We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning tools to gain utility from those data. We have compiled, curated, analyzed, and made available a new and more capable database of particle precipitation data that includes 51 satellite years of Defense Meteorological Satellite Program (DMSP) observations temporally aligned with solar wind and geomagnetic activity data. The new total electron energy flux particle precipitation nowcast model, a neural network called PrecipNet, takes advantage of increased expressive power afforded by machine learning approaches to appropriately utilize diverse information from the solar wind and geomagnetic activity and, importantly, their time histories. With a more capable representation of the organizing parameters and the target electron energy flux observations, PrecipNet achieves a >50% reduction in errors from a current state-of-the-art model (OVATION Prime), better captures the dynamic changes of the auroral flux, and provides evidence that it can capably reconstruct mesoscale phenomena. We create and apply a new framework for space weather model evaluation that culminates previous guidance from across the solar-terrestrial research community. The research approach and results are representative of the `new frontier' of space weather research at the intersection of traditional and data science-driven discovery and provides a foundation for future efforts.

Nearshore bathymetry, the topography of the ocean floor in coastal zones, is vital for predicting the surf zone hydrodynamics and for route planning to avoid subsurface features. Hence, it is increasingly important for a wide variety of applications, including shipping operations, coastal management, and risk assessment. However, direct high resolution surveys of nearshore bathymetry are rarely performed due to budget constraints and logistical restrictions. Another option when only sparse observations are available is to use Gaussian Process regression (GPR), also called Kriging. But GPR has difficulties recognizing patterns with sharp gradients, like those found around sand bars and submerged objects, especially when observations are sparse. In this work, we present several deep learning-based techniques to estimate nearshore bathymetry with sparse, multi-scale measurements. We propose a Deep Neural Network (DNN) to compute posterior estimates of the nearshore bathymetry, as well as a conditional Generative Adversarial Network (cGAN) that samples from the posterior distribution. We train our neural networks based on synthetic data generated from nearshore surveys provided by the U.S.\ Army Corps of Engineer Field Research Facility (FRF) in Duck, North Carolina. We compare our methods with Kriging on real surveys as well as surveys with artificially added sharp gradients. Results show that direct estimation by DNN gives better predictions than Kriging in this application. We use bootstrapping with DNN for uncertainty quantification. We also propose a method, named DNN-Kriging, that combines deep learning with Kriging and shows further improvement of the posterior estimates.

the White House released the first-ever guidance for Federal agencies on the regulation of artificial intelligence applications in the private sector, ...

Investments in cybersecurity and artificial intelligence efforts will likely continue to increase as overall defense spending remains flat in future years, but a worsening pandemic could dampen those projections, according to new analysis from the Professional Services Council's latest research on federal budgets. The Defense Department is largely expected to keep pace with current budget levels, potentially seeing very modest 2% growth to topline budgets, PSC's report projects. That trend could also extend to IT modernization efforts. Senate Appropriators weighed in today on 2021 spending, proposing a $696 billion defense budget, slightly above 2020 levels and slightly below the Trump administration's funding request. The House passed their funding bill in July at $694.6 billion.

A specialist cyber force of several hundred British hackers has been in the works for nearly three years, although its creation has been partly held back by turf wars between the spy agency GCHQ and the Ministry of Defence, to which the unit is expected to jointly report. The idea behind the new unit is to bring greater visibility and coherence to offensive cyber, a capability that the UK claims to have had for a decade but until recently has rarely acknowledged or discussed. Earlier in the autumn, Gen Patrick Sanders, the head of the UK's strategic command, said the military already had the capacity to "degrade, disrupt and destroy" enemies. Past operations include hacking into Islamic State systems in 2017 to understand how the terror group was operating a low-tech drone capability out of Mosul, which the military claims allowed it to understand how the drones were bought and how operators were trained. Creating a "Space Command" is a promise that was made in the Conservative election manifesto, and comes at a time when major military powers are rapidly showing an interest in space, largely because of the need to ensure the safety and security of satellites on which critical communications and location systems depend. The UK's new Space Operations Centre, based at the RAF headquarters in High Wycombe, comes less than a year after Donald Trump announced the creation of a new space force, arguing that "space is the world's new war-fighting domain," and that maintaining American superiority over Russia and China was "absolutely vital".

Two U.S. companies have recently completed what they say is the world's first dogfight between a real aircraft and an artificial intelligence-driven virtual fighter jet. The experiment, run by Red 6 and EpiSci, is the first step toward similar technology being provided to U.S. military fighter pilots, which would allow them to battle virtual adversaries as part of augmented reality training. You can read all about this potentially highly disruptive technology in this recent War Zone exclusive feature. The concept could help dramatically reduce the costs of air combat training compared to the adversary aircraft that currently have to physically fly against fighter pilots. It could also help solve a rash of other tactical challenges when it comes to replicating realistic foreign threats for fleet aviators.

Lilt, the AI-powered enterprise translation software and services company, announced that it has been awarded an AFWERX SBIR Phase II contract

International Business Machines (IBM) - Get Report and Advanced Micro Devices (AMD) - Get Report said they began a development program focused on cybersecurity and artificial intelligence. The development agreement will build on "open-source software, open standards, and open system architectures to drive confidential computing in hybrid cloud environments," the companies said in a statement. The agreement also will "support a broad range of accelerators across high-performance computing and enterprise critical capabilities, such as virtualization and encryption," they said. AMD, Santa Clara, Calif., is one of the world's biggest chipmakers and is thriving. IBM, the storied Armonk, N.Y., technology services company, has struggled to regain the glory of its past, when it led the computer-making industry.

Wipro Limited, a leading global information technology, consulting and business process services company, released its annual State of Cybersecurity Report (SOCR) that presents changing perspectives of cybersecurity globally. The report provides fresh insights on how Artificial Intelligence (AI) will be leveraged as part of defender stratagems as more organizations lock horns with sophisticated cyberattacks and become more resilient. There has been an increase in R&D with 49% of the worldwide cybersecurity related patents filed in the last four years being focussed on AI and Machine Learning (ML) application. Nearly half the organisations are expanding cognitive detection capabilities to tackle unknown attacks in their Security Operations Center (SOC). The report also illustrates a paradigm shift towards cyber resilience amid the rise in global remote work. It considers the impact of COVID-19 pandemic on cybersecurity landscape around the globe and provides a path for organizations to adapt with this new normal.

Moves have been made to restrict the use of facial recognition across the globe. In part one of this series on Face ID, Jennifer Strong and the team at MIT Technology Review explore the unexpected ways the technology is being used, including how technology is being turned on police. This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley and Emma Cillekens, and Karen Hao. Strong: A few things have happened since we last spoke about facial recognition. We've seen more places move to restrict its use while at the same time, schools and other public buildings have started using face I-D as part of their covid-prevention plans. We're even using it on animals and not just on faces with similarities to our own, like chimps and gorillas, Chinese tech firms use it on pigs, and Canadian scientists are working to identify whales, even grizzly bears.