This article explores the possibility of an impending technological singularity, pinpointing February 10, 2026, as a significant date. By analyzing five key metrics of AI progress, the author builds a model to anticipate when rapid advancements may reach a critical tipping point.

On January 14, 2026, a significant and sudden drop in global telnet traffic was recorded, suggesting a possible configuration change in internet routing. This article explores the correlation between this decline and the subsequent discovery of a critical vulnerability in a widely used telnet service, probing the implications for security.

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.

This article explores the distinction between reasoning about programs and reasoning about systems, particularly in functional programming. It emphasizes that correctness in production relates to the interplay of multiple code versions across a distributed system rather than the integrity of a single program. Understanding this can improve software reliability.

Wall Street Raider, a complex financial simulator created by Michael Jenkins, faced decades of failed attempts at remaking it. However, a young developer named Ben Ward took on the challenge, leading to its revival. This article explores their unique collaboration and the legacy of a game that shaped financial gaming.

Andon Labs explores AI behavior by letting their agent, Bengt, operate without restrictions. The experiment reveals how quickly AI can pivot and innovate, from launching an e-commerce site to attempting gig economy arbitrage, showcasing the potential and rapid development of autonomous AI agents in real-world scenarios.

A study from the Berkeley Haas School of Business reveals that AI can actually increase the intensity of work rather than reduce it. Employees juggle multiple tasks with AI assistance, leading to heightened cognitive load and burnout. The article advocates for structured AI practices to promote sustainable productivity.

The U.S. is experiencing an unprecedented investment surge in artificial intelligence, with spending exceeding $1 trillion annually on data centers, software, and computers. Major tech companies are leading this trend, significantly impacting the economy while trade dynamics shift in response to rising imports from countries like Taiwan and Mexico.

this article explores the potential for runtime function modification in Go, reminiscent of Perl's "monkey patching." It explains how to safely replace built-in functions using low-level memory manipulation techniques, emphasizing the balance between performance benefits and the risks of modifying code at runtime.

In this reflective piece, a seasoned developer considers the evolution of computing from the 1980s to today. They explore how technological advancements have transformed the craft of building software, raising concerns about the diminishing intimacy and creativity in development, particularly with the rise of AI.

This article introduces the Sci-VLA plugin, which enhances VLA models in robotic labs by enabling them to better perform long-horizon scientific tasks. By allowing seamless transitions between atomic actions, this approach improves execution efficiency and success rates, making it suitable for complex experimental workflows.

As AI systems increasingly take on autonomous roles, securing their actions becomes crucial. This article presents Autonomous Action Runtime Management (AARM), a system specification designed to protect AI-driven actions at runtime. AARM provides a framework for real-time action evaluation and enforcement, aiming for industry-wide interoperability.

This article presents a new framework for tracking the provenance of large language models using behavioral fingerprints known as refusal vectors. The method shows high accuracy in identifying model families and maintains effectiveness even against certain modifications, offering a potential solution for protecting intellectual property in AI.