For years now, the SEC has quietly advanced its data analytics so that the staff is better equipped to examine registrants and identifier outliers. Information from this analysis is used to direct risk-based examinations of registrants, including investment advisers. The Office of Compliance Inspections and Examinations also uses data-rich tools such as the National Exam Analytics Tool (NEAT) to improve its review of areas such as trading. For policy-making efforts, the various SEC divisions rely on the Office of Data Science and the Division of Economic Research and Analysis, which collectively maintain the Quantitative Research Analytical Data Support (QRADS) program. The rule-making divisions can use the data to direct rulemaking or enhance analysis to make rules more effective (and litigation proof).

A drone company that had to abandon its fast-food delivery tests has partnered with Ireland's health authority to deliver prescriptions instead. Manna Aero is working with the Health Service Executive to prescribe and deliver medicines and other essential supplies to vulnerable people in the small rural town of Moneygall. The company's trial uses autonomous drones made in Wales. And it is looking at the possibility of testing in the UK within weeks. The UK has already announced a test of drones to carry supplies to the Isle of Wight during the pandemic. Also, in Florida, care home residents will soon be able to have their prescriptions delivered.

Resistant AI, a Prague-based security company that protects AI systems from cyberattacks and fraud, has raised $2.75 million in a round co-led by Index Ventures and Credo Ventures. Seedcamp and angel investors such as Daniel Dines and Michal Pechoucek also participated. Deployed on top of existing systems, Resistant AI provides a typical security layer for financial services, such as protecting payments and detecting fraud or money laundering -- and also detects forged documents or spots sophisticated attackers attempting to copy the underlying ML model. "Historically, all systems that make high-value financial decisions become targeted. This is already happening with the automated systems deployed by our fintech and financial customers and we are here to protect them," says Martin Rehak, the startup's co-founder and CEO.

Quite recently, the US Patent and Trademark Office (USPTO) has ruled that Artificial Intelligence (AI) systems can't get the credit of a legal inventor in a patent filing. The ruling has come as a response to two Patent Applications filed corresponding to a flashing light and food container, which were created by an AI-based system known as DABUS. The USPTO has presented a lot of arguments concerning the same. The first and foremost argument corresponds to the Patent Law in the US, which repeatedly refers to the patent inventors or innovators by using humanlike pronouns like'himself' and'herself' and terms like'whoever.' The team that filed the patent applications had argued by saying that the patent law's references to an inventor as an'individual' could very well be applied to machines too.

Results of our survey, "Making Tough Choices: How CISOs Manage Escalating Threats and Limited Resources" show that CISOs currently devote 36% of their budgets to response and 33% to prevention. However, as security needs change, many CISOs are looking to shift budget away from prevention without reducing its effectiveness. An optimal budget would reduce spend on prevention and increase spending on detection and response to 33% and 40% of the security budget, respectively. This shift would give security teams the speed and flexibility they need to react quickly in the face of a threat from cybercriminals who are outpacing agencies' defensive capabilities. When breaches are inevitable, it is important to stop as many as possible at the point of intrusion, but it is even more important to detect and respond to them before they can do serious damage.

Jay-Z's company Roc Nation have filed takedown notices against "deepfake" videos that use artificial intelligence to make him rap Billy Joel's We Didn't Start the Fire and Hamlet's "To be or not to be" soliloquy. The two aforementioned videos have been removed, though others remain, including one of the rapper taking on the Book of Genesis. Vocal Synthesis said – via a deepfake video using the ersatz voices of Barack Obama and Donald Trump – that they had "no malicious purpose" and were "disappointed that Jay-Z and Roc Nation have decided to bully a small YouTuber in this way". The Guardian has contacted Roc Nation for comment. Deepfake videos have already caused great controversy in political and celebrity circles, with California outlawing them in 2018, and Facebook banning them in January.

A United Arab Emirates (UAE) drone strike on a biscuit factory near the Libyan capital Tripoli on November 18 killed eight civilians and injured 27 others, Human Rights Watch (HRW) said. In a report released on Wednesday, the rights group said the UAE appeared to take little or no action to minimise civilian casualties and called on Emirati authorities to conduct a transparent investigation into the incident. "Since the current armed conflict in Tripoli erupted in April 2019, the UAE has been conducting air and drone strikes to support the Libyan Arab Armed forces, previously known as the Libyan National Army [LNA], one of two major parties to the conflict, some of which have resulted in civilian casualties," HRW said. "All causalities in the November incident were civilian factory workers, including seven Libyans and 28 foreign nationals, all of them men." Human Rights Watch visited the site and found remnants of at least four Blue Arrow-7 (BA-7) laser-guided missiles that were launched by a Wing Loong-II drone.

Artificial intelligence has myriad use cases, but it turns out inventing devices isn't one of them -- at least in the eyes of the US Patent and Trademark Office. The agency issued a decision on two patent applications for devices created by an AI system, determining that only humans can legally be credited as inventors. The items in question -- an emergency flashlight and a shape-shifting drink container -- were the brainchildren of a system called DABUS. The Artificial Inventor Project filed the applications last year on behalf of the AI's creator, Stephen Thaler. AIP lawyers argued that, since Thaler didn't have any expertise in either of those types of products and couldn't have come up with them by himself, DABUS should be the credited inventor.

Computing with words (CWW) has emerged as a powerful tool for processing the linguistic information, especially the one generated by human beings. Various CWW approaches have emerged since the inception of CWW, such as perceptual computing, extension principle based CWW approach, symbolic method based CWW approach, and 2-tuple based CWW approach. Furthermore, perceptual computing can use interval approach (IA), enhanced interval approach (EIA), or Hao-Mendel approach (HMA), for data processing. There have been numerous works in which HMA was shown to be better at word modelling than EIA, and EIA better than IA. But, a deeper study of these works reveals that HMA captures lesser fuzziness than the EIA or IA. Thus, we feel that EIA is more suited for word modelling in multi-person systems and HMA for single-person systems (as EIA is an improvement over IA). Furthermore, another set of works, compared the performances perceptual computing to the other above said CWW approaches. In all these works, perceptual computing was shown to be better than other CWW approaches. However, none of the works tried to investigate the reason behind this observed better performance of perceptual computing. Also, no comparison has been performed for scenarios where the inputs are differentially weighted. Thus, the aim of this work is to empirically establish that EIA is suitable for multi-person systems and HMA for single-person systems. Another dimension of this work is also to empirically prove that perceptual computing gives better performance than other CWW approaches based on extension principle, symbolic method and 2-tuple especially in scenarios where inputs are differentially weighted.

Argumentation is a type of discourse where speakers try to persuade their audience about the reasonableness of a claim by presenting supportive arguments. Most work in argument mining has focused on modeling arguments in monologues. We propose a computational model for argument mining in online persuasive discussion forums that brings together the micro-level (argument as product) and macro-level (argument as process) models of argumentation. Fundamentally, this approach relies on identifying relations between components of arguments in a discussion thread. Our approach for relation prediction uses contextual information in terms of fine-tuning a pre-trained language model and leveraging discourse relations based on Rhetorical Structure Theory. We additionally propose a candidate selection method to automatically predict what parts of one's argument will be targeted by other participants in the discussion. Our models obtain significant improvements compared to recent state-of-the-art approaches using pointer networks and a pre-trained language model.