We present a framework for automated analysis and categorization of .onion websites in the darkweb to facilitate analyst situational awareness of new content that emerges from this dynamic landscape. Over the last two years, our team has developed a large-scale darkweb crawling infrastructure called OnionCrawler that acquires new onion domains on a daily basis, and crawls and indexes millions of pages from these new and previously known .onion sites. It stores this data into a research repository designed to help better understand Tor’s hidden service ecosystem. The analysis component of our framework is called Automated Tool for Onion Labeling (ATOL), which introduces a two-stage thematic labeling strategy: (1) it learns descriptive and discriminative keywords for different categories, and (2) uses these terms to map onion site content to a set of thematic labels. We also present empirical results of ATOL and our ongoing experimentation with it, as we have gained experience applying it to the entirety of our darkweb repository, now over 70 million indexed pages. We find that ATOL can perform site-level thematic label assignment more accurately than keywordbased schemes developed by domain experts — we expand the analyst-provided keywords using an automatic keyword discovery algorithm, and get 12% gain in accuracy by using a machine learning classification model. We also show how ATOL can discover categories on previously unlabeled onions and discuss applications of ATOL in supporting various analyses and investigations of the darkweb.

Establishing a safety standard for autonomous vehicles operating in open and dynamic environment is a challenge. As collisions are inevitable in over-constrained situations, we focus on deciding the liability for a hazard. Our insight is that hazards caused by malfunctions of autonomous vehicles result from loss of functional integrity. Design defects may leave it unnoticed, or the real-world may make integritypreserving motion infeasible. Guarantee of functional integrity in an observable way at run-time is indispensable for revealing defects by using formal root-cause analysis, and for supporting safety claims by dismissing unreasonable doubts about design defects. From a practitical standpoint, we attempt to formalize a verification problem that consists of a novel criterion for determining liability for hazard, a safety claim comprised of confirmed observable states, and assumptions underlying the safety claim. We propose a run-time scheme of monitoring events that may lead to violations of the assumptions and a precursor to root-causes leading to loss of functional integrity and consequent hazards. We formulate a means of preemptively detecting unsafe motions liable to be hazardous as satisfiability problem within the framework of an adversarial motion planning subject to assumptions on maneuverability of movers. A numerical study shows that the run-time scheme using non-linear programming (NLP) encoding is viable in a real-world setting.

Former ExxonMobil Corp. Chief Executive Rex Tillerson was sworn in only Wednesday, and already Congress is moving to benefit the new secretary of state's former--and only--place of work by shredding two major oil industry regulations. Early Friday morning, the Republican-led Senate voted 52 to 47 on a House resolution scrapping a Securities and Exchange Commission rule requiring companies like Exxon and Chevron Corp. to disclose payments they make to foreign governments for the ability to extract oil, minerals and natural gas from their territory. Known as the "extraction rule," it was meant to curb corruption and boost transparency within the oil industry. Standing before the upper house Thursday night, Sen. Elizabeth Warren of Massachusetts railed against the effort to discard the rule. "One of the Republican Party's first orders of business is a giveaway to ExxonMobil that will help corrupt and repressive foreign regimes and make it easy to funnel money to terrorists around the world," she said, adding that companies like Exxon "regularly pay millions" to "corrupt officials" for the rights to drill on their land, and highlighting the "years" necessary to garner bipartisan and even investor support for the law's passage.

By 2020, medical data is expected to double every 73 days. With the rapidly growing amount of health data being produced, it is no surprise that medical knowledge is being drowned in the sea of scientific data. To make use of the incredible amounts of medical data, health professionals are increasingly turning to artificial intelligence (AI) to help find patterns in the deluge of data to provide better diagnostics and treatment. And now, the Chan Zuckerberg Initiative may speed progress in that area. The philanthropic arm of Facebook CEO Mark Zuckerberg and his wife Priscilla Chan has just purchased a Canadian healthcare startup, Meta, which uses AI to find, review and compile scientific papers. Meta is the Chan Zuckerberg Initiative's first outright acquisition and will be made free to use for all researchers.

