A novel method, based on the combination of data assimilation and machine learning is introduced. The new hybrid approach is designed for a two-fold scope: (i) emulating hidden, possibly chaotic, dynamics and (ii) predicting their future states. The method consists in applying iteratively a data assimilation step, here an ensemble Kalman filter, and a neural network. Data assimilation is used to optimally combine a surrogate model with sparse noisy data. The output analysis is spatially complete and is used as a training set by the neural network to update the surrogate model. The two steps are then repeated iteratively. Numerical experiments have been carried out using the chaotic 40-variables Lorenz 96 model, proving both convergence and statistical skills of the proposed hybrid approach. The surrogate model shows short-term forecast skills up to two Lyapunov times, the retrieval of positive Lyapunov exponents as well as the more energetic frequencies of the power density spectrum. The sensitivity of the method to critical setup parameters is also presented: forecast skills decrease smoothly with increased observational noise but drops abruptly if less than half of the model domain is observed. The successful synergy between data assimilation and machine learning, proven here with a low-dimensional system, encourages further investigation of such hybrids with more sophisticated dynamics.

Its impact is drastic and real: Youtube's AIdriven recommendation system would present sports videos for days if one happens to watch a live baseball game on the platform [1]; email writing becomes much faster with machine learning (ML) based auto-completion [2]; many businesses have adopted natural language processing based chatbots as part of their customer services [3]. AI has also greatly advanced human capabilities in complex decision-making processes ranging from determining how to allocate security resources to protect airports [4] to games such as poker [5] and Go [6]. All such tangible and stunning progress suggests that an "AI summer" is happening. As some put it, "AI is the new electricity" [7]. Meanwhile, in the past decade, an emerging theme in the AI research community is the so-called "AI for social good" (AI4SG): researchers aim at developing AI methods and tools to address problems at the societal level and improve the wellbeing of the society.

THE THAMES seems to draw people who work on intelligence-gathering. The spooks of MI6 are housed in a funky-looking building overlooking the river. Two miles downstream, in a shared office space near Blackfriars Bridge, lives Arkera, a firm that uses machine-learning technology to sort intelligence from newspapers, websites and other public sources for emerging-market investors. London has the right time zone, between the Americas and Asia. It is a nice place to live.

BAGHDAD – Iraq's Parliament called for the expulsion of U.S. forces from the country in reaction to the American drone attack that killed a top Iranian general, raising the prospect of a troop withdrawal that could cripple the battle against the Islamic State group and allow a resurgence of the extremists. Lawmakers approved a resolution asking the Iraqi government to end the agreement under which Washington sent troops more than four years ago to help fight ISIS. The bill is nonbinding and subject to approval by the Iraqi government but has the backing of the outgoing prime minister. But the vote was another sign of the blowback from the U.S. airstrike Friday that killed Iranian Gen. Qassem Soleimani and a number of top Iraqi officials at the Baghdad airport. Soleimani was the architect of Iran's proxy wars across the Mideast and was blamed for the deaths of hundreds of Americans in roadside bombings and other attacks.

April 2, 2019; Dubai, United Arab Emirates – UAE businesses show a significant lead in both maturity and proactiveness when it comes to the adoption of artificial intelligence solutions, according to a Microsoft report titled'AI Pulse' which was released today. 'AI Pulse' is a global Microsoft initiative designed to establish the attitudes and intentions of senior executives around the world towards artificial intelligence. The report is the result of widespread research across the US and EMEA of senior-level decision makers from dozens of industries. The study also involved inputs from many renowned experts in the fields of leadership, including Susan Etlinger, Industry Analyst with Altimeter Group and Heike Bruch, Professor of Leadership at Switzerland's University of St. Gallen among other Microsoft Data Scientists. "UAE AI strategy 2031 is marking a new level of innovation and the government is significantly investing in the latest AI technologies and tools to enhance performance, efficiency and fuel growth. Microsoft strongly believes that AI technologies will have significant impact on what good leadership will mean for future generations, and that sparking conversation now about smart solutions will allow current private and public organisations to take proper stock of the implications of various technologies," said Sayed Hashish, Regional General Manager, Microsoft Gulf.

