arXiv has updated its submission rules for review articles and position papers in its computer science category. Now, these types of papers must be accepted by a peer-reviewed journal or conference before they can be submitted to arXiv. Authors need to provide proof of this peer review, or their submissions may be rejected.

This change is due to the overwhelming number of submissions arXiv has received recently, especially with the rise of generative AI making it easier to produce these types of papers. Previously, arXiv accepted a small number of high-quality review articles and position papers at the discretion of moderators, but the current volume has made it unmanageable.

The goal of this policy is to help readers find valuable content more easily and allow moderators to focus on officially accepted types of submissions. Review articles and position papers will still be accepted if they come from reputable sources that conduct thorough peer reviews.

To submit, authors must ensure their paper is accepted by a refereed venue and provide the necessary documentation. Submissions that do not meet these criteria will likely be rejected. Other arXiv categories may implement similar changes if they experience a rise in similar submissions.

SQLite is a file-based database engine used by Jellyfin to store data, but it has limitations, especially regarding concurrency, or multiple processes trying to access the database simultaneously. This can lead to issues like database lock errors, which can cause the application to crash.

The Write-Ahead-Log (WAL) feature of SQLite allows multiple write operations to occur by logging changes separately, but it doesn't eliminate all locking conflicts. Transactions in SQLite can block other operations and, in some cases, may result in unexpected database lock errors, particularly on certain systems.

Jellyfin faced issues with SQLite due to poor handling of parallel tasks, which overwhelmed the database with too many simultaneous write requests. To address this, Jellyfin has implemented strategies for managing database access using Entity Framework (EF) Core, allowing for better control over concurrency through interceptors.

Three locking strategies were introduced:

1. No-Lock: The default behavior, which does not impose any locks, suitable for most operations.
2. Optimistic Locking: Assumes operations will succeed and retries if they fail due to locks.
3. Pessimistic Locking: Ensures only one write operation occurs at a time, blocking all other writes and reads until the operation completes.

Initial tests showed these strategies improved stability for users experiencing lock issues. Jellyfin's approach can be adapted by other developers facing similar concurrency problems, making it a practical solution for managing SQLite's limitations.

No summary available.

When creating HTML tables with JavaScript, many people use methods like innerHTML, which can be insecure. However, there is an older API specifically for HTML tables that allows for better control. This API lets you create and manage table elements such as bodies, rows, cells, headers, footers, captions, and summaries without needing to re-render the entire table with each change.

Here's a simple example of how to create a table from a nested array:

let table = [
  ['one', 'two', 'three'],
  ['four', 'five', 'six']
];
let t = document.createElement('table');
document.body.appendChild(t);
table.forEach((row, ri) => {
  let r = t.insertRow(ri);
  row.forEach((l, i) => {
    let c = r.insertCell(i);
    c.innerText = l;
  });
});

You can access table cells using their index, like t.rows[1].cells[1], which gives you the cell containing 'five'. You can also add or delete rows and cells easily. For example, to add a new row at the end, use t.insertRow(-1).

Despite some quirks in the API, such as the need to use -1 to append rows and the inability to create header cells (TH), it offers a more structured way to manage tables. There is a suggestion to enhance this API by adding features and events, similar to updates made for HTML forms, to improve its functionality and usability.

Summary of CharlotteOS - Catten

Catten is an operating system kernel developed for the CharlotteOS project, intended to be flexible for various uses. It aims to be a monolithic kernel with low-level system calls, inspired by systems like Plan 9 and Fuchsia. Its design allows for different higher-level interfaces and includes a typesafe system namespace that uses URIs for paths. This feature enables network access to namespaces without local mounting, secured by strict access controls.

Currently, Catten is in early development, and contributors are encouraged to participate through their issue tracker, Discord, or Matrix.

Programming Languages

• Catten is written in Rust and specific assembly languages (using Intel syntax for x86_64).

External Dependencies

• C language libraries may be used if approved by maintainers. Other languages are not allowed unless they are high-quality Rust alternatives.

System Requirements

• Processor: x86_64 (with x2APIC LAPIC mode)
• Firmware: UEFI and ACPI
• Memory: Minimum 128 MiB (recommended 1 GiB)
• Storage: Minimum 4 GiB (recommended 64 GiB)
• Device Types: NVMe and USB mass storage
• Input/Output: Supports various display adapters, keyboards, and networking through USB.

Contributing and Licensing

• Contributions are welcome via their communication channels. The project is licensed under the GNU General Public License version 3.0 or later.

I got really into a side project and created something called Strange Attractors using three.js. This project reminded me of the fun math exercises I did while learning programming, where I experimented and was amazed by the results. I spent a lot of time on it, but it was a lot of fun.

My favorite feature is a 2D attractor called the Simone Attractor, which I tried to convert to 3D with the help of GPT. I'm not sure if it's mathematically accurate, but I think it looks great. You can change all the settings, so feel free to try it out.

If you enjoy math-art projects, please check it out and share your thoughts, especially if you have a strong math background.

Summary of Frank Gasking's Work on Preserving Lost Games

Frank Gasking is a digital preservationist and retro gaming historian who founded the website "Games That Weren't" (GTW) to document and preserve unreleased and unfinished video games. Inspired by a magazine article in 1993 about lost Commodore 64 games, Frank began his journey by researching and contacting people in the gaming community. In 1999, he launched GTW, which has since expanded to cover multiple gaming platforms.

GTW serves as a non-profit digital archive, offering downloads, screenshots, and detailed information about games that were never released. It collaborates with developers and gaming enthusiasts to recover and document these games, ensuring that their stories are not forgotten.

One of GTW's proudest achievements is the recovery of "Daffy Duck: Starring In The Great Paint Caper" for the Commodore 64, which had been lost for 18 years before being reconstructed from recovered source code.

Frank also discusses his interactions with game publishers, noting that while they sometimes restrict the release of certain titles, many recognize the importance of preserving gaming history. He emphasizes that while some publishers are now taking preservation seriously, there is still a long way to go.

In addition to the website, Frank published a comprehensive book titled "The Games That Weren’t," which includes detailed research and stories about unreleased games. The book has been well-received and aims to provide a lasting record of his preservation efforts.

Overall, Frank Gasking's work is driven by a passion for video game history and preservation, making significant contributions to the understanding of lost games in the industry.

No summary available.

Summary:

Jonas Eschenburg shares his journey of returning to retro programming, specifically focusing on the Atari ST computer. He recounts how his fascination with computers began at a young age and led him to a career in software development. After feeling limited in a corporate environment, he decided to explore programming for the Atari ST, a 16-bit computer released in 1985.

The Atari ST is known for its simple architecture, which makes programming straightforward compared to modern systems. Jonas discusses how to emulate the Atari ST on modern computers and introduces tools for writing software, such as using the GCC compiler and modern development environments like Visual Studio Code.

