Mary's journey through alcohol addiction led her to a clinical trial exploring semaglutide, a medication originally for diabetes and obesity. Remarkably, it diminished her cravings and allowed her to reflect on her life choices. Researchers are optimistic that GLP-1 drugs could offer new insights and treatments for addiction.

Recent exploitation of Ivanti Endpoint Manager Mobile (EPMM) reveals a new tactic—attackers are leaving dormant backdoors instead of executing immediate attacks. This article explores the implications of uploading in-memory Java class loaders, indicating a shift in strategies among cybercriminals aimed at long-term access.

The article explores the evolution of agentic AI from chatbots to advanced systems design, highlighting the role of open-source frameworks like LangChain and AutoGen. It provides a guide to essential tools for building robust agents that plan, execute, and learn, making it a valuable resource for developers.

AI has boosted productivity for engineers, allowing tasks to be completed faster. However, this increase often leads to more work and greater cognitive demands, resulting in exhaustion. The transition from creator to reviewer can be draining, as evaluating AI-generated output requires constant scrutiny and decision-making.

This article explores the nuanced relationship between developers and AI in software production. It suggests that while AI can enhance efficiency, it may also lead to misunderstandings around code ownership and context. Developers should prioritize investigation and understanding to ensure quality and accountability in their work.

Taiwan Semiconductor Manufacturing Corp. (TSMC) announced plans to produce advanced 3-nanometer AI semiconductors in Japan's Kumamoto Prefecture. This move aims to meet rising AI demand and strengthen Japan's chipmaking industry, with significant implications for economic security as Japan invests heavily in semiconductor technology.

The decline of Twitter has surprisingly led to an increase in LinkedIn activity, sparking discussions on technological understanding. Experts like Simon Wardley, Adam Jacob, and Bruce Perens explore the complexities of our relationship with technology, emphasizing the gaps in knowledge about systems we rely on daily, like telephony and software development.

In organizational settings, understanding game theory can illuminate the complexities of decision-making and behavior. This article explores how incentives shape individual actions, often leading to unintended consequences, and highlights the importance of clear rules and accountability in fostering a productive culture.

This article reflects on philosopher Nick Bostrom's "paperclip maximizer" thought experiment, suggesting it serves as a cautionary tale about our relentless pursuit of AI development. It delves into the potential existential risks tied to resource optimization, questioning the human impact as we strive for technological advancement.

Large Language Models are transforming the coding landscape, enabling programmers to complete tasks efficiently. As developers turn from traditional platforms like Stack Overflow to AI tools, the evolution of programming languages reflects a significant shift. This article explores the historical context of coding simplification and its implications for the future.

Moltbook, a viral social network for bots, reflects both the current AI obsession and the limitations of artificial intelligence. While it showcases bot interactions, much of the content is mere mimicry rather than genuine autonomy. Ultimately, Moltbook raises questions about the future of AI while revealing its present shortcomings.

The article explores the author's evolving experiences with programming and large language models (LLMs) over the past year, highlighting advancements in AI capabilities, shifts in coding environments, and the emergence of new tools like exe.dev. It reflects on both the joys and challenges brought by these innovations.

OneVision-Encoder rethinks video encoding by focusing on high-entropy regions for efficient visual understanding. This approach enhances accuracy without compromising performance, outperforming existing models in various tasks. By aligning architectures with information-theoretic principles, it offers a promising pathway for advancing multimodal intelligence.

This article introduces Variational In-Context Reward Modeling (ICRM), a novel approach allowing reward models to adapt to new preferences at test time. By leveraging Bayesian methods, ICRM enhances accuracy and practical application in reinforcement learning, producing measurable improvements in aligning models with user preferences.

StealthRL introduces a novel reinforcement learning framework designed to challenge AI-text detectors using adversarial paraphrasing. By optimizing for semantic preservation while evading detection, the framework exposes vulnerabilities across different detector families, highlighting significant robustness gaps in AI-text detection systems. The study underscores the need for improved security protocols.