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The article discusses the pros and cons of self-hosting PostgreSQL databases compared to using managed database services like Amazon RDS.

Key Points:

• Self-Hosting Misconceptions: Many believe self-hosting databases is risky and complex, but the author argues that it's often simpler and more cost-effective than using cloud services.
• Cloud Service Basics: Most managed database services, including RDS, run standard PostgreSQL with added operational tools. They provide conveniences like backups and monitoring but don't inherently offer better performance.
• Personal Experience: The author has successfully self-hosted PostgreSQL for two years, managing thousands of users with minimal issues, mainly related to a single manual migration.
• Cost Comparison: Managed services have become more expensive over time, making self-hosting a more attractive option for many users.
• Operational Management: Self-hosting requires regular maintenance but can be manageable. The author outlines a straightforward maintenance schedule that takes about 30 minutes a month.
• When to Self-Host: Self-hosting is recommended for most users unless they are beginners or very large companies needing specialized database expertise.
• Configuration Needs: Self-hosting does require careful configuration, particularly regarding memory management, connection management, and storage tuning.

In conclusion, the author encourages teams to consider self-hosting PostgreSQL, especially if they find managed services too costly. He suggests starting small to experience the benefits firsthand.

Immersa: 3D Presentation Tool Summary

Immersa is a web-based tool for creating 3D presentations with animated transitions. Here are the key features:

• 3D Capabilities: Import .glb 3D models, add 2D images, and create 3D text.
• Smooth Transitions: Animated transitions between slides are created automatically when you move, rotate, or scale objects.

How It Works:

1. Set up your first slide with 3D objects.
2. Duplicate the slide to create a new one.
3. Adjust the positions of the objects on the new slide.
4. During the presentation, Immersa smoothly transitions the objects between the slides.

Features:

• 3D Scene Editor with a full 3D viewport.
• Support for .glb 3D models and various image formats.
• Full-screen presentation mode and local storage for data.
• Undo/Redo functionality and keyboard shortcuts for easy navigation.

Getting Started:

• Requires Node.js, npm, and Java (JDK 11+).
• Installation involves cloning the repository, installing dependencies, and starting a development server.

Usage Guide:

• The editor has panels for slide management, a 3D viewport, and object properties.
• You can add content like 3D models, images, and text, and manipulate them easily.
• Presentations can be exported for later use.

Technical Details:

• Built using ClojureScript, with various libraries for 3D rendering and state management.
• Data is stored locally in your browser for persistence across sessions.

License: MIT License.

Overall, Immersa is a modern tool designed for creating engaging 3D presentations effortlessly.

Jeff Sherman from NIST reported that the atomic time scale at their Boulder campus has failed due to a power outage caused by strong winds and utility shutdowns for wildfire prevention. As a result, the Boulder Internet Time Services cannot provide accurate time. While backup generators kept some servers running, one crucial generator has failed, affecting the time distribution. The campus is currently closed, and repairs cannot start until staff can access the site and power is restored. They are working on alternative power sources to protect their hydrogen maser clocks. More updates will follow as the situation develops.

No summary available.

TailwindSQL Overview

TailwindSQL is a tool that allows you to write SQL queries in a way similar to how you use TailwindCSS, specifically designed for React Server Components.

Key Features:

• Tailwind-style Syntax: Use class names to create SQL queries.
• React Server Components: Executes queries without needing client-side JavaScript.
• SQLite: Utilizes better-sqlite3 for quick local database access.
• Zero Runtime: Queries are processed during build or render time.
• Multiple Render Modes: Output can be formatted as text, lists, tables, or JSON.

Example Usage:

• To fetch a user's name: <DB className="db-users-name-where-id-1" /> would return "Ada Lovelace".
• To list products: <DB className="db-products-title-limit-5" as="ul" /> would render a list of products.

Installation Steps:

1. Clone the repository and navigate to the folder.
2. Install dependencies with npm or yarn.
3. Seed the database with demo data.
4. Start the development server and open the local demo page.

How It Works:

• Parser: Converts class names into configurations for queries.
• Query Builder: Creates safe SQL queries from those configurations.
• DB Component: Executes the queries and displays the results.

Render Modes: Results can be displayed as inline text, block elements, lists, tables, or JSON.

Project Structure: The project is organized into directories for components, core logic, and the main app.

Purpose: TailwindSQL was created to explore the concept of CSS-driven database queries.

License: MIT License, allowing for flexible use with some restrictions on production deployment.

Built using Next.js and SQLite, TailwindSQL aims to simplify database interactions in React.

Summary of Agent Skills in Codex

Agent Skills allow you to enhance Codex with specific capabilities for different tasks. Each skill includes instructions, resources, and optional scripts so Codex can effectively carry out a workflow. Skills can be shared among teams and the community, following an open standard.

Key Features:

• Skill Structure: A skill consists of a SKILL.md file with instructions, plus optional scripts and resources.
• Invocation Methods: Skills can be activated in two ways:
  • Explicit Invocation: Directly mention a skill in your prompt using the /skills command or by typing $.
  • Implicit Invocation: Codex automatically uses a skill if the task matches its description.

Skill Storage Locations: Skills are stored in various locations, each with different scopes:

1. Current Working Directory - For skills relevant to a specific project.
2. Parent Directory - For shared skills in a parent folder.
3. Root Repository - For skills accessible to everyone in the repository.
4. User Folder - For personal skills applicable across repositories.
5. System Location - For default admin skills available to all users.
6. Bundled Skills - Pre-installed skills that everyone can use.

Creating and Installing Skills:

• To create a skill, use the built-in $skill-creator or manually create a folder with a SKILL.md file.
• To install new skills, use the $skill-installer command to download from a curated set on GitHub.

Examples of Skills:

• Plan a New Feature: Use the built-in $plan skill for research and planning.
• Access Context: Use $skill-installer to pull in context from tools like Linear or Notion.

For detailed information, check the documentation on Agent Skills.

No summary available.

No summary available.

Summary of CSS Grid Lanes

CSS Grid Lanes is a new way to create flexible masonry layouts on the web, introduced by Jen Simmons, Brandon Stewart, and Elika Etemad. It allows developers to use CSS Grid to design layouts that automatically adjust to different screen sizes without the need for media queries.

Key Features:

• Easy Setup: You can create a grid layout with just three lines of CSS, which makes it simple to implement.
• Dynamic Columns: The layout automatically fills available space with columns that are at least 250 pixels wide, allowing for a responsive design.
• Flexible Design: You can create varying lane sizes and span items across multiple columns for a creative look.
• Item Placement: Items can be explicitly placed in the grid, enhancing design control.
• Direction Control: Lanes can be set to flow in either direction, creating different layout shapes like columns or rows.
• Tolerance Adjustment: A new feature called "item-tolerance" helps control how closely items are placed next to each other, improving the user experience.

Try It Out: You can experiment with CSS Grid Lanes in Safari Technology Preview 234 and explore various demos available online.

What’s Next? The CSS Working Group is finalizing details, but the basic syntax is ready for use. Developers are encouraged to create demos and share their feedback.

This new feature promises to enhance web design possibilities significantly and is easy to learn and implement.

No summary available.

Charles is a tool that acts as an HTTP proxy and monitor, allowing developers to see all HTTP and SSL/HTTPS traffic between their computer and the internet. This includes details like requests, responses, and HTTP headers, which contain cookies and caching info.

Recent Updates:

• September 20, 2025: Version 5.0.3 released, fixing a performance issue on macOS.
• August 9, 2025: Version 5.0.2 released with bug fixes.
• March 12, 2025: Major release of Charles 5.
• January 24, 2024: Public beta 13 launched with UI improvements, including dark mode for Windows.
• July 7, 2023: Public beta 11 released with multiple enhancements.

Key Features:

• Records all internet traffic.
• Displays request and response details, including cookies.
• Supports SSL and HTTPS.
• Helps in debugging and testing by simulating slower internet connections.
• Configurable for various needs.

Developers can download a free trial of the latest version, 5.0.3, to explore its features.

Reflections on AI at the end of 2025 highlight significant advancements in technology and its impact on society. Key points include:

1. Widespread Use: AI has become a common tool in various fields, enhancing productivity and efficiency.
2. Ethical Concerns: There are ongoing discussions about the ethical implications of AI, including privacy issues and job displacement.
3. Human-AI Collaboration: Many industries are seeing successful collaboration between humans and AI, improving decision-making and creativity.
4. Regulations: Governments are starting to implement regulations to manage AI development and usage responsibly.
5. Future Potential: There is optimism about AI's potential to solve complex global challenges, such as climate change and healthcare.

