The North Atlantic Treaty Organization (NATO), the military alliance of 30 countries that border the North Atlantic Ocean, this week announced that it would adopt its first AI strategy and launch a "future-proofing" fund with the goal of investing around $1 billion. Speaking at a news conference, Secretary-General Jens Stoltenberg said that the effort was in response to "authoritarian regimes racing to develop new technologies." NATO's AI strategy will cover areas including data analysis, imagery, cyberdefense, he added. NATO said in a July press release that it was "currently finalizing" its strategy on AI" and that principles of responsible use of AI in defense will be "at the core" of the strategy. Speaking to Politico in March, NATO assistant secretary general for emerging security challenges David van Weel said that the strategy would identify ways to operate AI systems ethically, pinpoint military applications for the technology, and provide a "platform for allies to test their AI to see whether it's up to NATO standards."

NATO defense ministers on Friday approved the alliance's first strategy on artificial intelligence and the establishment of the NATO Innovation Fund. NATO allies signed an agreement on setting up the alliance's first Innovation Fund, Secretary-General Jens Stoltenberg announced following the second day of the NATO defense ministerial meeting. "NATO's new innovation fund will ensure us to not miss out on the latest technology and capabilities that will be critical to our security," he added. The initiative, financed by 17 NATO member states, will support research and development on emerging and disruptive technologies with over $1 billion. NATO defense ministers also adopted the alliance's first Artificial Intelligence Strategy that sets the standards for the use of this technology with the respect of international law.

NATO defence ministers have agreed upon a new master plan to defend against any potential Russian attack on multiple fronts, reaffirming the alliance's core goal of deterring Moscow despite a growing focus on China. The confidential strategy aims to prepare for any simultaneous attack in the Baltic and Black Sea regions that could include nuclear weapons, hacking of computer networks and assaults from space. "We continue to strengthen our alliance with better and modernised plans," NATO Secretary General Jens Stoltenberg said after the meeting on Thursday, which also agreed a $1bn fund to provide seed financing to develop new digital technologies. Officials stressed that they do not believe any Russian attack is imminent. Moscow has denied any aggressive intentions and said it is NATO that risks destabilising Europe with such preparations.

While convolutional neural networks (CNNs) have found wide adoption as state-of-the-art models for image-related tasks, their predictions are often highly sensitive to small input perturbations, which the human vision is robust against. This paper presents Perturber, a web-based application that allows users to instantaneously explore how CNN activations and predictions evolve when a 3D input scene is interactively perturbed. Perturber offers a large variety of scene modifications, such as camera controls, lighting and shading effects, background modifications, object morphing, as well as adversarial attacks, to facilitate the discovery of potential vulnerabilities. Fine-tuned model versions can be directly compared for qualitative evaluation of their robustness. Case studies with machine learning experts have shown that Perturber helps users to quickly generate hypotheses about model vulnerabilities and to qualitatively compare model behavior. Using quantitative analyses, we could replicate users' insights with other CNN architectures and input images, yielding new insights about the vulnerability of adversarially trained models.

A new center at Bigelow Laboratory is using cutting-edge artificial intelligence algorithms to forecast ocean activity, from toxic algal blooms to right whale migration, with the hopes of benefitting both coastal industries and the environment. People are expecting forecasts of all different kinds now, from COVID forecasts to political forecasts," said Nick Record, a senior research scientist at Bigelow Laboratory for Ocean Sciences in East Boothbay. "We're trying to tap into this societal need and demand for forecasts and apply it to ocean systems that we live in and rely on." The ability to accurately forecast complex ocean dynamics alone, such as temperature and salinity, is useful for the industries that use the coastline and the scientists that study it. With artificial intelligence, though, these forecasts will be constantly improving in accuracy even as the climate changes -- and, with it, Maine's ability to adapt to the changing coastline will improve as well.

Trust is ubiquitous, but the understanding, building, and retaining of trust has become a key challenge of our time, with the trust narrative evolving across a dynamic duality. On one hand, concerns around data privacy, security, and the ethical development of artificial intelligence (AI) abound; on the other, the "art of the possible" has been demonstrated through the positive purposes to which data and technology have been applied. Another dynamic has also evolved recently: data literacy. Over the last year, our everyday lives have been dominated by data, heightening levels of awareness, and helping move beyond data ubiquity to make analytics more ubiquitous too. But as people understand more about how organizations are using their data, they are increasingly concerned, bringing trust center stage.

The National Oceanic and Atmospheric Administration has shared what it says are the first images and video captured inside a hurricane by a surface drone. The agency placed the Saildrone Explorer SD 1045 in the path of the category-four Hurricane Sam. The saildrone overcame 50-foot waves and winds at speeds topping 120 miles per hour to capture data from the hurricane and offer a new perspective into such storms. The device has a special "hurricane wing" to help it survive the intense wind conditions. The SD 1045 is one of five saildrones that have been in the Atlantic Ocean during hurricane season.

NOAA and Saildrone Inc. are piloting five specially designed surface drones in the Atlantic Ocean to gather data around the clock to help understand the physical processes of hurricanes. NOAA and Saildrone Inc. are piloting five specially designed surface drones in the Atlantic Ocean to gather data around the clock to help understand the physical processes of hurricanes. Researchers for the National Oceanic and Atmospheric Administration have dispatched a surface drone inside Hurricane Sam as it barrels toward the Caribbean, giving scientists a new perspective of what it's like inside such a storm. The video and images shared were the first of their kind gathered by an "uncrewed surface vehicle" from inside a major hurricane as it moved across the Atlantic Ocean. The onboard camera shows eerily gray skies and turbulent ocean waters.

This specific morphology gives rise to several catchments with steep slopes and limited extension [1]. Autumn events, when deep Atlantic troughs more easily enter the Mediterranean area and activate very moist and unstable flow lifted by the mountain range, may determine catastrophic flood on these coastal areas characterized by a high population density (see [2, 3] for a review of climatology and typical atmospheric configurations of extreme precipitations over the Mediterranean area). Just as an example, the November 4th 2011 flood in Genoa determined six deaths and economic damages up to 100 million euros [4, 5, 6, 7]). A common feature in these extreme events are the presence of a quasi-stationary convective system with a spatial extension of few kilometers [8, 9, 10, 11, 12] Medium and long range either deterministic or ensemble Numerical Weather Prediction (NWP) models still struggle to correctly predict both the intensity and the location of these events, which can be triggered and enhanced by very small-scale features. High resolution convection-permitting NWP models manage to partly return a more realistic description of the dynamics of severe thunderstorms. Many studies addressed the role played by different components or settings of NWP models in order to better describe severe convective systems over the Liguria area, such as model resolution, initial conditions, microphysics schemes or small-scale patterns of the sea surface temperature ([6, 13, 14, 15, 16, 17, 18, 17, 19]).

NASA wants to push the concept of Swarm intelligence to new heights. Swarms of drones have gotten a lot of time in the spotlight lately, mostly for their use in potential military operations. The U.S. military is testing out swarm operations in simulations, while the British Army is using live drones operating in swarms during actual training operations. Other militaries are also interested in deploying swarms. One of the biggest advantages a swarm of drones has when performing military operations is its resiliency.