Summary of The Core Project - Tiny Core Linux

The Core Project is a flexible and modular Linux system that allows users to build their own desktops, servers, or appliances. It starts with a small base called Core (11MB), which includes the Linux kernel and essential files. TinyCore is an example of this system, featuring a lightweight desktop environment that is only 16MB.

CorePlus is an easy way for users to get started, offering community-built extensions for simple installation on various devices. However, it does not support all hardware or provide a complete desktop experience. Users can control which applications and hardware they want to include by installing additional packages from online repositories.

The latest version is 16.2. The project aims to create a fast, ultra-small graphical operating system that can boot from different sources, such as CD-ROMs or USB drives. It runs primarily in RAM, but users can choose to store additional applications on persistent devices.

The Tiny Core Linux community encourages involvement, allowing anyone to contribute by creating and sharing applications. The Tiny Core Linux Team is available to help users and developers.

For more information, join the Tiny Core community on forums and IRC.

Summary of HTML as an Accessible Format for Papers

Accessibility in research is important, and arXiv is responding by providing HTML versions of papers alongside PDFs. They are gradually converting over 2 million papers to HTML, although not all papers can be converted. Authors can preview their HTML papers during submission.

The move to HTML is necessary because most submissions (90%) are in LaTeX, which presents challenges in conversion to HTML. HTML is more accessible for users with disabilities, but the conversion process may have issues, which is why the HTML format is currently in "experimental" beta.

To help improve accessibility, the community is encouraged to read HTML papers and report any issues. Errors may occur, but feedback should focus on functionality rather than expecting an exact match to the PDF format, as HTML is inherently different.

Authors and developers can assist by following best practices for LaTeX markup and contributing to the improvement of conversions. Special thanks are extended to those who provided insights and to organizations that made the HTML project possible.

Linux Install Fest Summary

• Date and Location: The Linux Install Fest will take place on December 9, 2025, from 6 PM to 9 PM at the JAG3 classroom, Faculty of Mathematics, Jagićeva 5, Belgrade.

• Transportation: The venue is accessible via trams (5, 6, 7L, 14) and buses (21, 83) near Pijaca Đeram and Crveni krst stations.

• Event Purpose: The event aims to assist participants in installing the Linux operating system on their laptops. Experienced Linux users will be available for support, and short training sessions on topics like command line, git, and C programming may be offered based on interest.

• Post-Event Socializing: Attendees can continue to socialize at nearby bars after 9 PM.

• Recommended Linux Distributions:

  • Debian: Good for beginners with derivatives like Ubuntu, Mint, and Zorin.
  • Fedora: Also beginner-friendly but releases updates more frequently, which may affect stability.
  • Arch: Best for advanced users who want to customize their system.

• End of 10 Campaign: The event is part of a global initiative promoting Linux as a replacement for Windows 10, highlighting Linux's user-friendliness and environmental benefits.

• Installation Options:

  1. Virtual Machine: Install Linux on Windows, but it may run slower.
  2. Dual Boot: Install Linux alongside Windows; requires freeing up space.
  3. Replace Windows: Fully install Linux by removing Windows.

• Preparation: Participants should back up important data and can explore Linux distributions online before the event.

• Organizer: The event is organized by Decentrala, which promotes decentralized knowledge sharing and has hosted over 300 events.

• Upcoming Events: Additional sessions for beginners will be held on December 16 and December 23, covering the Linux command line and Git.

• Device Donations: Attendees can bring old devices for repair, which will help reduce electronic waste through the organization Ponovo.

The text outlines a guide for setting up Immich, a self-hosted photo manager, as an alternative to Google Photos. Here are the key points:

1. Backup Importance: The author prefers to keep a local copy of their data for backup and independence. They faced issues with the gphotos-sync tool and sought a new solution.

2. Hardware Setup: Immich is installed on a power-efficient Ryzen 7 Mini PC running Proxmox, allowing for virtual machines (VMs).

3. Installing Immich: A VM named “photos” is created for Immich, with specific resource allocations. It is installed on NixOS, and the author configures it to be accessible via a Tailscale VPN for security.

4. Photo Import Challenges: The initial photo import using the Immich CLI was unreliable, leading to the use of a third-party tool, immich-go, which improved the process by managing background tasks and handling Google Takeout metadata better.

5. Mobile App Setup: The Immich app is installed on the author’s iPhone for automatic photo backups. Notifications are recommended to be disabled to avoid interruptions.

6. Backup Strategy: The author follows a 3-2-1 backup strategy, using rsync to back up Immich data regularly.

7. Limitations: Immich lacks photo editing features, and sharing images still requires Google Photos.

8. Comparison with Alternatives: Immich is chosen over another tool, Ente, as it fits the author's needs better without the complexity of additional encryption.

9. Conclusion: Overall, Immich is praised for its speed and functionality, though there are suggestions for improving the CLI tool and mobile app configuration.

The author encourages readers to subscribe to their blog for more updates.

A Reddit user named Dycus created a compact camera using the sensor from an optical mouse, taking about 65 hours to complete. The result is a low-resolution black-and-white camera that has various shooting modes and is housed in a 3D-printed body.

This project stands out because it is a full camera design, unlike similar past projects that were less developed. The camera features multiple shooting modes, 64 shades of gray, adjustable exposure, and can store up to 48 pictures. Notably, it can take "smear shots" for panoramic images.

Although the camera's resolution is low—900 pixels compared to the one million needed for a megapixel—it can still capture recognizable images. Dycus compares its fun factor to that of the Game Boy Camera, which has low resolution but is enjoyable to use.

Summary of "Mapping Amazing: BeeMaps"

The text discusses the evolution of digital mapping and introduces Bee Maps, a company revolutionizing the way map data is collected.

1. Background: The author shares their experience starting in the mapping industry in 1985, highlighting the challenges of creating digital maps from outdated topographic sources without modern technology like aerial imagery.

2. Mapping Evolution: Initially, navigation systems did not provide detailed directions and relied on basic street data. As technology advanced, companies began using vehicles equipped with cameras to collect more information, leading to the development of Google Street View in 2007.

3. Current Challenges: Maintaining up-to-date map data is difficult and costly, especially for autonomous vehicles that require highly detailed maps known as HD Maps.

4. Introduction of Bee Maps: Founded in 2015 by Ariel Seidman, Bee Maps aims to simplify map data collection through a unique device that captures various road details. Users can earn cryptocurrency (HONEY) by driving with the device, incentivizing data collection.

5. Business Model: Bee Maps has shifted to a subscription service for their devices, which also provide dash cam features. They gather extensive data on road attributes and have started licensing this data to major companies.

6. Impressive Coverage: Bee Maps has mapped over 665 million kilometers of roads globally, far exceeding traditional mapping companies. Their approach results in a significantly larger and more active data collection fleet.

In summary, Bee Maps is transforming the mapping industry by combining innovative technology with a unique user-driven data collection model, making them a key player in the future of navigation and mapping services.

Summary of "Touching the Elephant - TPUs"

The Tensor Processing Unit (TPU) is Google’s specialized hardware for deep learning, developed over a decade ago in response to growing demands for processing power. While NVIDIA's GPUs have garnered attention for their role in AI, the TPU is notable as an early and effective hardware accelerator specifically designed for neural networks.

1. Origins and Purpose: Google recognized the need for more efficient processing in 2013, leading to the creation of the TPU to handle deep learning tasks. The TPU has evolved through several generations, with the latest, Ironwood, announced in 2025, showcasing impressive capabilities like 42.5 Exaflops performance with 9,216 chips.

2. Hardware Design: The TPU differs from general-purpose processors by being a Domain Specific Accelerator, optimized for specific tasks like matrix operations used in neural networks. This specialization allows it to achieve higher performance by focusing on the most common computations in these networks.

3. Generational Improvements: The TPU has gone through multiple iterations:

   • TPUv1 focused on fast inference (the process of making predictions) but lacked the flexibility needed for training.
   • TPUv2 introduced dual-core designs and better support for training by adding programmability and higher precision.
   • TPUv3 improved on TPUv2 with additional cores and memory capacity.
   • TPUv4 emphasized system scalability and energy efficiency, introducing shared memory to reduce trips to slower DRAM.

4. Networking and Scalability: The TPU’s architecture includes sophisticated networking capabilities, allowing multiple chips to communicate effectively. The introduction of Optical Circuit Switching (OCS) in TPUv4 enables flexible, high-bandwidth communication across chips and racks.

