When a police robot killed suspect Micah Johnson in Dallas early Friday morning, it was likely an unprecedented event. But according to Steve Ijames, recently retired assistant chief of police in Springfield, Missouri, and a recognized expert in SWAT tactics, it was not a watershed moment portending a weaponized robotic future. The standoff after the police massacre at a Black Lives Matter protest was unique for a number of reasons, he says. And it was likely the only choice the police had. The police department hasn't elaborated on the device the bomb-defusing robot used or how exactly it killed the suspect, nor on the circumstances that led to the decision.

FinTech business in Africa makes use of A.I & credit technology. MyBucks, a German listed FinTech company that holds three brands GetBucks, GetSure and GetBanked, has said its partnership with NGO (non-governmental organisation) Opportunity International continues to take strides forward in their vision of bringing financial inclusion to the unbanked and underbanked in emerging markets – most specifically in Africa. In a move that is contrary to the current trend worldwide where banks are acquiring FinTech companies to add value and expand services, the partnership marks, according to the company, the first time a FinTech company has acquired banks to bridge the gap between the virtual and traditional worlds of banking. This is ultimately to enable faster, more efficient and less expensive access to financial services for clients. The conclusion of the acquisition of four banks and two microfinance institutions from Opportunity International will add Ghana, Tanzania and Mozambique to MyBucks' country portfolio and regulatory approval has already been granted in Kenya, Tanzania and Mozambique.

Activists Cheer On EU's'Right To An Explanation' For Algorithmic Decisions, But How Will It Work When There's Nothing To Explain? I saw a lot of excitement and happiness a week or so ago around some reports that the EU's new General Data Protection Regulations (GDPR) might possibly include a "right to an explanation" for algorithmic decisions. It's not clear if this is absolutely true, but it's based on a reading of the agreed upon text of the GDPR, which is scheduled to go into effect in two years. Slated to take effect as law across the EU in 2018, it will restrict automated individual decision-making (that is, algorithms that make decisions based on user-level predictors) which "significantly affect" users. The law will also create a "right to explanation," whereby a user can ask for an explanation of an algorithmic decision that was made about them.

For more than 30 years, Gibbs has advised on and developed product and service marketing for many businesses and he has consulted, lectured, and authored numerous articles and books. So the UK has just given itself a national headache. Whether you think the Brexit was the right decision or a dangerous and unmitigated screw-up (as I do), the consequences of the referendum will be non-trivial and take years to complete. But the mechanics of the UK exiting the European Union aside, the question of how people now feel about the Brexit is interesting. Are they awash in jubilation or has buyer's remorse set in?

This week, self-driving Tesla had a fatal crash. Other than that – a lot about robots, can AI create an art, cloning animals and more! Ray Kurzweil and people like him believe the Singularity is just behind the corner and promise the new perfect world. They are very optimistic about the future. But sometimes you should listen to the other side to better understand the problem or vision.

Some scientists are hard at work making a "kill switch" to overpower a too-strong AI and protect us, if needed. Others are specifically teaching robots how to hunt prey, also to help us. Researchers at the University of Zurich's Institute of Neuroinformatics are teaching a small, truck-shaped robot to see, track, and hunt its prey (another small, truck-shaped robot). The predator robot uses an advanced "silicon retina" to see instead of a traditional camera. This "silicon retina," which is modeled after animals' eyes, uses pixels to smoothly detect changes in real time instead of slowly processing frame-by-frame images.

Witness video shows people running away from the scene of the Dallas shooting as police head towards the scene and usher people back. NEW YORK--When Dallas police detonated a "bomb robot" Thursday night to take down a sniper suspect, it was believed to be the first time a robot was used by law enforcement to kill a human being in the U.S. Dallas police chief David Brown explained in a press conference that "other options would have exposed our officers to grave danger." The action raises ethical questions about the role of robots in warfare, or in this case, police work, especially given continuing breakthroughs in machine learning and artificial intelligence. "I think for all of us, the first issue that comes to mind is some degree of relief," says Michael Kalichman, director of the Center for Ethics in Science and Technology. "While it's premature to judge exactly what happened, it certainly seems likely that this ended a tragedy that could have been far worse. However, we also can't help but think about where this will go next."

After sniper fire struck 12 police officers at a rally in downtown Dallas, killing five, police cornered a single suspect in a parking garage. After a prolonged exchange of gunfire and a five-hour-long standoff, police made what experts say was an unprecedented decision: to send in a police robot, jury-rigged with a bomb. "We saw no other option but to use our bomb robot and place a device on its extension for it to detonate where the suspect was," Dallas Police Chief David Brown told a news conference Friday. "Other options would have exposed our officers to grave danger. The suspect is deceased as a result of detonating the bomb."

The same type of bomb-carrying robot that Dallas police used to kill a sniper who shot and killed five officers during a Black Lives Matter rally could easily be fashioned and deployed by dozens of other police forces across the country. The robot that officers used to kill Micah Xavier Johnson is designed to find and disarm bombs, not deliver them. Robotics experts said the incident was the first time law enforcement has used a robot in a targeted killing in the U.S. These bomb-detecting robots are fairly inexpensive, often costing less than 10,000 each. But local, state, and federal law enforcement agencies can also request the devices at no cost through the military's 1033 program, which gives used military equipment that would otherwise be thrown away to U.S. law enforcement agencies.

This talk presents unsupervised analysis techniques that can be applied to collections of unstructured text documents for the purpose of discovering hidden topical trends, correlations or anomalies in their data. The techniques presented are applicable to a wide range of document types including news stories, technical blogs, customer feedback forms, congressional records, and legal documents, among many, many others. The talk will include introductory descriptions of the processing techniques needed to pre-process text data, discover salient multi-word phrases, and learn latent topic models describing the topical content of a collection of text data. The primary focus of the talk will be on analytic techniques that can be applied to the output of a latent topic model to extract trending topics over time, uncover topical correlations with other document features or meta-data, and discover anomalies in a text corpus. To illustrate these techniques, examples using news wire and congressional record data will demonstrate how important events in news wire data and anomalous congressional actions and interesting correlations can be discovered automatically using the presented unsupervised techniques.