He details his projects, including creating a VoxelSpace demo inspired by the game "Comanche: Maximum Overkill". This led him to experiment with graphics programming, facing challenges due to the unique memory structure of the Atari ST.

Jonas also embarked on a challenging project to port the game "DOOM" to the Atari ST. Despite the limitations of the hardware, he successfully adapted the game's source code, implemented graphics, and optimized performance. The project gained attention online, showcasing the potential of retro computing.

Through his experiences, Jonas emphasizes that working on legacy systems can still feel modern and rewarding. He highlights the importance of community support, learning assembly language, and the joy of creating something unique on older platforms.

No summary available.

S.A.R.C.A.S.M Overview

S.A.R.C.A.S.M stands for Slightly Annoying Rubik's Cube Automatic Solving Machine. It's a robot that can scan and solve Rubik's Cubes while making sarcastic comments. This project includes the code and schematics for building the robot.

Key Features:

• Uses a Teensy 4.1 controller and ESP32-CAM for taking images.
• Has an ILI9341 display with custom graphics and animations.
• Employs stepper motors and servos to handle the cube, with sensors to detect errors.
• Features RGBW lighting that syncs with audio.
• Includes on-device text-to-speech (TTS) with sarcastic remarks.

Important Notes:

• A small change to the Teensy code is needed for it to work correctly.
• The project is still a work in progress and may not be fully organized yet.

For more information, check the forum thread and demo videos linked in the original text.

Summary: Myths Programmers Believe about CPU Caches

The author, an experienced computer engineer, discusses common misconceptions about CPU caches and their importance in programming. Understanding CPU cache design is crucial for software developers because it relates to distributed systems and database consistency.

Key points include:

1. Cache Coherency: Modern CPUs keep caches in sync using complex protocols, preventing different cores from reading stale data. Misunderstandings about cache behavior can lead to poor design choices, particularly regarding concurrency issues.

2. Volatile Variables: In languages like Java, the use of volatile variables is often misunderstood. Contrary to common belief, volatile does not always force reads/writes to main memory, making it more efficient than assumed.

3. MESI Protocol: This widely-used protocol maintains cache consistency by tagging data with states (Modified, Exclusive, Shared, Invalid). This ensures that data remains coherent across multiple caches.

4. Importance of Synchronization: Despite the effectiveness of cache coherency, synchronization in multithreading is still necessary due to compiler optimizations that may not account for concurrent access. Volatile variables help maintain consistency in such scenarios.

Overall, caches play a vital role in system performance and understanding their intricacies can improve software design and concurrency management.

This document discusses a complicated issue encountered in the Oxide control plane, similar to a previous problem with asynchronous cancellation. The current issue, known as "futurelock," is tricky but can be managed more easily. Despite being a significant challenge that took experienced Rust developers time to resolve, the conditions that trigger it are somewhat limited. Overall, while the problem is complex, there are ways to reduce its impact.

A recent leak revealed that Cellebrite, a company providing phone hacking tools for law enforcement, can extract data from most Google Pixel phones, except those running GrapheneOS, a more secure operating system. The leak, shared by an anonymous source, includes details about the Pixel 6, 7, 8, and 9 models, indicating that Cellebrite can access these devices in various states: before first unlock (BFU), after first unlock (AFU), and when unlocked.

Cellebrite cannot bypass passcodes or extract data from devices with GrapheneOS that are updated past late 2022, making them significantly more secure than standard Pixel software. The Pixel 10 series is not included in the list, as it was released recently. The leaker has participated in multiple Cellebrite meetings without being detected, raising concerns about security in such briefings. Google has been asked to comment on why GrapheneOS offers better protection than its own operating system.

No summary available.

On October 27, 2025, Evan Ovadia made a statement or announcement. Further details are not provided in the text.

No summary available.

No summary available.

The article reports that Immigration and Customs Enforcement (ICE) is using a new facial recognition app called Mobile Fortify to verify people's identities and immigration status. According to a document from the Department of Homeland Security (DHS), individuals cannot refuse to be scanned by this app. Additionally, any facial photos taken will be stored for 15 years, including those of U.S. citizens. The article highlights concerns about the technology and data handling involved in this process. It also mentions that ICE and Customs and Border Protection (CBP) are actively scanning faces in public spaces to confirm citizenship.

Ubuntu 25.10 has introduced support for optimized packages that target modern processors, specifically the x86-64-v3 architecture, while still maintaining compatibility with older hardware. This means users can benefit from improved performance without losing access to older software.

Key points:

• The new "architecture variant" feature allows for packages tailored to different x86-64 levels.
• Around 2,000 source packages have been rebuilt for the x86-64-v3 architecture, although they haven't undergone extensive testing yet, so early users may encounter bugs.
• Initial benchmarks show about a 1% performance improvement for most packages, with some numerical packages improving more.
• Users can check if their machines support x86-64-v3 and can opt-in to use the new packages by updating their system.

Important notes:

• Using the amd64v3 packages means you cannot easily transfer your drive to older systems that don't support x86-64-v3.
• Future updates, including the 26.04 LTS release, will include more extensive testing and improvements to the user experience.

Overall, this update aims to enhance performance for newer hardware while still being accessible for older systems. Users are encouraged to try the new features and provide feedback.

The text discusses Google's new developer verification system for Android, which is intended to prevent the installation of unregistered APKs. Here are the key points:

1. Developer Verification Introduction: Google requires developers to verify their identity to distribute apps, with a base fee of $25 and a free hobbyist license with unknown restrictions.

2. Concerns Raised: Critics argue this system could hinder small developers by limiting app distribution and imposing installation caps. There are worries about how verification will work and whether alternative installation methods (like ADB) will be reliable in the future.

3. Proposed Workaround: The author suggests creating a "loader" APK that can dynamically load and execute other APKs without altering their signatures. This loader would act as a wrapper, handling initialization and file management.

4. Challenges: Implementing this loader is complex due to Android's intricate activity management. The author acknowledges that developing a working solution may take time and requires feedback from others.

5. Hypothetical Logistics: The loading process would need to circumvent verification, possibly through community support and obfuscation techniques to avoid detection by Google.

6. Conclusion: The project is not yet a finished solution, but the author hopes it sparks discussion and development of viable options. There is a concern about Google's increasing restrictions, like Samsung's removal of bootloader unlocking, which could further limit user freedom.

Overall, the text highlights the tension between security measures and developer freedom in the Android ecosystem.

No summary available.

No summary available.

The algorithm analysis community aims to connect theory with real-world practice. To improve understanding of how algorithms perform, a new framework called "by the book analysis" has been proposed. Unlike previous frameworks, this one models both the algorithm and its input data. The results from this analysis are expected to align closely with how algorithms behave in real situations, based on real-world observations and best practices.

