Published on December 25, 2025 at 06:01 CET (UTC+1)
Phoenix: A modern X server written from scratch in Zig (284 points by snvzz)
Phoenix is a new X server (the software that provides graphical displays on Unix-like systems) written from scratch in the Zig programming language. It is not yet ready for daily use but aims to be a simpler, more secure modern alternative to the Xorg server by supporting only a subset of the X11 protocol and modern hardware. Its security goals include using Zig's safety features and isolating applications by default with permission prompts for interaction.
Python Applied Mathematics Labs (32 points by vvin)
The Python Applied Mathematics Labs (ACME Labs) website provides educational labs designed to accompany the "Foundations of Applied Mathematics" textbook series. These labs teach core technical skills using Python's scientific stack (NumPy, SciPy, Matplotlib, pandas) and apply them to real-world problems like tsunami prediction, sound filtering, image compression, and facial recognition. They are intended to give hands-on experience connecting mathematical theory to practical computation.
Tell HN: Merry Christmas (783 points by basilikum)
This is a simple, festive "Tell HN" post wishing the Hacker News community a Merry Christmas. The author acknowledges different cultural celebrations and time zones while expressing hopes for rest and meaningful time with loved ones, and offers love to those who are alone. The post includes ASCII art of a Christmas tree, which some commenters initially mistook for obfuscated C code.
Microsoft denies rewriting Windows 11 in Rust using AI (20 points by zdw)
Microsoft has publicly denied rumors that it is using AI to rewrite Windows 11 in Rust. The rumors originated from a LinkedIn post by a Microsoft employee that claimed a massive, AI-driven code translation feat ("one engineer, one month, one million code"), which caused online outrage and skepticism. The article reports on Microsoft's official rejection of this claim as reported by Windows Latest.
Who Watches the Waymos? I do [video] (88 points by notgloating)
Based on the title and context, this YouTube video appears to feature an individual or group monitoring or analyzing the behavior of Waymo's autonomous vehicles. The phrase "Who watches the Waymos?" suggests a critical or investigative look at the operations and societal impact of this leading self-driving car company, though the specific content of the video cannot be confirmed from the preview.
Asterisk AI Voice Agent (68 points by akrulino)
Asterisk AI Voice Agent is an open-source project that integrates an AI voice agent with the Asterisk/FreePBX telephony platform using Audiosocket/RTP technology. This allows for the creation of AI-powered voice interfaces for phone systems, capable of handling calls automatically. The project includes an admin UI and is designed to be self-hosted, providing a tool for building automated customer service or interactive voice response systems.
Show HN: Minimalist editor that lives in browser, stores everything in the URL (265 points by medv)
This "Show HN" project is a minimalist, self-contained notes web app that runs entirely in the browser. Its key innovation is storing all note data compressed within the URL's hash fragment, allowing notes to be saved and shared simply by copying the URL. The app features auto-save, dark mode, mobile responsiveness, and requires no backend server.
CSRF protection without tokens or hidden form fields (136 points by adevilinyc)
This technical blog post details the author's journey to implement CSRF (Cross-Site Request Forgery) protection for their Microdot web framework. Initially expecting to use traditional tokens, the author discovered and describes a newer, simpler method that avoids tokens or hidden form fields altogether. The post discusses the general advice against rolling your own security but explains the necessity and process in this context.
Fabrice Bellard: Biography (2009) [pdf] (224 points by lioeters)
This is a PDF biography of the prolific programmer Fabrice Bellard, dated 2009. Bellard is renowned for creating influential projects like the FFmpeg multimedia library, the QEMU hardware emulator, and the Tiny C Compiler. The biography likely details his background, achievements, and his unique approach to software development that combines deep theoretical knowledge with practical implementation skill.
Research team digitizes more than 100 years of Canadian infectious disease data (84 points by XzetaU8)
A McMaster University research team, led by professor David Earn, has digitized over a century of historical Canadian infectious disease records, creating a new public database. The data, which includes hand-written weekly reports from 1939-1989 found in a ministry storage area, will allow researchers to study long-term patterns of disease incidence. This resource aims to strengthen public health preparedness and spur improvements in modern disease reporting standards.
AI Integration into Legacy Infrastructure: The Asterisk AI Voice Agent project demonstrates a clear trend of integrating modern AI (likely speech-to-text, LLMs, and text-to-speech) into established, widely-used legacy systems like telephony PBX. This matters because it shows the path to AI adoption is often through augmentation, not replacement. The takeaway is that significant commercial and practical AI opportunities lie in creating bridges to mature industries.
The Rise of AI-Assisted Code Migration & Security: While Microsoft denied the specific rumor, the very existence of the story and Microsoft's known efforts to replace unsafe code highlight a major trend: using AI to assist in large-scale code translation (e.g., C++ to Rust) and security hardening. This matters because manually securing critical legacy codebases is untenable. The implication is that AI-powered static analysis and transpilation will become essential tools for platform security.
Democratization of ML Education & Tools: The Python Applied Mathematics Labs represent the ongoing trend of democratizing applied AI/ML education. By providing hands-on labs connecting core math to implementation, they lower the barrier to entry. This matters for creating a larger, more skilled workforce. The actionable insight is that high-quality, practical educational content focused on fundamentals remains in high demand.
AI as a Catalyst for Data Liberation and Historical Analysis: The digitization of 100+ years of Canadian disease data underscores how modern data science and ML create value by liberating historical, unstructured data. This matters because AI models are hungry for high-quality, longitudinal datasets to identify patterns and train predictive systems. The trend is that any effort to digitize and structure historical records now has direct and powerful applications in AI-driven research and public health modeling.
Specialized, Lightweight AI Tools over Monolithic Solutions: The minimalist browser editor and the targeted Asterisk Voice Agent reflect a preference for specialized, lightweight tools that do one thing well, often client-side or open-source. In AI, this parallels the trend towards smaller, fine-tuned models over giant general-purpose ones for specific tasks (e.g., voice agent vs. full ChatGPT). The implication is that efficiency, privacy, and cost will drive development of compact, fit-for-purpose AI modules.
Increasing Scrutiny and "Watching" of AI Systems: The "Who Watches the Waymos?" video title points to the growing trend of independent scrutiny, auditing, and journalism focused on real-world AI system performance and ethics. This matters because public trust and regulatory oversight depend on transparent evaluation. For AI developers, the takeaway is that operational AI, especially in safety-critical domains like autonomous vehicles, will operate under continuous third-party observation.
Security Paradigms Must Evolve Alongside AI Tooling: The article on novel CSRF protection highlights that as AI enables new development methodologies (like auto-generated code), the underlying security foundations must also innovate. This matters because AI-generated code could introduce novel attack surfaces or obscure traditional ones. The trend is that security research must run in parallel with AI-assisted development, ensuring new protections are as agile as the new tools.
Analysis generated by deepseek-reasoner