Overall, AI has made great strides, but it also brings challenges that need careful consideration.

Raycaster (raycaster.ai), a startup from Y Combinator, is creating a document IDE for the life sciences industry, focusing on regulatory and quality work. Their product organizes complex documents, allowing users to search, cite, and edit efficiently.

They are looking to hire a Research Engineer who will help develop production systems and guide the company’s research direction. The role includes building workflows, improving document handling, and turning research ideas into features, with opportunities to publish findings.

Key qualifications include strong engineering skills, experience with evaluation processes, attention to user experience, and the ability to quickly learn new domains. Having prior publications or contributions to open-source projects is a plus.

The position is in-person at their NYC office, with a compensation package including a base salary and equity. Interested candidates should email [email protected] with examples of their work and research.

Summary of Mistral OCR 3 Announcement

Mistral OCR 3 is a new document processing tool that significantly improves accuracy and efficiency in extracting text from various document types. Key highlights include:

• Performance Upgrade: It boasts a 74% win rate over its predecessor, Mistral OCR 2, particularly on forms, scanned documents, complex tables, and handwriting.
• High Accuracy: Outperforms existing enterprise and AI-native OCR solutions.
• User-Friendly Interface: Features a drag-and-drop interface in the Document AI Playground for easy document parsing into clean text or structured JSON.
• Cost-Effective: Priced at $2 per 1,000 pages, with a 50% discount for batch processing, bringing the cost down to $1 per 1,000 pages.

Mistral OCR 3 excels in handling various document challenges, including complex tables, handwritten content, and low-quality scans. It is compatible with different languages and works well across various document formats.

Recommended Uses: Ideal for high-volume processing, automating document workflows, and digitizing handwritten or historical documents. Early users are successfully applying it to process invoices, digitize archives, and improve search capabilities.

Mistral OCR 3 is available now through an API and the Document AI Playground in Mistral AI Studio, and it maintains backward compatibility with Mistral OCR 2. For more information, visit mistral.ai/docs.

Researchers at the University of Warsaw have developed a new method to detect terahertz (THz) signals using a quantum antenna made from Rydberg atoms. This breakthrough allows for precise measurements of terahertz frequency combs, which are useful for calibrating instruments across various frequencies.

Terahertz radiation is situated between microwaves and infrared light and has potential applications in areas like package inspection, 6G communication, and organic compound analysis. However, measuring terahertz signals accurately has been challenging due to the rapid oscillations involved.

The research team used Rydberg atoms, which are highly sensitive to electric fields, as a "quantum antenna." By converting weak terahertz signals into light, they achieved the ability to measure individual components of a frequency comb—a task previously thought impossible. This method operates at room temperature, making it more practical for future applications and commercialization.

Their findings represent a significant advancement in terahertz metrology and may lead to new technologies that utilize this previously difficult-to-measure region of the electromagnetic spectrum.

This text indicates that a project or website is created using Zola, supported by Garage, and hosted on Deuxfleurs.

Electricity is now flowing through a new deep-level tunnel in South London that is the size of a train. This tunnel connects two substations, New Cross in Southwark and Hurst in Bexley, and is part of the London Power Tunnels 2 (LPT2) project. The first of two new power circuits, which runs 18 kilometers deep beneath the city, is now operational.

This new system replaces older cables that have been in use since the 1960s, moving power through wider tunnels rather than shallower street-level trenches. The entire LPT2 project, costing £1 billion, stretches 32.5 kilometers across seven boroughs from Wimbledon to Hurst.

Construction of the tunnels started in March 2020 and included three sections: Wimbledon to New Cross (12 km), New Cross to Hurst (18 km), and Hurst to Crayford (2.5 km). This project follows a previous phase completed in 2018, which also involved building new tunnels and substations in North London.

Airbus is planning to move its important applications to a European cloud service focused on digital sovereignty. However, the company estimates only an 80% chance of finding a suitable provider. Airbus needs this cloud to keep sensitive information under European control, especially due to concerns over U.S. laws that could affect data privacy.

The company, which has already transitioned some services to the cloud, aims to migrate key systems like ERP and CRM to this new platform. The request for proposals will start in early January, with a decision expected by summer, and the contract could be worth over €50 million for up to ten years.

Concerns about data sovereignty have intensified due to geopolitical issues, particularly with the return of Donald Trump to U.S. politics. This has led European companies to seek alternatives to U.S. cloud providers like Microsoft and AWS. Airbus's executive, Catherine Jestin, is waiting for European regulations to clarify data sovereignty and whether European cloud providers can meet their needs in time.

tvterm Overview

tvterm is an experimental terminal emulator that runs in your terminal, using the Turbo Vision framework. It showcases new features like 24-bit color support and is built on Paul Evan's libvterm, which is also utilized by Neovim and Emacs. It works on both Unix and Windows (Windows 10 version 1809 or later).

Building tvterm

To build tvterm, follow these steps:

1. Clone the repository with its submodules using:

   • git clone --recursive [repository URL]
   • If already cloned, run:
     • git submodule init && git submodule update

2. Install the necessary dependencies:

   • CMake
   • A C++14 compatible compiler
   • libvterm (can be built as part of tvterm or use a system version)

3. Install Turbo Vision dependencies:

   • libncursesw (for Unix)
   • libgpm (optional, for Linux)

4. Build tvterm using:

   • cmake . -B ./build -DCMAKE_BUILD_TYPE=Release
   • cmake --build ./build

If you have an older CMake version, use:

• Create a build directory and run:
  • mkdir -p build; cd build
  • cmake .. -DCMAKE_BUILD_TYPE=Release
  • cmake --build .

Future Features

tvterm is still a work in progress, and planned features include:

• UTF-8 support
• Support for fullwidth and zero-width characters
• Enhanced color support
• Scrollback functionality
• Text selection
• Text search
• Signal sending to child processes
• Text reflow when resizing
• Options for different terminal emulator implementations
• Improved dependency management

For more information, visit the project's GitHub page: tvterm GitHub.

The text discusses a new data structure called semistable::vector, which is an enhanced version of the standard C++ std::vector. Here are the key points:

1. Purpose: semistable::vector allows for iterator stability, meaning that iterators remain valid even after certain operations like inserting or removing elements.

2. Functionality:

   • It provides the same interface as std::vector but with better handling of iterators.
   • It uses a system of "epoch descriptors" to track changes and ensure that iterators function correctly after modifications.

3. Performance:

   • Benchmarks show that using semistable::vector for specific operations can have performance similar to std::vector when using its raw() method for direct access to elements.

4. Limitations:

   • Thread safety: While some operations are thread-safe, iterators cannot be used across threads without precautions.
   • Exception safety: The iterator stability may not hold if exceptions are thrown during operations.
   • If an iterator is kept around but not used while the vector changes, it can lead to memory issues.

5. Monothread Version: A simpler version of semistable::vector using a different pointer type shows improved performance.

Overall, semistable::vector aims to provide a reliable and efficient alternative to std::vector with enhanced stability for iterators.

The article by Nicholas A. Thompson argues against the mindset of individuals who claim, "I have nothing to hide." He believes that such attitudes threaten everyone’s freedom by creating a standard of "normalcy" that surveillance systems can exploit. When people live transparently, they unknowingly build a profile that can later be used against them if societal norms shift.

Thompson explains that when these individuals later seek privacy, their previous openness signals them as suspicious to surveillance systems, making them targets. This not only affects their own privacy but also undermines the efforts of others who are trying to maintain a low profile.

On a larger scale, the author warns that collective transparency weakens societal privacy defenses, making dissent more visible and vulnerable. The solution he proposes is to change the baseline by making privacy a default state, encouraging everyone to practice encryption and anonymity. Ultimately, the goal is to create a noisy environment where no one fits the typical profile, making it difficult for surveillance systems to identify individuals.

The text discusses the use of hash tables in Go, particularly using map[int]struct{} to track unique values instead of map[int]bool. The empty struct (struct{}) is a zero-sized type, which theoretically saves memory, as it occupies no space. However, a recent update (Go 1.24) introduced a new map implementation called Swiss Tables, which changed how memory is handled.

The author discovered that using struct{} did not reduce memory consumption as expected due to the way the Go compiler aligns memory. Each struct's size must accommodate alignment, meaning even an empty struct takes up 1 byte, leading to similar memory use as a boolean type, which also occupies 1 byte.