5. Software Integration: The TPU relies heavily on software to manage its operations, including scheduling tasks and ensuring efficient resource allocation. The XLA compiler optimizes programs for execution across the TPU architecture, while systems like Borg manage resource allocation and job scheduling.

6. Future Directions: As TPU technology evolves, newer models (TPUv5 and beyond) are expected to continue enhancing performance and efficiency, focusing on both training and inference workloads.

In summary, the TPU represents a significant advancement in hardware design for machine learning, driven by the need for specialized processing power, and continues to evolve with a focus on efficiency, scalability, and software integration.

The article discusses the author's successful use of a method called "one-shot decompilation" with an AI model named Claude. By running Claude in a loop for three weeks, the author achieved more progress on the game Snowboard Kids 2 than in the previous three months.

Key points include:

1. One-Shot Decompilation: This method involves giving Claude a function to decompile, and allowing it to work without human feedback. This increases efficiency but carries risks, such as exhausting Claude's processing quota without making progress.

2. Workflow: The process is automated using a script that manages various components:

   • Scorer: Chooses the easiest functions for Claude to decompile.
   • Claude: Performs the decompilation.
   • Tools: Provide necessary resources for Claude.
   • Driver: Manages the overall operation and logs progress.

3. Scoring Functions: The author initially used a formula to assess function complexity, later improving it with a logistic regression model for better accuracy.

4. Tooling: Simple Unix-like tools are used to help Claude. The tools have been designed to prevent errors and clarify outcomes to avoid wasted processing time.

5. Performance: Claude outperformed another AI model, Codex, in decompilation tasks. The author noted that traditional decompilation usually requires expert teams, but AI models like Claude can accelerate this process significantly.

6. Future of Decompilation: While Claude can handle many functions, the most challenging ones remain. The output from AI may still require human refinement for clarity and clarity in code.

The author encourages others interested in decompilation to engage with the project and explore its challenges.

On December 5, 2025, Cloudflare experienced a network outage from 08:47 to 09:12 UTC, lasting about 25 minutes. Approximately 28% of their HTTP traffic was affected, but the issue was not due to a cyber attack. It arose from changes made to their system while addressing a security vulnerability in React Server Components.

The problem occurred when Cloudflare attempted to increase the buffer size for HTTP requests. An internal testing tool was turned off to accommodate this change, but the way it was done led to errors in the proxy system, resulting in HTTP 500 error codes for affected customers. The issue was quickly identified and resolved.

Cloudflare acknowledged that this outage, following a previous incident on November 18, was unacceptable. They are implementing measures to prevent similar future incidents, including improved rollout processes, enhanced error handling, and better rollback capabilities. They plan to share more details on these efforts soon.

Overall, the incident highlighted weaknesses in Cloudflare's system that they are actively working to fix to ensure better reliability for their customers.

Summary of "Instant Supercompute: Launching Wolfram Compute Services"

On December 2, 2025, Wolfram released Wolfram Compute Services, allowing users to scale up computations in the Wolfram Language easily. Users can submit large calculations using the RemoteBatchSubmit function, which handles all dependencies and executes jobs on the Wolfram Cloud.

Key Features:

1. Scalability: Users can scale computations hundreds of times larger than their local capabilities. The service offers various machine options, from basic to high-performance setups with up to 192 cores and large memory.

2. Parallel Processing: Wolfram Compute Services facilitates large-scale parallelism, allowing users to run jobs simultaneously across many cores. This is especially useful for extensive computations, like testing millions of cellular automaton rules.

3. Ease of Use: Once a job is submitted, users receive notifications via email about the job status and can track progress through a dashboard. Results can be easily integrated back into the Wolfram Notebook environment.

4. Programmability: Users can customize job settings, including machine type and budget constraints. Notifications can be tailored for different job statuses, and results are stored temporarily for retrieval.

5. Future Developments: The service is part of a wider initiative to enhance Wolfram Language capabilities, with plans for synchronous remote computations and support for custom compute facilities.

Overall, Wolfram Compute Services provides an efficient solution for users needing substantial computational power without the hassle of managing hardware.

The author reflects on a quotation by José Saramago: "God is the silence of the universe, and man is the cry that gives meaning to that silence." While searching for this quote online, the author struggled to find it and initially suspected censorship by Google due to Saramago's critical views on religion. However, upon further searching with the full quote, they easily found it. This experience led the author to ponder the nature of information retrieval and Google's secretive methods for managing its data. They compare Google to a public library, expressing concern that, unlike libraries, corporations like Google prioritize profit over public trust and transparency. The author questions whether Google’s leaders fully understand their role and the implications of their practices.

NanoKVM is a low-cost hardware KVM switch created by the Chinese company Sipeed, allowing users to remotely control computers or servers through a web browser. It connects via HDMI and USB-C ports and can be powered by a USB connection to the target computer. It’s compact, open-source, and offers features like BIOS access and remote power management.

However, the device has significant security issues. Initially shipped with default passwords, it has multiple vulnerabilities, such as a lack of session invalidation and hardcoded encryption keys. Additionally, it communicates with Chinese servers and includes hacking tools. Alarmingly, it has a hidden microphone capable of recording audio, which was not disclosed in the product documentation.

Despite these flaws, users can install custom software to improve security. Some have started porting Linux distributions to the device. The situation raises concerns about privacy and security in technology, not just with NanoKVM but potentially with other devices as well.

No summary available.

No summary available.

Summary of Gemini 3 Pro Overview

Gemini 3 Pro is Google's advanced multimodal AI model, excelling in understanding documents, spatial relationships, screens, and videos. It enhances visual reasoning and document processing capabilities, making it suitable for diverse applications such as complex visual analysis and document interpretation.

Key Features:

1. Document Understanding: Gemini 3 Pro can accurately interpret messy, unstructured documents, including handwritten text and complex layouts. It can reverse-engineer visual documents into structured formats like HTML or LaTeX.

2. Spatial Understanding: The model can identify specific locations in images and assist in robotics or augmented reality tasks by generating spatial plans.

3. Screen Understanding: It effectively navigates and automates tasks on desktop and mobile screens, improving user interactions and task automation.

4. Video Understanding: The model processes videos at high speeds, analyzing rapid actions and understanding complex cause-and-effect relationships over time.

Applications:

• Education: Enhances learning with visual problem-solving in math and science.
• Medical Imaging: Excels in interpreting medical images and aiding in complex medical questions.
• Law and Finance: Improves document analysis in finance and law, making it easier to handle complex workflows and legal contracts.

Media Control: Developers can optimize the model's performance by adjusting image resolution settings for different tasks, balancing quality and cost.

Overall, Gemini 3 Pro represents a significant advancement in AI capabilities, providing powerful tools for developers to create innovative applications. For more information, users can explore the developer documentation and experiment with the model in Google AI Studio.

Netflix has announced plans to acquire Warner Bros. Discovery for $82.7 billion, which includes its film and television studios, HBO, and HBO Max. This deal is valued at $27.75 per share and is expected to be finalized after the separation of WBD’s Global Networks division in Q3 2026.

The acquisition aims to combine Netflix's streaming service with Warner Bros.' extensive library of beloved content, enhancing the entertainment options available to consumers. Key franchises such as "Game of Thrones," "Harry Potter," and "The Big Bang Theory" will now be part of Netflix's offerings. Both companies believe this merger will create more opportunities for creators and improve shareholder value by attracting more subscribers and increasing engagement.

Netflix plans to maintain Warner Bros.' current operations and enhance its production capacity, leading to job creation in the entertainment industry. The transaction has been approved by the boards of both companies and will require regulatory approvals and shareholder consent before completion.

The deal includes a mix of cash and Netflix shares for WBD shareholders, with specific terms outlined based on Netflix's stock performance at the time of the transaction.

No summary available.

No summary available.

Summary of Divine D. Rev. 1.1 Hardware Architecture

Divine D. is evolving into a stable, community-driven mobile system with the release of Rev. 1.1, which includes significant improvements over Rev. 1.0. Key updates include:

1. microSD Express: Enhanced storage technology with fast data transfer rates (up to 500 MB/s) and improved system performance.

2. Micro HDMI Output: New HDMI connector supports 8K video resolution at 60Hz, enhancing multimedia capabilities.

3. LoRa Subsystem: Introduces long-range, low-power wireless communication options for various applications, including IoT.

