Synadia and TigerBeetle have committed a total of $512,000 over two years to support the Zig Software Foundation (ZSF), reflecting their belief in Zig's potential for creating high-performance, reliable software.

Synadia's Role: Synadia connects major enterprises through secure communication across various environments. They help organizations modernize their systems, enabling them to build efficient microservices and data platforms. Their clients come from diverse sectors, including finance, gaming, and energy.

Collaboration with TigerBeetle: TigerBeetle, a financial database focused on reliability and performance, shares Synadia's values. Both companies aim to create predictable and trustworthy software. After discussions between the leaders of both companies, they decided to collaborate in supporting the ZSF.

Support for Zig Software Foundation: The Zig Software Foundation, led by Andrew Kelley, promotes the Zig programming language, known for its performance and reliability. Synadia and TigerBeetle are proud to support this initiative, believing Zig will be crucial for the future of distributed systems.

Company Backgrounds:

• Synadia: Creator of the Synadia Platform and NATS.io ecosystem, providing secure messaging across different environments.
• TigerBeetle: A database designed for safe and high-performance financial transactions.

This article provides a beginner-friendly guide on how to build a simple Linux micro-distribution from scratch, focusing on the RISC-V architecture using QEMU. Here are the key points:

1. Understanding the Kernel and Distribution: The Linux kernel manages hardware and provides interfaces for running applications. A Linux distribution combines the kernel with additional software and tools to create a functional operating system.

2. Building the Kernel: The guide explains how to download and configure the Linux kernel source code for RISC-V, followed by building it using a cross-compilation toolchain.

3. The Init Process: Once the kernel is loaded, it initiates the "init" process, which is the first user-space program that starts other processes.

4. Creating an Initramfs: To make the micro-distribution useful, an initial filesystem (initramfs) needs to be created, which includes an "init" program. This can be a simple C or Go program that interacts with the user.

5. Running the Micro-Distribution: The built kernel and initramfs can be run on QEMU, allowing users to see their custom micro-distribution in action.

6. Bonus - Using u-root: For a more functional distribution, the article suggests using the u-root project, which provides a ready-made user-space environment and allows the creation of a more useful initramfs.

7. Package Managers and Init Systems: These are essential components of a Linux distribution, managing software installations and system initialization processes.

Overall, the article emphasizes the layered architecture of Linux, where the kernel serves as the foundation for running user applications within a complex system.

Summary: 15 Years of Progress

The text compares two coding frameworks from 2010 and a modern one, highlighting that while the modern framework (React) looks cleaner at first, it complicates understanding due to its abstraction. React hides many operations which can lead to confusion for developers, especially when debugging common issues that arise in moderately complex applications.

In contrast, the older framework (Backbone) is straightforward and clear about its processes. This transparency makes it easier for junior developers to follow what's happening in the code. React's complexity requires a deeper understanding of its internals, which can be burdensome.

While React may be beneficial for large applications, the text questions its necessity for smaller projects that don't need such complexity. It calls for a simpler, more intuitive coding model that allows for easier understanding and debugging, similar to how Backbone and jQuery operated.

The end of support for Windows 10 in October 2025 is leading to a major replacement cycle for PCs, benefiting Apple significantly. Nearly 40% of PCs are still using Windows 10, prompting early upgrades in both business and consumer markets. Apple's Mac shipments rose by 14.9% in the third quarter of 2025, driven by demand for new MacBook models and increased enterprise use. Lenovo remains the largest PC vendor, with a 17.4% growth, while Asus and HP also saw increases. Dell's shipments, however, fell by 0.9%. The top five PC brands now hold about 75% of the market share, and companies are starting to promote PCs with AI features, although these haven't yet become major selling points.

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Summary of Unlocking Free WiFi on British Airways

In June 2025, a traveler flying British Airways noticed that they could access free WiFi for messaging by signing up for the airline's frequent flyer program, "The British Airways Club," even as an economy passenger. They discovered that the WiFi allowed messaging apps like WhatsApp, Signal, and WeChat, but not Discord.

Curious about how the system determined which apps to allow, the traveler speculated it might involve checking the domain names used in the connection, specifically through the SNI (Server Name Indication) feature. They ran tests to confirm that connections to sites not on a whitelist were reset, indicating that the airline monitored which websites were accessed.

By manipulating SNI, the traveler successfully set up a proxy server that masqueraded as the WhatsApp domain, allowing them to browse the internet while onboard. They confirmed that this worked by accessing various websites, albeit with limited speed and performance.

The traveler also explored the potential of ECH (Encrypted Client Hello), which could improve privacy by encrypting SNI information. They tested this and found it successful, using it to browse securely without being blocked.

Overall, this experience highlighted the complexities of internet privacy and the challenges posed by SNI, suggesting that users should be cautious about trusting it as a reliable security measure.

Summary of the Swift SDK for Android Announcement

On October 24, 2025, Joannis Orlandos announced the launch of the Swift SDK for Android, allowing developers to create Android applications using the Swift programming language. This development is the result of collaborative efforts from the Android workgroup and the broader Swift community.

Key points include:

• The SDK enables cross-platform development, making it easier to share code between different platforms.
• It is available as part of the Windows installer or can be downloaded separately for Linux and macOS.
• A "Getting Started" guide is provided to help developers begin using Swift on Android.
• Over 25% of existing Swift packages are already compatible with Android.
• The swift-java project allows integration between Java and Swift, facilitating code interoperability.
• The Android workgroup is seeking community feedback and is drafting a vision document to guide future development.

Developers are encouraged to share their experiences and participate in discussions on the Swift forums to help enhance the ecosystem.

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Summary of Valetudo:

Valetudo is software designed for vacuum robots that operates without cloud connectivity. Launched in 2018 by Sören Beye, it has become a reliable solution for many users—estimated to be in the thousands based on downloads and support group membership.

The software is open-source and licensed under Apache-2.0, allowing users to understand and modify it without relying on third parties. Valetudo is a personal project meant to provide free access, likened to a privately-owned public garden. Users can enjoy and contribute to it but have no authority to demand changes.

For more information, users can check the documentation, including a getting started guide, and explore supported robots for purchase. Communication regarding updates and community support can be found in the Valetudo Telegram group, though unofficial channels may have outdated info.

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A geometric puzzle dating back over 300 years has been solved: a shape called the Noperthedron has been found that cannot allow another identical shape to pass through it. This discovery comes from researchers Jakob Steininger and Sergey Yurkevich, who proved that no matter how you tunnel through a Noperthedron, a second one won't fit through.

The problem began with a bet made by Prince Rupert of the Rhine, who claimed that cubes could pass through each other if bored with a tunnel. Historically, many shapes, including cubes and several polyhedra, were found to have this property, leading mathematicians to believe that all convex polyhedra could do the same. However, the Noperthedron, with its complex structure of 90 vertices and 152 faces, has proven that this belief is not universally true.

Steininger and Yurkevich used a combination of theoretical advancements and extensive computer calculations to reach their conclusion. Their work involved examining how shadows cast by shapes can help determine if one shape can fit through another. They developed algorithms to analyze potential Rupert passages and confirmed the Noperthedron's unique properties.

This finding opens new avenues for exploring other shapes and understanding geometric properties, shifting the perception that all convex shapes have the Rupert property. Researchers are excited to continue investigating this area of mathematics.

The article discusses changes in iOS 26 that impact the detection of spyware, specifically Pegasus and Predator.

Key points include:

1. Shutdown.log Importance: The shutdown.log file has been crucial for identifying malware on iOS devices, as it logs activities even during shutdown.

2. Spyware Evolution: Pegasus spyware has evolved to erase traces from this log file, complicating detection efforts for security researchers. The developers have improved their methods to hide their activities better.

3. iOS 26 Changes: With the release of iOS 26, Apple modified how the shutdown.log is handled—now it gets overwritten on reboot, erasing previous data. This change makes it harder to find evidence of past infections.

4. Recommendations for Users: It's advised that users take a sysdiagnose of their devices before updating to iOS 26 to save current log data. Users may want to delay the update until Apple addresses this issue.

Overall, these developments pose challenges for investigators trying to identify spyware on devices amid rising spyware threats.