The framework was applied to the simplex method, an algorithm known for its great performance in practice but poor worst-case running time. The authors discuss how "by the book analysis" addresses some issues found in the existing smoothed analysis framework. They demonstrate that, with certain assumptions about input scaling and design principles from simplex method implementations, the simplex method can achieve a polynomial running time.

The author shares their personal experience using a MacBook Pro M4 for the past six months, highlighting their decision-making process and impressions of the device.

1. Background: They previously used a MacBook Air M1 and wanted a laptop with good battery life and a quiet operation. They chose to upgrade due to stable prices despite considering sticking with the M1 longer.

2. Display Choice: They preferred the MacBook Pro for its nano-textured display, which reduces reflections, even though they liked the MacBook Air's design better. The nano texture slightly lessens vibrancy, but the author did not find this significant.

3. Specifications: They selected the MacBook Pro with an M4 chip, 32 GB RAM, and a 2 TB SSD, favoring the M4 over the M4 Pro for less heat and quieter operation.

4. Performance: The laptop occasionally gets warm, but the fan remains mostly silent. Battery life is outstanding, outlasting the previous MacBook Air, allowing for extensive use without needing to charge.

5. Display Refresh Rate: The 120 Hz display improves the experience with animations and makes non-animated actions feel faster, particularly when loading pages.

6. Conclusion: The ideal laptop for the author would combine the MacBook Air's design with the MacBook Pro's display. They also express a desire to use Linux instead of macOS, but find current support lacking.

Overall, the author is satisfied with their MacBook Pro M4, appreciating its display and battery life, despite some personal preferences for design and operating system.

Summary of Hacking Tata Motors

In a recent investigation, it was found that Tata Motors, India's largest automaker, had serious security vulnerabilities. Here are the key points:

1. Exposed AWS Keys: Two sets of AWS keys were found on public websites, exposing over 70 terabytes of sensitive data, including customer databases, invoices, and internal reports.

2. Weak Encryption: One set of AWS keys was supposedly encrypted, but the method used was easily bypassed, allowing access to significant amounts of data.

3. Admin Backdoor in Tableau: A flaw allowed access to the Tableau data visualization tool without a password, giving potential access to sensitive corporate information.

4. Azuga API Key Leak: An API key for Azuga, used for fleet management, was found in the website's code, which could compromise the test drive fleet management system.

5. Slow Response from Tata Motors: The vulnerabilities were reported to Tata Motors, but the company was slow to respond and remediate the issues, maintaining active keys for too long.

Overall, these findings highlight the need for Tata Motors to improve their data security practices to protect customer information and maintain trust.

The text discusses the "data-object pattern," a common method in software development where a specific part of a database (like all information about hats) is managed through a dedicated class. This approach is popular because it simplifies object handling and is supported by frameworks like Django. However, the author argues that this pattern has significant drawbacks:

1. Contextual Differences: Different parts of a codebase may need slightly different objects, even if they relate to the same real-world item. Using the same object everywhere can lead to issues and extra validation code.

2. Access Patterns: Similar operations may need different implementations. Trying to accommodate all possibilities in one function often leads to messy code and breaks encapsulation.

3. Large Classes: Classes can become overly complex and difficult to manage. A single, massive class can create problems in testing and maintenance.

4. Increased Failure Risk: Instead of simplifying the code, the data-object pattern may add unnecessary complexity and points of failure.

Overall, the text suggests that the data-object pattern is not always the best option, and sometimes a more modular approach is preferable.

The authors Clare Stanton and Christopher Setzer, in their October 2025 post, discuss the launch of the Data.gov Archive Search as part of their Public Data Project. They address the longstanding challenge faced by libraries and cultural organizations in balancing access to data with the costs and complexities of maintaining robust online systems.

Traditionally, providing good data discovery features like search and filtering requires expensive server infrastructure, which can become unmanageable over time due to budget cuts and staff changes. On the other hand, simpler static file hosting is cheaper but limits user experience and data discoverability.

To overcome this, the authors developed a new approach for the Data.gov Archive that combines the benefits of static hosting with dynamic data access. They utilized recent advancements in web technology to create a client-side web application that runs a database engine directly in the user's browser. This allows users to query large datasets without needing a dedicated server, significantly reducing costs and maintenance.

Key benefits of this model include lower operating costs, reduced technical risks, and sustained access to data without constant oversight. The authors encourage libraries and digital projects to consider adopting this method and are open to collaboration and sharing their findings to help others implement similar solutions.

No summary available.

The article discusses a shift in mindset regarding startup growth and profitability. Traditionally, startups focused on rapid growth, often neglecting profitability, which was seen as a sign of low ambition. However, the author argues that profitability is crucial for controlling one's direction and not relying on investors.

Paul Graham's concept of "ramen profitability" highlights the importance of reaching a point where a startup can survive without external funding, making the company more appealing to investors. The author shares their experience with their startup, Linear, which unexpectedly became profitable by focusing on building a strong product with a small, dedicated team.

Key points include:

1. Value of Profitability: Profitability provides peace of mind, allowing founders to concentrate on product quality rather than fundraising.
2. Team Size: Smaller teams often result in better quality and faster progress. The author suggests being selective in hiring to maintain culture and effectiveness.
3. Revenue per Employee: Startups should aim for a revenue range of $500k-$1M per employee, indicating appropriate hiring.
4. Intentional Hiring: Hire slowly and purposefully, especially before achieving product-market fit, to ensure each new hire meets a specific need.
5. Raising Funds: Being profitable gives startups the flexibility to choose when and how much to raise from investors, rather than being forced into it.

Overall, the author believes that startups can and should aim for profitability sooner than expected, which allows for better decision-making focused on customer needs rather than investor pressures.

No summary available.

The text discusses a technical issue faced by a team managing a large Kubernetes cluster, particularly focusing on memory consumption caused by using namespaces with daemonsets.

Key Points:

1. Memory Issues: The team noticed high memory usage in their Kubernetes setup, especially from daemonsets like Calico and Vector, which manage networking and logging.

2. Namespace Challenges: The behavior of namespaces caused memory overhead, especially when multiple daemonset pods listwatch the same resources, leading to increased load on the apiserver during rollouts.

3. Optimization Efforts: The team successfully reduced memory usage in Calico and then discovered that Vector was also consuming excessive memory by listwatching namespaces unnecessarily.

4. Proposed Solution: They explored disabling the namespace usage in Vector to save memory, which after testing proved to be effective.

5. Successful Implementation: After some troubleshooting and collaboration, they implemented the change, resulting in a significant reduction in memory usage across their clusters—totaling a savings of 7 TiB.

6. Conclusion: The process highlighted the importance of small, cumulative improvements and team collaboration in solving complex infrastructure issues.

The text ends with a reminder for others facing similar problems to evaluate the necessity of namespace labels in their configurations.