4. New Power Switches: Improved power management with better efficiency and control over power distribution.

5. Haptic Engine: Added vibrations and feedback capabilities for user interface and alerts.

6. Under-Voltage Battery Monitor: Automatically manages battery power to prevent issues when battery voltage is low.

7. Battery Switch: Allows users to disconnect the battery while still powering the system through the charger.

8. New LEDs: Added indicators for system status, charging, battery health, and connectivity.

9. Expanded Accessory Interface: New magnetic pogo interface for connecting various accessories and enhancing experimentation.

10. M.2 B-key GSM and 4G Module: Replacement of the mini-PCIe connector for a smaller and more efficient module.

11. Design Fixes: Improvements based on feedback and testing from Rev. 1.0.

Overall, Rev. 1.1 focuses on enhancing connectivity, power management, and user experience, making it a more robust and flexible open-source hardware platform.

No summary available.

The author shares their experience of exploring the history of Huckleberry House, a refuge for runaway teenagers in San Francisco, inspired by a book called Season of the Witch. Intrigued by the founder's story, they visited the San Francisco Public Library to read letters exchanged between the teens and the founder, Larry Beggs. The letters revealed the struggles of these teens and Beggs's compassionate responses, emphasizing his genuine care without offering unsolicited advice.

The author felt a personal connection to the letters and reflected on the continuity between past and present, noting that both young people of the 1960s and today's youth seek guidance as they pursue their dreams in San Francisco. They highlight the importance of following one’s curiosity and taking time to explore, suggesting that such experiences can inspire and enrich one’s work. Huckleberry House still operates today, supporting at-risk teens, and the author invites donations to both Huckleberry House and their own nonprofit, Nautilus, which helps young innovators.

Summary

Join a team focused on helping engineers improve important systems by building fast and reliable backends for real-time infrastructure insights.

Key Requirements:

• Work in GMT+2 to GMT-6 time zones.
• Strong experience with Node.js and TypeScript, including fixing memory leaks and performance problems.
• Proficient in writing complex PostgreSQL queries and optimizing database performance.
• Quick to address and resolve issues, with a passion for releasing new features.
• Experience building projects from the ground up.
• Preferred: Familiarity with GraphQL and designing efficient schemas.

Recent Challenges:

• Scaled to support thousands of GitHub organizations and repositories, requiring significant changes to APIs and infrastructure.
• Developed a system to automatically fix infrastructure issues, combining AI and static analysis for quality control.
• Created the Issue Explorer to help enterprise customers manage and analyze large volumes of infrastructure issues.

Core Values:

• Customer Focus: Build relationships with users to ensure their success.
• Transparency: Share both successes and challenges to foster trust and better decision-making.
• Action-Oriented: Prioritize executing plans quickly and efficiently while supporting each other.

Benefits:

• Remote work with no commuting.
• Regular company gatherings.
• Employee-friendly equity with a 10-year exercise window.
• 401k matching and health insurance (for US employees).
• 31 days of paid leave per year, plus 12 weeks of paid parental leave.

No summary available.

Frinkiac has almost 3 million images from The Simpsons. Start looking for your favorite scenes now!

Summary of "Idiomatic Rust: Patterns for Defensive Programming in Rust"

Key Concepts:

• Defensive programming in Rust emphasizes writing code that anticipates and prevents errors by leveraging the compiler's capabilities.
• Developers should be wary of comments like "// this should never happen," as they often indicate overlooked edge cases.

Common Code Smells and Patterns:

1. Indexing Into a Vector: Instead of checking if a vector is empty and then accessing an element, use pattern matching. This ensures all cases are handled by the compiler.

2. Lazy Use of Default: Avoid using ..Default::default() when initializing structs, as it can lead to unnoticed defaults. Instead, explicitly set all fields to ensure clarity and compiler checks.

3. Fragile Trait Implementations: Use destructuring in trait implementations (e.g., PartialEq) to ensure that any new fields added will require updates to handle equality checks correctly.

4. Use TryFrom for Fallible Conversions: Instead of using From for conversions that might fail, use TryFrom to make the failure explicit.

5. Non-Exhaustive Matches: Always list all match arms explicitly to avoid missing new cases. This helps ensure that the compiler will remind you to handle any new variants.

6. Temporary Mutability: Use temporary variables to limit mutability only to where it's necessary, preventing unintended modifications later.

7. Defensive Constructors: Make struct construction go through a constructor that enforces validation by using private fields or the #[non_exhaustive] attribute to prevent direct instantiation.

8. Use of #[must_use]: Annotate important return types with #[must_use] to ensure that users of your API do not ignore significant results.

9. Avoid Boolean Parameters: Replace boolean parameters with enums or a parameter struct to improve code readability and prevent errors.

Clippy Lints: Use Clippy lints to automatically enforce these defensive programming patterns, helping to catch potential issues early.

Conclusion: By applying these patterns, developers can create more robust and maintainable Rust code that reduces bugs and handles future changes gracefully. The goal is to use Rust’s type system and compiler features to prevent errors before they occur.

The article discusses a concept called "shredding" in software engineering, which involves rewriting code in a more effective way by taking it apart and rebuilding it. This approach is different from typical refactoring, as it often includes deleting multiple components at once and starting fresh instead of making small changes.

At Zed, the author observes that shredding is a common practice among the team, allowing them to improve the codebase significantly. They emphasize the importance of confidence and experience when deciding to shred code, as it requires the ability to recognize when a complete overhaul is necessary.

The author notes that despite regular shredding, the codebase remains stable, possibly due to the team's expertise and careful planning. Shredding helps eliminate unnecessary parts of the code and encourages continual improvement, akin to a snake shedding its skin to renew itself. The article concludes by encouraging readers who appreciate this approach to subscribe for more insights.

No summary available.

No summary available.

Multithreading.js Summary

Multithreading.js is a TypeScript library that introduces advanced concurrency features to JavaScript, inspired by Rust. It simplifies the use of Web Workers for multi-threaded programming, managing complexities like memory safety and synchronization.

Key Features:

• Thread Pool: Automatically manages a pool of threads based on the system's capabilities.
• Shared Memory: Safely shares data between threads using tools like Mutexes and Read-Write Locks.
• Scoped Imports: Easily import modules in worker tasks without complex path issues.
• Move Semantics: Transfers data ownership to reduce cloning overhead.

Installation: Use npm install multithreading.

Core Concepts:

1. Spawn Function: The main way to run tasks in background threads.
2. Data Transfer: Use move() to send data to workers; it can either transfer objects or clone them.
3. SharedJsonBuffer: Allows shared memory for JSON objects with efficient updates.

Synchronization Primitives:

• Mutex: Ensures exclusive access to resources.
• RwLock: Allows multiple readers but only one writer.
• Semaphore: Controls the number of threads accessing a resource.
• Condvar: Lets threads wait for a specific condition before proceeding.

Channels: Supports multi-producer, multi-consumer communication between threads, allowing for efficient data handling without manual locks.

Module Importing: Easily load modules in workers with dynamic imports.

Browser Compatibility: Works in modern browsers, but certain features require specific security headers for shared memory.

CSP Requirements: Adjust Content Security Policy headers for proper functionality in secure environments.

This library streamlines multi-threading in JavaScript, making it easier for developers to write efficient, concurrent code.

The text discusses immigration topics and emphasizes that the speaker cannot give legal advice on specific cases due to liability concerns. They encourage factual discussions in questions and answers. A link to previous discussions is also provided.

The article discusses recent findings about adenosine signaling as a key mechanism behind rapid-acting antidepressant treatments like ketamine, electroconvulsive therapy (ECT), and acute intermittent hypoxia (aIH). Researchers found that these treatments increase adenosine levels in the brain, specifically in mood-regulatory areas.

• Key Findings:

  • Ketamine works mainly by changing how energy is used in brain cells rather than blocking specific receptors.
  • All three treatments activate adenosine receptors (A1 and A2A), leading to beneficial changes in brain function that result in quick relief from depression symptoms.

• Impact of Caffeine:

  • The article raises questions about caffeine's role in depression treatment. Regular coffee consumption might help prevent depression (protective effect), while drinking coffee right before treatment could potentially disrupt the effectiveness of rapid antidepressants.