The article discusses the importance of hyperlinks in context engineering for language models (LLMs). It highlights the need to balance having access to relevant context without overwhelming models with too much information. Key strategies for managing this include:

1. Retrieval Augmented Generation (RAG): Dynamically fetching relevant context for queries.
2. Subagents: Using specialized instructions and tools to streamline the main task.
3. get_ Tools*: Allowing models to request information as needed.

The author argues that hyperlinks are an underused technique that can enhance context management. By using hyperlinks, models can explore and access information incrementally, similar to how humans navigate the web. With hyperlinks, models can retrieve relevant context in a flexible and efficient manner.

The article also introduces the concept of “Hypertext as the Engine of Agent State,” which suggests that hyperlinks can enable agents to discover and utilize both local and web-based data more effectively.

To implement a hyperlink-based context system, the author proposes a simple setup involving a tool that accepts URIs and an entry point to bring context into play. Benefits of using links include their ease of implementation, token efficiency, and ability to provide just-in-time context, improving the relevance and freshness of the information accessed.

The article concludes by encouraging developers to consider using hyperlinks in their agents instead of creating multiple specialized tools. The author believes that as context engineering evolves, hyperlinks will play a crucial role in enhancing how agents access and utilize information.

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Summary

The text discusses the slow adoption of heat pumps in America despite their proven efficiency and environmental benefits. Key points include:

• Heat Pumps Overview: Heat pumps are not new technology; they have been around for over a century and can efficiently heat and cool homes. They often outperform traditional heating systems in efficiency and cost.

• Current Challenges: The main barriers to widespread adoption are cultural, economic, and educational rather than technological. Homeowners need to be informed about the benefits, and contractors must be trained to install them properly.

• Cultural Shift: There is growing acceptance and support for heat pumps, with programs like the Inflation Reduction Act providing financial incentives for installation.

• Performance in Cold Climates: Modern heat pumps can function effectively in cold weather, debunking previous myths about their limitations.

• Future Focus: The series will explore key strategies to accelerate heat pump adoption, emphasizing that success relies more on human factors and effective execution than on new inventions.

Overall, the text emphasizes that while heat pumps are ready for wider use, overcoming the barriers related to people's perceptions and knowledge is crucial for their success.

Blaise Agüera y Arcas discusses important lessons from artificial intelligence (AI) related to evolution, computing, and the nature of the mind. He emphasizes how AI can help us understand complex concepts and the connections between technology and human thought. The foreword highlights the significance of these insights in shaping our understanding of intelligence and its development over time.

Since 2012, deep learning frameworks like PyTorch and TensorFlow have gained popularity in research and industry. Currently, PyTorch is becoming the preferred choice among researchers, while TensorFlow remains dominant in industry settings.

Recent data shows that at major conferences, PyTorch papers outnumber those using TensorFlow, indicating a shift in research preferences. For example, at the 2019 CVPR conference, 69% of papers used PyTorch, compared to much lower rates for TensorFlow. Researchers favor PyTorch for its simplicity, user-friendly API, and perceived performance advantages.

In contrast, TensorFlow is still widely used in industry due to its production capabilities, such as better support for deployment and performance optimization. However, both frameworks are evolving: PyTorch has introduced features for deployment, while TensorFlow has adopted eager execution mode to enhance usability.

The future landscape of machine learning frameworks seems to be a balance between research and industry needs, with PyTorch leading research and TensorFlow maintaining its foothold in production. The ongoing development of both frameworks will determine their roles in the future of machine learning.

My friend Sam has a feature on his website for sending anonymous messages, which inspired me to create something similar. I used a receipt printer I had on my desk to print messages physically. I built a webpage (ping.aschmelyun.com) where people can type and send messages that are printed directly on my desk.

I used an Epson TM-T88IV thermal receipt printer, which doesn’t need ink because it prints using heat on special paper. Since it’s an older model, I connected it to a Raspberry Pi, which allows me to send print commands using a language called ESC/POS. I created the website using PHP and the Laravel framework, ensuring messages are validated and stored in case of printer issues.

Instead of hosting the site separately, I ran it directly on the Raspberry Pi and used Cloudflare Tunnels to make it accessible online. Since launching, I've received over a thousand messages from around the world, including funny poems, ASCII art, and recipes. Many messages included locations, prompting me to pin them on a world map.

The project has been a fun way to connect with people anonymously, and I enjoyed creating it. If you're interested in the source code, it's available on my GitHub.

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In October 2025, the author shares their perspective on using AI in coding, comparing their approach to that of a surgeon. They argue that, like surgeons, coders should focus on high-value tasks while delegating secondary, less critical tasks to AI. This allows them to concentrate on what they do best, such as UI prototyping.

The author highlights several tasks they find helpful to assign to AI, including writing guides, experimenting with code changes, fixing errors, and creating documentation. They prefer to run these tasks in the background while they work on core projects.

They differentiate between using AI for primary tasks, where they maintain close oversight and detail, and for secondary tasks, where they allow more autonomy. The author believes this method eliminates the traditional concerns of assigning grunt work to lower-status team members, as AI can handle those tasks anytime.

Working at Notion, the author appreciates the company's support for AI tools, which enhances productivity. They aim to extend this "surgeon-like" approach to a wider range of knowledge workers, emphasizing the importance of focusing on the main tasks while AI manages the grunt work.

Twake Drive Summary

Twake Drive is an open-source alternative to Google Drive. To set it up locally, follow these steps:

1. Clone the Repository: Use the command:

   git clone https://github.com/linagora/twake-drive
   

2. Run with Docker:

   • Navigate to the directory: cd tdrive
   • Start the application using:

     docker compose -f docker-compose.minimal.yml up
     

3. Access the App: Open your browser and go to http://localhost/.

Development Requirements:

• Node.js (version 18 or higher)
• MongoDB
• Yarn (recommended)

Setup Instructions:

• Start MongoDB with:

  docker run -p 27017:27017 -d mongo
  

• To run the frontend, use:

  cd tdrive/frontend/; yarn dev:start
  

• To run the backend, use:

  cd tdrive/backend/node/; SEARCH_DRIVER=mongodb DB_DRIVER=mongodb PUBSUB_TYPE=local \
  DB_MONGO_URI=mongodb://localhost:27017 STORAGE_LOCAL_PATH=/[full-path-to-store-documents]/documents \
  NODE_ENV=development yarn dev
  

If additional parameters are needed, modify the development.json file in tdrive/backend/node/config/.

The app will run on port 3000.

License: Twake Drive is licensed under Affero GPL v3.

Since it opened in 2019, Britain's National Centre for Gaming Disorders has seen many teenagers, often encouraged by their parents, seeking help for video game addiction. Recently, the clinic has also started treating more adults, with 67 people over the age of 40 receiving care. The oldest patient is a 72-year-old woman who is addicted to smartphone games.

Summary: Diamond Blankets for Cooling Future Chips

As technology advances, the heat generated by powerful computing devices is becoming a significant issue. High-performance chips, like CPUs and GPUs, produce excessive heat, which can lead to reduced performance and damage. To address this, researchers at Stanford University have developed a method to integrate diamond, a highly thermally conductive material, into chips to better manage heat.

Key points include:

1. Heat Problem: Modern chips with many transistors generate heat that can create hot spots, affecting performance and reliability.

2. Diamond Solution: Diamond is an excellent heat conductor and can be integrated into chips at lower temperatures, allowing it to spread heat effectively without damaging delicate components.

3. Research Breakthrough: The Stanford team has successfully grown a thin layer of polycrystalline diamond on chips at temperatures safe for electronic components, significantly reducing device temperatures.

4. Testing and Results: Initial tests with gallium-nitride transistors showed a temperature drop of over 50°C, improving performance. This technology could be crucial for future chip designs, especially for advanced 3D stacked architectures.

5. Industry Collaboration: The research is attracting interest from major companies like Samsung and TSMC, aiming to integrate diamond thermal solutions into various electronic devices.

6. Future Potential: If successful, this diamond-based cooling method could transform thermal management in electronics, enabling higher performance without the constraints of heat buildup.

Overall, the integration of diamond into chip architecture offers a promising solution to one of the biggest challenges in modern computing.

Summary of Luau Performance Features

Luau aims to provide high-performance code primarily for gameplay, focusing on two goals: improving the speed of idiomatic code and enabling further optimizations through careful tuning. It emphasizes stable performance in interpreted contexts since JIT compilation isn't available on many platforms.

