The importance of asymmetries in prediction problems arising in economics has been recognized for a long time. In this paper, we focus on binary choice problems in a data-rich environment with general loss functions. In contrast to the asymmetric regression problems, the binary choice with general loss functions and high-dimensional datasets is challenging and not well understood. Econometricians have studied binary choice problems for a long time, but the literature does not offer computationally attractive solutions in data-rich environments. In contrast, the machine learning literature has many computationally attractive algorithms that form the basis for much of the automated procedures that are implemented in practice, but it is focused on symmetric loss functions that are independent of individual characteristics. One of the main contributions of our paper is to show that the theoretically valid predictions of binary outcomes with arbitrary loss functions can be achieved via a very simple reweighting of the logistic regression, or other state-of-the-art machine learning techniques, such as boosting or (deep) neural networks. We apply our analysis to racial justice in pretrial detention.

In this paper, we investigate the potential effect of the adversarially training on the robustness of six advanced deep neural networks against a variety of targeted and non-targeted adversarial attacks. We firstly show that, the ResNet-56 model trained on the 2D representation of the discrete wavelet transform appended with the tonnetz chromagram outperforms other models in terms of recognition accuracy. Then we demonstrate the positive impact of adversarially training on this model as well as other deep architectures against six types of attack algorithms (white and black-box) with the cost of the reduced recognition accuracy and limited adversarial perturbation. We run our experiments on two benchmarking environmental sound datasets and show that without any imposed limitations on the budget allocations for the adversary, the fooling rate of the adversarially trained models can exceed 90\%. In other words, adversarial attacks exist in any scales, but they might require higher adversarial perturbations compared to non-adversarially trained models.

Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE, which supports many of the expressive temporal features of the ANML modeling language without loosing efficiency. FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge. A novel reachability analysis technique is proposed and used to develop causal networks to constrain the search space. It is employed for the design of informed heuristics, inference methods and efficient search strategies. Experimental results on common benchmarks in the field permit to assess the components and search strategies of FAPE, and to compare it to IPC planners. The results show the proposed approach to be competitive with less expressive planners and often superior when hierarchical control knowledge is provided. FAPE, a freely available system, provides other features, not covered here, such as the integration of planning with acting, and the handling of sensing actions in partially observable environments.

Sinai School of Medicine, Stanford University and the Northern California Institute for Research and Education, IBM Research is undertaking a new research initiative funded by the National Institutes of Health. As part of a broader $99 million, 5-year research initiative spanning multiple public and private organizations and research institutions, this work will tap into AI and big data to help better identify individuals at high-risk of developing schizophrenia, a serious mental illness affecting how a person thinks, feels and behaves. Schizophrenia is often characterized by alterations to a person's thoughts, feelings and behaviors, which can include a loss of contact with reality known as psychosis. A better understanding of how this disease could be detected prior to psychosis could help to postpone or even prevent the transition to psychosis, as well as possibly improve outcomes. The project is a component of the Accelerating Medicines Partnership (AMP), a collaboration between the National Institutes of Health (NIH), the U.S. Food and Drug Administration (FDA), pharmaceutical companies, biotech firms and nonprofit organizations.

Cyberattacks have never been more successful than in the last year, and for 2020 an alarming increase of cybercrimes is expected, factoring in the surge of critical IT assaults that arose with the spread of COVID-19. And in a world where the enormous capabilities of artificial intelligence (AI) and machine learning (ML) are continuously growing, the potential for attackers to exploit them cannot be ignored. In 2019, four out of five organizations were victim to at least one successful attack to their IT security, according to CyberEdge's annual Cyberthreat Defense Report (CDR). And with the number of corporate endpoints becoming more and more with the increased need for remote working, the traditional cybersecurity strategy based on the detection of malware starting from what is external to the company perimeter is not feasible anymore. That's why IT professionals are most concerned about the security of IT components that are relatively new such as containers, or those that are infrequently connected to the corporate network and harder to monitor, such as tablets, mobile phones and other IoT devices.

Perched in his fire tower high above the pine trees, Nick Dutton leans back and nods to the cascading hills and mountains behind him. "I love being out here, just away from stuff," he says. "I mean, you can't really complain." Dutton, a fire tower operator, is sitting in his office, a tiny cabin propped high above the treetops by metal supports that sway with the wind. His walls are littered with compass points and references, each a guide to the bush stretching in every direction along the eastern ACT-NSW border.

Amazon Go is the first store where no checkout is required. Customer simply enter the store using the Amazon Go app to browse and take the required products or items they want and then leave. Customer being able to purchase, products without suing a counter or checkout. The following video shows how Self-driving Robot (Delivery Bot and named as YAPE) brings goods directly to you, it uses Facial Recognition to recognize the customer to deliver. It makes delivery fast and easy, bot easily navigates sidewalks. YAPE has a 70 kg loading capacity and can travel 80km on a single charge.

From self-driving cars, to digital assistants, artificial intelligence (AI) is fast becoming an integral technology in our lives today. But this same technology that can help to make our day-to-day life easier is also being incorporated into weapons for use in combat situations. And some existing weapons systems already include autonomous capabilities based on AI, developing weaponised AI further means machines could potentially make decisions to harm and kill people based on their programming, without human intervention. Countries that back the use of AI weapons claim it allows them to respond to emerging threats at greater than human speed. They also say it reduces the risk to military personnel and increases the ability to hit targets with greater precision.

U.S. Space Force officials swear in first recruits for the defense branch on'Fox & amp; Friends.' CAPE CANAVERAL, Fla. – A NASA spacecraft is stuffed with so much asteroid rubble from this week's grab that it's jammed open and precious particles are drifting away in space, scientists said Friday. Scientists announced the news three days after the spacecraft named Osiris-Rex briefly touched asteroid Bennu, NASA's first attempt at such a mission. The mission's lead scientist, Dante Lauretta of the University of Arizona, said Tuesday's operation 200 million miles away collected far more material than expected for return to Earth -- in the hundreds of grams. The sample container on the end of the robot arm penetrated so deeply into the asteroid and with such force, however, that rocks got sucked in and became wedged around the rim of the lid. In this image taken from video released by NASA, the Osiris-Rex spacecraft touches the surface of asteroid Bennu on Tuesday, Oct. 20, 2020.

Thankfully, in many cases, we live up to it. But our present digital reality is quite different, even sobering. Fighting terrorists for nearly 20 years after 9/11, we remained a flip-phone military in what is now a smartphone world. Infrastructure to support a robust digital force remains painfully absent. Consequently, service members lead personal lives digitally connected to almost everything and military lives connected to almost nothing.