In summary, the research highlights the importance of adenosine in treating depression and suggests that caffeine's effects may vary depending on how it is consumed.

No summary available.

No summary available.

The author created a mobile app using Expo (React Native) for a neobank that serves over 6,500 nonprofit organizations and handles $6 million per month. While being a full-time student, they faced challenges getting permission from Apple and Google for advanced features like Tap to Pay and Push Provisioning. This process involved many emails, tests, and compliance checks.

After receiving permission, they found that any small fixes required a new app build, which was time-consuming. To solve this, they used Expo’s EAS update service for "over the air updates," allowing remote updates without new builds.

The author spent 250 hours building the app, which was a valuable learning experience. They welcome feedback on the app and mention that it was open-sourced on GitHub in March.

Tides are influenced by the Moon's and Sun's gravity, which creates high and low tides in the oceans. The Moon's gravity pulls on the Earth, causing water to bulge out on the sides closest and farthest from it, leading to high and low tides approximately every 12 hours. The Sun also affects tides; when the Sun, Moon, and Earth align, we experience higher high tides (called Spring Tides) and lower low tides. Conversely, when they are at right angles, we have lower high tides (Neap Tides).

The Earth's tilt and the presence of land also complicate tidal patterns. Different locations experience varying tidal schedules and heights due to the shape and depth of the coastline. Historically, predicting tides was complex and labor-intensive, requiring machines developed in the 1800s that automated calculations. Today, computers have replaced these machines, making tidal predictions much easier.

Despite advancements, the study of tides is still complex, with many factors influencing the final tidal behavior at any specific location.

Guide to Making a CHIP-8 Emulator Summary

This guide provides a clear roadmap for developing a CHIP-8 emulator, a common beginner project for those interested in emulator development. It emphasizes the following key points:

1. Understanding CHIP-8: CHIP-8 is not hardware but an interpreter for running programs on various computers. It was created in 1977 to simplify programming for early microcomputers. Over time, it has seen various implementations and specifications.

2. Prerequisites: Familiarity with programming and knowledge of binary and hexadecimal systems are essential. You’ll also need a way to handle graphics and input, often through graphical libraries like SDL.

3. Technical Specifications:

   • Memory: 4 KB RAM
   • Display: 64x32 pixels (or 128x64 for SUPER-CHIP)
   • Registers: 16 general-purpose 8-bit registers (V0 to VF), an index register (I), and a program counter (PC).
   • Timers: Two 8-bit timers (delay and sound).

4. Core Components:

   • Fetch/Decode/Execute Loop: The emulator continuously fetches instructions from memory, decodes them, and executes them.
   • Instructions: There are various instructions for operations such as jumps, arithmetic, and graphics rendering.

5. Building the Emulator: The guide suggests starting with simple instructions (like clearing the screen) and gradually implementing more complex ones. Testing with known programs (like the IBM logo) is encouraged to verify functionality.

6. Troubleshooting: Debugging capabilities are crucial. The guide recommends adding features to step through instructions and view register contents to identify issues.

7. Next Steps: Once the emulator is complete, users can create their own CHIP-8 games, add support for extensions like SUPER-CHIP and XO-CHIP, or develop emulators for other systems.

This guide is designed to help users build their own CHIP-8 emulator while providing historical context and technical details necessary for implementation.

Summary:

The article discusses Greg Kuperberg, a teenager who developed three notable arcade games for the IBM-PC in the early 1980s. His first game, "PC-Man," was a well-received clone of Pac-Man that stood out for its quality and gameplay compared to other PC games of the time. Kuperberg was just 15 when he created these games while working for Orion Software, a company founded by Kevin Azzouz.

The text reflects on the nostalgia of early computer gaming and questions whether today’s youth still experience the same excitement for technology. Kuperberg attributes his interest in programming to his mathematician parents and early exposure to computing at a university. After his brief gaming career, he pursued mathematics, earning a PhD and becoming a professor. Kuperberg believes that programming languages like Python may ignite similar sparks of interest in today's youth as BASIC did for him.

Overall, the article captures Kuperberg's journey from a young game developer to a respected mathematician while exploring the impact of early video games on his life and the potential for inspiration in the current technological landscape.

Summary of Perpetual Futures

Perpetual futures, often called "perps," are a unique financial instrument popular in the cryptocurrency market. They allow traders to bet on the price of assets like Bitcoin without a fixed expiration date, unlike traditional futures contracts. This flexibility has made perps a dominant trading method in crypto, with their volume often far exceeding that of spot trading.

The appeal of perps lies in their ability to provide high-risk trading opportunities while reducing the capital needed for exchanges and market makers. However, this structure resembles a casino, where participants can win or lose money based on price fluctuations, with exchanges needing to maintain trust by holding enough assets to cover potential payouts.

A significant feature of perps is their multiple daily settlement system, where gains and losses are adjusted every few hours through a mechanism called the funding rate. This system can lead to situations where traders use high leverage (up to 100x), which can amplify both gains and losses.

The concept of "automatic deleveraging" (ADL) is crucial in the perp market. If market conditions lead to insufficient funds to cover losses, some profitable traders may find their positions forcibly reduced, leading to unexpected outcomes. This contrasts with traditional finance, where more structured risk management practices exist.

Despite their popularity in crypto, traditional finance is unlikely to adopt perps significantly because existing derivatives already serve their purpose effectively and the risks associated with such leveraged trading are less acceptable in conventional markets. Overall, while perps offer exciting trading possibilities, they carry high risks due to their speculative nature and the complexities involved in their operation.

Summary: Making RSS More Fun

The author expresses a dislike for traditional RSS readers, finding them overwhelming and tedious. They prefer a user experience similar to TikTok, where content is presented based on personal interests without the pressure of unread items. The goal is to create a simple platform where users can discover and enjoy content from small websites, upvote their favorites, and share them with others, without ads or extensive data collection.

The proposed service allows users to submit and rate websites, with a system that highlights popular content based on community feedback. The backend uses FastAPI and SQLite to manage data and track user interactions. The author emphasizes that this project is a personal hobby and not a commercial venture.

The current setup has over 600,000 pages indexed, but the author acknowledges some challenges, such as creating a user-friendly login process and managing keyboard shortcuts. They are open to feedback and plan to improve the service by categorizing content and enhancing user experience. The author encourages others to try the service and provide input.

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No summary available.

The article discusses creating the Fizz Buzz sequence using CSS, with the goal of achieving this in the fewest lines possible. The challenge is that all output must come from the CSS itself, without using HTML text or JavaScript. The author proposes a solution that requires four lines of CSS code.

Here’s the CSS used:

1. li { counter-increment: n }
2. li:not(:nth-child(5n))::before { content: counter(n) }
3. li:nth-child(3n)::before { content: "Fizz" }
4. li:nth-child(5n)::after { content: "Buzz" }

The article notes that while some may try to use an ordered list to simplify the task, this approach violates the rule of generating all integers directly from the stylesheet. The author also mentions that while the focus is on minimizing lines, one could also aim to reduce the number of bytes used in the code, with the minified version of the CSS being 152 bytes. Further optimizations are suggested as exercises for readers.

Summary of Albert Michelson’s Harmonic Analyzer

This document discusses Albert Michelson's Harmonic Analyzer, a machine he created in the late 1800s to perform Fourier analysis. The analyzer can both add sine and cosine waves (Fourier synthesis) and break down complex functions into simpler sinusoidal components (Fourier analysis).

Key points include:

• Purpose: Michelson designed the analyzer to simplify the labor-intensive process of performing Fourier analysis manually, which he found challenging when analyzing light frequencies from flames.
• Design: The machine uses gears, springs, and levers to generate and combine sinusoidal waves. It can create a variety of wave patterns, not just simple sine or cosine waves.
• Historical Context: The harmonic analyzer was inspired by earlier models but improved by replacing ropes with springs to enhance accuracy and functionality.
• Legacy: While Michelson envisioned a more complex version with 1000 elements, it was never built. However, the principles of his analyzer are now embedded in modern technology, like computers and mobile devices used for signal processing and image manipulation.

The document also invites readers to watch a related video series on the EngineerGuy YouTube channel for a visual exploration of the machine's operation.

Researchers at the University of British Columbia Okanagan have mathematically proven that our universe cannot be a simulation. Using Gödel's incompleteness theorem, they showed that reality requires an understanding that goes beyond any algorithm or computation. This challenges the popular idea that we might be living in a simulated reality, as it demonstrates that the universe's fundamental nature cannot be fully captured by computational methods.