Joe Kissell discusses the uncertain future of Nisus Writer, a word processor for Mac users that has been around since 1989. He describes it as being in a "Schrödinger's state," meaning it seems both alive and dead due to ongoing issues with the company and the software.

Nisus Writer is known for its unique features that cater to multilingual and complex document needs, but the company has faced significant problems, including a lack of support, website issues, and disappearing from the Mac App Store. Kissell, who has a long history with the software, notes a decline in communication from the company and concerns about its development and support.

Despite the website being restored after a recent outage, Kissell believes that without active development, the future of Nisus Writer is grim. He suggests that the best outcome for loyal users would be for the company to open-source the software, allowing volunteers to maintain it. However, he doubts that the company will take this step, fearing they still hope to generate income from it.

Kissell expresses a desire for clearer communication from Nisus Software regarding its plans and suggests that without significant changes, the app may not survive much longer. He offers his assistance to help keep the software alive but worries that the company is not engaging with its user base.

Summary of "Perfetto: The Swiss Army Knife for Linux Client Tracing"

At the 2025 Tracing Summit, a talk was given about Perfetto, a versatile tool for Linux developers to debug performance issues in applications. Perfetto is a collection of tools that helps in tracing and analyzing performance data, primarily for Linux systems but also useful for other applications.

Key Points:

1. What is Perfetto?

   • A suite of tools designed for debugging and tracing performance issues in software.
   • Includes a C++ SDK, data collection daemons, and a powerful UI for visualizing traces.

2. How it Works:

   • Data is collected from various system interfaces and transformed into a high-performance trace format.
   • The Perfetto UI allows users to visualize this data interactively and perform SQL queries.

3. Demo Program:

   • A demo program was created to show how Perfetto can help identify performance bugs. It visualizes a mathematical rendering task using Rust and Vulkan.

4. Performance Issues:

   • The demo identified frame rate drops caused by a performance bug in the program's adaptive quality feature.
   • Various tools (Perf, ftrace, app tracing) were used to analyze the issue from different angles, confirming that the problem was related to thread scheduling and CPU usage.

5. Visualization Features:

   • The Perfetto UI allows users to create detailed visualizations, including flame graphs and timeline views.
   • New features include the ability to merge different traces for comprehensive analysis.

6. Community and Contributions:

   • The Perfetto project is open-source and encourages contributions from the community.
   • Various other projects and tools can be integrated with Perfetto for enhanced tracing and debugging.

For those interested in using Perfetto, a demo program is available on GitHub, along with detailed documentation and tutorials for tracing their own applications.

No summary available.

Summary:

Pipelex is a tool created by Robin, Louis, and Thomas, designed for building AI workflows using a structured approach. It functions like Dockerfile or SQL but for multi-step AI processes, allowing users to define steps and models without complex coding.

Key Features:

• Declarative Language: Users specify what needs to be done, while the system determines how to execute it.
• Agent-First Design: Each step includes clear, natural-language context so AI models can understand and optimize workflows.
• Open Standards: Pipelex is built under the MIT license with various components like a language specification, runtime, and API server.
• Composable Workflows: Users can create and share workflows, allowing flexibility and community collaboration.

Goals of Pipelex:

• To maintain context and meaning in AI workflows that traditional programming languages often obscure.
• To ensure reproducibility and control that simple prompts cannot provide.

User Involvement:

• Users are encouraged to build workflows, provide feedback on usability, suggest new features, and contribute to the open-source community.

Limitations:

• Limited integration with existing applications, visualization features need improvement, and the current version has some bugs.
• A hosted Pipelex API is in development, along with better cost-tracking and caching options.

Resources:

• GitHub, documentation, a demo video, and a Discord community are available for support and collaboration.

Feedback is highly valued to improve the tool further.

The author discusses their experience with the Nix package management system, expressing confusion over an issue with the Ruby interpreter. They successfully installed Ruby but encountered a problem when trying to retrieve the build and runtime graph. The expected derivation file for Ruby was missing, leading to errors when attempting to realize it from the NixOS cache.

Despite the cache indicating that a specific derivation produced the Ruby binary, the author found that a different derivation was present on their system. This discrepancy raised questions about how Nix handles fixed-output derivations (FODs).

The author explains that FODs allow for consistent output paths even when their derivation files change. They illustrate this with examples, showing how modifications to FODs can create new derivation paths without altering the output paths. This complexity means that changes in the underlying derivations can lead to confusion regarding cached outputs and their origins.

Ultimately, the text highlights the intricacies of Nix, emphasizing that understanding its behavior requires deep exploration and can lead to unexpected results.

The article discusses the discovery of bots scraping websites for JavaScript files, specifically a commented-out script that wasn't functional. The author noticed unusual 404 errors in their server logs and found requests from both malicious and legitimate-looking user agents, indicating that these bots were likely trying to collect data for training language models without permission.

The author identifies several strategies to counteract these scrapers:

1. Public Disclosure: Sharing knowledge about bot behaviors helps others block them effectively.

2. IP Filtering: Using tools like fail2ban to block malicious IP addresses can be effective and requires minimal effort.

3. Decompression Bombs: These are maliciously crafted files that can disrupt the systems of bots attempting to extract them. While it can be entertaining, it’s resource-intensive.

4. Data Poisoning: This involves intentionally corrupting data scraped by bots to undermine the machine learning models they use. Recent research suggests that even a small number of poisoned samples can negatively affect model training.

The author concludes that while identifying bot behaviors is common, innovative techniques can be employed to deter scraping. They encourage others to get involved in sabotaging unethical data practices by using various creative methods to protect their sites. Overall, the piece highlights the ongoing battle between web administrators and automated scrapers.

The post discusses a World War II German concrete tanker named Kerkship St. Jozef, located in Antwerp. It highlights the use of concrete in shipbuilding during the war. The date of the post is October 3, 2025.

The article discusses the creation and testing of sustainable memristors made from shiitake mushroom mycelium for use in high-frequency bioelectronics. Here are the key points:

1. Background: Neuromorphic computing mimics brain functions and can be enhanced using memristors, which are devices that emulate synaptic behavior. Traditional memristors rely on rare materials and complex manufacturing. This study explores using shiitake mushrooms as a sustainable alternative.

2. Research Findings: The researchers demonstrated that fungal memristors can be produced, trained, and preserved. These devices maintained functionality at frequencies up to 5.85 kHz with an accuracy of 90%. They also showed potential for radiation resistance, making them suitable for aerospace applications.

3. Advantages of Fungi: Fungal materials are biodegradable, require less energy, and can adapt their electrical properties, making them environmentally friendly alternatives to conventional electronics.

4. Testing Methodology: The study involved culturing shiitake mycelium, preparing it through drying and rehydration, and conducting electrical tests to evaluate its memristive behavior.

