Nowadays neural-network-based image- and video-quality metrics show better performance compared to traditional methods. However, they also became more vulnerable to adversarial attacks that increase metrics' scores without improving visual quality. The existing benchmarks of quality metrics compare their performance in terms of correlation with subjective quality and calculation time. However, the adversarial robustness of image-quality metrics is also an area worth researching. In this paper, we analyse modern metrics' robustness to different adversarial attacks. We adopted adversarial attacks from computer vision tasks and compared attacks' efficiency against 15 no-reference image/video-quality metrics. Some metrics showed high resistance to adversarial attacks which makes their usage in benchmarks safer than vulnerable metrics. The benchmark accepts new metrics submissions for researchers who want to make their metrics more robust to attacks or to find such metrics for their needs. Try our benchmark using pip install robustness-benchmark.

Effectively specifying and implementing robotic missions poses a set of challenges to software engineering for robotic systems. These challenges stem from the need to formalize and execute a robot's high-level tasks while considering various application scenarios and conditions, also known as contexts, in real-world operational environments. Writing correct mission specifications that explicitly account for multiple contexts can be tedious and error-prone. Furthermore, as the number of contexts, and consequently the complexity of the specification, increases, generating a correct-by-construction implementation (e.g., by using synthesis methods) can become intractable. A viable approach to address these issues is to decompose the mission specification into smaller, manageable sub-missions, with each sub-mission tailored to a specific context. Nevertheless, this compositional approach introduces its own set of challenges in ensuring the overall mission's correctness. In this paper, we propose a novel compositional framework for specifying and implementing contextual robotic missions using assume-guarantee contracts. The mission specification is structured in a hierarchical and modular fashion, allowing for each sub-mission to be synthesized as an independent robot controller. We address the problem of dynamically switching between sub-mission controllers while ensuring correctness under predefined conditions.

The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning (ML) models -- algorithms that have been trained on data without being explicitly programmed -- and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template's use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.

Production of the Tesla CyberTruck is delayed, so a man in Vietnam made his own. A Tesla engineer was reportedly a victim of a bloody attack by a robot at a factory near Austin, Texas. Recent reports revealed that a 2021 injury report which claims the robot that was designed to move aluminum car parts, pinned the engineer against a surface and dug its metal claws into the his back and arm, according to witnesses who spoke to The Information in a story published last month. After another worker hit an emergency stop button, the engineer maneuvered his way out of the robot's grasp, falling a couple of feet down a chute designed to collect scrap aluminum and leaving a trail of blood behind him, one of the witnesses told The Information. The attack reportedly occurred while the engineer was programming software for two disabled Tesla robots nearby.

At the latest congressional hearing on A.I., the hype was high. "Since the release of ChatGPT just over a year ago, it's become clear A.I. could soon disrupt nearly every facet of our economy," said Rep. Nancy Mace, chair of the U.S. congressional Subcommittee on Cybersecurity, Information Technology, and Government Innovation. "The A.I. genie is out of the bottle and it can't be put back in." A.I. does seem like a genie: The technology is new and mysterious, we aren't sure exactly how it works, and we know it is very powerful. We are also afraid of it: In a poll conducted in the summer of 2023, over half of Americans said they were more concerned than excited about A.I.; there is widespread speculation about what effects the technology will have on our economy, our jobs (lolsob), our education system, our art; and tech leaders have warned that the technology puts the fate of humanity at risk.

Let's take a look at how OpenAI and its chatbot have impacted consumer electronics in 2023 and where they might lead the industry in the new year. "Meteoric" doesn't do justice to OpenAI's rise this year. The company released ChatGPT on November 30, 2022. Within five days, the program had passed 1 million users; by January, 100 million people a month were logging on to use it. It took Facebook four and a half years to reach those sorts of engagement numbers.

It was an amazing year for games. While there were no new consoles,we did get new VR headsets and a wave of new handheld PCs offered even more options for playing games on the go (or at least on the couch). That's reflected in many of our picks for best games of the year, with several PC-only choices. The year kicked off with a fantastic remake of space horror Dead Space and the breakout success, Pizza Tower. But there were so many more.

If 2022 was the year the generative AI boom started, 2023 was the year of the generative AI panic. Just over 12 months since OpenAI released ChatGPT and set a record for the fastest-growing consumer product, it appears to have also helped set a record for fastest government intervention in a new technology. The US Federal Elections Commission is looking into deceptive campaign ads, Congress is calling for oversight into how AI companies develop and label training data for their algorithms, and the European Union passed its new AI Act with last-minute tweaks to respond to generative AI. But for all the novelty and speed, generative AI's problems are also painfully familiar. OpenAI and its rivals racing to launch new AI models are facing problems that have dogged social platforms, that earlier era-shaping new technology, for nearly two decades.

In 2023, the world has felt like it was balanced on a precipice. A United States presidential election looms, with a resurgent candidate that threatens to bring with him all the chaos of 2016 and 2020. Artificial intelligence developed so quickly that it seemed to have suddenly sprung into being, heralding vast societal promise and disruption just around the bend of its exponential curve. And the world's richest man continued to use his power to push for a more reckless tech world, from free-for-all social media and oversold assisted-driving features to AI with a "rebellious streak." In the midst of that uncertainty, a new war between Israel and Hamas added more atrocities alongside the slow-burning horrors of Russia's invasion of Ukraine.

Jodi Long was caught off guard by the cage filled with cameras meant to capture images of her face and body. "I was a little freaked out because, before I walked in there, I said I don't remember this being in my contract," the actor said. The filmmakers needed her digital scan, Long was told, because they wanted to make sure her arms were positioned correctly in a scene where she holds a computer-generated character. That moment in 2020 stuck with Long, president of SAG-AFTRA's Los Angeles local, while she was negotiating for protections around the use of artificial intelligence when actors went on strike. In November, the actors guild reached a deal with Hollywood studios that -- among other things -- required consent and compensation for the use of a worker's digital replica.