Dr. Mir Faizal and his team found that while physics has evolved from classical views to quantum mechanics, there is a deeper level of reality, described as a "Platonic realm," from which space and time emerge. However, even this informational structure cannot be completely understood through computation alone.

Their findings indicate that some truths in reality, known as "Gödelian truths," cannot be proven by any logical sequence that a computer might follow. This means that a complete understanding of physical reality requires a type of comprehension that is non-algorithmic and cannot be simulated.

In conclusion, the researchers argue that since the fundamental aspects of reality cannot be simulated, the universe itself cannot be a simulation, providing a definitive answer to a longstanding philosophical question.

Summary of "Most Technical Problems Are Really People Problems"

In the blog post by Joe Schrag, he discusses his experiences with technical debt at a previous company, where outdated code and a lack of unit tests created significant challenges. He highlights a specific project where a large amount of code was duplicated to run on a different platform, leading to the creation of two separate codebases that would diverge over time.

Schrag emphasizes that many technical problems stem from issues related to people, such as unclear requirements, unrealistic deadlines, and resistance to change among developers. He learned that trying to fix these problems with technical solutions alone often fails because the underlying issues involve company culture and individual mindsets.

He argues that effective communication about technical debt and its importance is crucial for management, especially for those without an engineering background. Schrag concludes that successful engineers should not only be technically skilled but also adept at navigating interpersonal dynamics and project risks to drive initiatives forward.

Kraa is a new web-based markdown editor created by a team of three. It aims to offer a minimal and distraction-free writing experience while still being feature-rich. Key features include:

• A simple interface for focused writing and reading.
• Easy sharing of text via links with options for 'read' or 'edit' access, including password protection.
• Real-time editing and chat capabilities without the need for a send button.
• Mobile-friendly, with plans for dedicated apps in the future.

You can try live demo examples without needing an account. Feedback is welcome!

Summary of Nimony Design Principles

Nimony is a new compiler for a version of the Nim programming language, eventually leading to Nim 3.0. It aims to be efficient for hard real-time and embedded systems, focusing on memory safety and predictable execution times.

Key Features:

1. Memory Management: Nimony uses automatic memory management (MM) similar to Nim 2.0, Rust, and C++. It simplifies memory handling while maintaining safety, with a focus on scope-based MM.

2. Error Handling: Unlike modern languages that avoid exceptions, Nimony retains traditional exception handling but requires routines that can raise exceptions to be annotated. Additionally, it introduces a type-safe ErrorCode enum for better error management across libraries.

3. Out of Memory (OOM) Handling: Nimony treats OOM situations as errors rather than crashes, allowing programs to continue running. It features an overridable handler that can manage OOM situations gracefully.

4. Generics and Static Typing: Nimony improves on Nim's generics with complete type checking, allowing for better error messages and IDE support. Generics are essential for creating custom containers.

5. Concurrency and Parallelism: Nimony simplifies asynchronous and multi-threaded programming with a unified construct called spawn. It uses a continuation-based model for concurrency, while parallelism is easier to implement.

6. Meta Programming: Nimony allows for advanced meta-programming through compiler plugins, enabling custom behaviors without modifying the core language.

Conclusion:

Nimony is an ambitious evolution of Nim, incorporating practical experiences and innovative approaches to error handling and meta-programming. The project is ongoing, with a planned release in autumn 2025. Contributions and support are welcomed as the team continues to develop and refine the language.

Summary: DNS over TLS with LetsEncrypt

LetsEncrypt recently announced the ability to issue certificates for IP addresses, but it's still in testing. You can request to join the testing list, but it's not fully available yet.

To use LetsEncrypt, you need an ACME client, with the popular one being Certbot. However, it doesn't yet support IP addresses. Another client called Lego does support this feature and allows you to request certificates using a method that proves ownership of the IP address.

To set up a DNS server using these certificates, you configure the Bind9 DNS server on a Debian-based system. You create a configuration file to load the TLS certificate and key, and specify the listener settings for DNS over TLS on port 853.

Certificates from LetsEncrypt for IP addresses have a short lifespan of about 7 days, so you need to automate the renewal process. You can do this with a command in a script and set up a systemd timer to run the script daily.

Finally, you can test your DNS over TLS setup using the dig tool to ensure everything is working correctly.

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Summary: Stacked Diffs with git rebase --onto

Overview: Using git rebase --onto helps you cleanly rebase dependent branches (stacked diffs) without bringing in unnecessary commits.

Key Points:

1. What are Stacked Diffs?

   • Stacked diffs involve breaking down large features into smaller, related pull requests (PRs), making them easier to review.
   • Example structure:
     • main └── feature-1 └── feature-2 └── feature-3
   • The challenge is syncing these branches when the main branch updates.

2. Regular Rebase vs. Rebase --onto:

   • A regular rebase moves commits from one branch to another but can cause issues with stacked branches, leading to duplicate or conflicting commits.
   • git rebase --onto allows you to specify exactly which commits to move and where, preventing problems with outdated commits in dependent branches.

3. Step-by-Step Usage:

   • Create a marker branch for tracking the state of a parent branch.
   • When the main branch updates:
     1. Rebase the first feature branch onto main.
     2. Use git rebase --onto to sync the dependent branch.
     3. Update the marker branch after each sync.

4. Post-Merge Cleanup:

   • After merging the first feature into main, you can clean up the history of dependent branches by removing the commits from the merged feature.

5. Final Thoughts:

   • While using git rebase --onto may seem complex at first, it simplifies managing multiple related branches in the long run.
   • Remember to keep your marker branches updated and expect to use force pushes frequently.

This approach leads to smaller, focused PRs, quicker reviews, and a cleaner commit history, making it worthwhile despite the initial learning curve.

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The text appears to be a snippet from a GitHub repository named "norvig/pytudes." Here are the key points:

• The repository has a significant number of stars (24.1k) and forks (2.5k), indicating it is popular.
• There are various directories and files, primarily in Jupyter Notebook format (.ipynb), related to different projects and topics, including Advent challenges from different years (2016-2025), algorithms, and coding exercises.
• Users can manage notifications, view issues, and make pull requests, although there is a note about an error loading the page.
• The repository contains a diverse range of content such as images and markdown files, emphasizing a focus on coding and computational challenges.

Overall, it's a collection of coding exercises and projects aimed at learning and practicing programming concepts.

Prophit is an AI-powered search engine designed for stock investing. It helps users identify trends and pick winning companies before they become widely known. The platform encourages individuals to trust their instincts and observations rather than relying solely on Wall Street experts. Prophit allows users to capitalize on their unique insights and turn them into investment opportunities. With Prophit, you can discover potential winners, compete with friends, and build your portfolio based on your own knowledge and taste.

The AI Trade Arena was created by Kam and Josh to test how well large language models (LLMs) like GPT-5 and Claude can trade stocks. They each received $100,000 in a simulated trading environment for eight months to see how much profit they could generate. The trading was based on real stock prices, with the LLMs given access to historical market data and news as if they were trading in the past.

The experiment aimed to understand how these AI models analyze information and make trading decisions, while ensuring that they couldn't rely on future knowledge. Although the results are not statistically significant yet, they provide insight into the models' performance and decision-making processes.

Grok performed the best in trading, while Gemini struggled due to a non-tech-heavy portfolio. The researchers plan to conduct more experiments, including live trading, to further evaluate the models' capabilities and improve their trading strategies.

The ultimate goal is to gain a better understanding of how these AI models operate in financial markets, distinguishing between skill and luck in their trading decisions. The project emphasizes transparency in the decision-making process, allowing for better analysis of how different factors affect trading outcomes. An interactive demo is available for users to explore the results and trade strategies.

In November, the price of a 32GB DDR5 RAM kit surged by 156% within three weeks, leading to concerns about a potential RAM shortage. This situation arose due to three main events:

1. OpenAI's Major Deals: OpenAI unexpectedly signed two large contracts with Samsung and SK Hynix, securing 40% of the world’s DRAM supply. This caught the industry off guard, as competitors were unprepared for such significant moves.

2. Panic Buying: The sudden news led to panic among tech companies and competitors, resulting in aggressive buying to secure remaining RAM supplies. Many were worried about possible future shortages without warnings from their suppliers.