Before Go 1.24, maps stored keys and values in separate arrays, allowing the compiler to omit the values array entirely when using struct{}. Now, this optimization is not effective anymore, making the approach less useful and potentially reducing code readability.

The author cautions against blindly trusting information from language models (LLMs) and highlights the importance of understanding the underlying implementations in Go.

Under certain conditions, airplanes create contrails that can last for hours and form artificial clouds. These clouds can trap heat, contributing to global warming.

On December 17, 2025, NOAA introduced new AI-driven global weather prediction models that greatly enhance forecast speed, efficiency, and accuracy. These models aim to provide faster and more precise weather forecasts while using significantly less computing power.

The new AI models include three main applications:

1. AIGFS (Artificial Intelligence Global Forecast System): This model delivers quicker weather forecasts with up to 99.7% less computing resources than traditional models. It shows improved accuracy, especially in tracking tropical cyclones, though it still needs to enhance intensity predictions.

2. AIGEFS (Artificial Intelligence Global Ensemble Forecast System): This system offers a range of possible weather outcomes rather than a single forecast, improving forecast skill and requiring only 9% of the resources of traditional ensemble systems.

3. HGEFS (Hybrid-GEFS): This innovative model combines AI and traditional forecasting methods, creating a more robust ensemble that better represents forecast uncertainty. It outperforms both the traditional GEFS and AIGEFS.

These advancements stem from Project EAGLE, a collaboration involving various NOAA divisions and partners from academia and industry, utilizing Google's GraphCast model for initial development. Overall, these new AI models are expected to significantly improve the accuracy and timeliness of weather forecasts, helping to protect lives and property.

Summary: Fuzix on Raspberry Pi Pico

Fuzix is a lightweight operating system based on UNIX, designed to run on microcontrollers like the Raspberry Pi Pico. The author, intrigued by hobby operating systems, decided to try Fuzix on their Pico.

To compile Fuzix, the author used a Debian Bookworm environment and created a Dockerfile for the necessary dependencies. They downloaded the Fuzix source code, removed a non-compatible game, and compiled it for the Pico.

The compilation resulted in two files: fuzix.uf2 (the kernel) and filesystem.uf2. These files can be flashed onto the Pico by holding the "BOOTSEL" button while connecting it to a computer. The author used the onboard flash for storage.

After installation, the author connected to the Pico over Serial and accessed a simple UNIX shell. They were impressed to see the system running on such a small device, which allowed for basic tasks like GPIO manipulation and script execution. Overall, it was a fascinating experience to run UNIX on a microcontroller.

2025 LLM Year in Review Summary

2025 was a significant year for Large Language Models (LLMs), marked by notable advancements and shifts in technology. Here are the key developments:

1. Reinforcement Learning from Verifiable Rewards (RLVR): A new training method emerged, allowing LLMs to learn problem-solving strategies by optimizing against clear, objective rewards. This led to longer training times and a focus on developing reasoning capabilities.

2. Understanding LLM Intelligence: The industry began to see LLMs not as evolving beings (like animals) but as "ghosts" that mimic human intelligence in specific contexts. This shift in perspective highlighted the inconsistent performance of LLMs, which can excel in some areas while struggling in others.

3. New LLM Applications (Cursor): The rise of applications like Cursor showcased a new layer of LLM usage, where these apps manage multiple LLM interactions and provide tailored user interfaces, suggesting a future where LLMs are integrated into various professional fields.

4. Claude Code (CC): This LLM agent demonstrated a new way of interacting with AI, running locally on users' computers and allowing for personalized problem-solving, rather than relying on cloud-based solutions.

5. Vibe Coding: A new trend where programming can be done using natural language, making it accessible to everyone and facilitating rapid development of software without traditional coding skills.

6. Nano Banana (Google Gemini): This model illustrated the future of user interfaces for LLMs, suggesting a move towards visually engaging interactions rather than just text-based commands.

Overall, 2025 showed that while LLMs have great potential, they are still developing. There’s room for innovation and exploration in the field, with many ideas yet to be realized.

Summary of TP-Link Tapo C200 Vulnerabilities and Reverse Engineering

In a recent exploration of the TP-Link Tapo C200 IP camera, vulnerabilities were discovered that pose significant security risks. The author, Simone Margaritelli, documented the process, which involved using AI tools for reverse engineering the camera's firmware. Here are the key points:

1. Reverse Engineering Approach: The author suggests starting with inexpensive IP cameras for learning reverse engineering. The Tapo C200 was chosen for its affordability and functionality, and the exploration aimed to identify vulnerabilities in its firmware.

2. Firmware Extraction: The camera's firmware was easily obtained from an unprotected TP-Link S3 bucket, allowing access to all firmware versions.

3. Security Vulnerabilities Found:

   • CVE-2025-8065: A memory overflow vulnerability in the ONVIF SOAP XML parser allows attackers to crash the camera by sending excessive XML elements.
   • CVE-2025-14299: An integer overflow in the HTTPS server’s Content-Length parsing can also crash the camera when receiving a large header value.
   • CVE-2025-14300: A lack of authentication in the WiFi configuration API lets attackers change the camera's WiFi settings, enabling them to hijack the camera's connection.
   • WiFi Network Scanning: The camera can be queried for nearby WiFi networks without authentication, potentially revealing sensitive information about its location.

4. Disclosure Process: After reporting these vulnerabilities to TP-Link, the timeline for remediation was delayed, leading to public disclosure after the company failed to address the issues in a timely manner.

5. Conflict of Interest: TP-Link, as a CVE Numbering Authority, has the authority to assign vulnerabilities to its products, raising concerns about transparency and accountability in how they handle security issues.

This investigation highlights significant security flaws in the Tapo C200 camera, emphasizing the importance of responsible vulnerability disclosure and the need for improved security practices in IoT devices.

No summary available.

Graphite has announced that it is joining Cursor. You can read more about it on their blog at the provided link.

The text describes the "sharp" Node-API module, which is used for quickly converting large images into smaller, web-friendly formats like JPEG, PNG, WebP, GIF, and AVIF. It's compatible with various JavaScript environments that support Node-API v9, such as Node.js, Deno, and Bun.

Key features include:

• Image resizing is 4x-5x faster than ImageMagick and GraphicsMagick.
• It correctly handles color spaces, ICC profiles, and transparency.
• Maintains high quality through Lanczos resampling.
• Supports additional operations like rotation, extraction, and gamma correction.
• Works without needing extra installations on most macOS, Windows, and Linux systems.

For installation and usage examples, you can visit sharp.pixelplumbing.com. Basic code snippets are provided for using the module with callbacks, promises, async/await, and streams.

The module is open-source, licensed under the Apache License 2.0, allowing users to report issues, request features, and contribute code.

Summary of "A Better Zip Bomb" by David Fifield

This article explains how to create a "non-recursive zip bomb," a type of zip file that can expand significantly without needing to decompress nested zip files. Instead of relying on recursion, this method overlaps files within the zip container, leading to an impressive compression ratio—up to 28 million, where a 10MB input can expand to 281TB.

Key Points:

• The zip bomb uses the DEFLATE compression algorithm, which is widely accepted by zip parsers.
• It achieves huge expansion by referencing a small amount of highly compressed data (called a "kernel") multiple times instead of duplicating it.
• The output size grows quadratically with the input size, making larger input sizes yield better compression ratios.
• The technique is compatible with most zip parsers but may not work with all due to differences in how they handle file metadata.

Examples of compression ratios achieved:

• 42kB compressed to 5.5GB
• 10MB compressed to 281TB
• 46MB (using Zip64) compressed to 4.5PB

The article also discusses the structure of zip files, the importance of overlapping files for maximizing compression, and the challenges of maintaining compatibility across different zip parsers.

The text contains links to news articles about a shooting incident involving a suspect associated with Brown University. It discusses the investigation into the shooting and mentions the use of controversial technology in solving such cases. The articles provide updates and details about the situation.

I created a lightweight PDF generation library called tinypdf for a Node.js app, which is only 3.3KB when minified and gzipped. It allows you to create invoices with:

• Text (using Helvetica, with color and alignment options)
• Rectangles and lines
• JPEG images
• Multiple pages and custom sizes

However, it does not support custom fonts, PNG/SVG images, forms, encryption, or converting HTML to PDF. It's designed to cover 95% of the needs for invoices, receipts, reports, tickets, and labels.

You can find it on GitHub: tinypdf and install it via npm with npm install tinypdf.

Rodrigo Pombo's post outlines a step-by-step guide to building a simplified version of React, called Didact, from scratch, focusing on React 16.8. The guide will cover the following key steps:

1. createElement Function: This function will transform JSX into a JavaScript object representing the React element, storing its type and properties.