Key Features:

1. Fast Bytecode Interpreter: Luau has a highly tuned bytecode interpreter, which can match the performance of LuaJIT in certain workloads. The interpreter uses advanced techniques to achieve efficiency while maintaining portability.

2. Optimizing Compiler: Luau employs a multi-pass compiler that generates bytecode from source code, allowing for better optimizations. It can perform optimizations like constant folding and upvalue optimizations based on type information.

3. Debugger Efficiency: Luau avoids traditional debugging hooks to maintain performance, using first-class support for breakpoints instead.

4. Inline Caching: This feature speeds up table and global variable access by predicting hash slots for field lookups.

5. Fast Method Calls: Method calls are optimized through specialized instructions and caching techniques to reduce overhead.

6. Optimized Built-in Functions: Certain built-in functions are optimized for speed through a mechanism that bypasses typical overhead.

7. Table Optimizations: Luau enhances table operations, including efficient iteration and length calculations. It recommends using specific methods for table creation and modification to maximize performance.

8. Native Vector Math: Luau supports native 3-component floating-point vectors, optimizing performance for mathematical operations.

9. Garbage Collector Improvements: The garbage collector is incremental, aiming to minimize pauses during execution. It includes optimizations for sweeping and pacing to maintain performance.

10. Closure Caching: Reuses function objects for closures when they are semantically identical, reducing memory allocation overhead.

11. Memory Allocator: Luau uses a specialized memory allocator to optimize common allocation patterns, improving overall performance.

12. Advanced Optimizations: At higher optimization levels, Luau can perform function inlining and loop unrolling to further speed up execution.

Overall, Luau is designed to provide robust performance improvements while maintaining compatibility with existing Lua code.

Fast TypeScript Analyzer (FTA)

FTA is a rapid tool for analyzing TypeScript code, built using Rust. It helps developers understand the complexity and maintainability of their code by providing straightforward analytics.

Key Features:

• Speed: Analyzes up to 1600 files per second on standard hardware.
• Supports JavaScript: In addition to TypeScript, it can analyze JavaScript code.
• Scoring System: Generates an overall FTA Score for each file, where a lower score indicates better quality. It also provides detailed metrics like cyclomatic complexity and Halstead metrics.

Usage: To start using FTA, you can run the command:

npx fta-cli path/to/project

This will analyze the specified project and display the results in a table format, indicating the number of lines, FTA score, and an assessment of each file.

Example Output:

• For a file named index.js, it may show:
  • Lines: 212
  • FTA Score: 64.43
  • Assessment: Needs improvement

Additional Information:

• The tool is open-source, allowing users to contribute and discuss on its GitHub repository.
• Users can explore more metrics and functionalities through the Playground and detailed documentation.

Get Involved: Interested users can participate in its development on GitHub.

European police have arrested seven people and dismantled a significant cybercrime network, known as Operation SIMCARTEL, that created nearly 50 million fake online accounts for fraudulent activities. This operation involved collaboration between police in Latvia, Austria, Estonia, and Finland.

Key details include:

• Authorities seized 1,200 SIM boxes with 40,000 active SIM cards, five internet servers, and two illegal service websites.
• The network provided temporary phone numbers to criminals, helping them bypass security measures and create fake accounts for scams like investment fraud and phishing.
• Significant financial losses were reported, with around €4.5 million lost in Austria and €420,000 in Latvia.
• Police also confiscated €431,000 from criminals' bank accounts and approximately $516,000 in cryptocurrency.
• The investigation was supported by Europol and the Shadowserver Foundation, which helped analyze and dismantle the criminal infrastructure.

This operation highlights the ongoing battle against cybercrime and the collaborative efforts of law enforcement agencies across Europe.

The text discusses the importance of formalizing mathematics, particularly using computer systems like Lean, beyond just catching errors. Here are the key points:

1. Purpose of Formalization: Writing formal proofs helps ensure accuracy in mathematics, similar to how safety checklists work in engineering. It's not just about correcting mistakes; it brings additional benefits.

2. Personal Motivation: The author enjoys the process of formalizing math as it combines their interests in math, computers, and puzzles.

3. TypeScript Analogy: The author compares formalizing math to using TypeScript, a programming language that helps catch errors. However, the real benefits of TypeScript extend beyond error detection:

   • It enhances development tools, allowing better navigation and refactoring of code.
   • It serves as a design language, enabling teams to specify designs before implementation.
   • It provides immediate feedback while coding, which can be very helpful.

4. Benefits of Lean for Mathematics:

   • It supports various mathematical tools, offering features like clickable definitions and automatic documentation.
   • It allows for better analysis of mathematical trends and dependencies between theorems.
   • It facilitates version control, helping track changes and dependencies in mathematical results.

5. Efficiency and Acceptance: While formalization may require proving many trivial statements, it could make mathematical processes more efficient and enjoyable. Notably, the author mentions that even formal statements alone can be valuable.

6. Future of Mathematics: The text concludes by questioning if these benefits will encourage mathematicians to adopt new tools and methods, despite their steep learning curves. Only time will tell if this shift will happen.

Summary: How to Make a Smith Chart

A Smith chart is a graphical tool used in electrical engineering, representing the mapping of a Cartesian grid through a specific mathematical function. This guide focuses on how to create a Smith chart, not on its applications.

1. Basic Concept: The Smith chart is derived from the function ( f(z) = \frac{(z - 1)}{(z + 1)} ), which transforms points in the right half of the z-plane to points in the w-plane.

2. Möbius Transformations: The function is a type of Möbius transformation, which can map circles and lines in the z-plane to circles and lines in the w-plane.

3. Mapping Points:

   • The imaginary axis in the z-plane maps to the unit circle in the w-plane.
   • The right half-plane gets mapped inside the unit circle.
   • Vertical lines in the z-plane become circles in the w-plane, tangent to the unit circle at ( w = 1 ).
   • Horizontal lines in the z-plane also map to circles, which pass through the point ( w = 1 ).

4. Spacing: The transformation creates an uneven spacing in the w-plane. To create a usable Smith chart, the original grid in the z-plane must be designed with more vertical lines near the origin than further out.

This process creates a Smith chart that visually represents complex impedance in a way that is useful for electrical engineering. The next post will discuss how to adjust spacing for better usability.

Summary of Mesh2Motion

Mesh2Motion is a free and open-source web application designed to animate 3D models. It supports humanoid, four-legged, and bird creatures and allows users to import models in GLB, GLTF, and FBX formats. Key features include:

• Rigging Options: Users can choose human or animal skeletons and easily position them.
• Undo/Redo Function: Correct mistakes easily while working on animations.
• Animation Export: Export multiple animations at once in the widely-used GLB format, with access to a human animation library from Quaternius.

The project aims to provide a user-friendly tool for animating 3D models for web and game development, ensuring everything is available for both personal and commercial use. You can find the source code on GitHub and report any issues or give feedback there as well.

For more information, visit the GitHub page: Mesh2Motion GitHub or follow @scottpetrovic on social media.

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Charlie and Jackson, the founders of Conductor, started their company after leaving their jobs at Point72 and Netflix. They met while playing ultimate frisbee at Brown eight years ago. Conductor is a tool that helps engineers at leading companies like YC, Linear, and Notion improve their work processes. One user praised it for significantly enhancing their productivity.

The founders believe that as technology evolves, people will shift from writing code to managing teams of AIs, creating a need for new tools, and they want help to design these tools.

Conductor's team currently consists of three members, and they are looking to hire a versatile person who can generate ideas, communicate with users, design, and build products. The ideal candidate should prefer a fast-paced work environment, take pride in their work, and have strong opinions about software. Experience with Typescript is not mandatory, as the focus is on the ability to learn.

In terms of compensation, Conductor aims to offer competitive salaries and substantial equity, allowing employees to have a significant impact. They provide health benefits, a 401k match, and prioritize overall well-being. Employees receive the necessary tools for productivity and have the freedom to manage their work expenses without bureaucratic hurdles.

Conductor encourages employees to contribute ideas for benefits and improvements, embracing a flexible and innovative company culture.