3. Lack of Safety Stock: The DRAM market had little safety stock available due to previous tariff uncertainties, falling prices over the summer, and stalled manufacturing equipment. This made the market particularly vulnerable to sudden supply disruptions.

Additionally, OpenAI's deals were not for finished RAM but for raw wafers, suggesting their strategy may include stockpiling to limit competitors’ access. This situation is expected to affect various hardware products, with RAM itself already facing a price explosion, and other products like SSDs and GPUs likely to follow suit.

The article concludes with a warning for consumers and businesses about which products to buy soon to avoid the effects of this RAM shortage, indicating that the issues might last for at least six to nine months.

CachyOS has exciting news: Framework, a company known for its modular laptops, is now sponsoring them. They provided a Framework Laptop 16 to help optimize CachyOS for modern hardware and are donating $250 monthly. This support makes up about 10% of CachyOS's total monthly donations, helping to stabilize their operations and move towards full-time development. The community is encouraged to check out Framework's blog for more details on their sponsorships. Thanks to Framework and the CachyOS community for their support!

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The text discusses the size of large language models (LLMs), which can have billions of parameters. While larger models are necessary for tasks like chat applications that require understanding and generating human-like responses, not all applications need such complexity. For example, specific tasks like SQL autocomplete or structured data extraction do not require such large models, as they have limited input and predictable outputs.

The author highlights that running these large models can be expensive, both in terms of computing power and infrastructure. They suggest that the future may involve smaller, task-specific models that are easier and cheaper to deploy. There are already tools available to create and run these smaller models, and the author is hopeful about a future where models with around 15 million parameters could be sufficient for many tasks.

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Summary: Why We Built Lightpanda in Zig

Francis Bouvier, the cofounder of Lightpanda, chose the Zig programming language to build a web browser due to its simplicity and modern features, which he found more manageable than C++ or Rust. The project aims to offer developers a faster and more reliable way to automate web tasks.

Key Points:

1. Choice of Language: Zig was selected for its performance, simplicity, and modern tooling. It provides a good balance compared to C++ and Rust, which are more complex.

2. Performance Needs: Building a browser requires high performance and control over memory, which Zig supports well with explicit memory allocators.

3. Integration with JavaScript: Lightpanda uses the V8 JavaScript engine. Zig’s excellent C interoperability allows it to interact with V8, which is crucial for rendering dynamic web content.

4. Avoiding C++ Complexity: C++ was considered but dismissed due to its complexity and memory management issues. Zig’s straightforward approach to memory management is preferred.

5. Rust Limitations: Although Rust offers safety and good tooling, it introduces complexity with its ownership model, making it less suitable for Lightpanda’s needs.

6. Benefits of Zig:

   • Explicit Memory Management: Zig's allocator model allows precise control over memory usage.
   • Compile-Time Features: Zig can automate repetitive code generation, making development easier.
   • Easy C Interoperability: Directly importing C libraries simplifies integration.

7. Build System: Zig has a simple build system that eases the management of dependencies and compilation processes.

8. Fast Compilation: Zig compiles quickly, enhancing the development feedback loop.

9. Community and Learning: The Zig community is small but supportive, making it easier for newcomers to learn the language.

In conclusion, Zig has enabled the successful development of Lightpanda by offering a clear, efficient, and manageable programming environment. For those interested in learning more about Zig, the official documentation and community resources provide helpful guidance.

The author created a simple pastebin tool called pbnj, designed for ease of use and quick deployment. Key features include:

• A clean interface with syntax highlighting for over 100 programming languages.
• Easy deployment to Cloudflare with a free tier for around 100,000 pastes.
• A command-line interface (CLI) that allows users to quickly get a shareable URL.
• Memorable URLs for pastes, like "crunchy-peanut-butter-sandwich."
• Options for private pastes with secret keys and a web interface for non-terminal use.

However, pbnj is not intended to replace services like Gist. It doesn't support accounts, multi-user functionality, or features like expiring pastes or comments. It’s aimed at users who prefer self-hosting and want control over their data.

For more information, you can try the live demo or check it out on GitHub. The author welcomes feedback and questions.

The author expresses a surprising attachment to LinkedIn, likening it to a reliable but clumsy social network amidst the chaos of others. However, they are concerned about the prevalence of people using language models (LLMs) to create content on the platform. The writing generated by LLMs often lacks authenticity and can be off-putting, leading readers to question the realness of the content and the writer's voice.

The author appreciates LLMs for tasks like brainstorming and editing but emphasizes that they are not effective writers and cannot replace individual voices. They urge users to have confidence in their own writing and to create original content to ensure their messages are genuine and engaging.

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A significant research article from 2000, which claimed that the herbicide glyphosate was safe, has been retracted due to serious issues that affect its credibility. The journal Regulatory Toxicology and Pharmacology announced this decision on November 28, 2023, 25 years after the article's publication. The retraction followed the release of internal documents from Monsanto that revealed the article was ghostwritten by company employees, not the scientists listed as authors. Ghostwriting, where companies pay researchers to lend their names to studies they did not write, is considered a form of scientific fraud. This practice aims to make studies appear more credible.

Summary of the Debug Adapter Protocol as a REPL

The Debug Adapter Protocol (DAP) is primarily designed for debugging tools, but it can also effectively serve as a REPL (Read-Eval-Print Loop) interface for programming languages, as demonstrated by the creation of nluarepl, a REPL for Neovim's Lua interpreter.

Key points include:

• REPL Functionality: A typical REPL allows users to enter expressions, which are evaluated, and results or errors are returned. DAP includes an evaluate command for this purpose, enabling expression evaluation.
• Response Format: The response to an evaluation includes a result string, an optional type, and a variablesReference for accessing structured data, which allows users to explore complex data more easily.
• Variable Handling: Variables in DAP are structured and can be deeply nested, sharing characteristics with the initial evaluation results.
• Additional Features: DAP supports command completion and finding variable definitions, enhancing the REPL experience.
• Implementation Details: While using DAP for a REPL simplifies certain tasks, it also requires implementing some aspects that may not be necessary for a basic REPL, like RPC mechanisms and breakpoint handling.
• Developer Motivation: The author chose DAP to avoid creating a new REPL interface from scratch, allowing reuse of familiar UI elements and configurations from existing tools.

Overall, DAP offers a robust framework for building REPL interfaces, combining debugging capabilities with interactive language evaluation.

The author has created a simple chess learning app for their 7-year-old daughter. It includes puzzles and a fun game called "radioactive pooping knights," inspired by an Irish chess website. In this game, two knights move around the board leaving "poo" behind, and players must avoid stepping on it. The app is best enjoyed with sound on, though this is subjective. Additionally, any donations made to support the app will go to the author's daughter, who is close to reaching the payout threshold of $10.

Synadia and TigerBeetle Donate $512,000 to Zig Software Foundation

On October 25, 2025, Synadia and TigerBeetle announced a joint pledge of $512,000 to the Zig Software Foundation over the next two years. This funding aims to support the development of the Zig programming language and its community.

Why Choose Zig?

• Joran Dirk Greef, the founder of TigerBeetle, chose Zig for its design and safety features, which are suitable for developing safe and efficient software.
• Zig's memory management simplifies coding by centralizing resource allocation, avoiding complex features like Rust's borrow checker.
• Unlike Rust, which can crash when out of memory, Zig allows for explicit memory allocation, which is crucial for safety-critical applications like TigerBeetle.

Zig's Advantages

• Zig offers a philosophy of no hidden allocations or control flows, making it easier for developers to understand and use.
• It provides features like checked arithmetic, which helps prevent bugs, and has a straightforward, minimalistic design.
• The language's simplicity allows programmers from various backgrounds to learn it quickly.

Progress and Success

• Since its launch, TigerBeetle has successfully processed transactions and is being adopted by major financial institutions.
• The Zig language has matured, leading to improvements in performance and productivity.

Pledge Details

• The donation will be made in monthly installments, with each company contributing $256,000.
• The goal is to support the ongoing development of Zig without seeking special privileges or influence over its governance.

Community Call to Action

• The announcement encourages others, especially tech leaders, to contribute to the Zig Software Foundation to help foster its growth and sustainability.

Overall, the investment reflects confidence in Zig's future and its potential to shape systems software development.