2. Render Function: This function will handle rendering elements to the DOM, creating DOM nodes based on the React element tree.

3. Concurrent Mode: A method to break rendering work into smaller units, allowing the browser to prioritize tasks like user input.

4. Fibers: A data structure to represent units of work, enabling efficient traversal through the element tree during rendering.

5. Render and Commit Phases: The process of updating the DOM only after all rendering work is done, to avoid displaying incomplete UI.

6. Reconciliation: The method to compare old and new elements to update or delete DOM nodes as necessary.

7. Function Components: Support for function components, which do not have a corresponding DOM node and derive children from function execution.

8. Hooks: Adding state management with useState to function components, allowing for component reactivity.

The post emphasizes a focus on understanding React's architecture and encourages readers to experiment with their own versions by adding features or optimizations. The goal is to help developers learn about React's inner workings while creating a simplified version.

Carolina Cloud offers managed data science infrastructure at about one-third the cost of AWS. The founder left a previous job after seeing companies struggle with high cloud bills for simple workloads. Examples included a $1,000 monthly charge for a basic virtual machine and $50,000 for a high-RAM instance.

Carolina Cloud is designed for data scientists and small teams who need powerful computing without the high costs. They provide:

• Standard Ubuntu virtual machines (VMs)
• Easy-to-use Marimo notebooks
• One-click RStudio Server and Shiny hosting
• Upcoming S3-compatible storage
• Discounts for prepaying for as little as two weeks
• A secure, compliant data center in Charlotte, NC

Their pricing is straightforward: $0.005 per vCPU per hour and $0.005 per GiB of RAM per hour. For example, a 32 vCPU, 128GB RAM instance costs around $240 per month, compared to over $800 on AWS.

Carolina Cloud is not trying to replace all AWS services but is ideal for users like hedge funds, biotech teams, or researchers who need powerful VMs without unexpected fees. For more information, visit console.carolinacloud.io.

Summary of Rust's Block Pattern by John Nunley

John Nunley introduces a coding pattern in Rust called the "block pattern," which helps make Rust code cleaner and more robust. This pattern takes advantage of Rust's feature where blocks of code can be treated as expressions.

Key Points:

1. Understanding the Block Pattern:

   • A block can contain multiple statements and expressions. For example, you can define variables and perform operations within a block, and the result can be assigned to a variable.

2. Example Problem:

   • A function that loads a configuration file and sends HTTP requests can become cluttered with multiple temporary variables that are only used once.

3. Refactoring with the Block Pattern:

   • By encapsulating configuration loading and parsing logic within a block, you can:
     • Clarify the intention of the code.
     • Reduce namespace pollution, as temporary variables are scoped to the block.
     • Free resources quickly, as variables go out of scope at the block's end.

4. Advantages Over Functions:

   • Keeps the code flow inline, improving readability.
   • Avoids the need to pass many variables as parameters if you use a lot of them within the block.

5. Managing Mutability:

   • The block pattern can help limit the scope of mutable variables, reducing the risk of unintentional changes later in the function.

The author encourages Rust developers, especially beginners, to consider using this block pattern to enhance code quality.

No summary available.

No summary available.

The text mentions an update for "Qwen/Qwen-Image-Layered," which includes a feature for converting image-text to images. The update was made 1 day ago and has received 1.07k interactions, with 270 of those being specific engagements.

Summary of the FreeBSD Foundation's Laptop Support and Usability Project

Program Overview:

• Name: Laptop Support and Usability
• Funding: Supported by the FreeBSD Foundation and Quantum Leap Research, with a budget of $750,000.
• Start Date: Q4 2024, expected to last 1-2 years.
• Key People:
  • Sponsor: Ed Maste
  • Manager: Alice Sowerby

Objectives:

• Improve FreeBSD functionality for better performance on laptops.
• Focus on security, user experience, and reducing barriers to adoption.

Planned Improvements:

• Updates to FreeBSD 14.x and above for better WiFi, audio, graphics, Bluetooth, and more.
• Creation of documentation and guides for new features.

Community Involvement:

• A Laptop and Desktop Working Group is available for community feedback and collaboration.
• Discussion threads on various topics like power management and security are encouraged.

Communication:

• Monthly updates and a public roadmap will keep the community informed.
• Users are encouraged to join the Desktop mailing list for general updates.

Target Users:

• While primarily aimed at developers, the project seeks to enhance the experience for all laptop users.

User Experience Focus:

• The project emphasizes user experience, aiming to make FreeBSD easier to set up and use on laptops.

This project aims to make FreeBSD a more accessible and user-friendly operating system for laptop users.

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Summary:

AI companies claim that engineering is becoming obsolete, yet their actions reveal otherwise. For instance, Anthropic acquired a team whose most active contributor was an AI, despite being able to access their code for free. This suggests that while AI can generate code, the real value lies in the human team's judgment and decision-making skills.

The article argues that the true bottleneck in technology isn't producing code but understanding which code is essential and making informed choices. Companies are investing heavily to acquire talented engineers because they recognize the importance of human insight in navigating complex problems.

As a technical leader, it's important to value your skilled workers and leverage AI to enhance their capabilities, rather than using it as an excuse to undervalue them. Focus on developing critical skills like system design and risk assessment, and maintain a healthy development pipeline for junior engineers. Ultimately, pay attention to what companies do (like acquiring talent) rather than what they say about AI and coding.

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Summary: Lock Down Your GitHub Actions

GitHub Actions lacks a built-in way to lock dependency versions, which can lead to issues like:

1. Mutable Tags: Version tags (e.g., @v4) can change to different code without notice.
2. Hidden Dependencies: Composite actions may include dependencies that are not visible or easily audited.

Solution: The tool gh-actions-lockfile creates a lockfile that secures all actions, including hidden dependencies, by pinning them to specific commit SHAs with integrity hashes. This ensures you know exactly which version of the code is used and verifies its integrity.

Features:

• Pins actions to specific commit SHAs.
• Includes integrity hashes for security.
• Manages transitive dependencies.
• Visualizes the action dependency tree.
• Can be used as a GitHub Action or CLI tool.

Getting Started:

• Use the GitHub Action: - uses: gjtorikian/gh-actions-lockfile@v1 with the mode set to either 'verify' or 'generate'.
• CLI commands available for generating lockfiles, verifying workflows, and listing dependencies.

Secure your GitHub workflows today!

Summary of GotaTun Announcement

GotaTun is a new version of WireGuard® developed by Mullvad VPN, created using the Rust programming language. It is based on the BoringTun project from Cloudflare and aims to be fast, efficient, and reliable. GotaTun includes privacy features like DAITA and Multihop and has been optimized for Android.

Mullvad has previously used wireguard-go, which faced many issues, including a high crash rate—over 85% of crashes reported in their apps were due to wireguard-go. By switching to GotaTun, Mullvad has significantly reduced crashes from 0.40% to 0.01% since its launch on Android in late November 2025. Users have reported improved speeds and lower battery usage.

Moving forward, Mullvad plans to conduct a security audit, replace wireguard-go with GotaTun on all platforms, and enhance performance throughout 2026.

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A recent security vulnerability in Avelo Airlines' reservation system exposed millions of passenger records, including personal information and payment details. The flaw allowed attackers to exploit a missing last name verification and lack of rate limiting, making it possible to access sensitive data through brute-force attacks.

Key Points:

1. Vulnerability Discovery: The issue was identified on October 15, 2025, and reported to Avelo Airlines, who promptly responded and fixed the problem by November 13, 2025.

2. Nature of the Flaw: Normally, accessing flight reservations requires a confirmation code and the passenger's last name. However, Avelo's system allowed access using only the confirmation code, significantly reducing the difficulty of a brute-force attack.

3. Attack Feasibility: An attacker could guess all possible confirmation codes in about 6 hours using basic technology and without any cost barriers.

4. Data Exposure: The vulnerability could expose full names, dates of birth, government ID numbers, contact information, flight details, and partial payment card data.

5. Response and Remediation: Avelo Airlines reacted quickly to patch the vulnerabilities after being notified, demonstrating effective handling of the situation.

6. Lessons Learned: This incident highlights the importance of implementing multiple security checks and rate limiting to protect sensitive information.

Overall, the situation serves as a reminder for developers to prioritize security measures in order to safeguard personal data.

The text discusses the challenges and lessons learned from implementing a custom partitioning system for Postgres in the Hatchet project.