Summary of Mistakes Engineers Make in Code Reviews

In recent years, code reviews have become more crucial as engineers spend significant time evaluating code generated by AI tools. However, many engineers struggle with effective code reviews. Here are the key points to improve code review practices:

1. Look Beyond the Diff: Don't focus only on the differences in code (the diff). Valuable insights come from understanding the entire codebase. For example, noting that a method already exists elsewhere or suggesting better file organization can greatly enhance code quality.

2. Limit Comments: Aim to provide no more than five or six comments in a review. Excessive comments can overwhelm the reviewer and dilute the importance of key feedback. Instead of commenting on every instance of a style issue, summarize the change in one comment and let the engineer make the corrections.

3. Avoid Personal Style Imposition: Don't review code based on how you would write it. Recognize that there are multiple acceptable approaches to solving problems in code. If you find a difference in style but it’s still acceptable, approve it without comment to avoid unnecessary conflicts.

4. Use Clear Review Statuses: Clearly indicate whether you approve, have comments, or are blocking a review. Leaving unclear feedback can create confusion about whether changes can be merged.

5. Favor Approvals: In general, most code reviews should result in approvals unless there are significant issues. Excessive blocking reviews often indicate structural problems within teams.

6. Final Thoughts: Each engineer may have different priorities in code reviews, but focusing on essential feedback, limiting comments, and being supportive will lead to better collaboration and code quality.

These principles also apply when reviewing code from AI, with an emphasis on maintaining quality oversight.

Summary of "The Goon Squad" by Daniel Kolitz

The article discusses the rise of a new subculture known as "gooning," which revolves around a specific form of masturbation that is communal and goal-oriented. The term gained prominence after the tragic death of a young man, Nautica Malone, who became a symbol for this movement. Gooning involves reaching a "goonstate," a euphoric experience achieved through prolonged sessions of edging—masturbating without climaxing.

Gooners, typically young men, often share their experiences and rituals online, creating spaces like "gooncaves" where they consume porn together. The community thrives on platforms like Discord, which cater to their interests. The culture has evolved significantly alongside the accessibility of online pornography, with many gooners consuming extreme content from a young age.

Kolitz explores the psychological effects of this culture, noting that many participants use gooning as a coping mechanism for loneliness and societal disconnection. The article reveals that the goonstate is not frequently attained, but the rituals surrounding it foster a sense of community among participants.

While some gooners engage in "feeding" (sharing curated porn) and "wankbattling" (competitive porn selection), others embrace a more extreme identity as "pornosexuals," who fulfill their sexual needs entirely through pornography. The article raises concerns about the potential for addiction and the negative impact of this lifestyle on personal relationships.

In conclusion, Kolitz reflects on the broader implications of gooning as a symptom of a culture increasingly retreating from real-life connections, driven by the overwhelming presence of digital content and community.

Steinar H. Gunderson discusses his experiences with modern perfect hashing for strings, particularly his own implementation, which was not widely adopted despite being faster than existing solutions like gperf. Perfect hashing is a method to map a known set of strings to unique integers without collisions.

Key points include:

1. Problem Definition: The goal is to create a system that maps a fixed set of strings to specific integers while rejecting others, similar to a hash table but optimized for known string sets.

2. Implementation Strategy: Gunderson splits strings by length to simplify processing, allowing for optimization. He notes challenges with certain techniques, like using PEXT (a bit extraction instruction) which may not work on all systems, particularly non-x86 architectures.

3. Magic Numbers: He discusses using "magic" numbers (specific multipliers) to reduce collisions when hashing. This technique, borrowed from computer chess, allows for effective indexing of strings.

4. Performance: His implementation is about twice as fast as gperf and results in smaller compiled code. He emphasizes the importance of optimizing both speed and memory usage.

5. Finding Magic Values: Finding good magic numbers requires trial and error, and he introduces the "killer heuristic" for faster checks to avoid collisions in hash buckets.

6. Flexibility in Approach: Depending on the number of strings, he notes that simpler methods like direct comparison can be effective, especially for smaller sets.

Gunderson concludes by suggesting there’s room for improvement in the field of perfect hashing, inviting others to explore modern implementations.

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Language models are getting better, but they still struggle with multi-digit multiplication. This study explores why this happens by analyzing a model that successfully learns multiplication through an implicit reasoning process. Here are the key findings:

1. Long-range Structure: The model is able to handle the long-range connections needed for multi-digit multiplication.
2. Mechanism: It uses attention to create a structure that helps it remember and retrieve partial products during calculations.
3. Geometry: The model effectively combines digit pairs and represents them in a way that is both smart and efficient, which standard models do not do.

The researchers also found that typical fine-tuning methods lead to a model that misses these important long-range connections. They tested their ideas by adding a new loss function that helps the model learn to keep track of ongoing sums, which improved its ability to multiply. Overall, the study highlights a problem in how Transformers learn long-range dependencies and shows how a better approach can fix this issue.

On October 20, 2025, a developer announced a surprise Halloween release of mod_blog, a blogging tool that normally receives updates at Christmas. This time, the update involves removing some long-standing features due to low usage and bugs.

The developer explained that they had previously removed features that were no longer useful, but this update is different because it eliminates functionality that's been part of the code since the beginning. They primarily stopped using the web interface for writing posts because they switched to their own markup language, leading to unused code.

During a code fix, the developer found a bug related to C programming language rules, which they had missed because of their infrequent use of the web interface. After correcting the bug, they also decided to remove the email notification feature due to spam issues and low interest, opting instead for a new notification method.

Overall, they removed over 3,000 lines of code from mod_blog, which they found to be a bit daunting but necessary for maintenance. This release is marked by the spooky theme of Halloween, symbolizing the unsettling experience of removing old features.

Product Update Summary: Typst 0.14 (October 24, 2025)

Typst 0.14 has been released, featuring important updates aimed at improving accessibility and usability for various document types. Here are the key points:

1. Accessibility by Default: Typst now automatically creates accessible PDF documents, making it easier to meet accessibility regulations. Users can enable stricter checks for compliance.

2. PDF Features:

   • PDFs can now be used as images in documents, enhancing the handling of complex illustrations.
   • Support for multiple PDF standards has been expanded, allowing users to choose the best format for their needs.

3. Character-Level Justification: This new feature improves paragraph layout by adjusting spacing between characters, resulting in more visually balanced text.

4. Enhanced HTML Export: The HTML export feature has been upgraded, including better semantic mapping of Typst elements to HTML and a new typed HTML interface for easier element creation.

5. Migration to Typst 0.14: Most documents will work as before, with some minor breaking changes and deprecated features. Users are encouraged to check for necessary updates.

6. Community Engagement: A community call is scheduled for November 7th to discuss the new version and gather user feedback.

For more details and to explore the new features, users can open their projects in the web app or run a command line update.

Summary: Interstellar Mission to a Black Hole

The article discusses the potential for interstellar missions to explore black holes, focusing on ideas proposed by Cosimo Bambi from Fudan University. Traditionally, interstellar travel has aimed at targets like Proxima Centauri, but Bambi suggests that exploring nearby black holes could be equally valuable.

The closest known black hole, GAIA-BH1, is about 1,560 light years away, but estimates suggest there may be many more black holes within 20-25 light years of Earth. Detecting these black holes can be challenging, as most are isolated. However, using advanced observational techniques and new telescopes, scientists believe they can identify black holes by studying their gravitational effects on nearby stars.

If a black hole is found closer to us, it could serve as a mission target for future spacecraft. Such missions could help us understand the nature of black holes, test fundamental physics, and explore concepts like event horizons and gravitational waves. Bambi's research also touches on how dark matter might relate to black hole formation, suggesting new ways to detect them through exoplanets.

Overall, the idea of launching an interstellar mission to a black hole presents exciting possibilities for scientific discovery and understanding of the universe.

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The user is frustrated because they added credits to their OpenAI API account but now must go through a verification process that requires sharing personal information with a third-party vendor, which they are uncomfortable with. They requested a refund but were told it's against the policy. As a result, they plan to cancel their ChatGPT Plus subscription, dispute the payment, and switch to a cheaper alternative called Deepseek. They noted that verification is only necessary for GPT-5, while GPT-4o does not require it.

