Researchers at Google have introduced a "sleep phase" in continual learning for large language models, allowing these systems to incorporate new information while minimizing forgetting. This approach mimics human memory processes and demonstrates significant improvements in knowledge retention and reasoning capabilities, setting a new standard for language model adaptation.

Gemini 4 Carbon represents a significant advancement in AI model capabilities, particularly in cybersecurity and long-horizon engineering tasks. With superior performance in vulnerability detection and secure code generation, Carbon sets new benchmarks while emphasizing safety and alignment. Access will be gradually extended to select partners for further testing and feedback.

Qwenputer is an experimental model that integrates a RISC-V CPU within the weights of Qwen 3.5, utilizing its Gated DeltaNet layers as RAM. This internal CPU can execute arithmetic operations and programming code without external tools, demonstrating a novel approach to memory and computation in AI models.

AI is increasingly being used to generate low-quality academic papers, raising concerns about trust in scientific publishing. This article outlines an experiment where an AI-generated paper was submitted to a journal, illustrating the challenges of distinguishing genuine research from AI-driven forgeries and the broader implications for the academic community.

Google's Gemini 4 Carbon has topped the Artificial Analysis Intelligence Index v5, showcasing impressive gains in reasoning, knowledge, and scientific tasks. While it excels in several areas, it still trails behind competitors in coding and knowledge work. The model is currently available for select users at a promotional price.

Good developers express caution towards agentic development due to concerns about quality and reliability in production environments. While coding agents can expedite production, their uncertainty about the tools and processes remains prevalent. This article explores the balance between leveraging technology and maintaining trust in software development practices.

Mistral Large 4 (Le Chonk), a cutting-edge 1-trillion-parameter model, enhances coding and cybersecurity performance with innovative reasoning modes. Trained in Europe and fully open-weight, it empowers developers with customizable deployment options while leading benchmarks for coding and defensive tasks, advancing the capabilities of sovereign AI.

Proton CEO Andy Yen is pushing the company toward aggressive AI adoption, urging employees to prioritize speed over security. Despite Proton's reputation for privacy, internal reports reveal a culture of fear and pressure, as workers struggle to voice concerns about the rapid shift to AI technologies.

MIT professor Eric So discusses in his new book, "The Collision: What AI Does to Us," the subtle impact of AI on cognitive abilities. He reflects on his personal experience with AI dependence and offers insights into how technology can blur the line between efficiency and original thought, urging awareness of our mental processes.

This article explores the performance differences in high-speed interconnects for multi-node AI workloads. It highlights the advantages of NVIDIA's NVL72 systems, which enhance GPU communication via NVLink, and discusses how effective workload placement can mitigate bottlenecks during training and inference. Techniques like tensor and expert parallelism are detailed for optimizing efficiency.

Brno University of Technology graduates Tomáš Mikolov and Filip Maleňák received state honors from the Czech President for their significant contributions to technology and science. Mikolov is recognized for his work in artificial intelligence, while Maleňák created the life-saving Záchranka app, showcasing the impact of technical education in practical applications.

Duet is redefining chatbot interactions by prioritizing speed, simplicity, and user-friendly channel management. Unlike other assistants, it handles session organization and access policies effectively, ensuring responsiveness without compromising security. Although still in beta, its innovative approach could set a new standard for chatbot experiences.

This article presents the Algebraic World Model (AWM), a framework enabling AI to reason about unknown environments. By exploring interactions and generating formal proofs, AWM demonstrates its ability to solve complex problems in Lean 4, surpassing existing AI tools in accuracy and efficiency.

This article explores the issue of over-refusal in safety-aligned large language models, which leads to the rejection of harmless queries. The authors propose a new framework, GOAL, aimed at improving the separation of harmful and harmless samples while maintaining safety and performance in AI systems.

This study explores post-training techniques for mixture-of-experts models to enhance efficiency in consolidating independently optimized specialists. The proposed method shows significant improvements in integration scores and processing speed, demonstrating effective training strategies for better performance in various reasoning tasks compared to existing models.