Context. The security of critical infrastructure has been a pressing concern since the advent of computers and has become even more critical in today's era of cyber warfare. Protecting mission-critical systems (MCSs), essential for national security, requires swift and robust governance, yet recent events reveal the increasing difficulty of meeting these challenges. Aim. Building on prior research showcasing the potential of Generative AI (GAI), such as Large Language Models, in enhancing risk analysis, we aim to explore practitioners' views on integrating GAI into the governance of IT MCSs. Our goal is to provide actionable insights and recommendations for stakeholders, including researchers, practitioners, and policymakers. Method. We designed a survey to collect practical experiences, concerns, and expectations of practitioners who develop and implement security solutions in the context of MCSs. Conclusions and Future Works. Our findings highlight that the safe use of LLMs in MCS governance requires interdisciplinary collaboration. Researchers should focus on designing regulation-oriented models and focus on accountability; practitioners emphasize data protection and transparency, while policymakers must establish a unified AI framework with global benchmarks to ensure ethical and secure LLMs-based MCS governance.

The advancements in generative AI inevitably raise concerns about their risks and safety implications, which, in return, catalyzes significant progress in AI safety. However, as this field continues to evolve, a critical question arises: are our current efforts on AI safety aligned with the advancements of AI as well as the long-term goal of human civilization? This paper presents a blueprint for an advanced human society and leverages this vision to guide current AI safety efforts. It outlines a future where the Internet of Everything becomes reality, and creates a roadmap of significant technological advancements towards this envisioned future. For each stage of the advancements, this paper forecasts potential AI safety issues that humanity may face. By projecting current efforts against this blueprint, this paper examines the alignment between the current efforts and the long-term needs, and highlights unique challenges and missions that demand increasing attention from AI safety practitioners in the 2020s. This vision paper aims to offer a broader perspective on AI safety, emphasizing that our current efforts should not only address immediate concerns but also anticipate potential risks in the expanding AI landscape, thereby promoting a safe and sustainable future of AI and human civilization.

The human cell is a miserable thing to study. Tens of trillions of them exist in the body, forming an enormous and intricate network that governs every disease and metabolic process. Each cell in that circuit is itself the product of an equally dense and complex interplay among genes, proteins, and other bits of profoundly small biological machinery. Our understanding of this world is hazy and constantly in flux. As recently as a few years ago, scientists thought there were only a few hundred distinct cell types, but new technologies have revealed thousands (and that's just the start).

With the rapid development of generative artificial intelligence, particularly large language models, a number of sub-fields of deep learning have made significant progress and are now very useful in everyday applications. For example, well-known financial institutions simulate a wide range of scenarios for various models created by their research teams using reinforcement learning, both before production and after regular operations. In this work, we propose a backdoor attack that focuses solely on data poisoning. This particular backdoor attack is classified as an attack without prior consideration or trigger, and we name it FinanceLLMsBackRL. Our aim is to examine the potential effects of large language models that use reinforcement learning systems for text production or speech recognition, finance, physics, or the ecosystem of contemporary artificial intelligence models.

This paper explores and assesses in what ways generative AI can assist in translating survey instruments. Writing effective survey questions is a challenging and complex task, made even more difficult for surveys that will be translated and deployed in multiple linguistic and cultural settings. Translation errors can be detrimental, with known errors rendering data unusable for its intended purpose and undetected errors leading to incorrect conclusions. A growing number of institutions face this problem as surveys deployed by private and academic organizations globalize, and the success of their current efforts depends heavily on researchers' and translators' expertise and the amount of time each party has to contribute to the task. Thus, multilinguistic and multicultural surveys produced by teams with limited expertise, budgets, or time are at significant risk for translation-based errors in their data. We implement a zero-shot prompt experiment using ChatGPT to explore generative AI's ability to identify features of questions that might be difficult to translate to a linguistic audience other than the source language. We find that ChatGPT can provide meaningful feedback on translation issues, including common source survey language, inconsistent conceptualization, sensitivity and formality issues, and nonexistent concepts. In addition, we provide detailed information on the practicality of the approach, including accessing the necessary software, associated costs, and computational run times. Lastly, based on our findings, we propose avenues for future research that integrate AI into survey translation practices.

PUBG: Battlegrounds will add non-player characters powered by NVIDIA ACE generative AI. These PUBG Allies are being dubbed Co-Playable Characters, and they can have real-time conversations with a player about what's happening in a match. They can also adapt their strategies and gameplay to work with the player's style. "We will continue to innovate user experiences by integrating CPC into our games and aim to establish it as a benchmark for the gaming industry," said Kangwook Lee, head of Krafton's deep learning division. Krafton will also publish upcoming life simulator inZOI, and had a CES demo of a CPC in that game as well.

OpenAI CEO Sam Altman recently published a post on his personal blog reflecting on AI progress and his predictions for how the technology will impact humanity's future. "We are now confident we know how to build AGI [artificial general intelligence] as we have traditionally understood it,"Altman wrote. He added that OpenAI, the company behind ChatGPT, is beginning to turn its attention to superintelligence. While there is no universally accepted definition for AGI, OpenAI has historically defined it as "a highly autonomous system that outperforms humans at most economically valuable work." Although AI systems already outperform humans in narrow domains, such as chess, the key to AGI is generality.

Annie Altman, the sister of OpenAI founder and CEO Sam Altman, has sued her brother accusing him of sexually assaulting her when she was a minor. In a complaint filed this week with a Missouri federal court, Annie Altman alleges her older brother committed "numerous acts of rape, sexual assault, sexual abuse, molestation, sodomy, and battery" from 1997 to 2006, with the abuse starting when she was only three years old. In a joint statement he made alongside his mother and two younger brothers, Sam Altman said "all of [Annie's] claims are utterly untrue." The Altmans say they've tried to support Annie in "many ways" over the years, including by offering direct financial assistance. My sister has filed a lawsuit against me.

Kurt Knutsson discusses some tips to keep you safe. BEWARE DEEPFAKE SCAMS: The FBI is issuing a warning that criminals are increasingly using generative AI technologies, particularly deepfakes, to exploit unsuspecting individuals. This alert serves as a reminder of the growing sophistication and accessibility of these technologies and the urgent need for vigilance in protecting ourselves from potential scams. ROBOTICS ERA: Nvidia CEO Jensen Huang said the artificial intelligence revolution is on the verge of delivering breakthroughs in robotics at the annual Consumer Electronics Show conference in Las Vegas. AI technology is being used more and more by doctors.

Meta caused a stir last week when it let slip that it intends to populate its platform with a significant number of entirely artificial users in the not too distant future. "We expect these AIs to actually, over time, exist on our platforms, kind of in the same way that accounts do," Connor Hayes, vice-president of product for generative AI at Meta, told The Financial Times. "They'll have bios and profile pictures and be able to generate and share content powered by AI on the platform ... that's where we see all of this going." The fact that Meta seems happy to fill its platform with AI slop and accelerate the "enshittification" of the internet as we know it is concerning. Some people then noticed that Facebook was in fact already awash with strange AI-generated individuals, most of which stopped posting a while ago.