A comprehensive study from The Wharton School and GBK Collective examines the complex reality of generative AI adoption in businesses. It uncovers significant gaps in perceptions between executives and mid-level managers, highlights a decline in training investments, and raises concerns about skill atrophy amidst technological integration.

Australia's parliament has approved contentious legislation permitting intelligence agencies to access encrypted digital communications, raising concerns among privacy advocates and cryptographers. The law could set a concerning precedent for global digital security standards, as tech companies may be compelled to create access tools, risking widespread exploitation.

The paper details experiments with Google DeepMind's AlphaEvolve tool, highlighting its use in optimizing mathematical problems across analysis, combinatorics, and geometry. AlphaEvolve offers notable advantages in scalability, adaptability, and solution interpretability, achieving competitive results while requiring less domain expertise compared to traditional methods.

The rise of AI in vulnerability reporting has led to a concerning influx of low-quality submissions, termed "AI slop." This trend complicates the work of maintainers and dilutes the value of genuine findings. The author reflects on their decade of experience in bug bounty programs, highlighting the urgent need for clarity in this evolving landscape.

Parallel Search introduces a specialized web search API designed exclusively for AI agents, optimizing for context and token relevance. With improved accuracy and reduced costs for complex queries, it outperforms traditional search systems by enabling efficient multi-hop reasoning, ultimately transforming how AI interacts with web data.

TabPFN-2.5 marks a significant advancement in tabular AI, offering enhanced scalability and improved performance compared to previous models. With the ability to handle larger datasets and faster inference times, it outperforms traditional tuned models and delivers reliable results for various applications in data-driven fields.

A recent data breach has unveiled 2 billion unique email addresses and over 1.3 billion passwords, raising alarm about credential stuffing risks. The article explores data verification processes, the implications for users, and stresses the importance of updating compromised passwords to enhance online security.

This article explores a new method for improving communication between large language models by using vector translations. The approach enhances semantic exchange while minimizing computational costs, demonstrating that models can share meaning more effectively. This could pave the way for more collaborative AI systems.

This article examines Deep Knowledge Tracing (DKT) and its ability to model causal relationships in educational contexts. The authors argue that DKT's predictive power stems from its focus on causal structures rather than merely bidirectional knowledge relationships. They propose a method for extracting these structures, providing new insights into effective knowledge tracing.

This paper presents a new approach to 3D object reconstruction from multi-view images, combining geometry and appearance optimization. The proposed framework enhances mesh geometry and color simultaneously, improving quality for tasks like relighting and shape deformation, while ensuring consistency with input images and geometric data.

Shotgun is a command-line tool that generates codebase-aware specifications for AI coding agents like Codex and Cursor. By analyzing your repository, it ensures that AI builds align with project architecture, providing comprehensive specs that help maintain context throughout development. Ideal for enhancing AI integration in coding.

The Agent Development Kit (ADK) for Go is an open-source toolkit designed for building and deploying AI agents. It emphasizes flexibility and control, supporting multi-agent systems and cloud-native deployment. Ideal for developers, ADK simplifies the creation of complex workflows with Go's performance and concurrency strengths.

Texo is a minimalist, free, and open-source LaTeX OCR model designed for efficient performance with only 20M parameters. It offers fast inference, is trainable on consumer-level GPUs, and aims to provide an accessible option for STEM and AI learners in need of precise document recognition.

This article outlines the features and installation steps for integrating browser automation into Claude Code using the Stagehand framework. It emphasizes natural language instructions for efficient interactions. Setup instructions, troubleshooting tips, and helpful resources are provided for users looking to streamline browser tasks.

Tunarr enables users to create and manage live TV channels using content from Plex, Jellyfin, or Emby servers. With features like advanced filtering, improved scheduling, and browser streaming, this evolving tool aims to enhance user experience while offering flexible channel customization options.