In our latest benchmark, open-weight model GLM 5.2 from Zhipu AI achieved a surprising 39% F1 score in detecting IDOR vulnerabilities, outperforming Claude Code. While it falls short of Semgrep's multimodal pipeline, our findings highlight the role of model structure versus the harness in performance.

This article explores the complexities of shell scripting and the limitations of the POSIX specification. It highlights how different shell implementations interpret commands inconsistently, emphasizing the importance of testing scripts across various shells to ensure true portability. The author advocates for a more thorough validation process in shell documentation.

WAL-RUS is a new open-source Rust-based tool designed for PostgreSQL backups and WAL archival. It addresses memory predictability issues often encountered with existing systems like WAL-G, while ensuring compatibility and efficiency. This solution aims to optimize resource usage in resource-constrained environments, facilitating easier capacity planning.

AI tools can enhance your thinking by revealing the clarity or confusion in your ideas. Instead of relying on them for answers, use them to challenge and refine your judgment. Those who leverage AI thoughtfully will thrive in a landscape increasingly filled with average output.

China aims for full domestic production of chipmaking equipment, targeting greater self-sufficiency. While progress is evident, especially in chip manufacturing, lithography remains a challenge. The complexity and high cost of lithography machines, dominated by ASML and a few others, continue to hinder China's ambitions in chip technology.

Flock cameras, originally designed as automated license plate readers, offer expansive surveillance capabilities that raise privacy concerns. They track vehicles and individuals using AI but have faced criticism for security flaws and misuse by law enforcement. With over 100,000 cameras nationwide, their presence is becoming pervasive and controversial.

Apple's new Sparse Image Format (ASIF) introduced in macOS 26 Tahoe enhances virtual machine storage by allowing large files to be stored in a smaller, "sparse" manner. This article explores the process of creating and analyzing ASIF files, offering insights into reverse engineering and file format parsing.

AI tools to assist her in writing. This article explores how AI is changing the software engineering landscape, enabling developers to focus more on oversight and creative decision-making while relying on AI for code generation. It parallels this shift with the experiences of novelists harnessing technology for increased productivity.

This article critiques current adaptations of the mirror test for large language models, arguing that they miss the point of self-awareness measurement. It proposes a new method based on modifying textual outputs, using a case study of the Gemma 4 31B model to explore anomaly detection in machine responses.

In his new book, Falk Huettig explores the transformative effects of reading on cognitive development, memory, and even face recognition. Drawing from interdisciplinary research, he argues that literacy enhances brain function rather than undermining it, revealing reading as a powerful yet often overlooked cognitive tool.

The Fintech Engineering Handbook offers essential patterns for designing software systems focused on money management. It serves as a guide for newcomers to fintech, seasoned professionals needing reference, and those outside the field seeking insights into financial software design. Key principles include data integrity and precise currency handling.

Chinese firm 360 and Tokyo-based Sakana AI have launched new AI models amid ongoing U.S. export bans on advanced technologies. Tulongfeng focuses on cybersecurity, while Fugu is designed for orchestrating model access. Both companies aim to capture market opportunities as traditional U.S. models face restrictions.

This article presents the Learning to Allocate (L2A) framework for dynamic resource-adaptive inference in large language models. By integrating real-time resource conditions, L2A optimizes performance while conserving computational resources, allowing models to efficiently adapt to fluctuating cloud environments without significant loss in accuracy.

RS-Diffuser introduces a new framework for risk-sensitive offline reinforcement learning, enhancing decision-making in safety-critical applications. By combining diffusion-based trajectory generation with distributional value critics, it allows for flexible behavior adjustment while improving both performance and safety compared to traditional methods.

This article explores a new method for selecting layers in hybrid attention models, focusing on efficiency in long-context inference. By employing NLL-guided layer selection, the approach balances accuracy and computational costs, achieving high performance with fewer full-attention layers, ultimately advancing the deployment of large language models.