Nine people were shot and wounded, one critically, in a Houston neighborhood Monday morning by a lawyer who had issues with his law firm, authorities said. The first report of the shootings began at about 6:30 a.m. CDT, Police Chief Martha Montalvo said at a news conference, and when officers arrived, the suspect began firing at them. Police shot the man, whom Montalvo did not identify and who later died at the scene. Numerous weapons were found at the scene, Montalvo said, and a bomb-squad robot is looking at a Porsche that's believed to be the shooter's.

Last Monday, the Obama Administration released a hundred-and-twelve-page policy tome, "Federal Automated Vehicles Policy," which, despite its sleep-inducing title, found an eager readership. The document contained long-awaited regulatory guidance on self-driving cars--a concept that has gone from sci-fi fantasy to legitimate industry in just a few short years. The official reaction from manufacturers has been muted. Nonetheless, the internal reaction was likely relief. Without federal recognition and regulatory authority, the autonomous-vehicle industry exists in legal limbo.

Artificial Intelligence (AI), long the subject of science fiction, is now becoming more and more widespread and is seen as an increasingly important computer science across multiple industries. In Financial Services in particular, Machine Learning and Natural Language Processing is increasingly used today to make sense of big, complex data in a wide range of areas. One such area is regulatory compliance. The use of AI – particularly Natural Language Understanding (NLU), a subset of Natural Language Processing – can help firms to realise a number of benefits, including improving the speed and efficiency with which they achieve compliance, and making that compliance much more robust. As we've seen over just the last couple of years with the introduction of MiFID I & II, UCITS, AIFMD and the like, there is a constant stream of documents being issued by regulators, which can each run to hundreds, or even thousands, of pages.

Robots have considerable potential to make human lives better, but only if humans start doing some "big thinking" now about how to ensure that the effects of artificial intelligence are beneficial. That was the view of A.I. experts during a panel discussion on the topic Tuesday at the Heidelberg Laureate Forum in Germany. "We've got to take responsibility for the technology we create," said Noel Sharkey, an emeritus professor of A.I. and robotics at the University of Sheffield as well as chair of the International Committee for Robot Arms Control and cofounder of the Foundation for Responsible Robotics. "We've got to do some big thinking here." The number of robots in use around the world is skyrocketing, Sharkey said.

To ease the burden, a group of local entrepreneurs - some of whom are former lawyers - have designed a website that helps lawyers search faster, keep notes and organise their research better. Launched in January, Intelllex, meaning "intelligent law", has already attracted more than 1,000 users - about half of whom are lawyers and the rest law students. Lawyers said it has reduced their research time by 30 to 60 per cent, meaning they can handle more cases. "A junior litigation lawyer spends 35 per cent of his time every day doing research," said Mr Chang.

Legal research can be the bane of every lawyer and law student's existence. From poring over textbooks in law libraries to trawling through cases online and offline to prepare for submissions, it is a process that can take hours. To ease the burden, a group of local entrepreneurs - some of whom are former lawyers - have designed a website that helps lawyers search faster, keep notes and organise their research better. Launched in January, Intelllex, meaning "intelligent law", has already attracted more than 1,000 users - about half of whom are lawyers and the rest law students. The service is currently free, but a subscription fee is likely to be introduced next year.

As many noted during the AI Now Experts' Workshop, the means to create and train AI systems are expensive and limited to a handful of large actors. Or, put simply, it's not possible to DIY AI without significant resources. Training AI models requires a huge amount of data – the more the better. It also requires significant computing power, which is expensive. This limits fundamental research to those who can afford such access, and thus limits the possibility of democratically creating AI systems that serve the goals of diverse populations.

Mr. Robot is a show built on hacks. The mother of all hacks serves as the big cliffhanger at the end of the show's first season, and nearly every plot development leading up to it was nudged along by some kind of exploit. It's rare to get through an episode without at least one digital intrusion, often drawn from real life. Each week, we'll be running through Mr. Robot's C Y B E R activities -- who got hacked, why, and how much magic would be required to make them actually work. We take one week off on the Mr. Robot Digital After Show (Hacking Robot will be doing a full download tonight on USA; we're back next week) and of course, everything goes off. Stage Two seems to be underway?

Responses to a White House request for information about the future of artificial intelligence show a continued... This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent. By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time.

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