Summary of Stardust

Stardust is a unikernel operating system designed to run cloud applications securely in a simple environment. It uses a hypervisor, which manages the physical resources and is considered trustworthy. Stardust has a small code base that is easy to maintain. It combines a minimal kernel with a single application and the necessary libraries into one executable binary, creating a fixed virtual machine image.

Key features of Stardust include support for multiple cores, preemptive threads, basic block and networking drivers, and standard POSIX-compatible libraries. It is currently used for teaching and research at the University of St Andrews.

Projects Related to Stardust:

• Stardust: Unikernel implementation in C.
• Stardust-oxide: Re-implementation in Rust.
• Duster: A small debugger for para-virtualized unikernels on the Xen hypervisor.

Talks on Stardust: Several talks and presentations have been made about Stardust at various workshops and conferences, covering topics like debugging unikernels and their support for lightweight microservices.

Notable Material: There are published materials and dissertations related to Stardust and its applications in unikernel technology.

Summary of Spectral Rendering vs. RGB Rendering

This blog post explores the differences between RGB rendering and spectral rendering, particularly focusing on their effectiveness in accurately representing light and colors.

1. Rendering Methods:

   • RGB Rendering: Uses simple color mixing with red, green, and blue components to display colors. It does not accurately represent the physical properties of light.
   • Spectral Rendering: Utilizes detailed light and reflectance spectra for more accurate color representation. This method considers the full range of wavelengths in light.

2. Illuminant Types:

   • The post compares results using various light sources, such as illuminant E (constant spectrum) and D65 (white light).
   • Results show that RGB and spectral renderings yield similar outcomes for constant spectra, but differences emerge with more complex light sources (like LEDs and incandescent bulbs).

3. Effects of Different Light Sources:

   • LEDs: Minor differences in color rendering.
   • Incandescent Bulbs: RGB rendering can lead to overly saturated colors, while spectral rendering provides more realistic color shifts.
   • Fluorescent and Metal Halide Lamps: More pronounced differences, as spectral rendering can alter color saturation significantly.

4. Monochromatic Light:

   • When using nearly monochromatic light (e.g., sodium lamps), spectral rendering shows drastic differences since it retains the color characteristics more faithfully than RGB rendering.

5. Challenges with RGB:

   • RGB rendering simplifies color representation and can result in "out of gamut" colors that are not accurately displayed. Spectral rendering better manages these situations by modeling light transport realistically.

6. Conclusion:

   • While RGB rendering is widely used, it does not align with physical light behavior. Spectral rendering offers a more accurate method for color reproduction, crucial for realistic lighting design and blending rendered images with real footage. The post advocates for the adoption of spectral rendering techniques in both production and real-time rendering environments.

Overall, spectral rendering is presented as a more scientifically grounded approach, providing better color accuracy and greater versatility in handling different light sources.

The article discusses a surprising trend at elite universities like Stanford, where 38% of students claim to have disabilities, primarily mental health conditions and learning disabilities such as anxiety and ADHD. This raises concerns about the legitimacy of these claims, as many believe that students who struggle academically are more likely to attend community colleges rather than prestigious institutions.

Professors suggest that many of these students are affluent individuals seeking accommodations to avoid poor grades rather than genuinely disabled individuals. The Americans with Disabilities Act allows for broad accommodations with minimal documentation, leading some students to view mental health issues as part of their identity.

The rise in disability claims may stem from how conditions are portrayed online, which can distort perceptions of what is "normal." Influencers on platforms like TikTok often label minor struggles as signs of disability, contributing to a culture of risk aversion among students. This fear of failure leads many to seek diagnoses for struggles that were once considered typical.

Overall, the article argues that these accommodations can hinder genuine intellectual growth, as they allow students to avoid facing challenges that are essential for personal development.

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Summary of CUDA-L2: Enhancing Matrix Multiplication with Reinforcement Learning

CUDA-L2 is a new system that uses large language models and reinforcement learning to improve the performance of Half-precision General Matrix Multiply (HGEMM) CUDA kernels. It outperforms existing matrix multiplication libraries, including torch.matmul and NVIDIA's cuBLAS, across various configurations on the A100 GPU.

Key Updates:

• As of December 2, 2025, optimized HGEMM kernels for 1,000 configurations have been released.
• Future plans include supporting 32-bit accumulators, denser matrix configurations, additional GPU architectures, and easier deployment for open-source LLMs.

Frequently Asked Questions:

• Compatibility: A100 kernels are best used on A100 GPUs for optimal speed. They may work on other machines but without guaranteed performance.
• Configuration Support: Users can find the nearest larger configuration or request specific dimensions on GitHub.

Installation Guide:

1. Requirements: Ensure you have Python and PyTorch (version 2.6.0 or higher).
2. Clone CUTLASS: Download NVIDIA CUTLASS version v4.2.1.
3. Set Environment Variables: Configure the CUTLASS_DIR and TORCH_CUDA_ARCH_LIST for your setup.

Usage Instructions:

• To evaluate performance, use the provided eval_one_file.sh script with specified parameters for matrix size, warm-up time, and mode (offline or server).

For any inquiries, users can reach out via GitHub issues or contact [email protected].

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Ghostty is now a non-profit project sponsored by Hack Club, a recognized 501(c)(3) organization. This arrangement allows Ghostty to operate tax-exempt while Hack Club handles compliance and financial oversight.

The non-profit status ensures that Ghostty remains free and open source, and it protects the project from being misused or sold for profit. The goal is to create a sustainable future for Ghostty that isn't reliant on a single person's involvement.

From a technical standpoint, Ghostty's goals and licensing will remain unchanged. However, it can now accept tax-deductible donations, which will help fund the project, compensate contributors, and cover operational costs. All financial transactions will be transparent, and the project will maintain its commitment to public benefit.

Hack Club will receive 7% of donations to support its services and mission. Additionally, a personal donation of $150,000 will be made to Hack Club to further enhance their work.

The project encourages community support through donations, assuring contributors that their funds will be used for public-benefit goals. Overall, this transition aims to establish Ghostty as a trusted open-source infrastructure project.

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Tacopy: Tail-Call Optimization for Python

Tacopy is a Python library designed to optimize tail-recursive functions by converting them into iterative loops. This helps prevent stack overflow errors, even with deep recursion.

Key Features:

• Automatic Tail-Call Optimization: Converts tail-recursive functions into loops for better performance.
• Stack Overflow Prevention: Handles deep recursion without exceeding Python's recursion limits.
• Performance Improvement: Functions can run 1.41x to 2.88x faster than standard recursion.
• Validation: Checks if functions are tail-recursive before optimization.
• No Runtime Overhead: The optimization occurs at decoration time.
• Function Metadata Preservation: Maintains docstrings and type hints during optimization.

Installation:

• Recommended: Install using uv with uv add tacopy-optimization.
• Alternatively, use pip install tacopy-optimization.

Quick Start Example: You can use Tacopy to optimize recursive functions. For instance, the factorial function can be defined as:

from tacopy import tacopy

@tacopy
def factorial_mod_k(acc: int, n: int, k: int) -> int:
    if n == 0:
        return acc % k
    return factorial_mod_k(acc * n % k, n - 1, k)

This allows calculating large factorials without stack overflow.

How It Works: Tacopy transforms the function's code into an iterative version using an Abstract Syntax Tree (AST). It replaces recursive calls with loop constructs.

Requirements for Tail Recursion:

• The function must be at the module level.
• All recursive calls must be in tail position, meaning they are the last operation in the function.
• Async functions are not supported.

Limitations:

• Tacopy only works with module-level functions and does not support async functions or mutual recursion.
• Requires Python 3.10 or higher.

Development and Testing: Developers can clone the repository, install dependencies, and run tests. Contributions are welcome, and the project is licensed under the GNU General Public License v3.0.

Overall, Tacopy is a useful tool for Python developers looking to enhance the performance and reliability of recursive functions.

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The letter addresses Oracle's ownership of the JavaScript trademark, arguing that it has been abandoned and should be released into the public domain. JavaScript is the most popular programming language, widely used by developers, but many are unaware that Oracle controls the trademark. The letter points out that Oracle has never actively used the trademark for any product, and its continued ownership causes confusion in the developer community.

The author explains that trademark abandonment occurs when a mark is not used or becomes generic. Both conditions apply to JavaScript, as Oracle has not provided a product under this name and has allowed it to become a generic term. They call for the USPTO to recognize JavaScript as a generic name and urge Oracle to voluntarily release the trademark.

