have blocked the roughly £55billion ($69billion) purchase. If Microsoft moves forward with the purchase, gamers in the UK would be unable to purchase or download any titles from the Activision catalogue, including COD, World of Warcraft, Overwatch, Diablo, and Candy Crush. Brad Smith, the president of Microsoft, has arranged to meet with the Chancellor this week to discuss the proposal, as well as the'potential of AI' and the'need for thoughtful regulation of it', a spokesperson told Bloomberg. Analysts predict the Government and Microsoft will reach an agreement before'extreme measures', like prohibiting access to Activision games, take place.

The Olympics announced its second-ever esports series last week, which means that in 2023, video games will be part of the world's most revered sporting event. Players can sign up for qualifying rounds, some of which are already underway. The series will culminate in a live event in Singapore in June, part of the first Olympics esports week, where qualifiers will compete across nine virtual sports. This should be a huge moment that the gaming and esports worlds would both be celebrating. Instead, esports professionals have been despairing over the games that have been included.

It's possible to love a video game. To be devoted to it, to value what it does for you, and how it makes you feel. To want the best for it. Not in the same way you love a person -- or at least, I hope not. But take a look at any major fan convention for video games, movies, TV, or almost anything that develops a subculture, and you can see this love is real, active, and powerful. And if it's possible to love a video game, then of course it's possible to fall out of love.

It's possible to love a video game. To be devoted to it, to value what it does for you and how it makes you feel, and to want the best for it. Not in the same way you love a person -- or at least, I hope not. But take a look at any major fan convention for video games, movies, TV, or almost anything that develops a subculture, and you can see this love is real, active, and powerful. And if it's possible to love a video game, then of course it's possible to fall out of love. To feel disconnected from what first drew you to it.

Integrated Development Environments (IDEs) provide tool support to automate many source code editing tasks. Traditionally, IDEs use only the spatial context, i.e., the location where the developer is editing, to generate candidate edit recommendations. However, spatial context alone is often not sufficient to confidently predict the developer's next edit, and thus IDEs generate many suggestions at a location. Therefore, IDEs generally do not actively offer suggestions and instead, the developer is usually required to click on a specific icon or menu and then select from a large list of potential suggestions. As a consequence, developers often miss the opportunity to use the tool support because they are not aware it exists or forget to use it. To better understand common patterns in developer behavior and produce better edit recommendations, we can additionally use the temporal context, i.e., the edits that a developer was recently performing. To enable edit recommendations based on temporal context, we present Overwatch, a novel technique for learning edit sequence patterns from traces of developers' edits performed in an IDE. Our experiments show that Overwatch has 78% precision and that Overwatch not only completed edits when developers missed the opportunity to use the IDE tool support but also predicted new edits that have no tool support in the IDE.

McCree, a popular hero in Blizzard's team-based shooter "Overwatch," is getting renamed. The playable character was originally a nod to Jesse McCree, a game designer who no longer works at Blizzard in the wake of a California Department of Fair Employment and Housing lawsuit against its parent company, Activision Blizzard, alleging widespread sexual harassment and discrimination. Further, employees at Blizzard have told The Post that similar changes will soon be coming to "World of Warcraft," which contains several characters and one city named after multiple former Blizzard developers.

The minds at Respawn Entertainment are wizards when it comes to the action-adventure genre. Twenty-fourteen's Titanfall and its criminally underrated followup, 2016's Titanfall 2, challenged traditional boots-on-the-ground shooters with a heightened sense of scale and verticality, while the more recent Jedi: Fallen Order etched itself as one of the greatest Star Wars narratives told in any medium. The Los Angeles studio's fixation with exoskeletons, Blade Runner, and visuals that bleed Wachowski and Masamune Shirow's Ghost In The Shell is nothing new, but they are intertwined with world-building to create headier pockets of science fiction bliss. The free-to-play shooter set in the Titanfall universe first launched in February 2019. No extended gameplay reveals that cringe out with comms from Chad and the rest of the QA team.