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On October 22, 2025, I spoke at a gathering of Claude Code enthusiasts in San Francisco. My talk focused on a dilemma: while using coding agents with few restrictions (referred to as "YOLO mode") provides great benefits, it also poses significant risks.

Key points from my presentation include:

1. YOLO Mode Benefits: This mode allows coding agents to operate independently, solving complex problems while you focus on other tasks. I shared three recent projects I completed using YOLO mode, showcasing its efficiency.

2. Risks of YOLO Mode: Despite the advantages, using YOLO mode is risky due to potential prompt injection attacks. These occur when untrusted content is merged with trusted instructions, leading to vulnerabilities.

3. Prompt Injection: I described prompt injection as a major threat, especially when coding agents have access to private data. Attackers can exploit this vulnerability to gain control over the agent and potentially leak sensitive information.

4. Sandboxing as a Solution: To mitigate these risks, I emphasized the importance of running coding agents in a sandbox environment, ideally on someone else's computer, to limit potential damage.

5. Sandboxing Challenges: While controlling file access is straightforward, managing network connections to prevent data exfiltration is more complex. Recent updates to Claude Code include improved sandboxing features, using tools like Apple's sandbox-exec command, despite its deprecated status.

In conclusion, while it's tempting to use coding agents freely, it’s essential to do so safely within a sandbox to protect your data.

Transformer-based large models are great for natural language processing and computer vision but struggle with efficiency because of the way they handle input data. Recent methods to improve this have had problems, like losing important meaning or being slow. To solve these issues, we introduce ChunkLLM, a simple and flexible training framework.

ChunkLLM includes two main parts: the QK Adapter (which has Q-Adapter and K-Adapter) and the Chunk Adapter. The QK Adapter is added to each model layer to help compress features and focus on relevant chunks of information. The Chunk Adapter works at the lowest layer to identify boundaries between chunks using context clues.

During training, the main model parameters stay the same while only the QK and Chunk Adapters are trained. We also use a special training method called attention distillation to improve the identification of key chunks. In the inference phase, the model speeds up processing by only selecting chunks when it finds a chunk boundary.

Tests on various long and short text tasks show that ChunkLLM performs similarly to existing models on short texts and retains 98.64% performance on longer texts, with a 48.58% efficiency in key-value cache usage. Remarkably, it can be up to 4.48 times faster than standard Transformers when processing long texts.

The article by Evelina Fedorenko and Rosemary Varley investigates the relationship between language and thought. It explores whether complex thinking is possible without language by examining individuals with global aphasia, who have lost nearly all language abilities but can still perform tasks involving math, logic, music, and navigation. This suggests that thought and language are distinct.

Neuroimaging studies show that brain areas related to language are activated when people process sentences, but not when they engage in non-linguistic tasks like arithmetic or listening to music. The authors argue that many cognitive abilities, such as arithmetic, executive functions, theory of mind, music processing, and spatial navigation, do not rely on language and are supported by different brain regions.

The article emphasizes that while language processing involves specific brain areas, damage to these regions affects language abilities but not other cognitive functions. This indicates that language is not necessary for various forms of complex thought. Overall, the findings support the idea that thought can exist independently of language.

The text criticizes the practice of using AI-generated feedback, like from ChatGPT, in work reviews without adding personal insights. The author expresses frustration when someone simply copies and pastes AI suggestions instead of providing their own analysis. They emphasize that AI lacks the contextual understanding that team members have, and relying on it can lead to confusion and extra work for others.

Good feedback should be specific and based on the reviewer’s understanding, not just a regurgitation of AI output. While AI can be a helpful tool for brainstorming and learning, it should not replace genuine thought and engagement in reviews. Team members should take responsibility for their reviews and provide meaningful, context-aware feedback.

Summary of VisiCalc and its Impact

VisiCalc, developed by Dan Bricklin and Bob Frankston in 1978, was the first computerized spreadsheet and played a crucial role in the success of the Apple II. It allowed users to perform complex calculations and was so influential that it's estimated 25% of Apple II sales were driven by the desire to use VisiCalc.

The software introduced a user-friendly interface and features that remain foundational in modern spreadsheets, such as the A1 cell notation and the "slash menu" for commands. VisiCalc's tutorial effectively taught users how to utilize its functions, showcasing its flexibility for various applications, including complex agricultural calculations.

Despite its limitations, such as a 40-column display and basic graphing capabilities, VisiCalc's design and functionality laid the groundwork for future spreadsheet software. Its legacy persists in contemporary tools like Excel, which still incorporate many of its core features.

VisiCalc's adaptability has allowed it to remain relevant even in 2025, demonstrating its lasting impact on data management and calculations across different fields. However, users today may find challenges in transitioning data to modern applications and the lack of advanced features like graphing.

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Summary of "The Missing Semester of Your CS Education"

This course addresses an important topic often overlooked in computer science classes: mastering the tools you use. While traditional classes focus on advanced subjects, they do not teach students how to effectively use essential tools like the command line, text editors, and version control systems.

Key Points:

• Understanding and using these tools efficiently can save time and help solve complex problems.
• The course covers various topics over several days, including:
  • Shell and scripting
  • Text editors (like Vim)
  • Data wrangling
  • Command-line environment
  • Version control (Git)
  • Debugging and profiling
  • Metaprogramming
  • Security and cryptography
• Lectures are recorded and available on YouTube.

The course is co-taught by Anish, Jon, and Jose, and is available not just at MIT but also shared online for broader access. Translations of the course materials are encouraged and can be submitted for inclusion.

Acknowledgments go to those who helped make the course possible through resources and support.

A new paper published in Physical Review Letters discusses important findings in a specific area of research. You can read it for more detailed information by following this link: Physical Review Letters Paper.

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In 1922, Johnny Hopson, known as the "Father of the Tops," discovered a unique butterfly in the snow in Australia. This butterfly was later named the flame hairstreak by Dr. Gustavus Athol Waterhouse, who recognized it as a new species. However, in 2016, a scientist named Dr. Michael Braby found that a supposed specimen of this butterfly was actually a painted fake.

The story takes a darker turn with Colin Wyatt, a British collector who stole thousands of butterfly specimens from Australian museums in the late 1940s. His thefts were discovered in 1947 when missing specimens were reported, leading to an investigation that revealed Wyatt had taken many rare butterflies and shipped them to England.

Wyatt, who had ingratiated himself with the scientific community, confessed that his thefts were driven by personal issues. His actions raised serious concerns about the security of museum collections and the trustworthiness of amateur collectors. Although many stolen specimens were recovered, the impact of Wyatt's thefts continues to be felt in the scientific community today, as researchers like Braby work to restore the integrity of collections and address the historical context of collecting practices.

The text discusses a new camera called Roc Camera, which aims to capture authentic photos in a world where images are often manipulated or created by AI.

Key Points:

• The Roc Camera uses advanced technology, including a 16MP sensor and a Raspberry Pi, to take unique photos.
• It creates a Zero Knowledge Proof of the photo's data to verify its authenticity.
• The camera is designed to help users capture verifiably real moments, addressing the confusion between real and AI-generated images.
• It is currently accepting orders for $399, with shipping expected in 2-3 weeks.

Overall, Roc Camera is positioned as a solution to the growing problem of image authenticity in the digital age.

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Summary of Clojure Zippers

Clojure zippers are a unique tool for navigating and modifying data structures like vectors, maps, and XML. They allow you to move through a collection (or tree) both vertically (up and down) and horizontally (left and right), and to add, edit, or delete elements.

Key Points:

1. Basics of Zippers: A zipper is a wrapper that lets you traverse and manipulate data structures efficiently. It maintains a "location" that includes both the data and the position within it.

2. Navigating with Zippers:

   • You can move down to children or up to parents.
   • You can move left or right among siblings.
   • Each movement creates a new location without changing the original data.

3. Creating a Zipper: To create a zipper, you need to define functions that determine if a node is a branch and how to retrieve its children. This is done using the zip/zipper function from the clojure.zip package.

4. Example: For a vector [1 2 3], you can wrap it in a zipper and navigate to access specific elements. For instance, moving right from the first element will lead you to the second element.

5. Null Handling: If you try to navigate outside the bounds of the collection, the zipper will return nil, indicating an invalid location. Care should be taken to avoid dead ends.