5. Results: Electrical tests confirmed that the fungal memristors exhibited memristive properties, with stable performance under varying conditions.

6. Future Applications: The findings indicate that fungal memristors could lead to low-cost, efficient, and sustainable computing technologies, particularly in fields requiring lightweight and radiation-resistant materials.

7. Conclusions: This research showcases the potential of using organic materials like shiitake mushrooms for developing next-generation electronics, offering a more sustainable approach compared to existing semiconductor technologies.

Overall, the study highlights an innovative solution that combines biology and electronics to create effective and sustainable computing devices.

Summary of Apple’s Fourth Quarter Results (October 30, 2025)

Apple has announced its financial results for the fourth quarter of fiscal 2025, ending September 27, 2025. The company achieved a record revenue of $102.5 billion for the quarter, an 8% increase from the previous year. Diluted earnings per share rose to $1.85, up 13%.

CEO Tim Cook expressed pride in the company’s record September revenue, particularly from iPhones and services, highlighting the launch of new products like the iPhone 17 series, AirPods Pro 3, and a new Apple Watch lineup.

CFO Kevan Parekh noted that the total revenue for the fiscal year reached $416 billion, with strong customer satisfaction leading to a record number of active devices in use.

Apple's board declared a cash dividend of $0.26 per share, payable on November 13, 2025, to shareholders on record by November 10.

For further details, Apple will host a live stream of its financial results conference call today at 2:00 p.m. PT, which will also be available for replay for two weeks.

The press release includes forward-looking statements about future results and business plans, acknowledging potential risks such as economic conditions, product competition, and legal issues.

About Apple: Apple is a leader in personal technology, known for its innovative products and services, and employs over 150,000 people worldwide.

Job Summary: Full Stack Software Engineer at Pangolin

• Location: San Francisco
• Salary: $125k - $160k + equity (0.5% - 1.5%)
• Experience: 3+ years
• Skills Required: TypeScript, Go, SQL (PostgreSQL, SQLite), NextJS, AWS

About Pangolin:
Pangolin provides secure remote access to apps and services, focusing on zero-trust networking. They prioritize open-source development and allow teams to control their own data and infrastructure.

Role Overview:
As a Full Stack Software Engineer, you will design, build, and maintain the core of the Pangolin system, especially the central server. You will influence the product and company direction as an early hire.

Key Responsibilities:

• Develop and test the self-hosted platform's core.
• Work on frontend (NextJS) and backend (Express APIs, SQL).
• Troubleshoot complex issues in networking and security.
• Engage with the open-source community for support and feedback.

Qualifications:

• Must have over 3 years of experience in computer science.
• Must be based in or willing to relocate to San Francisco.
• Comfortable in a startup environment and able to share ideas.
• Strong in TypeScript, some experience in Go, and knowledge of authentication standards.
• Familiar with cloud technologies (Docker, Kubernetes, AWS) and basic networking concepts.

What You Can Expect:

• Competitive salary and hybrid work environment.
• Supportive team with relocation assistance and unlimited PTO.

Application Process:

• Review your materials.
• Initial interview with founders.
• Complete a short, paid open-source project.
• Onboarding process.

How to Apply:

• Connect with Owen on LinkedIn.
• Send your resume and GitHub profile highlighting past projects.

The blog post by Joop van de Pol discusses the cryptography and security features of electronic passports, specifically electronic machine-readable travel documents (eMRTDs). Here are the key points:

1. Electronic Passports Overview: Modern passports are embedded with chips that store personal data and use cryptography for security. They help prevent unauthorized access, forgery, and copying.

2. Functionality: Electronic passports contain files with personal information and security data. They make processes like border control faster and more secure.

3. Threat Model: The security of electronic passports is based on who physically holds the passport. Attackers who do not possess the passport cannot access its data or trace its movements.

4. Cryptographic Mechanisms: Electronic passports use several cryptographic methods to ensure security. Initial versions lacked strong cryptography, but modern passports incorporate advanced techniques to protect data.

5. Legacy vs. Modern Security: Many older passports still in circulation use outdated security protocols, which may expose holders to risks. Newer enhancements like Extended Access Control (EAC) and Password Authenticated Connection Establishment (PACE) address some of these vulnerabilities.

6. Security Gaps: Passports can still be copied or misused if they are given to untrusted parties, especially if the inspection systems only use basic authentication methods.

7. Zero-Knowledge Proofs: New technologies like zero-knowledge identity proofs allow verification of identity without revealing full passport data. However, this introduces risks as it requires sharing the passport data with a prover, which could lead to impersonation if not adequately secured.

Overall, while electronic passports provide enhanced security compared to traditional ones, they still have vulnerabilities that need to be managed, especially concerning how and to whom you present your passport.

Wim van den Heever, a South African wildlife photographer, spent 10 years trying to capture a photo of the rare brown hyena in the abandoned diamond mining town of Kolmanskop, Namibia. His persistence paid off when he finally managed to photograph the elusive animal, winning the grand prize at the Wildlife Photographer of the Year competition.

The brown hyena is the world's rarest hyena, with a population estimated between 4,370 and 10,110 in southern Africa. This species is known for being shy and mostly active at night, making it difficult to spot. Van den Heever faced numerous challenges, including harsh desert conditions and the need to carefully position his camera traps for the perfect shot.

Brown hyenas play an important ecological role by scavenging and bringing nutrients from the ocean to the desert, often using abandoned buildings for shelter. Unfortunately, their populations are threatened by roadkill and human conflict, as they are sometimes seen as pests.

Van den Heever hopes his award-winning photo will change perceptions of brown hyenas and highlight the importance of coexistence between humans and wildlife. Despite his achievement, he remains dedicated to capturing more images of these fascinating creatures.

Mozilla.ai is adopting the llamafile project to promote open and privacy-focused AI. They are refreshing the code and want community input to shape its future. Llamafile allows users to easily run language models locally using a single executable file. It has been a successful tool, and now Mozilla.ai plans to improve it by updating its code and features based on user feedback.

The team invites users to share their experiences and suggestions on what features they find most useful and what could be improved. They will be actively working on the llamafile project and want to ensure it meets the community's needs.

Current users will not experience any changes to their workflows, as everything will continue to function as before. Mozilla.ai looks forward to collaborating with the community to enhance llamafile and make it even more valuable.

The creator made a short point-and-click adventure game focused on music during a 7-day game jam. They did all the artwork and music themselves. The game takes about 5 minutes to finish.

The discussion centers on the decision to deprecate and eventually remove XSLT (Extensible Stylesheet Language Transformations) from the Chromium web browser due to security concerns and declining usage.