Key Points:

1. Background on Hatchet: Hatchet is a durable queue built on Postgres that processes many tasks daily. Initially, it stored all tasks in one table, but as the data grew, performance issues arose due to table bloat and slow deletion processes.

2. Partitioning Decision: To manage large volumes of data, Hatchet implemented time-based partitioning for certain tables. They aimed to avoid reliance on external extensions for better compatibility across different Postgres providers.

3. Partition Management: They developed a system to create new partitions and drop old ones while minimizing locking issues. However, after deployment, they noticed significant slowdowns in query performance.

4. Query Performance Issues: Slow queries were linked to partitioned tables, especially those involving JOINs. The query planner struggled with incorrect row estimates for these queries.

5. Solution Found: The problem was traced back to the lack of accurate statistics for the partitioned tables, as autovacuum does not analyze them automatically. Manually running the ANALYZE command on the parent table resolved the performance issues.

6. Lessons Learned:

   • Use DETACH PARTITION...CONCURRENTLY to avoid locking problems when removing partitions.
   • Regularly run ANALYZE on parent partition tables to maintain query performance.
   • Ensure autovacuum is functioning for child partitions.

Overall, the experience emphasized the importance of managing statistics for partitioned tables to maintain efficient query performance.

The setting vm.overcommit_memory=2 is recommended for servers because it improves memory allocation reliability.

The Linux kernel allows tuning of memory allocation behavior through the vm.overcommit_memory setting. By default, overcommit is enabled, which means the kernel often grants memory requests even if there isn't enough memory available. While this can help developers, it complicates error handling because the allocation's success does not guarantee that memory will actually be available later.

When a program requests memory, if overcommit is disabled, the kernel checks for available memory before granting the request. However, with overcommit enabled, the request is approved immediately, leading to potential allocation failures that only become apparent when the memory is accessed. This makes debugging harder, as failures are not reported at the time of allocation but later, often resulting in abrupt process terminations without clear error messages.

An example of this issue is seen with Redis, which warns users to enable overcommit to avoid failures during low memory conditions. The article argues that this approach shifts the responsibility of handling memory errors from developers to the kernel, which is poor engineering practice. Instead of relying on overcommit, developers should address memory allocation issues more directly.

Texas is suing major TV manufacturers—Sony, Samsung, LG, Hisense, and TCL—claiming they are secretly recording what people watch in their homes. Attorney General Ken Paxton alleges these TVs use a feature called Automatic Content Recognition (ACR) to gather personal viewing data without users' consent, which is then used for targeted advertising. This includes tracking content from various sources like streaming services and connected devices.

The lawsuit accuses these companies of misleading consumers about how ACR works, with some TVs allegedly taking screenshots every half-second. Paxton also raises concerns about TCL and Hisense being connected to China, labeling their devices as "Chinese-sponsored surveillance."

He argues that these practices violate Texas consumer protection laws and seeks penalties, as well as a ban on collecting and sharing data. Paxton emphasizes that owning a TV should not mean giving up personal privacy.

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In 1999, a company decommissioned an HP 9000/720 workstation, which had been used as a boot server for X terminals. The machine had a failing disk but was forgotten until the company decided to get rid of all X terminals. The author, who had good relations with the company, took the machine, intending to run OpenBSD instead of HP/UX.

The OpenBSD porting effort for the HP PA-RISC architecture was mainly led by Michael Shalayeff, who faced many challenges due to a lack of documentation. The author provided support and testing, while another developer, Matt Fredette, began creating a NetBSD port based on Shalayeff's work. This encouraged further activity on the OpenBSD side, resulting in improvements and new kernels to test.

One significant challenge was making the HP 712 workstation run without a keyboard, which was restricted by its firmware. Instructions existed to bypass this limitation, but they were complicated and risky. The author decided to modify OpenBSD's boot loader to allow users to change the console settings easily, ultimately leading to successful serial console operation on multiple HP models.

The author tested various console speeds for the HP 712, discovering that lower speeds caused considerable delays during boot, making the process tedious but necessary for ensuring the code's reliability. Eventually, OpenBSD supported headless operation at higher speeds, enhancing usability for users wanting to run their systems without a keyboard.

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The Buteyko method is a breathing technique developed in the 1950s by Russian physiologist Konstantin Buteyko. It aims to help people, particularly those with asthma and other respiratory issues, by promoting slower and shallower breathing to counteract hyperventilation. The method includes exercises that focus on nasal breathing, breath control, and relaxation.

Key points about the Buteyko method include:

1. Breathing Regulation: It seeks to correct rapid breathing patterns and reduce reliance on medications for asthma and other respiratory conditions.

2. Core Principles: The method emphasizes three main components:

   • Nasal Breathing: It is thought to help clean and warm the air before it reaches the lungs.
   • Reduced Breathing: Individuals practice controlling their breath to lower the volume of air they take in.
   • Relaxation: Emphasizes the importance of staying calm to prevent worsening of asthma symptoms.

3. Controversy and Evidence: While some people report significant improvements using the Buteyko method, the medical community remains skeptical due to limited scientific evidence supporting its effectiveness. Studies have shown mixed results, and many have methodological flaws. Major health reviews have not found strong support for the method's claims.

4. Popularity: The Buteyko method has gained attention in various countries, with some anecdotal reports of success. However, it is not widely accepted in conventional medicine.

Overall, the Buteyko method is a breathing retraining technique that some believe can help with asthma, but its effectiveness remains debated within the medical field.

Daniel, a 16-year-old high school senior, spends his free time finding security vulnerabilities in big companies. Recently, he and his friends discovered serious security flaws in Mintlify, an AI documentation platform used by major companies.

Daniel found a critical cross-site scripting (XSS) vulnerability that could allow attackers to inject harmful scripts into documentation, potentially stealing user credentials. He began exploring this after Discord switched to using Mintlify for their documentation.

While investigating, Daniel discovered that Mintlify's API allowed access to documentation files without proper checks. After some research, he found a way to embed JavaScript in an SVG file, which he uploaded to his documentation and accessed through Discord, proving the vulnerability.

Daniel collaborated with friends who were also looking into Mintlify and they reported their findings to Discord and Mintlify. Discord took immediate action, shutting down their documentation temporarily and reverting to the old system. Mintlify's team also worked with the group to address the vulnerabilities.

The impact of the XSS flaw was significant, affecting many Mintlify customers, including large companies like Twitter and Vercel. In total, the group received around $11,000 in bug bounties for their responsible disclosure of the vulnerabilities.

On December 18, 2025, Apple provided access to a Mac Studio cluster to test a new feature called RDMA (Remote Direct Memory Access) over Thunderbolt in macOS 26.2. This feature allows multiple Macs to share a large pool of RAM, making it beneficial for running large AI models. The setup I tested, costing nearly $40,000, includes Macs with a total of 1.5 TB of memory.

Historically, Apple has struggled in the high-performance computing (HPC) space, with past efforts like Xgrid failing to gain traction. However, the M3 Ultra Mac Studio shows promise for local AI model execution, significantly reducing memory access latency, which enhances performance.

The Macs have strong performance capabilities, consuming low power and remaining quiet. They are not the cheapest options on the market, especially compared to competitors like Nvidia and AMD, but they deliver impressive results.

Setting up the Macs in a mini rack was made easier with a new product from DeskPi. However, managing the Macs as a cluster has its challenges, particularly due to limitations in macOS for operations like system updates.

I conducted various tests, including benchmarks that showed the M3 Ultra Mac Studio outperforming competing systems in both single and multi-core performance. The M3 Ultra also excelled in AI inference tasks, demonstrating its strength in handling large models.

While the RDMA feature is promising, it still has stability issues, and managing a cluster of Macs can be more cumbersome compared to Linux systems. Future improvements could include better support for more Macs and enhanced software capabilities.

In conclusion, the Mac Studio cluster showcases significant potential for AI applications, though managing it presents challenges. The high cost may deter some users, but its performance and efficiency make it a noteworthy option in the current market.

The author has released the source code for Commander Keen 1-3 to celebrate Keen's 35th anniversary. This package includes all known versions of the games, from an early beta of Keen 1 to a rare later release. To compile the code into identical versions of the original games, users need specific software: Turbo C++ 1.00 and Turbo Assembler (2.0 or higher) for most versions, and Borland C++ 2.0 for later special releases.

The reconstruction of this code started in early 2021, but it faced challenges due to the author's access to the wrong compiler version, which produced slightly different results. The author also had to carefully manage variable names in the code to ensure they compiled correctly.

The author mentions that some of the code in the project is based on routines used in other games, which led to legal troubles for the original developers.

