When HSBC Holdings Plc thwarted a $500 million central-bank heist, sophisticated computer software didn't raise the alarm. The funds flowed undetected from Angola's reserves to a dormant company's account in London. It was a teller at a suburban bank branch who became suspicious, declined a request to transfer $2 million, and triggered a review that uncovered the scam, according to one account of the episode. That was two years ago, and the finance industry's battle to stop the illicit transfer of as much as $2 trillion a year around the globe hasn't become any easier. At least a half-dozen lenders in Europe have found themselves at the center of fresh allegations of dirty money schemes in the past year.

In recent years, defense officials have been banging the drum about the importance of adopting artificial intelligence to assist with everything from operating autonomous platforms to intelligence analysis to logistics and back office functions. But the Pentagon is not pumping enough money into this technology, according to one expert. "The critical question is whether the United States will be at the forefront of these developments or lag behind, reacting to advances in this space by competitors such as China," Susanna Blume, director of the defense program at the Center for a New American Security, said in a recent report titled, "Strategy to Ask: Analysis of the 2020 Defense Budget Request." The request includes just $927 million for the Pentagon's AI efforts, about 0.13 percent of the department's proposed $718 billion topline, she noted. "Given the enormous implications of artificial intelligence for the future of warfare, it should be a far higher priority for DoD in the technology development space, and certainly a higher priority than the current No. 1 -- development of hypersonic weapons," she said.

Cybersecurity used to exist in the realm of science fiction. Think retinal scans from Star Trek. I cut my teeth on Star Trek and I'm still holding out for a Tricorder during my lifetime. In the present, we live a hyper-connected life, with technology informing everything we do. We use smart devices like phones and watches.

DARPA, European Human Brain Project, and Pentagon advisor Dr. James Giordano describes neuronanorobotic Brain to computer interface mind control weapons for remote monitoring and manipulation of brains neural circuitry. This allows an individuals consciousness to be cloned onto their very own digital avatar in a Sentient World Simulation on a supercomputer. A direct link between a targeted individual and their digital avatar exists so that everything done in the real world occurs in the computer simulation. By manipulating the digital avatar in the computer simulation a persons thoughts, beliefs, perceptions, and behavior are manipulated in the real world. This is remote mind control.

The UK Department for Transport is planning to make use of artificial intelligence (AI) in the future to end holiday jams resulting from roadworks. Navigational apps powered by the disruptive technology, which will be developed to implement the same, are expected to help drivers to plan their trips. The apps are expected to give drivers the confidence to plan their key trips without the fear of getting stuck in traffic, apart from reducing congestion, delays and air pollution. The department said that the government will be opening up data on planned changes to the road network, showcasing possible traffic jams up to months in advance. This change in policy is expected to help motorists enjoy quicker and easier getaways on bank holidays in the near future.

The invention of an artificial super-intelligence has been a central theme in science fiction since at least the 19th century. From E.M. Forster's short story The Machine Stops (1909) to the recent HBO television series Westworld, writers have tended to portray this possibility as an unmitigated disaster. But this issue is no longer one of fiction. Prominent contemporary scientists and engineers are now also worried that super-AI could one day surpass human intelligence (an event known as the "singularity") and become humanity's "worst mistake". Current trends suggest we are set to enter an international arms race for such a technology.

Recent exploration of optimal individualized decision rules (IDRs) for patients in precision medicine has attracted a lot of attention due to the heterogeneous responses of patients to different treatments. In the existing literature of precision medicine, an optimal IDR is defined as a decision function mapping from the patients' covariate space into the treatment space that maximizes the expected outcome of each individual. Motivated by the concept of Optimized Certainty Equivalent (OCE) introduced originally in \cite{ben1986expected} that includes the popular conditional-value-of risk (CVaR) \cite{rockafellar2000optimization}, we propose a decision-rule based optimized covariates dependent equivalent (CDE) for individualized decision making problems. Our proposed IDR-CDE broadens the existing expected-mean outcome framework in precision medicine and enriches the previous concept of the OCE. Numerical experiments demonstrate that our overall approach outperforms existing methods in estimating optimal IDRs under heavy-tail distributions of the data.

European Law now requires AI to be explainable in the context of adverse decisions affecting European Union (EU) citizens. At the same time, it is expected that there will be increasing instances of AI failure as it operates on imperfect data. This paper puts forward a neurally-inspired framework called decision stacks that can provide for a way forward in research aimed at developing explainable AI. Leveraging findings from memory systems in biological brains, the decision stack framework operationalizes the definition of explainability and then proposes a test that can potentially reveal how a given AI decision came to its conclusion.

Unmanned aircraft systems can perform some more dangerous and difficult missions than manned aircraft systems. In some highly complicated and changeable tasks, such as air combat, the maneuvering decision mechanism is required to sense the combat situation accurately and make the optimal strategy in real-time. This paper presents a formulation of a 3-D one-on-one air combat maneuvering problem and an approximate dynamic programming approach for computing an optimal policy on autonomous maneuvering decision making. The aircraft learns combat strategies in a Reinforcement Leaning method, while sensing the environment, taking available maneuvering actions and getting feedback reward signals. To solve the problem of dimensional explosion in the air combat, the proposed method is implemented through feature selection, trajectory sampling, function approximation and Bellman backup operation in the air combat simulation environment. This approximate dynamic programming approach provides a fast response to a rapidly changing tactical situation, learns in long-term planning, without any explicitly coded air combat rule base.

Early Tuesday, Hezbollah changed its description of the first drone, saying that it had been carrying 12 pounds of explosives. The group's officials had previously said the first drone was for surveillance while the second was laden with explosives. Hezbollah is a political party represented in the Lebanese government as well as the country's most formidable military force. It fought a devastating war against Israel in 2006 and has more recently sent fighters to help President Bashar al-Assad of Syria fight rebels seeking to overthrow him. Israel and Iran have long been staunch enemies, but the conflict has heated up recently as Israel has increasingly attacked armed groups that Iran backs to extend its influence in the Arab world.