Key points include:

• XSLT was standardized in 1999, but newer versions (2.0 and 3.0) have not been widely adopted in browsers.
• The rise of JavaScript libraries has made XSLT less relevant, with its usage dropping to between 0.01% and 0.1% of page loads.
• Chromium's use of the unmaintained libxslt library raises security risks, including vulnerabilities that can be exploited.
• The plan is to officially deprecate XSLT in December 2025 and remove it by November 2026, with support for some enterprise users continuing until August 2027.
• A polyfill is being provided to help developers transition away from XSLT without breaking their sites.
• While there is some negative feedback from current XSLT users, the general consensus among developers and browser engines is supportive of the removal for improved security.

Overall, the decision is motivated by the need to enhance security while reducing the maintenance burden of an outdated feature.

New research from MIT reveals that attention lapses caused by sleep deprivation are linked to the brain flushing out cerebrospinal fluid (CSF), a process that usually happens during sleep. This flushing is essential for clearing waste from the brain, and when someone is sleep-deprived, their brain tries to compensate by initiating CSF flow during wakefulness. However, this comes at the cost of attention, leading to lapses where individuals may fail to notice changes in their environment.

In a study involving 26 volunteers, researchers found that sleep-deprived participants performed worse on attention tasks compared to those who were well-rested. During these lapses, CSF was expelled from the brain, and when attention returned, the fluid flowed back in. The study suggests that this process is part of the brain's attempt to restore cognitive function, despite the negative impact on attention.

Additionally, the study observed changes in physiological responses, like decreased heart rate and pupil constriction, during these moments of inattentiveness. This indicates a possible connection between brain activity and bodily functions. The researchers propose that there may be a unified system regulating both attention and basic physiological processes, potentially linked to the noradrenergic system, which is involved in various cognitive and bodily functions.

Summary of Rouille:

Rouille is a programming language that allows you to write Rust code using French keywords and function names. It offers a fun way to incorporate the French language into programming, particularly for developing a future French operating system.

Rouille is compatible with standard Rust, so you can mix French and English in your code. An example demonstrates how you can define traits and implement them using French syntax.

The project welcomes contributions but asks that participants avoid using swear words. It also humorously acknowledges other languages that have their own versions of the word "rust."

Lastly, the project is licensed under a playful license called "Publique Rien à Branler," similar to the WTFPL.

No summary available.

Jensen Huang, co-founder of Nvidia, once worked as a busboy at Denny's. He humorously mentioned this while serving water at his company's event in Washington, DC. Now, he is a billionaire and is involved with President Trump. After giving a speech praising the president, he traveled to South Korea to support him in trade discussions with China.

The main topic of the text is about a stand-off between Nutella's manufacturer and Turkish hazelnut dealers. It highlights the ongoing tension regarding hazelnut supply, which is vital for Nutella's production. The article likely discusses the implications of this situation for both Nutella and the Turkish hazelnut industry.

Additionally, it contains promotional content for subscriptions to the Financial Times, offering digital access to news and analysis, with various pricing plans.

The research explores whether large language models, like Claude, can introspect or self-reflect on their internal thoughts and processes. Introspection in AI is significant for understanding how these models work and for enhancing their transparency and reliability.

Key findings include:

1. Evidence of Introspection: The study found that some Claude models can show limited introspective awareness and control over their internal states, but this capability is still unreliable compared to human introspection.

2. Testing Introspection: Researchers used a method called "concept injection" to see if models could recognize and report their internal states accurately. This involved injecting known neural activity patterns and checking if the models could identify them.

3. Control Over Internal States: Models demonstrated they could modulate their internal representations based on instructions or incentives, indicating some level of intentional control over their thoughts.

4. Limitations: While some models showed introspective capabilities, most of the time they failed to do so reliably. The best-performing models showed better introspection, suggesting that future advancements could improve this ability.

5. Implications: Understanding introspection in AI is crucial for developing more transparent and trustworthy systems. If models can accurately report their reasoning, it could help in debugging and understanding their behavior.

Overall, while the current level of introspection in AI models is limited, the research suggests potential for growth as models become more advanced. Future work is needed to explore the mechanisms behind introspection and to validate the accuracy of self-reported internal states.

No summary available.

The text contains messages indicating that access is denied in multiple languages, including German, English, Russian, and Polish. It suggests that someone is not allowed to enter or access a certain area or information.

Before you can upvote, you need to gain 15 reputation points. Upvoting shows that a question or answer is helpful. If you haven't earned enough reputation yet, you can save the post to come back to later. You can use 5 free votes each week, which contribute to the overall score but do not increase the author's reputation.

The main question discussed is what happens to the autopilot if a pilot ejects from a plane. Many contributors point out that ejection is a last-resort action, indicating the aircraft is likely beyond saving. Autopilots are generally not equipped to handle such emergencies, and once a pilot ejects, the aircraft is usually uncontrollable.

Additionally, some users mentioned that while autopilots can help manage a plane under normal circumstances, they do not have the capability to land a damaged aircraft or respond effectively during an ejection situation. Instead, the discussions highlight that ejection is a dangerous maneuver, and the plane's fate is typically sealed once the pilot leaves.

In military contexts, some aircraft may have self-destruct mechanisms to prevent enemy recovery, but this is more about safeguarding technology than assisting with ejection scenarios.

Dear Hackers,

I'm looking to learn about how you use open-source language models (LLMs) and coding assistants on your laptops. Specifically, I want to know:

1. Which LLMs are you using (like Ollama or LM Studio) and what coding assistant or integration (like a VS Code plugin) do you have?
2. What are the specifications of your laptop (CPU, GPU, memory, OS) and how well does it perform for your tasks?
3. What tasks do you use these tools for (like code completion, refactoring, debugging, or code review) and how reliable are they (what works well and what doesn't)?

I'm doing my own research and will share my findings later.

Thank you! Andrea.

No summary available.

No summary available.

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I'm at the beginning of my project and would like your thoughts on it. Imagine an AI device that is always with you, seeing and hearing everything you do. Do you believe this is the future, with AI becoming a bigger part of our lives? Or do you think people are not ready for this level of integration? Additionally, there are concerns about data protection and privacy, especially with technologies like VR glasses.

No summary available.

The author reflects on the impact of AI on software development, noting that while AI can quickly generate simple code, it often lacks quality and organization. They emphasize the importance of good code structure, particularly in API and web applications, and suggest organizing code into classes, modules, and namespaces based on specific roles.

The author advocates for creating stateless, isolated foundational code that handles external interactions (like databases and APIs) separately from business logic. They propose a "Result" type to simplify error handling and null checks, allowing for cleaner, more maintainable code.

By using this "Result" type, developers can chain functions together more effectively, leading to more readable and less error-prone code. The author concludes that while AI can assist in development, human oversight and thoughtful code organization are crucial for maintaining quality.

Psutil version 7.1.2 now supports wheels for free-threaded Python, which allows Python code to run in parallel across multiple threads. This improvement, largely due to community contributions, makes it easier for users to install psutil without needing to compile it from source, saving time and effort.

