Big data, blockchain and artificial intelligence can take your cybersecurity strategy to the next level. When we go online, we leave traces of our data. We would never want our data falling into the wrong hands. Organizations that gather our data recognize this as a customer-centric and regulatory requirement; thus spending a lot of time and money to take active measures for enhancing cybersecurity. The craze for accelerating innovation, productivity, and revenue growth has compelled various organizations to embrace digitization.

Hollywood's Captain Kirk, 90-year-old William Shatner, blasted into space Wednesday in a convergence of science fiction and science reality, reaching the final frontier on board a ship built by Jeff Bezos's Blue Origin company. The Star Trek hero became the oldest person to ride a rocket, eclipsing the previous record -- set by a passenger on a similar jaunt on a Bezos spaceship in July -- by eight years. Dressed in a royal blue flight suit, Shatner joined three fellow passengers, four to five decades younger, on board the fully automated capsule that took off from remote West Texas for an up-and-down flight scheduled to last just 10 minutes or so. The spaceship aimed for an altitude of 106 kilometres (66 miles), at the fringes of space, after which the capsule was set to parachute back to the desert floor. Sci-fi fans revelled in the opportunity to see the man best known as the stalwart Captain James T Kirk of the starship Enterprise boldly go where no star of American TV has gone before.

Abu Dhabi is to launch a dedicated artificial intelligence research centre to help cement the UAE's growing status as a global centre for technological innovation. The state-of-the-art complex will be central to the work of the capital's Technology Innovation Institute, which already is home to the Middle East's first quantum computer and to teams of researchers developing advanced materials, drones and robots for commercial use. The centre aims to bridge the gap between the research centre's seven labs and the spreading field of AI, providing oversight and technical know-how. Take, for example, an autonomous boat under development at TII's robotics lab, which is being designed to self-navigate to the site of an oil spill, send out dozens of robotic "fish" to assess the damage to marine life, all while sending information to drones hovering above to determine a course for clean-up. This scenario relies heavily on AI capabilities and is one of dozens of commercial projects being developed at TII's Masdar City campus.

Researchers have developed a new method to detect rogue planets outside the solar system, worlds that wander their galaxies alone without a parent star. The technique, devised by NASA Goddard Space Flight Center scientist, Richard K. Barry, unites astronomy's future--in the form of the soon-to-launch Nancy Grace Roman Space Telescope--with its past, a method used by 19th-century astronomers to measure distances. The Contemporaneous LEnsing Parallax and Autonomous TRansient Assay (CLEoPATRA) mission will use parallax to measure distances, but the method will be bolstered by artificial intelligence (AI) developed by Dr. Greg Olmschenk. Olmschenk's program, RApid Machine learnEd Triage (RAMjET), will learn patterns through provided examples filtering out useless information and ensuring that of the millions of stars observed by CLEoPATRA per hour, only useful information is transmitted back to Earth. Recent research published in The Astronomical Journal suggests that exoplanets that exist in the Universe without a parent star could be more common than stars themselves, but until now spotting them has been difficult.

"It is likely a matter of time until an AI will be able to simulate human thought, think creatively, and independently identify and solve problems…. If current laws remain unchanged…the owner of the AI-generated IP can and likely will attempt to protect AI-based inventions as trade secrets to the extent possible." The past few years saw a meteoric rise of artificial intelligence (AI) products, services, and applications. AI has evolved from merely a buzzword or a cool new idea to a substantively used tool in a variety of applications, including autonomous driving, natural language processing, drug development, finance and cybersecurity among others. Companies, universities, and inventors world-wide noted the importance of AI and began seeking to patent various aspects of AI technology.

State government interest in artificial intelligence technology is on the rise, according to experts and a state official who spoke at an event here this week. Nelson Moe, Virginia's chief information officer, said he and his team see opportunities for incorporating predictive analytics into government agency workflows, and that AI technology could help with things like detecting waste, fraud and abuse, and supporting decisions in areas ranging from finance to traffic management. "We want to take it up the value chain, across the board," Moe said during a conference the National Association of State Chief Information Officers held here this week. He noted that Virginia recently fast-tracked the implementation of robotic process automation, or RPA, to help with processing unemployment claims. Moe said the technology cut the time needed to review certain unemployment information from hours to minutes.

There is no doubt that artificial intelligence (AI) is on the cusp of achieving significant disruption across several sectors in the world -- one can simply look to companies like American company Alfi (NASDAQ: ALF) which is attempting to revolutionize the ad-tech industry with privacy-conscious AI --. It is becoming a key driver of productivity and gross domestic product growth for many nations and is pushing the boundaries of technology as we know it. According to a report, the United States leads the AI pack today, with China in a close 2nd and the European Union in 3rd. Out of 100 total available points in the report's scoring methodology, the United States leads with 44.2 points, China with 32.3, and the European Union with 23.5. Although it may seem like the U.S. has an unassailable lead, the fact is that China is rapidly catching up and stands today as a full-spectrum peer competitor of the U.S. in many applications of AI.

We describe a Question Answering (QA) dataset that contains complex questions with conditional answers, i.e. the answers are only applicable when certain conditions apply. We call this dataset ConditionalQA. In addition to conditional answers, the dataset also features: (1) long context documents with information that is related in logically complex ways; (2) multi-hop questions that require compositional logical reasoning; (3) a combination of extractive questions, yes/no questions, questions with multiple answers, and not-answerable questions; (4) questions asked without knowing the answers. We show that ConditionalQA is challenging for many of the existing QA models, especially in selecting answer conditions. We believe that this dataset will motivate further research in answering complex questions over long documents. Data and leaderboard are publicly available at \url{https://github.com/haitian-sun/ConditionalQA}.

Autonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-critical applications, but require rigorous testing before deployment. The complexity of these systems often precludes the use of formal verification and real-world testing can be too dangerous during development. Therefore, simulation-based techniques have been developed that treat the system under test as a black box operating in a simulated environment. Safety validation tasks include finding disturbances in the environment that cause the system to fail (falsification), finding the most-likely failure, and estimating the probability that the system fails. Motivated by the prevalence of safety-critical artificial intelligence, this work provides a survey of state-of-the-art safety validation techniques for CPS with a focus on applied algorithms and their modifications for the safety validation problem. We present and discuss algorithms in the domains of optimization, path planning, reinforcement learning, and importance sampling. Problem decomposition techniques are presented to help scale algorithms to large state spaces, which are common for CPS. A brief overview of safety-critical applications is given, including autonomous vehicles and aircraft collision avoidance systems. Finally, we present a survey of existing academic and commercially available safety validation tools.

The major finding, of this article, is an ensemble method, but more exactly, a novel, better ranked voting system (and other variations of it), that aims to solve the problem of finding the best candidate to represent the voters. We have the source code on GitHub, for making realistic simulations of elections, based on artificial intelligence for comparing different variations of the algorithm, and other already known algorithms. We have convincing evidence that our algorithm is better than Instant-Runoff Voting, Preferential Block Voting, Single Transferable Vote, and First Past The Post (if certain, natural conditions are met, to support the wisdom of the crowds). By also comparing with the best voter, we demonstrated the wisdom of the crowds, suggesting that democracy (distributed system) is a better option than dictatorship (centralized system), if those certain, natural conditions are met. Voting systems are not restricted to politics, they are ensemble methods for artificial intelligence, but the context of this article is natural intelligence. It is important to find a system that is fair (e.g. freedom of expression on the ballot exists), especially when the outcome of the voting system has social impact: some voting systems have the unfair inevitability to trend (over time) towards the same two major candidates (Duverger's law).