6. Complex Structures: Zippers can also work with nested structures, allowing you to navigate through layers of data, such as lists within lists.

7. Built-in Zippers: Clojure provides built-in zippers, like vector-zip for vectors and xml-zip for XML, which simplify navigation for specific data types.

Understanding zippers can enhance your programming skills in Clojure by providing a powerful way to work with complex data structures.

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The text explains why /dev/null can be considered an ACID-compliant database, focusing on four key properties:

1. Atomicity: Operations are either fully completed or not at all. Anything written to /dev/null is either discarded completely or not written.

2. Consistency: The system always remains in a valid state. /dev/null is always empty, regardless of what is written to it.

3. Isolation: Multiple processes can write to /dev/null simultaneously without any conflicts, as nothing is stored.

4. Durability: Once a write operation occurs, it remains effective, even after a crash. /dev/null will always contain nothing.

However, the only downside is that it offers 0 bytes of free storage. For more space, you need to contact the author directly.

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The text states that the copyright for the Forum of Incident Response and Security Teams, Inc. covers the years 2015 to 2025, and all rights are reserved.

Summary of LightlyStudio

LightlyStudio is an open-source tool designed to help you manage and annotate your data efficiently in one place. It works well on Macbooks with M1 chips and supports various datasets like COCO and ImageNet.

Installation:

• Requires Python 3.8 or higher.
• Install using: pip install lightly-studio

Quickstart:

• You can use example datasets by cloning the provided repository or by using your own datasets.
• Different scripts are available for various tasks like image-only datasets, YOLO object detection, COCO instance segmentation, and COCO captions. Each requires creating a specific Python script and running it.

Python Interface:

• LightlyStudio provides a powerful Python interface to manipulate datasets.
• The main element is the Dataset, which lets you set up data, start the user interface, and perform queries.
• You can load data from different sources, like local folders or cloud storage.

Dataset Features:

• You can access and modify individual samples within a dataset, including attributes like tags and metadata.
• It supports advanced querying to filter and sort samples based on specific criteria.

Selection Feature:

• LightlyStudio allows for automated data selection, helping you choose the most representative and diverse samples, which can improve model training efficiency.

Updates:

• The current version is 0.4.0, released on October 21, 2025.

Contributions:

• Contributions are welcome; users can check the issues page for tasks or suggest new improvements.

For more details, you can visit the LightlyStudio GitHub page.

Counter-Strike's player economy has recently experienced a significant decline, losing about $1.84 billion in value—25%—in just one night. This drop was triggered by a new update from Valve, which allowed players to trade lower-tier cosmetic items for highly sought-after items like Knives and Gloves. Previously, these rare items could sell for prices as high as $20,000, but after the update, their values have plummeted. For example, the Butterfly Knife's price dropped from around $20,000 to approximately $12,000.

The update has caused a rush of sellers trying to recover their investments, resulting in a chaotic trading environment. While some lower-tier items may have increased in value, the overall market for high-end Counter-Strike cosmetics is in turmoil, drawing comparisons to the volatility of NFTs and cryptocurrencies. The future of the market remains uncertain as players and traders await further developments.

The U.S. National Highway Traffic Safety Administration (NHTSA) has started a preliminary investigation into around 2,000 Waymo self-driving vehicles. This investigation follows reports that Waymo's robotaxis may not have correctly obeyed traffic laws regarding stopped school buses. A recent media report showed a Waymo vehicle that initially stopped but then drove around a school bus with flashing lights and a stop sign, putting students at risk.

Waymo, a subsidiary of Alphabet, claims it has already made improvements to ensure its vehicles stop for school buses and plans to release additional software updates. The company emphasized that safety around children is a top priority. The vehicle involved was using Waymo's latest automated driving technology and was operating without a human driver at the time.

This investigation is part of ongoing regulatory scrutiny of self-driving technologies and follows a previous NHTSA investigation into Waymo that concluded without significant penalties after addressing earlier issues.

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Summary: GizmoEdge Takes on the 1 Trillion Row Challenge

GizmoEdge, a distributed SQL engine, successfully tackled the Coiled 1 Trillion Row Challenge using a 1,000-worker cluster on Azure. The objective was to quickly process and summarize one trillion records from a dataset.

Setup:

• The cluster utilized 1,000 workers, each powered by DuckDB and managed by Kubernetes on Azure.
• Each worker had 3.8 vCPUs and 30 GiB of RAM, with the entire setup requiring around 63 nodes.

Performance Results:

• A basic query counting all rows took less than 0.5 seconds.
• An aggregation query (finding min, max, and average measurements by station) completed in under 5 seconds, processing about 2.4 billion rows per grouped result.

How GizmoEdge Works:

• It parses SQL queries and distributes tasks among workers while ensuring secure communication through TLS-encrypted channels.
• Each worker verifies data integrity and executes queries in parallel, sending results back to the server for aggregation.

Heterogeneous Capability:

• GizmoEdge can run across various devices, from cloud servers to IoT devices.

Additional Information:

• GizmoSQL, another product from GizmoData, also completed the challenge on a single-node setup, processing the dataset in just over 2 minutes.
• GizmoEdge remains in pre-production, seeking partners interested in exploring its capabilities for large-scale data analytics.

For more details, visit the challenge's official repository and check out the performance of GizmoSQL.

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The text discusses the use of memory maps to improve file access speed in applications, particularly in the context of Go programming. Here are the key points:

1. System Calls and Performance: Making system calls is slow because they involve entering the kernel. For better performance during disk I/O, memory maps can be used.

2. What are Memory Maps?: Memory maps allow a file to be treated as part of the virtual memory, enabling faster access. Instead of seeking and reading, you can read directly from a pointer to the memory-mapped file.

3. Performance Comparison: A Go library demonstrated significant performance improvements using memory maps:

   • Random lookups: 3.3 ns/op with mmap vs. 416.4 ns/op with ReaderAt.
   • Iteration: 1.3 ns/op with mmap vs. 333.3 ns/op with ReaderAt.

4. Downside of Memory Maps: Writing to a memory map can be inefficient due to page faults. Writing causes the CPU to allocate new memory pages and read data from the file, which is slow. Benchmarks showed writing through memory maps can take much longer (up to 1870 ns/op) compared to other methods.

5. Real-world Application: The author has worked on an HTTP-backed filesystem for high-performance computing, where replacing slow database lookups with memory maps led to a 25x performance improvement.

In summary, while memory maps significantly enhance read performance, they are not ideal for writing, which can be inefficient.

SierraDB: A Distributed Event Store Built in Rust

Overview: SierraDB is a new type of database specifically designed for event sourcing, a method of storing data that ensures you can track all changes over time. Traditional databases often don’t meet the unique needs of event sourcing, which inspired the development of SierraDB.

Key Features:

• Designed for Event Sourcing: Unlike general-purpose databases, SierraDB is built to meet the specific requirements of event sourcing, including efficient storage and processing of events.
• Built in Rust: Rust provides consistent performance and memory safety without the delays caused by garbage collection, which is beneficial for high-performance databases.
• Scalable Architecture: SierraDB supports horizontal scaling, allowing users to start with one node and expand to many nodes as needed, optimizing for both performance and organization of data.
• Gapless Sequence Numbers: Each event in a stream has a unique, incrementing version number, ensuring no events are lost and enabling efficient conflict management.
• Integrated Subscriptions: Users can easily subscribe to events and receive updates in real-time, making it simpler to keep projections and event handlers synchronized with the event log.
• Efficient Data Handling: Events are stored in append-only files, allowing for immutable data, which simplifies indexing and ensures performance.

Operational Design:

• Partitions and Buckets: SierraDB organizes data into partitions and buckets, allowing for efficient processing of writes and reads, while maintaining high concurrency.
• Watermark System: This system ensures that users can read events consistently without gaps, even if some writes are still pending confirmation.
• Consensus Mechanism: SierraDB uses a unique approach for distributed consensus that allows for fast reads without requiring coordination for every operation.

User Experience:

• Easy to Use: SierraDB uses the RESP3 protocol, making it compatible with existing Redis clients. This means developers can start using it with minimal setup.
• Observability Tools: An interface called SierraDB Inspector allows users to visualize and explore their events easily, enhancing debugging and understanding of event flows.