Overall, the release aims to provide fans with the opportunity to explore and modify the classic games.

Summary:

Senior engineers stand out because they excel at reducing ambiguity. While mid-level engineers can handle clear tasks well, senior engineers thrive when faced with unclear problems. They ask the right questions, distinguish important issues from noise, and prioritize tasks effectively, turning vague requirements into actionable plans.

This ability to clarify problems is crucial because it helps prevent misunderstandings and project delays. Unfortunately, many companies struggle to assess this skill during hiring processes, often focusing on technical skills rather than problem-solving abilities.

To gauge if you're operating at a senior level, consider how you handle ambiguous tasks. Instead of waiting for clarification or jumping into coding, a senior engineer would spend time clarifying the issue first. This skill can be developed through practice, so take on vague assignments to improve.

The text discusses a common issue in technical documentation reviews where every comment appears equally urgent, leading to wasted time and missed critical issues. To address this, the author suggests implementing a tagging system for review comments that indicates both the severity and category of each comment.

Key Points:

1. Problem Identified: Review comments lack prioritization, causing contributors to focus on non-urgent issues while missing critical bugs.

2. Tagging System Proposal: Each comment should have a tag indicating:

   • Severity:
     • Blocker: Must fix before merging.
     • Improvement: Should fix before publication.
     • Optional: Personal preference.
   • Category:
     • Clarity, bug, organization, style, or consistency.

3. Benefits of Tagging:

   • Contributors can quickly identify and prioritize critical fixes.
   • Reduces overwhelm by categorizing comments.
   • Accelerates the review process and improves team communication.

4. Limitations: The system does not address slow review times, poor feedback quality, or replace the need for good judgment in assessing comment importance.

5. Implementation Advice: Start tagging comments immediately to enhance efficiency in reviews.

By adopting this system, teams can reduce debates about what blocks merging and streamline the review process.

OpenRouter has introduced a new feature called Response Healing, which automatically fixes errors in JSON responses generated by language models (LLMs) before they reach applications. This feature aims to improve the reliability of structured outputs, addressing common mistakes like incorrect syntax that can lead to application failures.

Key points include:

• Significant Improvements: After implementing Response Healing, the defect rate for popular models like Gemini 2.0 Flash dropped by 80%, and for Qwen3 235B, it fell by 99.8%.

• Impact of Small Changes: Reducing the defect rate from 2% to 1% can significantly lower the number of bugs and support requests, leading to better overall system reliability.

• Common Errors Fixed: The feature addresses common JSON issues such as trailing commas, unescaped characters, and missing brackets.

• Performance Metrics: The plugin has shown high success rates in fixing JSON errors for various models, with some achieving near-perfect healing rates.

• Ease of Use: Response Healing is optional and can be easily enabled in the OpenRouter settings. It adds minimal latency, typically less than 1 millisecond.

• Limitations: While it fixes syntax errors, it does not ensure that the JSON matches specific schemas or addresses streaming requests. XML outputs can also be healed upon request.

Overall, Response Healing aims to enhance the reliability of structured outputs from LLMs, allowing developers to focus on more complex semantic issues in their applications.

Bob and Arun, the creators of Stickerbox, wanted to explore what AI for kids would look like. They focused on harnessing children's creativity and imaginations through a safe and fun tool. Stickerbox is a voice-activated sticker printer that combines AI image generation with thermal printing, allowing kids to turn their ideas into real stickers they can color, stick, and share.

The magic happens when kids see their imaginative creations, like a ghost on a skateboard or a superhero dog, transformed into actual stickers, which delights them. The project faced unexpected challenges, such as sourcing safe materials, ensuring child safety, and creating a user-friendly interface for young children. They also prioritized kids' data privacy to make parents comfortable with the device.

Stickerbox aims to make AI safe and enjoyable for kids. They invite feedback and offer a discount code for those interested in purchasing the product.

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Summary of CS251: Great Ideas in Theoretical Computer Science

Course Overview: CS251 at CMU focuses on the detailed study of computation, an essential element in understanding technology and the universe. The course aims to equip students with the formal tools and language needed to explore key concepts and results in theoretical computer science.

Part 1: Formalizing Computation

1. Introduction: Introduces theoretical computer science, emphasizing formal representation of data and computational problems.
2. Finite Automata: Covers deterministic finite automata (DFA), a basic model of computation, and prepares students for understanding algorithms.
3. Turing Machines: Introduces Turing machines, a foundational model for all computational devices, and discusses computable problems.
4. Limits of Computation: Explores undecidable problems, using techniques like diagonalization and reductions.
5. Limits of Human Reasoning: Discusses the formalization of mathematical reasoning and its connection to computation.

Part 2: Computational Complexity 6. Time Complexity: Examines the complexity of decidable problems, focusing on time as a resource for evaluating algorithms. 7. Graph Theory: Introduces graph fundamentals, which are vital for many computational problems and their complexities. 8. P vs NP: Explores the NP complexity class and the significant open question of whether P equals NP, with implications for various fields. 9. Randomized Algorithms: Discusses the role of randomness in algorithms, highlighting the existence of efficient randomized solutions that may not have deterministic counterparts. 10. Cryptography: Traces the evolution of cryptography, emphasizing how computational complexity shapes secure communication protocols.

Part 3: Highlights of Theoretical Computer Science 11. Extra Topics: Presents additional key areas within theoretical computer science.

This course aims to deepen your understanding of computation and its implications across various domains.

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Summary of TimeCapsule LLM

TimeCapsule LLM is a language model designed to replicate historical language and perspectives by training exclusively on data from specific time periods, particularly London from 1800 to 1875. The model aims to reduce modern biases and reflect the vocabulary and worldview of the era.

Key Versions:

• v0: Responds with 1800s language but often produces incoherent sentences due to limited training data.
• v0.5: Improved coherence and Victorian writing style, yet still prone to factual errors and retains some OCR errors.
• v1: Capable of connecting real historical events with figures from the dataset, showing greater contextual understanding.
• v2mini-eval1: Further refined but encountered tokenization issues, resulting in fragmented outputs.

Training Process:

1. Data Collection: Gather public domain texts from the chosen historical period.
2. Text Cleaning: Remove errors and irrelevant information from the data.
3. Tokenizer Development: Create a custom tokenizer for the cleaned data.
4. Model Training: Follow specific architectures for training, such as nanoGPT.

The goal of the TimeCapsule LLM project is to create a model that authentically represents historical language without modern influence.

Summary of "AIPrompt Caching: 10x Cheaper LLM Tokens"

Prompt caching allows users to access cheaper tokens (10x less) for AI models from OpenAI and Anthropic. It can also significantly reduce response time, especially for longer prompts. The process involves storing certain data from previous requests to avoid recalculating everything each time a prompt is sent.

Key Points:

1. Cached Tokens: These tokens are cheaper and improve response speed by reducing the amount of data that needs to be processed for repeated prompts.
2. Understanding LLMs: Large language models (LLMs) work using complex mathematical functions that convert text (prompts) into numerical representations (tokens) and back again.
3. Tokenization and Embeddings: Text is broken down into tokens, which are then converted into embeddings—numerical representations that capture the meaning and context of the text.
4. Attention Mechanism: This part of the model determines how much attention each token should receive in relation to others, allowing the model to generate more relevant responses.
5. KV Caching: By caching the K (key) and V (value) matrices from previous calculations, the model saves time and resources, enabling faster token processing for similar prompts.
6. Different Approaches by Providers: OpenAI automates caching, while Anthropic gives users more control over caching duration, making it suitable for specific applications.

In conclusion, understanding and utilizing prompt caching can lead to significant cost savings and efficiency when using AI models.

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The author is interested in having a unique digital identity and decides to explore the world of custom license plates after receiving reminders from the DMV to renew their vehicle registration. They discover a hierarchy of rare license plates, with single numbers being the rarest.

To find available custom plate combinations, the author uses a website called PlateRadar, which charges $20 a month for access to this information. They find that Florida offers a free vanity plate checker, which allows users to check multiple combinations quickly.

The author, being an engineer, automates the process of checking plate availability using a script. They create a microservice that checks for rare combinations frequently and store the results in a database. During their search, they find desirable combinations like "WEBSITE" and "SITE," but the most coveted two-letter combination, "EO," becomes unavailable before they can claim it.

However, after some persistence, they discover another rare two-letter combination, "HY," becomes available. They rush to the DMV and successfully reserve it. The author concludes that with determination and coding skills, it's possible to claim unique license plates.