You're responsible if your dog does something wrong, why not for your AI? Who is accountable for an artificial intelligence or robot which performs an action that brings harm to people? That action might be accidental but it's one of many questions society might need to ask itself about the autonomy and accountability of AI when more advanced forms of it such as driverless vehicles -- likely to be the first robots we learn to trust -- drones, and even military weapons become more widely deployed. AI and legal experts are attempting to figure it out, but there's no simple answer. Google's next big step for AI: Getting robots to teach each other new skills Robots haven't reached human intelligence yet, but Google's researchers are showing how they're closing the gap using downloadable intelligence. Speaking on a British Academy panel about robots and the law at The Royal Society, one expert suggested that the answer could be right under our noses.

TOLEDO, Ohio – Police say a 14-year-old Ohio girl told them she fatally shot her 15-year-old brother after they fought over a video-game system and he repeatedly hit her in the face. A Lucas County Juvenile Court judge on Wednesday found sufficient probable cause to charge the girl with murder in the December shooting death of her brother. The Associated Press generally doesn't identify juveniles charged with crimes. Toledo police Detective Jeff Clark testified the girl told him that her brother hit her in the face so many times before the shooting that it felt like she was being hit with a baseball bat. Prosecutors have filed a motion to transfer the case to adult court.

GoPro CEO Nick Woodman introduces the foldable Karma drone during a press event in Olympic Valley, Calif. in September. Six days after the release of GoPro's first-ever drone in October, Brian Warholak was itching to get airborne. As an employee at a Chesapeake, Va.-based government contractor, Warholak, 43, had few opportunities during the workweek to fly his new toy. But on Friday, he left his desk early, unpacked his GoPro Karma from its carrying case and set it on a manicured lawn near the company parking lot. In the video of Warholak's aeronautic excursion, the drone lurches upward, pausing for its master to pan the attached camera.

Artificial Lawyer recently caught up with Michael Kholodenko, co-founder of Seattle, US-based start-up, Binadox, which makes use of Natural Language Processing (NLP) to provide a compliance tool for software licences that can prevent costly legal violations. At first you may think this does not sound that world-changing, but sometimes it is the very precise uses of AI technology that end up creating a very successful and useful product for lawyers and legal departments. This would appear to be doubly so, as Bindox points out, because getting your software licences in a mess, or just allowing staff to click'Yes – Accept Terms' can open a Pandora's box of legal problems. Bindadox seeks to meet this problem head on in an automated way. Fundamentally the software seeks to answer two questions: what happens when an employee downloads new software or subscribes to a cloud service (SaaS) and clicks on the little'Yes' box that agrees to the licence terms, with all the legal issues that suddenly connects to?

They cover more than 70% of the earth's surface and the sheer size of the oceans makes tracking and measuring life under water an enormous task. New advances in satellite observation, open data and machine learning now allow us to process the massive amounts of data being produced. And they could not have come at a better time for protecting life under water, which is United Nations' Sustainable Development Goal No. 14 (SDG14). Last year was particularly challenging for most life underneath our world's oceans. Despite the dearth of bad news for the world's oceans, there is hope that 2017 can turn the tide for life under the sea thanks, in part, to machine learning.

Tax experts can find deductions that you might otherwise miss, but they're only human -- they can only find so many potential savings, let alone paint a larger picture of your finances. They're about to get a helping hand, though. IBM is partnering with H&R Block to make Watson a part of the tax filing process at locations across the US starting on February 6th. After you participate in an initial interview, the artificial intelligence will offer suggestions to Tax Pros (read: experts) looking for deductions, and illustrate the bigger picture for you on a dedicated client screen. Ideally, Watson's ability to understand context and intent will turn your statements into tangible data that leads to bigger tax breaks. This doesn't guarantee that Watson will find dramatic savings.