Specifically they present the reward-is-enough hypothesis that "Intelligence, and its associated abilities, can be understood as subserving the maximisation of reward by an agent acting in its environment", and argue in favour of reward maximisation as a pathway to the creation of artificial general intelligence (AGI). While others have criticised this hypothesis and the subsequent claims [44,54,60,64], here we make the argument that Silver et al. have erred in focusing on the maximisation of scalar rewards. The ability to consider multiple conflicting objectives is a critical aspect of both natural and artificial intelligence, and one which will not necessarily arise or be adequately addressed by maximising a scalar reward. In addition, even if the maximisation of a scalar reward is sufficient to support the emergence of AGI, we contend that this approach is undesirable as it greatly increases the likelihood of adverse outcomes resulting from the deployment of that AGI. Therefore, we advocate that a more appropriate model of intelligence should explicitly consider multiple objectives via the use of vector-valued rewards. Our paper starts by confirming that the reward-is-enough hypothesis is indeed referring specifically to scalar rather than vector rewards (Section 2). In Section 3 we then consider limitations of scalar rewards compared to vector rewards, and review the list of intelligent abilities proposed by Silver et al. to determine which of these exhibit multi-objective characteristics. Section 4 identifies multi-objective aspects of natural intelligence (animal and human). Section 5 considers the possibility of vector rewards being internally derived by an agent in response to a global scalar reward.

Adversarial examples can easily degrade the classification performance in neural networks. Empirical methods for promoting robustness to such examples have been proposed, but often lack both analytical insights and formal guarantees. Recently, some robustness certificates have appeared in the literature based on system theoretic notions. This work proposes an incremental dissipativity-based robustness certificate for neural networks in the form of a linear matrix inequality for each layer. We also propose an equivalent spectral norm bound for this certificate which is scalable to neural networks with multiple layers. We demonstrate the improved performance against adversarial attacks on a feed-forward neural network trained on MNIST and an Alexnet trained using CIFAR-10.

This paper presents a machine learning approach to model the electric consumption of electric vehicles at macroscopic level, i.e., in the absence of a speed profile, while preserving microscopic level accuracy. For this work, we leveraged a high-performance, agent-based transportation tool to model trips that occur in the Greater Chicago region under various scenario changes, along with physics-based modeling and simulation tools to provide high-fidelity energy consumption values. The generated results constitute a very large dataset of vehicle-route energy outcomes that capture variability in vehicle and routing setting, and in which high-fidelity time series of vehicle speed dynamics is masked. We show that although all internal dynamics that affect energy consumption are masked, it is possible to learn aggregate-level energy consumption values quite accurately with a deep learning approach. When large-scale data is available, and with carefully tailored feature engineering, a well-designed model can overcome and retrieve latent information. This model has been deployed and integrated within POLARIS Transportation System Simulation Tool to support real-time behavioral transportation models for individual charging decision-making, and rerouting of electric vehicles.

CLOUDSEC 2021, one of the industry's biggest cybersecurity events hosted by Trend Micro Incorporated attracted thought leaders and technology experts across sectors speaking at the virtual event this year. The speakers opined that Modern Architecture, Security by Design, Attack Surface and Business Enabler are the four key aspects that will play a pivotal role for organisations in defining their cybersecurity posture. The panelists emphasized that the need of the hour is to develop a platform-based approach than having a single point-based approach. With innovation fueling the change in enterprise architecture, unsecure innovation could lead to data loss and breaches. Hence, it is important to create a culture of cybersecurity where business leaders talk about the importance of cybersecurity within the company, and this is where Security by Design comes into picture. With an increased adoption of DevOps and Infrastructure as Code security, there is an explosion of the attack surface.

The Food and Drug Administration recently sought comments on the role of transparency for artificial intelligence and machine learning-enabled medical devices. The FDA invited comments in follow up to a recent workshop on the topic. The workshop was part of a series of efforts the FDA has had in this space. These include its Digital Health Center of Excellence and a five-part Action Plan for AI and machine-learning enabled medical devices. As part of the action plan, the FDA indicated it wants to issue guidance on software learning over time and help the industry be "patient-centered."

There is a lot more than the usual amount of handwringing over AI these days. Former Google CEO Eric Schmidt and former US Secretary of State and National Security Advisor Henry Kissinger put out a new book last week warning of AI's dangers. Fresh AI warnings have also been issued by professors Stuart Russell (UC Berkeley) and Youval Harari (University of Jerusalem). Op-eds from the editorial board at the Guardian and Maureen Dowd at the New York Times have amplified these concerns. Facebook -- now rebranded as Meta -- has come under growing pressure for its algorithms creating social toxicity, but it is hardly alone.

Artificial intelligence (AI) is often touted as the most exciting technology of our age, promising to transform our economies, lives, and capabilities. Some even see AI as making steady progress towards the development of'intelligence machines' that will soon surpass human skills in most areas. AI has indeed made rapid advances over the last decade or so, especially owing to the application of modern statistical and machine learning techniques to huge unstructured data sets. It has already influenced almost all industries: AI algorithms are now used by all online platforms and in industries that range from manufacturing to health, finance, wholesale, and retail. Government agencies have also started relying on AI, particularly in the criminal justice system and in customs and immigration control.

All three examples show how deeply integrated artificial intelligence technologies already are in our lives. Should we worry about biases or "bad quality" in these applications? The smart speaker played music from a band called "Chess" when I asked to play "jazz." This might be funny – but think of automated decision systems based on AI that decide whether to give a loan, provide health care services or offer a job, all of which are real-world applications already. AI technology will shape our future even more – so we need to be able to trust it. Would you enter an autonomous driving car when it operates totally without your command and control?

Of the hundreds of millions of pieces of debris floating in space, a significant portion could wind up forming a'ring' around the Earth, similar to the solar system's gas giants, a University of Utah professor has warned. The debris is likely to give Earth'its own rings' made of'space junk,' University of Utah researcher Jake Abbott said in a recent interview with the Salt Lake Tribune. However, Abbott and his team are working on a way to clean up the debris, putting a magnet posted at the end of a robotic arm and using the magnet's eddy currents to collect the space trash. NASA estimates there are at least 23,000 pieces of debris that enter low-Earth orbit (LEO) larger than a softball in orbit, but there are probably 500,000 pieces between 0.4 inches and four inches. It's possible there are 170 million pieces of space debris that are smaller than 0.4 inches, the European Space Agency added.

Minister of Education, Culture, Research, and Technology, Nadiem Makarim has called for the simultaneous development of artificial intelligence and character intelligence on the part of its users and creators. The minister emphasised that artificial intelligence has been in development for at least two decades and is now a part of people's daily lives in the country. Administrative duties, which are typically a burden for lecturers during the accreditation application process, can now be facilitated using technology. Education will also become more personal as students will be able to develop themselves based on their interests and skills. Makarim encouraged students to develop not only their general intelligence but also their character to face future challenges.