Large language models are evolving to handle longer sequences, with some models now supporting up to 256K tokens. This article explores how integrating the NVSHMEM communication library with the XLA compiler optimizes training efficiency, resulting in significant speed improvements for long-context workloads, particularly when using ring attention.

The financial landscape is on the brink of transformation as autonomous AI agents begin to conduct transactions without human intervention. This shift requires new systems designed for agentic commerce, utilizing protocols like x402 and PayPal's Agentic Commerce Services. As this infrastructure evolves, it could significantly reshape economic activity, driven by innovative AI-driven transactions.

AI coding assistants can streamline development, but some pose serious risks. The MaliciousCorgi campaign reveals two popular VS Code extensions that not only assist but also secretly harvest sensitive data and files, exposing developers to significant security threats. Ensure your workspace stays safe with tools designed to verify extension behavior.

Game Arena is evolving to advance AI benchmarking by introducing new challenges in poker and Werewolf alongside chess. These games not only evaluate strategic reasoning and social dynamics but also foster agent safety research, providing crucial insights into AI behavior in real-world scenarios.

The article explores the largest numbers that can be represented and computed within 64 bits, comparing traditional data types like uint64_t with more complex constructs such as Turing machines and lambda calculus. It examines concepts like the Busy Beaver function and how they surpass commonly known large numbers, emphasizing the boundaries of programming languages.

This research examines how AI systems fail, focusing on the balance between systematic misalignment and incoherence. Findings show that as tasks become more complex, failures lean towards incoherence, suggesting future AI shortcomings may resemble unpredictable accidents rather than coherent goal misalignment. This has vital implications for AI safety and alignment research.

Bunny Database, now in public preview, is a managed SQLite-compatible service designed for developers seeking a reliable, cost-effective database solution. With one-click deployment, low latency, and usage-based pricing, it simplifies managing your app's database without the complexities or expenses of traditional DBaaS platforms.

This article analyzes the evolving landscape of copyright law in light of generative AI. It discusses how AI exposes the inconsistencies in copyright enforcement that have long existed, revealing the challenges of applying traditional rules to modern technology. The implications for creativity and distribution are explored.

France and other European nations are shifting away from U.S. tech giants like Zoom and Microsoft Teams to promote digital sovereignty. This movement aims to enhance data privacy and security by adopting homegrown and open-source solutions. The trend reflects growing concerns over reliance on foreign digital services amid geopolitical tensions.

Deno Sandbox offers a secure environment for running untrusted code generated by LLMs, ensuring API keys and sensitive information are protected from exfiltration. With lightweight microVMs and easy deployment to Deno Deploy, it streamlines the development process while enhancing security.

This article explores how to effectively sandbox AI agents like Claude Code on a Linux system using bubblewrap. It discusses the challenges of managing permissions, offers a customized bubblewrap script setup, and provides tips for adapting the solution to different projects and AI agents.

Xcode 26.3 introduces agentic coding, allowing developers to utilize AI agents like Anthropic’s Claude and OpenAI’s Codex for enhanced app development. By streamlining workflows and facilitating task management, this update empowers developers to focus on innovation while leveraging advanced AI capabilities throughout the development process.

This article presents CORE, an optimization method designed to control output rankings in LLM-based search engines. By appending strategically crafted content, CORE enhances visibility for small businesses and independent creators, achieving impressive success rates across various product categories while maintaining content fluency.

This article introduces Reasoning Cache (RC), an iterative decoding algorithm designed to enhance the extrapolation abilities of large language models during both training and inference. By utilizing RC, models significantly improve their reasoning performance over longer horizons, demonstrating effective adaptation to new challenges at test time.

This study explores outlier dynamics in large language model pretraining using NVFP4, highlighting how architectural components contribute to outlier sensitivity. The authors propose the Hot-Channel Patch mechanism to reduce quantization loss, resulting in improved efficiency and accuracy in training models compared to traditional methods.