Future Goals: SierraDB is currently stable and aims to become a production-ready, open-source event store. The developer encourages contributions to improve documentation and features.

Getting Started: Developers can easily set up SierraDB using Docker and start experimenting with event sourcing right away.

The article discusses how algorithms, particularly pricing algorithms used by sellers, can unintentionally lead to higher prices in the market.

Key Points:

1. Competition vs. Collusion: Traditionally, merchants compete to set lower prices. However, there’s a risk of collusion, which is illegal. Nowadays, many sellers use algorithms that adjust prices based on market data, complicating regulation.

2. Algorithmic Behavior: Research has shown that algorithms can learn to collude without being explicitly programmed to do so. For example, when two algorithms compete, they may respond by raising prices instead of lowering them, creating a situation similar to collusion.

3. Regulatory Challenges: Regulators typically look for explicit collusion to maintain fair pricing, but algorithms do not meet in secret. This makes it difficult to identify when prices are unfairly high.

4. Game Theory Insights: The research applies game theory to understand the dynamics of these algorithms. Even algorithms designed to optimize profit can lead to high prices in unexpected ways.

5. Potential Solutions: While some propose banning certain types of algorithms to prevent collusion, it’s complicated. Algorithms that are simple and nonresponsive might seem harmless but can lead to price increases.

6. Ongoing Research: Experts acknowledge that there’s still much to learn about how algorithmic pricing affects the market, and finding effective regulatory measures is crucial.

Overall, the interplay between algorithms and pricing strategies poses significant challenges for ensuring fair market prices.

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Summary of "The Great SaaS-Lighting: How IT Users Got Gaslit"

The article critiques the Software as a Service (SaaS) model, arguing that it often prioritizes customer lock-in over genuine customer satisfaction. Major companies like Microsoft and Google create products that users feel compelled to buy, rather than ones that truly meet their needs. While many SaaS vendors employ customer success managers to assist users, the focus tends to be on keeping customers subscribed rather than ensuring their overall success.

The author highlights the dangers of relying on best practices and industry standards, which can lead to mediocrity and fail to adapt to changing circumstances. Many software applications offer similar solutions, lacking true innovation. The SaaS landscape is compared to a 1980s shopping mall, where options are predictable and controlled, with major companies dominating the market.

In conclusion, the future of technology should focus on tailored solutions that meet unique needs rather than conforming to a one-size-fits-all approach. The author advocates for more personalized and effective information systems.

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Summary:

Claude is rolling out a memory feature for Pro and Max plan users, which allows it to remember project details and preferences, making it easier to manage ongoing work. Users can control what Claude remembers and can have incognito chats that don’t save to memory. The memory feature has been tested for safety, ensuring that it doesn't reinforce harmful patterns or compromise sensitive topics.

Memory is designed to enhance productivity by keeping track of team processes and client needs while separating information by project. Users can view and edit what Claude remembers, and the feature is optional. Incognito chat provides a way to converse without saving any details, ideal for sensitive discussions.

To start using memory, users can enable it in Settings and ask Claude about past work to see what it remembers. This rollout includes a focus on responsible deployment and ongoing evaluation of the memory feature.

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The author is introducing a new multilingual model in their Chonky series of text-splitting models. This new model builds on previous versions that were mainly trained on English texts. The latest model, called mmBERT, has been trained on a large dataset covering 1833 languages.

To improve the model's capabilities, the author expanded the training data to include books from Project Gutenberg in various languages and made adjustments to better handle real-world data. However, evaluating the model has been challenging due to the lack of labeled datasets for non-standard text formats.

The author attempted to fine-tune a larger version of mmBERT, but it did not perform as well as the smaller model. They encourage users to try out the new multilingual model and provide feedback.

Links to the new model, all Chonky models, and the Chonky wrapper library are provided for those interested.

Summary: The Search Problem

Key Insight: Binary search trees (BSTs) are efficient in theory (O(log n)), but when searching large datasets stored on disk, they become slow due to high disk read times. In contrast, B-trees are designed to minimize disk reads, making them far superior for real-world applications like file systems and databases.

1. Initial Experiment: The author implemented a binary search tree for a file system project. Searching 100,000 files was quick in RAM but took 380 milliseconds once simulated disk I/O was considered. This was much slower than expected, prompting a deeper investigation.

2. The Problem with Binary Trees: While BSTs perform well in memory, their efficiency diminishes with disk access, where each comparison can take significantly longer (up to 10 milliseconds). This can lead to long search times, particularly when many files are involved.

3. B-Trees as a Solution: B-trees improve performance by allowing each node to store multiple keys, resulting in fewer disk reads. For example, searching one million files might only require three disk reads with a B-tree, compared to dozens with a BST.

4. Real-World Applications: B-trees are widely used in various systems, including:

   • File Systems: ext4 and NTFS use B-trees for indexing files, allowing quick access.
   • Databases: B-trees enable rapid searching and indexing, significantly speeding up queries.
   • Version Control: Git uses B-tree-like structures for efficiently managing large collections of files.

5. Performance Comparison: Benchmarks showed that B-trees consistently outperformed BSTs, especially under adverse conditions like sequential data insertion, where BSTs can degenerate into linked lists.

6. Lessons Learned:

   • Balanced structures are not always optimal for disk performance.
   • Simplicity can lead to inefficiencies in real-world scenarios.
   • It's essential to measure performance rather than rely solely on theoretical analysis.

7. Philosophical Shift: Understanding the medium (disk vs. memory) and its costs (latency, bandwidth) is crucial for designing efficient data structures. B-trees exemplify how to align data structures with the realities of hardware.

In conclusion, B-trees are essential for efficient data management in modern computing, making them vital for anyone involved in systems design or software engineering.

WebDAV Isn't Dead Yet

The author discusses the relevance and utility of WebDAV, especially as alternatives like S3 become dominant. Here are the key points:

• Current State of File Transfer Protocols: FTP is outdated, and SFTP relies too much on SSH. Amazon's S3 has become the go-to for file storage, which benefits Amazon but causes difficulties for users needing simpler solutions.

• Who Benefits from WebDAV?: Individuals working on personal projects or self-hosting often don't need the complexities of S3. They require basic features: authentication, file writing, file syncing, and some privacy for stored files. They don't need advanced features like versioning or complex permissions.

• Accessing WebDAV: Many tools can connect to WebDAV, including MacOS Finder, Windows Explorer, rclone, and popular FTP clients. Most web servers support it, and it can be easily integrated with existing setups.

• WebDAV’s Continued Relevance: WebDAV is still useful and widely supported, even if some consider it outdated. It underlies protocols like CardDAV and CalDAV for syncing contacts and calendars.

• Using WebDAV with Apache: The author shares a specific setup using Apache with LDAP authentication, which allows for private user directories. This setup gives users secure access to their files.

• Applications: The author uses WebDAV for various applications, including note-taking and media management.

In conclusion, despite its perception as outdated, WebDAV is still a viable and useful solution for many users.

The widespread use of large language models (LLMs) has led to repetitive and low-quality text, known as "slop," making AI-generated content easily identifiable. To address this issue, we developed Antislop, a framework with tools to detect and remove these overused phrases.

Antislop includes three main components:

1. Antislop Sampler: This tool reduces unwanted phrases during text generation without losing vocabulary.
2. Automated Pipeline: This system identifies common slop patterns in LLM outputs compared to human writing and creates training data for improvement.
3. Final Token Preference Optimization (FTPO): A new fine-tuning method that adjusts specific tokens to remove slop patterns effectively.

Our research shows that some slop phrases are used over 1,000 times more in LLM outputs than in human text. The Antislop Sampler can suppress over 8,000 patterns while keeping text quality high, whereas traditional token banning fails after just 2,000 patterns. FTPO achieves a 90% reduction in slop while maintaining or even enhancing performance on various tasks. In contrast, another method called DPO reduces slop less effectively and harms writing quality. We have made all our code and results publicly available.

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Here’s a simplified summary of the key points regarding Rust's ownership and borrowing:

1. Ownership Structure: In Rust, ownership is tree-shaped, meaning each object can have one owner and may have multiple children. An object must be owned by one parent.

2. Borrowing Rules:

   • Mutable Borrow Exclusiveness: If one mutable borrow exists, no other borrows can occur simultaneously.
   • Contagious Borrowing: Borrowing a child object also borrows its parent and ancestors, which can lead to complications.