The American drone attack that killed Iranian Gen. Qassem Soleimani last week is the latest move in a low-level war between Iran and the U.S. that has been waged with varying degrees of intensity for over 40 years – and is likely to continue long into the future. Some people fear that recent events will escalate the long conflict into a costly all-out war between the two countries. Others may welcome what they see as the necessary and inevitable showdown leading ultimately to regime change in Tehran. The killing of Soleimani – the most prominent military figure in Iran and close to Supreme Leader Ayatollah Ali Khamenei – can be seen as an escalation and will almost certainly provoke Iranian retaliation. President Trump's boast of ordering the killing of Soleimani may further increase pressure on Iran to respond.

The major objective of the Cognitive Systems & Artificial Intelligence In BFSI market report is to help the user understand the market in terms of its definition, segmentation, market potential, influential trends, and the challenges that the market is facing. This research is conducted to understand the current landscape of the market, especially in 2019 up-to the forecast year 2025. The readers will find this report very helpful in understanding the Cognitive Systems & Artificial Intelligence In BFSI market in depth. The data and the information regarding the market are taken from reliable sources such as websites, annual reports of the companies, journals, and others and were checked and validated by the industry experts. The facts and data are represented in the report using diagrams, graphs, pie charts, and other pictorial representations.

Combinatorial optimization problems arise in a wide range of applications from diverse domains. Many of these problems are NP-hard and designing efficient heuristics for them requires considerable time and experimentation. On the other hand, the number of optimization problems in the industry continues to grow. In recent years, machine learning techniques have been explored to address this gap. We propose a framework for leveraging machine learning techniques to scale-up exact combinatorial optimization algorithms. In contrast to the existing approaches based on deep-learning, reinforcement learning and restricted Boltzmann machines that attempt to directly learn the output of the optimization problem from its input (with limited success), our framework learns the relatively simpler task of pruning the elements in order to reduce the size of the problem instances. In addition, our framework uses only interpretable learning models based on intuitive features and thus the learning process provides deeper insights into the optimization problem and the instance class, that can be used for designing better heuristics. For the classical maximum clique enumeration problem, we show that our framework can prune a large fraction of the input graph (around 99 % of nodes in case of sparse graphs) and still detect almost all of the maximum cliques. This results in several fold speedups of state-of-the-art algorithms. Furthermore, the model used in our framework highlights that the chi-squared value of neighborhood degree has a statistically significant correlation with the presence of a node in a maximum clique, particularly in dense graphs which constitute a significant challenge for modern solvers. We leverage this insight to design a novel heuristic for this problem outperforming the state-of-the-art. Our heuristic is also of independent interest for maximum clique detection and enumeration.

We propose a framework for defining a Boolean algebra over the space of tasks. This allows us to formulate new tasks in terms of the negation, disjunction and conjunction of a set of base tasks. We then show that by learning goal-oriented value functions and restricting the transition dynamics of the tasks, an agent can solve these new tasks with no further learning. We prove that by composing these value functions in specific ways, we immediately recover the optimal policies for all tasks expressible under the Boolean algebra. We verify our approach in two domains, including a high-dimensional video game environment requiring function approximation, where an agent first learns a set of base skills, and then composes them to solve a super-exponential number of new tasks.

WhiteFox Defense Strategic Advisor and drone expert Brett Velicovich discusses the operation and mission of the airstrike that hit General Qassem Soleimani. You only get "one shot" while taking down a target like Iranian General Qassem Soleimani, drone expert Brett Velicovich said Saturday. Appearing on "America's News HQ: Weekend" with host Ed Henry, Velicovich -- who once tracked Soleimani's movements -- said that the drone strike on Soleimani was a " forceful reminder that the Iranians can no longer attack Americans with impunity, [as well as] that the U.S. government can retaliate with a wide variety of options that are both devastating actions that are short of war." "Thanks to President Trump's decisive action, we are able to use one of the tools within the government's arsenal to strike and to strike Soleimani with precision," he added. The MQ-9 Reaper drone was used to strike Soleimani early Friday at the Baghdad International Airport. With a range of 1,150 miles and the ability to fly at altitudes of 50,000 feet, the Reaper weighs almost 5,000 pounds.