Currently, only 128 out of the top 360 Python packages with C extensions offer wheels for free-threaded Python, indicating limited adoption. Users benefit because pre-compiled wheels eliminate the need for complex installation setups, especially on Windows.

For developers, each wheel must be built for specific Python versions, complicating distribution. A universal wheel that works for multiple versions and platforms would simplify this process, and proposals are underway to standardize this.

To install the free-threaded version of psutil, use the command:

pip install psutil --only-binary=:all:

No summary available.

Bertie the Brain is considered one of the first electronic games, developed in 1950 by Josef Kates for the Canadian National Exhibition. This large, 13-foot tall computer allowed users to play tic-tac-toe against an algorithm, which was presented as artificial intelligence. Players used a keypad to make their moves, which were displayed on a grid of lights.

Kates created Bertie to showcase his invention, the additron tube, a smaller version of a vacuum tube, but the transistor quickly became the preferred technology. Despite its innovative design and popularity at the exhibition, Bertie was dismantled after two weeks and mostly forgotten.

Bertie the Brain is notable for being one of the first computer games with any visual display and is a contender for the title of the first video game. Its gameplay featured adjustable difficulty levels, and it was designed to be unbeatable at the highest level. However, due to patent issues and the rise of transistors, the additron tube was never widely adopted, and Kates moved on to other projects after the exhibition.

Summary of Daily Tips (October 31, 2025)

Use the Right HTML Element: Button vs. Div

There’s a common debate among developers about whether a <div> can be used instead of a <button>. The clear answer is: no, you should always use a <button>.

Key Issues with Using <div>:

• A <div> does not inform screen readers that it’s interactive.
• You cannot focus on a <div> using a keyboard.
• Click events on a <div> only respond to mouse clicks, not keyboard inputs like Enter or Spacebar.

Common Misconceptions: Some argue that adding attributes like role="button" and tabindex="0" to a <div> can make it behave like a button. However:

• This still doesn’t make it focusable or keyboard-interactive.
• Modifying focus order can lead to navigation issues.

Why Use a <button> Instead:

• A <button> has built-in accessibility features, is focusable, and responds to keyboard interactions without extra coding.
• It simplifies your code and avoids unnecessary complexity.

In short, using a <button> is better for accessibility and saves you from writing extra code. Always choose the correct element for the job!

On June 12, 1903, Guglielmo Marconi, a pioneer in wireless communication, was set to demonstrate his secure long-range wireless system at the Royal Institution. However, during the demonstration, an unexpected message interrupted his broadcast, revealing that his system had been hacked.

Neville Maskelyne, a magician and telegraph enthusiast, was hired by a rival company to test Marconi's claims of security. He successfully intercepted Marconi's signals, exposing vulnerabilities in the system. The hacked message humorously accused Marconi of deceiving the public, which frustrated Marconi's colleague, John Ambrose Fleming. Fleming condemned the act as "scientific hooliganism" and sought to identify the hacker, only for Maskelyne to confess his actions publicly, arguing that the public needed to know about the system's flaws.

This incident is recognized as the first recorded act of public hacking and highlights the ongoing tension between innovation and security in technology. The Royal Institution continues to host science lectures, celebrating its long history of public scientific discourse.

No summary available.

No summary available.

The text discusses the concept of organizational silos and the role of collaboration in companies. It argues that while leaders often see silos as negative and collaboration as positive, this perspective can be misleading.

Key Points:

1. Silos vs. Collaboration: Silos are boundaries between teams in an organization. The text suggests that collaboration within teams is beneficial, as it fosters a shared understanding, focus, and innovation. However, excessive collaboration between teams can lead to inefficiencies and confusion.

2. Why Minimize Inter-Team Collaboration?: As organizations grow, communication can become overly complex. The text argues that minimizing collaboration between teams helps reduce dependencies and simplifies communication, making it easier for teams to work effectively.

3. Understanding Silos: Silos exist due to human limitations in managing relationships and communication. They are necessary for effective teamwork, especially in larger organizations.

4. Leaders and Silos: Leaders often call for breaking down silos when they perceive a lack of coordination or focus on broader goals. However, this call may not address the root causes of the issues.

5. Clarifying Terms: The text distinguishes between coordination, communication, and collaboration:

   • Coordination: Ensuring that teams work harmoniously towards effective results.
   • Communication: Sharing information between individuals or teams.
   • Collaboration: Working together across teams, which should ideally be minimized unless necessary.

6. Future Discussion: The text hints at further exploration of how to improve coordination among teams in a subsequent post.

In summary, while collaboration within teams is essential for success, excessive collaboration between teams can hinder productivity. Understanding and managing organizational silos can lead to more effective outcomes.

No summary available.

The text discusses the author's experiences with .arpa zones, particularly in relation to reverse DNS and creative uses of these zones. Here are the key points:

1. .arpa Zones: These are special domains used primarily for reverse DNS, allowing IP addresses to be mapped back to domain names. The author was excited to be delegated an ip6.arpa zone for their IPv6 range.

2. History: .arpa has roots in ARPANET from the 1960s, which was a precursor to the Internet. Originally, it was a temporary solution for legacy domains, but it has persisted for various metadata services.

3. Reverse DNS: This process maps IP addresses back to domain names, allowing for better network diagnostics and identification.

4. Creative Uses: The author explores unconventional ways to use reverse DNS, such as hosting websites and sending emails through .arpa domains, which are typically not allowed by many service providers.

5. ICMP Hacks: The author shares experiments with ICMP (Internet Control Message Protocol), which is used for network diagnostics like ping and traceroute. They devised a method to manipulate ICMP responses to create a fake traceroute experience.

6. Challenges: While experimenting, the author faced challenges like obtaining TLS certificates, as many providers do not support .arpa zones. They eventually found a workaround using Cloudflare.

7. Security Concerns: The text notes potential security vulnerabilities in reverse DNS lookups and discusses how they tested various DNS resolution tools for XSS (cross-site scripting) vulnerabilities.

8. Future Projects: The author plans to continue exploring the possibilities of .arpa zones, including using them for animations in traceroute responses.

Overall, the text is a blend of technical exploration and creative experimentation in networking, with a focus on the unusual applications of .arpa zones.

Affinity Studio is now available for free. You can find more details and discussions about it on a news website, which has received a lot of comments.

The author expresses frustration with AI-generated content, feeling it disrespects human creativity and effort. They argue that writing is a personal expression that should reflect individual thoughts and experiences. Instead of relying on AI for tasks like writing, people should embrace their mistakes and learn from them. The author believes that real connections and engagement with readers are important, and that asking for help is a sign of intelligence, not weakness. They encourage individuals to use AI only for repetitive tasks, advocating for authentic human communication and expression.