Anthropic conducted over 1,250 interviews about AI in the workplace, revealing that while many people have positive views about AI, a significant majority—85.7%—are struggling with unresolved feelings about its impact on their work. This group is not entirely negative or positive; they are simply conflicted and continue to use AI despite these tensions.

The research identified three groups based on their experiences with AI:

1. Scientists - Thriving and treating AI as a tool.
2. Workforce - Managing to adapt.
3. Creatives - Experiencing an existential crisis, with 72% feeling a threat to their identity and 44.8% questioning the meaning of their work due to AI.

Interestingly, creatives have the highest struggle scores and the fastest adoption rates of AI, indicating they are embracing AI while feeling conflicted about their authenticity and the value of their work. Many express guilt about using AI, feeling it undermines their originality.

The study also found that the main reason people distrust AI is due to "hallucinations"—the AI's confident but incorrect outputs—rather than simple errors. Trust in AI varies among groups, with scientists showing the highest levels of trust due to their verification practices.

The findings highlight the need for individuals to consciously navigate their use of AI, separating their identity from AI outputs and maintaining personal accountability. Overall, while AI can enhance productivity, it also raises significant questions about authenticity, meaning, and trust in professional settings.

The author created Misata to improve data generation for dashboards by ensuring relational and temporal integrity, which existing tools struggle with. Misata allows users to define data rules in natural language.

Here's how it works:

1. LLM Layer: It uses Groq/Llama-3.3 to convert user-defined stories into a JSON schema for data constraints.
2. Simulation Layer: It employs Vectorized NumPy to generate data quickly, ensuring that parent data exists before child data to maintain relationships.

Performance-wise, it can generate around 250,000 rows per second on an M1 Air. Currently in early alpha, it features an experimental "Graph Reverse Engineering" that can translate simple charts into data.

The author is seeking feedback on the architecture of simulator.py, which currently uses in-memory data storage (Pandas) but is considering switching to DuckDB for handling larger datasets.

Summary: Designing a Passive LiDAR Detector Device

Samy Kamkar discussed the potential of using LiDAR for detecting when an iPhone's camera app is opened during his talk at DEF CON 32. Inspired by this idea, the author explored creating a device to detect LiDAR signals from iPhones.

Key points include:

1. LiDAR Technology: The iPhone's TrueDepth system uses a 60Hz infrared signal for depth sensing. This system activates when the camera app is opened, making it detectable even before a photo is taken.

2. Detection Challenges: The author faced initial skepticism about the viability of a small detection device. After experimenting with various components, they realized the need for a deeper understanding of the target LiDAR signals.

3. Hardware Development: The device must detect 940nm infrared signals and distinguish them from other sources. The author tested different photodiodes and found that specific peak photodiodes offered the clearest signals.

4. Signal Processing: Successful detection requires measuring the signal frequency and processing it quickly. The author chose a SAMD21 microcontroller for its efficient processing capabilities.

5. Design Iterations: Several hardware designs were explored, including:

   • Using Schmitt Triggers for fast signal processing.
   • Implementing operational amplifiers for better signal stability.
   • Considering a photodiode grid for more precise detection but ultimately deciding against it due to complexity.

6. Next Steps: The author plans to develop firmware for the hardware to demonstrate its effectiveness in detecting LiDAR signals.

Overall, the project aims to create a device that can reliably detect and analyze LiDAR signals from smartphones.

The article discusses improvements made to the ClickHouse database system, specifically focusing on optimizing the aggregation merge process for fixed hash maps.

Key Points:

1. Performance Variation: Running similar queries can result in significantly different performance. The author observed this when executing two queries that were almost identical but used different methods to calculate a grouping value.

2. Aggregation Mechanics: The performance differences stem from how ClickHouse handles aggregation. When grouping by a number that can fit into a smaller type, ClickHouse can use a more efficient array-based hashmap. Otherwise, it resorts to a two-level hash map, which is slower.

3. Optimization Approach: To improve performance, the author implemented a method where each thread processes different subsets of the keys simultaneously, avoiding race conditions and eliminating the need for complex conversions between data structures.

4. Challenges Faced: During development, the author encountered issues such as memory corruption and race conditions due to improper usage of memory management techniques. They realized that the memory management system used in ClickHouse was not thread-safe, which led to errors when multiple threads accessed shared memory.

5. Trivial Performance Decline: Interestingly, the optimization did not yield benefits for simpler aggregation functions like count or sum. The author disabled the optimization for these cases after discovering that the overhead of parallel processing outweighed the benefits.

6. Final Improvements: The solution included extracting minimum and maximum indices before merging to minimize processing time, thus enhancing overall performance.

In summary, the author documented their experience of optimizing ClickHouse's aggregation process, addressing performance issues, and resolving technical challenges encountered during implementation.

Summary of "Building a Transparent Keyserver"

On December 19, 2025, a new keyserver was developed to securely look up age public keys while ensuring transparency and user privacy. This keyserver uses a technology called transparency logs (tlogs) to hold the operator accountable, preventing the injection of malicious keys.

Key Features:

1. Centralized Keyserver: Users can log in with their email to manage their public keys, making it easier to handle identity and spam issues.
2. Transparency Logs: These logs are append-only lists that provide cryptographic proof of entries. They allow users to verify the inclusion of their keys, ensuring the operator cannot hide or alter data.
3. Verifiable Random Functions (VRFs): To protect user privacy, email addresses are hashed using VRFs, making it hard for attackers to enumerate users.
4. Anti-Poisoning Measures: Instead of storing raw public keys in the log, their hashes are stored, while the actual keys are kept in a database to prevent harmful content from being logged.
5. Witness Network: This system ensures that the log's integrity is maintained, preventing the operator from showing different versions of the log to different users.

Implementation Steps:

• The keyserver was built in under 500 lines of code, integrating the transparency features through a series of small, manageable changes.
• Monitoring tools were introduced to allow users to verify their keys against the log.

Conclusion: The project demonstrates how to use tlogs to create a secure, user-friendly keyserver that balances accountability and privacy. This new keyserver is live at keyserver.geomys.org and aims to improve user trust in centralized systems. Future work includes enhancing monitoring capabilities and adding revocation features.

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Summary:

The author bought an old Dell Precision T3610 workstation and upgraded it with Proxmox, RAM, and SSDs. They wanted to replace the existing Intel Xeon E5-1650 v2 CPU with a newer Xeon E7-8890 v4, which they believed was compatible because both CPUs were listed as using the FCLGA2011 socket. However, when the new CPU arrived, it didn’t fit due to differences in socket variations—Socket R for the old CPU and Socket R2 for the new one. The author found the naming scheme confusing and frustrating, as even Intel's documentation failed to clarify the differences. In the end, they kept the incompatible CPU as a backup for a future server, viewing the experience as a learning opportunity rather than a major loss.

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Summary of the External Content Links Program for US Developers

Developers in the US must enroll in Google's external content links program by January 28, 2026, if they want to use links for app downloads or transactions. Currently, Google is not charging fees for these links, but will do so in the future.

Key Points:

1. Program Purpose: This program allows developers to link users to external content, like purchasing in-app items or downloading apps not managed by Google Play.

2. Requirements for Enrollment:

   • Developers must enroll and get approval for their apps.
   • Links must only be for users in the US and its territories.
   • Apps must comply with Google Play Developer Policies, except for payment policies.
   • Developers must integrate specific APIs for external links.
   • Must provide customer support for transactions outside of Google Play.

3. Destination Requirements:

   • Links must direct users to safe and approved content.
   • Users must be informed about the purpose of the links.
   • User data must be protected, and misleading links are prohibited.

4. Fees: Future fees for transactions will be 10% for subscriptions and 20% for other in-app purchases. Download fees will vary by app category.

5. Eligibility: Only US mobile or tablet apps can enroll.

6. Enrollment Steps:

   • Review eligibility criteria.
   • Complete a declaration form and integrate necessary APIs.
   • Register and declare any linked external apps.

7. Additional Notes:

   • This program is optional; developers can choose not to participate.
   • There is no limit to the number of external links a developer can use.
   • Developers can use both Google Play's billing system and the external links program.

For more information or questions, developers can contact Google support.

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The author acknowledges that while the statement isn't entirely accurate, the website bettermotherfuckingwebsite.com is an excellent educational resource that significantly influenced how they created their own site. However, they prefer to keep some details under wraps.

The author reflects on their past mistakes in implementing ring buffers, specifically a one-element version. They describe two common implementations: one using an array with two indices (read and write) and another using an array with one index and one length field.

