Despite the robust structure of the Internet, it is still susceptible to disruptive routing updates that prevent network traffic from reaching its destination. In this work, we propose a method for early detection of large-scale disruptions based on the analysis of bursty BGP announcements. We hypothesize that the occurrence of large-scale disruptions is preceded by bursty announcements. Our method is grounded in analysis of changes in the inter-arrival times of announcements. BGP announcements that are associated with disruptive updates tend to occur in groups of relatively high frequency, followed by periods of infrequent activity. To test our hypothesis, we quantify the burstiness of inter-arrival times around the date and times of three large-scale incidents: the Indosat hijacking event in April 2014, the Telecom Malaysia leak in June 2015, and the Bharti Airtel Ltd. hijack in November 2015. We show that we can detect these events several hours prior to when they were originally detected. We propose an algorithm that leverages the burstiness of disruptive updates to provide early detection of large-scale malicious incidents using local collector data. We describe limitations, open challenges, and how this method can be used for large-scale routing anomaly detection.

Hindsight Experience Replay (HER) is a multi-goal reinforcement learning algorithm for sparse reward functions. The algorithm treats every failure as a success for an alternative (virtual) goal that has been achieved in the episode. Virtual goals are randomly selected, irrespective of which are most instructive for the agent. In this paper, we present two improvements over the existing HER algorithm. First, we prioritize virtual goals from which the agent will learn more valuable information. We call this property the instructiveness of the virtual goal and define it by a heuristic measure, which expresses how well the agent will be able to generalize from that virtual goal to actual goals. Secondly, we reduce existing bias in HER by the removal of misleading samples. To test our algorithms, we built two challenging environments with sparse reward functions. Our empirical results in both environments show vast improvement in the final success rate and sample efficiency when compared to the original HER algorithm.

Swarms of AI driven robots that can patrol borders from the land, sea and sky could soon be manning Europe's borders. A mass network of drones, land vehicles and water crafts is being developed into fully automated surveillance systems with the support of EU countries. Multiple sensors on roaming robots will be able to identify and track human activity and report risks to border officials. Concerns have been raised that such powerful technology in the wrong hands have could be used to develop'killer robots'. Swarms of AI driven robots that can patrol borders by surveillance of the sea (top left) and land (top right) could soon be manning Europe's borders.

In this Oct. 31, 2018, file photo, a man, who declined to be identified, has his face painted to represent efforts to defeat facial recognition during a protest at Amazon headquarters over the company's facial recognition system, "Rekognition," in Seattle. San Francisco is on track to become the first U.S. city to ban the use of facial recognition by police and other city agencies. SAN FRANCISCO – San Francisco is on track to become the first U.S. city to ban the use of facial recognition by police and other city agencies, reflecting a growing backlash against a technology that's creeping into airports, motor vehicle departments, stores, stadiums and home security cameras. Government agencies around the U.S. have used the technology for more than a decade to scan databases for suspects and prevent identity fraud. But recent advances in artificial intelligence have created more sophisticated computer vision tools, making it easier for police to pinpoint a missing child or protester in a moving crowd or for retailers to analyze a shopper's facial expressions as they peruse store shelves.

Deepfakes are video manipulations that can make people say seemingly strange things. Barack Obama and Nicolas Cage have been featured in these videos. It used to take a lot of time and expertise to realistically falsify videos. For decades, authentic-looking video renderings were only seen in big-budget sci-fi movies films like "Star Wars." However, thanks to the rise in artificial intelligence, doctoring footage has become more accessible than ever, which researchers say poses a threat to national security.

What makes a good video game movie? Is there even such a thing? The curse of the video game movie has long been documented, and the stigma that it's impossible to make a good one regardless of how much money you throw at it or who plays the lead has dogged the genre for years. Video games are more lucrative than Hollywood films overall, yet video game adaptations still struggle to be taken seriously by studio executives, who often misunderstand what makes the source material so popular to begin with. The anatomy of what makes a game-to-film adaptation tick is particularly relevant now with the release of Detective Pikachu, an adaptation of one of the franchise's lesser-known properties, a spinoff crime-solving game by the same name.

With current technologies like artificial intelligence, machine learning and data analytics being democratized in everyday applications, the IT industry has almost successfully transitioned into the Digital Era. When talking about digitization, one idea most industry leaders agree upon is that automation is the need of the hour. Along with other new age technologies, Robotic Process Automation (RPA) too has made a mark in the IT industry and according to Gartner 85 percent of big organizations will have deployed some form of RPA by the year 2022. While RPA is meant to bring about efficiency and reduce errors made in mundane and tedious work done manually by humans, it does give rise to the question of will there be a loss of jobs in the IT industry due to democratization of RPA. Automation, a popular emerging technology has an assured place in the future of global businesses.

With current technologies like artificial intelligence, machine learning and data analytics being democratized in everyday applications, the IT industry has almost successfully transitioned into the Digital Era. When talking about digitization, one idea most industry leaders agree upon is that automation is the need of the hour. Along with other new age technologies, Robotic Process Automation (RPA) too has made a mark in the IT industry and according to Gartner 85 percent of big organizations will have deployed some form of RPA by the year 2022. While RPA is meant to bring about efficiency and reduce errors made in mundane and tedious work done manually by humans, it does give rise to the question of will there be a loss of jobs in the IT industry due to democratization of RPA. Automation, a popular emerging technology has an assured place in the future of global businesses.

Domino's Pizza has collaborated with blockchain AI platform SingularityNET to integrate AI algorithms and solutions in its Singapore and Malaysia operations. The US pizza chain aims to improve its supply chain processes and logistics in the two southeast Asian countries, conducting feasibility studies, running AI-focused workshops by incorporating advanced technologies, and developing new algorithms that will benefit business processes. Domino's has more 260 stores and 4,000 employees in Singapore and Malaysia and is expanding business rapidly. The SingularityNET system is claimed to greatly help both divisions enhance their growth and efficiency by including unique algorithms in its AGI ecosystem into its operations. Henceforth, both of these divisions of Domino's will use AGI utility token, which was created to enable some basic functions of SingularityNET's decentralised marketplace, namely, frictionless and publicly-auditable transactions between AI services, and the incentivisation of development for new AI services.

Artificial intelligence (AI) and analytics are providing clinicians and researchers with actionable insights, from early detection to end-of-life-care, and by changing the way research is done and diagnoses are made. However, unlocking the data treasure trove is not a simple exercise for any healthcare organisation. With Asia-Pacific (APAC) expected to become the global leader in IoT spending according to IDC1, healthcare is unsurprisingly becoming increasingly connected in the region. However, it is this connectivity that adds complexity to the data challenge. Healthcare data is now growing at a rate of 48 per cent every year.