3. Handling References:

   • If references are tree-structured, they are straightforward. Shared references complicate things, especially with mutable objects.
   • For immutable shared objects, use scoped borrowing or reference counting (Rc or Arc).
   • For mutable shared objects, or if there are cycles in references, you face more challenges.

4. Common Issues: Many problems arise when trying to borrow in ways that conflict with Rust's rules, especially with contagious borrowing.

5. Workarounds for Borrowing Issues:

   • Data-oriented Design: Avoid unnecessary getters and setters; make fields public if possible.
   • Split Borrowing: Borrow different parts of data separately.
   • Deferred Mutation: Instead of mutating data directly, queue mutation commands and execute them later.
   • Avoid In-place Mutation: Create new data versions instead of modifying existing ones.

6. Deferred Mutation Benefits: This method allows for easier debugging, parallel processing, and can improve performance by treating mutations as commands that are executed later.

By using these strategies, you can navigate Rust's borrowing system more effectively and avoid common pitfalls, especially for newcomers.

The text discusses the disconnect between technical experts and builders of functional software, particularly in the AI space. When a working app is launched, technical experts often provide critical feedback on potential issues, focusing on technical flaws. However, many of these apps are successful and generating revenue, even if they don't meet ideal technical standards.

The author highlights that while technical concerns like race conditions and database issues are valid, most applications never reach a scale where these problems significantly impact users. Successful builders prioritize solving real user problems over adhering to complex technical requirements.

The key message is that focusing on product-market fit is more important than perfecting the technology. Builders should concentrate on meeting the needs of their current users rather than worrying about hypothetical issues that may arise in the future.

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Summary of VST 3.8 SDK Release

Steinberg Media Technologies has released the VST SDK version 3.8. Key updates include:

1. New Licensing: VST 3 is now open source under the MIT license.
2. MIDI Support: Introduced new interfaces for MIDI 2.0 and added missing controller numbers for MIDI 1.0.
3. Wayland Support: Added preliminary support for Wayland on Linux with new interfaces and platform UI types.
4. VSTGUI Update: Version 4.15.0 includes:
   • A new Task Concurrency API for managing tasks in the background.
   • Support for custom view layouts and a grid view similar to CSS Grid.
   • New features like scripting for UIDescription and enhancements to text and scroll views.
5. Documentation: Updated to reflect the new licensing model and VST usage guidelines.
6. CMake Fixes: Resolved issues related to symlinks and toolset configurations.
7. Examples and Helper Classes: Added support for new MIDI enums and fixed various bugs in validators and the VST3PluginTestHost.

The SDK can be downloaded from Steinberg's website, and additional support for third-party developers is available on GitHub.

A major poker fraud scheme has been uncovered, involving high-profile sports figures and sophisticated technology. The scheme used X-ray card tables, secret cameras, and special glasses to cheat wealthy gamblers out of at least $7 million in illegal poker games. Prosecutors say this operation, compared to a Hollywood movie, involved members of mafia crime families and led to over 30 arrests, including former NBA player Damon Jones and Portland Trail Blazers coach Chauncey Billups.

The fraudulent games operated since 2019, targeting unsuspecting players—referred to as "fishes"—who were lured by the chance to play with celebrities. All participants, including dealers and technology, were in on the scam, which used advanced wireless communication to signal who had the best hand. The scheme also involved laundering money through cryptocurrency and shell companies.

Authorities assert that this operation exploited victims across the U.S. and helped fund organized crime. Billups and Jones have been charged with various crimes, while the NBA is cooperating with the investigation.

Diffusion-based large language models (Diffusion LLMs) can generate text quickly and simultaneously, but they often perform slower than traditional models. This is mainly because they don't use a Key-Value (KV) Cache, and their quality drops when generating multiple tokens at once.

To improve this, researchers developed a new KV Cache system that allows for reuse without significant quality loss. They also found that the quality issues in parallel decoding come from breaking token connections. To fix this, they introduced a method that only decodes tokens when the model is confident, which helps maintain quality.

Tests on models like LLaDA and Dream showed a significant increase in speed (up to 27.6 times faster) with only a small decrease in accuracy, making Diffusion LLMs more competitive with traditional models.

Summary of "Creating an IGCSE Pseudocode Interpreter (Part 2)"

The author has completed an IGCSE pseudocode interpreter called beancode, available on GitHub. After a year of development, the author shares insights on its creation and features. The interpreter is built using Python and consists of three main components: a lexer, a parser, and an interpreter.

Key Features:

• The lexer and parser are described as "basic" and "limited," with several quirks in error detection and token handling.
• The interpreter executes pseudocode and includes features like lowercase keywords, file inclusion, and type inference.
• Users can create arrays and matrices and utilize introspection to check variable types.

Unique Aspects:

• The REPL (Read-Eval-Print Loop) allows users to interactively run code and view variable states.
• All variables are global, which can lead to unexpected behavior in sub-scopes.
• Performance varies based on the Python implementation; using PyPy improves speed significantly.

The author plans to maintain this interpreter and aims to develop a more advanced compiler in the future. The project has garnered interest from educators, indicating its potential use as a teaching tool.

Summary:

The xyflow repository offers powerful open-source libraries for creating node-based user interfaces using React and Svelte. It includes four packages: React Flow 12, React Flow 11, Svelte Flow, and a shared helper library.

Commercial Use:

• Personal projects can use these libraries freely, and users can support the project by reporting bugs and sharing their work.
• For organizations using these libraries commercially, support is encouraged through GitHub Sponsors to ensure ongoing development and maintenance.

Getting Started:

• To start using React Flow or Svelte Flow, refer to their respective learning sections.
• Installation commands:
  • For React Flow: npm install @xyflow/react
  • For Svelte Flow: npm install @xyflow/svelte

Basic Usage Examples:

• React Flow:

  • Import necessary components and set up initial nodes and edges to create a flow diagram.

• Svelte Flow:

  • Use Svelte's writable stores for nodes and edges, and set up a similar flow diagram.

Releases:

• The release process involves creating pull requests for updates and using changesets for version management.

Contact and License:

• The libraries are maintained by the xyflow team, and inquiries can be made via their contact form or Discord. They are licensed under MIT.

Summary of How Radios Work

Radios are essential for modern electronics, yet their workings can be complex. This article aims to explain radio basics simply, focusing on antennas, receivers, and signal modulation.

1. Antenna Basics:

   • An antenna can be imagined as a charged capacitor that emits electric fields when charges move back and forth.
   • A good example is the half-wave dipole antenna, which consists of two rods and works best when each rod is a quarter wavelength long (λ/4).
   • The antenna resonates, meaning it can effectively radiate energy when the signal matches its size.

2. Antenna Functionality:

   • Antennas need to convert electrical energy into electromagnetic waves. The more charges that move and the higher the frequency of the signal, the more effective the antenna.
   • There are different types of antennas, like monopoles or arrays, which can improve performance and directionality.

3. Signal Modulation:

   • Modulation is how information is encoded onto a radio wave. Common methods include Amplitude Modulation (AM), Frequency Modulation (FM), and Phase Modulation (PM).
   • Each type alters the carrier wave in specific ways to convey information.

4. Radio Receiver (Superheterodyne):

   • Most radios use a superheterodyne design, which mixes the incoming signal with a specific frequency to convert it to a lower, manageable intermediate frequency (IF).
   • This allows for better filtering and clearer reception of desired signals, avoiding interference from other frequencies.

In summary, radios work by using antennas to transmit and receive signals, which are modulated to carry information. Understanding these concepts helps demystify how radios operate in our daily lives.

The author created ImageConverter.dev to provide a better alternative to free image converter sites that require uploads or slow down conversions. This tool runs entirely on your device, ensuring that your images remain private. It allows you to convert images between JPG, PNG, and WebP formats and works offline once loaded.

ImageConverter.dev uses the Canvas API and WebAssembly for quick conversions directly in the browser, avoiding uploads, tracking, and server costs. The creator aimed to develop a fast, ad-free, and lightweight solution for personal image handling that could replace traditional desktop tools.

The author invites users to try the tool at imageconverter.dev and is seeking feedback on its performance across different browsers and devices.