The first method wastes one slot in the array, making it less efficient, especially for small buffers. The second method avoids wasting space but complicates concurrent access since both reader and writer modify the length field, which can lead to caching issues.

The author proposes a third method that uses two unmasked indices, allowing them to grow unbounded and wrap around naturally without needing additional state variables. This method effectively addresses the space-wasting issue and simplifies the code.

Despite its advantages, the author notes that many programmers still use the older, less efficient methods, possibly due to tradition or a misunderstanding of integer overflow. They express curiosity about why better implementations are not more widely adopted and hint at a follow-up post about other common misconceptions in programming.

hk - An Operating System Kernel in Rust

Key Features:

• Modern Design: Built for multi-threaded and multi-core 64-bit processors (x86-64 and aarch64).
• Device Management: Uses a device tree to describe hardware, making it flexible and easy to manage.
• Linux Compatibility: Uses the Linux syscall ABI for different architectures.

Development Notes:

• There are plans for a new device driver model and eBPF support.
• To build and test, run make check or make check-arm, and use make help for more guidance.
• Requires tools like QEMU, dosfstools, and ISO tools.

Trees rely on a network of fungi and bacteria in the soil, known as the "wood wide web," to exchange nutrients. Scientists have now mapped this network globally, covering over 28,000 tree species in more than 70 countries. The research was sparked by earlier work that identified the global distribution of trees, revealing there are about 3 trillion trees on Earth.

The study identified different types of fungi associated with various trees. For example, oak and pine trees are linked to ectomycorrhizal (EM) fungi, which create large underground networks, while maple and cedar trees associate with arbuscular mycorrhizal (AM) fungi, which form smaller networks. Additionally, some trees, like legumes, work with bacteria to convert atmospheric nitrogen into a usable form for plants.

Researchers used computer algorithms to analyze the relationships between these fungi and local environmental factors, allowing them to predict the types of fungi in areas without data, especially in Africa and Asia. They found that in cooler regions, EM fungi dominate, whereas in warmer tropical areas, AM fungi are more prevalent. Nitrogen-fixing bacteria thrive in hot, dry environments.

While the findings provide valuable insights into forest ecosystems, some scientists caution that other factors influencing soil microbes may not have been fully accounted for. Nevertheless, this mapping is expected to aid in understanding carbon storage in forests and their role in climate change. Crowther predicts that as the climate warms, a shift from EM to AM trees may occur, potentially releasing more carbon dioxide into the atmosphere and accelerating climate change.

The Central Pangean Mountains were a major mountain range that existed during the Carboniferous, Permian, and Triassic periods when the supercontinent Pangaea formed. This range, which included what are now the Scottish Highlands, the Appalachians, the Ouachita Mountains, and the Little Atlas of Morocco, was created by the collision of the supercontinents Laurussia and Gondwana.

Over time, especially during the Permian period, the mountains were worn down by weathering, leading to a decrease in their height and the formation of deep plains. By the Middle Triassic, they were much smaller, and by the beginning of the Jurassic period, the mountainous region in Western Europe had mostly disappeared, leaving only highland areas separated by deep ocean basins.

Summary of T5Gemma 2

T5Gemma 2 is a new version of an encoder-decoder model that significantly improves upon its predecessor, T5Gemma, by introducing important architectural changes and features from the Gemma 3 family.

Key Features:

• Multi-Modal Capability: T5Gemma 2 can process both text and images, making it suitable for tasks like visual question answering.
• Long Context Handling: It can manage context windows of up to 128,000 tokens, improving its ability to work with lengthy inputs.
• Compact Models: The new models come in various sizes (270M, 1B, and 4B parameters), making them efficient for on-device applications.

Architectural Innovations:

• Tied Embeddings: This reduces the number of parameters by linking the encoder and decoder embeddings.
• Merged Attention: A unified attention layer combines self- and cross-attention, simplifying the model and enhancing performance.

Performance Enhancements:

• T5Gemma 2 shows strong results in multimodal tasks and is better at handling long contexts compared to its predecessors. It excels in various coding, reasoning, and multilingual tasks.

Availability: Pre-trained models are accessible for developers to use and fine-tune for specific applications.

Overall, T5Gemma 2 sets a new standard for compact encoder-decoder models with its advanced capabilities and efficiency.

No summary available.

Summary of FunctionGemma Release

On December 18, 2025, a new version of the Gemma 3 model called FunctionGemma was released. This model is specifically designed for function calling, allowing it to perform tasks beyond simple conversation. Key features include:

1. Enhanced Functionality: FunctionGemma can execute commands and summarize results in natural language, making it versatile for both users and systems.

2. Customization: Users can fine-tune the model to boost its reliability significantly, from 58% to 85% in specific tasks.

3. Optimized for Edge Devices: The model is lightweight enough to run on devices like mobile phones and NVIDIA Jetson Nano, ensuring quick and private operations.

4. Ecosystem Support: FunctionGemma works with popular tools for training and deployment, making it easy to integrate into various applications.

5. Use Cases: It is ideal for applications with defined actions, requiring low latency and privacy, and can handle both local tasks and route complex tasks to larger models.

The release includes demos in the Google AI Edge Gallery, showcasing how users can interact with the model through voice commands and mobile applications. Developers are encouraged to explore, train, and deploy their own specialized agents using FunctionGemma.

Grand Theft Auto: Vice City is now available to play in your web browser through an open-source project called reVC. This project allows you to experience a technology demo of the classic game on DOS.Zone. The game engine has been redesigned to work well in browsers, using modern technologies like WebAssembly for smooth performance without needing to install anything.

This demo is a non-commercial project and is not connected to the original game's developers or publishers. It does not include any original game assets, so players must legally own the original game to fully enjoy it. The demo is meant for educational and research purposes, showcasing how complex game engines can run in a browser.

The project respects copyright laws and only uses publicly available open-source code. Any game assets included are minimal and sourced legally, restricted to work only on DOS.Zone. Users must provide their own original game files to access the full game, and ownership is verified for compliance.

If you are a copyright holder and believe this project infringes your rights, you can contact them via email for review.

The text discusses the perception of ancient Greek and Roman art, particularly focusing on the reconstructions of colored statues.

1. Statues Overview: The article highlights several notable sculptures, including the Townley Venus and the Augustus of the Prima Porta, emphasizing their beauty and the fact that they were originally painted, which is often overlooked today.

2. Modern Reconstructions: Recent efforts to reconstruct the original colors of these statues have led to public interest. However, these reconstructions are often viewed as unattractive compared to the original white marble versions.

3. Changing Tastes: The text suggests that modern tastes differ significantly from those of ancient Greeks and Romans. This difference in aesthetic appreciation may explain why the reconstructions appear ugly to contemporary viewers.

4. Critique of Reconstructions: The author argues that the reconstructions are poorly executed and do not accurately reflect the original artistic intentions. They suggest that ancient depictions and other art forms from that time indicate a more sophisticated use of color than is seen in modern reconstructions.

5. Expertise and Public Perception: The poor quality of the reconstructions may stem from a lack of skill among those creating them and a strict adherence to archaeological evidence that limits artistic expression. Despite their unattractiveness, these reconstructions have sparked significant interest and discussion about ancient art.

6. Conclusion: The text questions whether the ugly nature of these reconstructions is intentional, possibly to draw attention to the fact that ancient sculptures were colorful. It concludes that while the reconstructions may not be true to the originals, they serve to highlight the misconception that ancient art was solely monochrome.

The article discusses the "stochastic parrot" narrative, which suggests that AI models, like language models, simply mimic language patterns without true understanding. The author argues that this idea is outdated and has been disproven by advancements in physics and AI research. They assert that AI can now create and understand language in more complex ways than previously thought, moving beyond just imitation. This shift in perspective highlights the evolving capabilities of AI and challenges old assumptions about its nature.

The author created a tool called Linggen to improve their workflow when working on complex multi-node systems. They found it frustrating to repeatedly explain their system to language models (LLMs), and traditional documentation was hard to search.

Key Features of Linggen:

• Workflow Integration: A VS Code extension that helps start the day by quickly loading project memory and context.
• Local-First Technology: Built with Rust and LanceDB, keeping all data on the user's machine without needing accounts.
• Team Memory: Automatically provides context to teammates' LLMs.
• Visual Map: Shows file dependencies and helps manage changes effectively.
• Compatibility: Works with Cursor, Zed, and Claude Desktop.

Linggen saves the author a lot of time, and they are interested in hearing how others manage their complex system contexts.

For more information, visit their GitHub repository and website.