The letter encourages readers to support the cause by signing an open letter and offers avenues for legal assistance in challenging Oracle's trademark ownership. In summary, the authors seek to clarify the status of the JavaScript trademark and advocate for its release into the public domain.

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In Berlin, a new amendment to the Police Act allows police to secretly enter homes to install surveillance software, known as state trojans, on suspects' devices. This change, supported by the ruling coalition and some opposition parties, has sparked significant criticism for violating privacy rights.

Key points of the amendment include:

1. Secret Home Entry: Police can physically enter a suspect's home if they cannot remotely install spyware to monitor encrypted communications.

2. Expanded Surveillance: The law increases police powers to use body cameras in private spaces and to conduct extensive mobile phone data searches, potentially tracking many innocent citizens.

3. Facial Recognition and AI Use: The police are permitted to use biometric data for facial recognition and can train AI systems with real police data.

4. Longer Preventive Detention: The maximum duration for holding suspects without charge is extended from 48 hours to up to 7 days in cases of imminent terrorist threats.

Critics, including civil rights groups and opposition politicians, argue that these measures represent a dangerous infringement on civil liberties and privacy, marking a significant increase in state surveillance power.

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The author shares their experience of getting back into physical AI projects using a Raspberry Pi Zero 2 W. After a busy work period focusing on fine-tuning a complex AI model, they are now looking to create a remote-controlled car to help address their home security worries, such as checking if the refrigerator is closed or if their cat is okay.

They purchased a 2WD car kit and combined it with the Raspberry Pi, a motor driver, batteries, and a USB camera. The setup allows for control of the motors and live video streaming. The author explains how to set up the Raspberry Pi, install necessary software, and create a web interface for controlling the car and viewing the video feed.

To manage multiple services smoothly, the author uses Nginx to combine the web interface and streaming under one URL, and systemd to ensure the services automatically restart on boot. They also set up a Cloudflare Tunnel for remote access without exposing their home IP address.

Ultimately, the author finds the Raspberry Pi and Linux ecosystem exciting and wishes they had discovered it earlier, hoping their blog might inspire others to explore similar projects.

In democracies, major policy decisions require majority support, so leaders must gain public backing to govern. Traditionally, they relied on tools like education and media to influence opinions. However, new AI technology makes it cheaper and easier to shape public views. This study presents a model showing that elites can decide how much to alter public preferences while considering costs and majority rules.

When one elite controls the narrative, their actions often lead to more polarized opinions, a trend that worsens with better persuasion tools. In contrast, when two opposing elites take turns in power, they may use the same technology to create stable opinion groups that are harder for rivals to change. Thus, advancements in persuasion can either increase or decrease polarization depending on the political context. Overall, these developments suggest that polarization is becoming a strategic tool in governance, affecting the stability of democracies as AI technology evolves.

Postgres has a lightweight version built with WASM that is less than 3MB when compressed.

Summary:

v1.0 Live offers a service that allows you to expose your local web server to the internet easily. You can create instant public URLs without any installation—just use a simple SSH command.

Key features include:

• Instant Deployment: You can go live in seconds with zero configuration or installation.
• Secure Tunnels: All connections are automatically encrypted with HTTPS.
• Public URLs: You get a random subdomain instantly for sharing, without needing to register.

The service is free, but you may have questions about limits, custom domains, and security.

Res Obscura is a history blog created by Benjamin Breen that has been active since 2010. Breen started writing it while he was a PhD student, aiming to post daily. Over the years, he built a community with other history bloggers and enjoyed sharing unique historical subjects. However, he became disillusioned with the clickbait nature of blogging and social media. In 2023, he transitioned to a Substack newsletter, which reignited his passion for writing online. He appreciates the niche topics he covers and enjoys sharing knowledge that isn’t readily available elsewhere. After 15 years and over 8,300 subscribers, Breen is seeking support to continue his work, offering a holiday discount for subscriptions.

Summary of GUI Wonderland #3 – At IT School with Apple Lisa

This episode focuses on the Apple Lisa, the first personal computer with a graphical user interface (GUI), released in January 1983. The Lisa was designed for office use, targeting users who were not tech-savvy and needed an easy-to-use interface.

Key Points:

• Development Background: The Lisa project started in 1978, aiming to improve upon the Apple II and III. Apple created a new division, Personal Office Systems (POS), to handle this project separately from the Apple II team.

• Inspiration from Xerox: In 1979, Steve Jobs and other Apple developers visited Xerox PARC, where they were introduced to innovative technologies, including the Smalltalk environment. This visit significantly influenced the design of the Lisa, leading to the development of features like overlapping windows and a mouse.

• Market Positioning: Initially, the Lisa was expected to compete with the Xerox Star, but it faced challenges due to its high price of nearly $10,000. During its development, a more affordable alternative, the Macintosh, was also being created, ultimately overshadowing the Lisa.

• Launch and Reception: Apple heavily marketed the Lisa, but it struggled in the market and was discontinued by 1986. Despite its failure, the Lisa was groundbreaking for its GUI, setting the stage for future personal computers.

• Legacy: The Lisa's development laid the groundwork for modern computing interfaces, influencing later products like the Macintosh.

Overall, the Apple Lisa was a pioneering machine that introduced many essential concepts in computer usability, despite its commercial struggles.

Summary of the Differences Between IndyCar and F1 Cars

IndyCar and Formula 1 (F1) cars are both types of formula racing vehicles, but they have many key differences:

1. Focus: IndyCar is primarily a drivers' championship, while F1 is a constructors' championship, emphasizing team innovation and technology.

2. Car Design:

   • Chassis: IndyCars are made by Dallara, while F1 teams build their own cars, allowing for more customization.
   • Weight: IndyCars are slightly lighter (around 1700 pounds) than F1 cars (about 1759 pounds) when including the driver.
   • Cockpit Protection: IndyCars use an aeroscreen; F1 uses a HALO device.

3. Downforce: F1 cars generate much more downforce, making them faster in corners. IndyCars are designed for better driver skill and less reliance on downforce.

4. Engines: Both use hybrid turbo engines, but IndyCars have less power (650-700 hp) compared to F1 cars (800-850 hp). IndyCar engines are built for durability with lower RPM limits.

5. Tires: F1 tires are softer and provide more grip, while IndyCar tires are harder and more durable, focusing on longevity for safety on ovals.

6. Brakes: F1 brakes are more advanced and require frequent replacement, while IndyCar brakes last much longer but are less effective.

7. Development: F1 teams have more freedom to innovate and improve their cars throughout the season, while IndyCar has stricter regulations, focusing on a spec-racing model.

8. Performance: Overall, F1 cars are faster, especially on traditional road circuits, due to their superior design and technology.

In races on the same track, F1 cars consistently achieve faster lap times than IndyCars.

Bun has been acquired by Anthropic, which plans to use Bun as the foundation for its AI coding tools, like Claude Code and Claude Agent SDK. Key points include:

What Stays the Same:

• Bun remains open-source and MIT-licensed.
• It will continue to be actively maintained by the same team.
• Development will still take place publicly on GitHub.
• The focus will be on improving JavaScript tooling and Node.js compatibility.

What Changes:

• There will be efforts to make coding tools faster and more efficient.
• Bun will see quicker updates and improvements.

Background:

• Bun was created to improve JavaScript development speed and was officially released in July 2022. Since then, it has gained significant popularity and funding.

The Future:

• Joining Anthropic provides Bun with long-term stability and resources, allowing the team to focus on developing top-tier JavaScript tools while adapting to the rapid advancements in AI coding.
• Bun's core principles and dedication to performance will remain unchanged, and it will continue to evolve in response to AI developments.

In summary, Bun's acquisition by Anthropic positions it for growth and innovation in the AI coding space while maintaining its foundational qualities.

Summary of SVG Filters - Clickjacking 2.0

Clickjacking is a deceptive technique where an attacker tricks users into interacting with hidden elements of another website, usually through an iframe. While traditional clickjacking is effective for simple actions, it struggles with more complex interactions. A new method called “SVG clickjacking” enhances this technique, allowing for more intricate attacks and various ways to steal data.

The text includes detailed CSS styles for UI elements involved in the SVG clickjacking technique, describing their appearance, behavior, and how they interact with user actions. The focus is on creating engaging and deceptive interfaces that manipulate user interactions without their awareness.

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