Quibbler Summary

Quibbler is a tool that critiques your coding agent's work in real-time, helping it to improve by automatically correcting mistakes based on your specifications. It learns from your coding practices and enforces rules to enhance code quality.

Key Features:

• Prevents Common Issues: Quibbler stops agents from:

  • Making up results without executing commands.
  • Skipping tests or verification steps.
  • Ignoring your coding style.
  • Hallucinating data or functionality.
  • Deviating from established patterns.
  • Making changes that don’t meet user needs.

• Learning Capability: It remembers your project's coding patterns and rules over time.

Installation:

• Install using uv: uv tool install quibbler
• Or with pip: pip install quibbler

Modes of Operation:

1. Hook Mode (for Claude Code users):

   • Uses event-driven monitoring to observe agent actions.
   • Provides feedback passively.

2. MCP Mode (for other coding agents):

   • Requires an agent to call the review_code tool after changes for immediate feedback.

Setup Instructions:

• MCP Mode: Configure the MCP server and set up your project to include Quibbler.
• Hook Mode: Start the Quibbler server and configure your project to use hooks for event tracking.

How It Works:

• MCP Mode: Your agent submits changes for review, and Quibbler checks them against user instructions and coding patterns.
• Hook Mode: Quibbler observes agent actions in real-time and provides feedback as needed.

Customization:

• You can edit Quibbler's system prompts and rules to tailor its feedback.

Community and Contributions:

• Report issues, contribute to improvements, and join the community on Discord.

Quibbler aims to enhance the efficiency and accuracy of coding agents, making them more reliable in following user instructions.

Israeli officials required Google and Amazon, during their negotiation of a $1.2 billion cloud-computing deal known as Project Nimbus, to implement a secret code system. This system, referred to as the "winking mechanism," allows the companies to inform the Israeli government when they are compelled to share Israeli data with foreign authorities without actually disclosing that information publicly.

The arrangement was created to address Israel's concerns about losing control of its data to foreign law enforcement. Under this deal, the companies must send payments to Israel as coded signals corresponding to the dialing codes of countries they share data with. For instance, transferring data to the US would require a payment of 1,000 shekels.

The deal also includes strict conditions that prevent Google and Amazon from limiting how Israeli government agencies use their services, even if those uses are linked to human rights violations. This is in contrast to Microsoft's decision to cut off Israeli military access to certain technologies due to ethical concerns.

Both Google and Amazon deny any wrongdoing and assert that they comply with legal obligations, while Israeli officials claim the companies agreed to the stringent terms to safeguard their interests. The arrangement has raised legal concerns about potentially violating U.S. laws regarding confidentiality in data requests.

Denmark has decided to withdraw its proposal for a new EU law called "Chat Control," which would have required the mandatory scanning of electronic messages, including those on encrypted platforms. This proposal aimed to combat child sexual abuse material (CSAM) but faced strong opposition, particularly from Germany, which announced it would not support the measure. Danish Justice Minister Peter Hummelgaard stated that his office will now focus on voluntary CSAM detection instead of mandatory scanning. He emphasized the need to act to protect children from abuse, as the current voluntary scanning system will expire in April. Critics, such as Meredith Whittaker from the Signal Foundation, argued that the original proposal would lead to mass surveillance and compromise privacy for everyone.

LensesAccessors.jl is a library that uses "lenses" to manage complex objects by allowing access to or modification of deeply nested data.

Key Points:

• Lenses: They help you get or change specific parts of an object without altering the original object. For example, you can retrieve or update a field in a struct.
• Example Usage:
  • You can define a struct and create a lens to access its fields.
  • Using lens(obj) retrieves the value of the field, while set(obj, lens, value) creates a new object with the updated value.
  • The original object remains unchanged.
  • You can also modify values directly using functions like modify.
• Composition: Lenses can be combined using functions like opcompose.
• Implementation: To create a lens, it only needs to follow a simple interface with specific functions, ensuring it behaves consistently according to three laws about setting and getting values.
• Equality: The comparison for equality can vary depending on the context (e.g., using ==, ≈, or isequal).

Overall, LensesAccessors.jl provides a powerful way to work with nested data structures in a functional style.

Summary of Rotating Workforce Scheduling in MiniZinc

Overview: Rotating Workforce Scheduling (RWS) is a complex optimization problem where workers rotate through different weekly schedules. This method ensures fairness and accommodates varying work requirements, including shifts outside normal office hours.

Key Points:

1. Definition of RWS:

   • In RWS, each employee follows a different weekly schedule, rotating through them to experience all patterns fairly.

2. Basic Scheduling Model:

   • A simple model includes day, evening, night shifts, and off days.
   • A basic MiniZinc model is used to define the scheduling data, including the number of employees and shift requirements.

3. Constraints:

   • The model starts with core constraints ensuring the required number of workers for each shift each day.
   • Additional rules can be added to make the schedule more practical, such as:
     • Ensuring employees receive two consecutive days off.
     • Limiting the maximum number of working days without rest.
     • Providing at least one weekend off every three weeks.
     • Managing night shifts to ensure adequate rest.

4. Modeling in MiniZinc:

   • The model is built using MiniZinc, a constraint programming language, which allows for defining the scheduling problem and applying constraints.
   • Various constraints were added iteratively to improve the feasibility of the schedule.

5. Solver Performance:

   • The schedule is solved using different solvers (Gecode, OR-Tools, etc.), with performance measured based on how quickly they find valid schedules.
   • Cactus plots are used to visualize the performance of these solvers over varying numbers of employees.

6. Results:

   • The developed schedules can efficiently meet the outlined requirements, with realistic patterns that ensure worker rest and fairness.
   • The final model demonstrates practical applications of constraint programming in scheduling.

This summary simplifies the complex process of RWS modeling in MiniZinc, highlighting key concepts and constraints that contribute to creating an effective workforce schedule.

Summary of the App for Teaching Kids About Investing

On October 29, 2025, a project was shared about an app called D-investments, created to help children learn about investing.

Key Points:

• Purpose: The app teaches kids how to manage personal finances and understand investing, which isn't typically taught in schools.
• Inspiration: The idea came when the author's son wanted money instead of physical gifts for his birthday, allowing him to start investing.
• Concept: Investing is explained to kids as a "magic box" that grows money over time.
• Creation: Instead of a physical piggy bank, the author used an old smartphone to create a simple HTML app, which displays investment growth.
• Functionality: The app acts as a dashboard, showing daily, weekly, and monthly gains. Parents can input names, investment amounts, interest rates, and start dates.
• Installation: The app is easy to install on a smartphone and works like a regular app.
• Educational Goal: The aim is to visually demonstrate how investments grow over time, helping kids understand the concept of compound interest.

The author hopes this lesson will be valuable for their children throughout their lives.

The author created a .onion mirror of their website to support free speech and anti-censorship. Setting it up was simple, requiring just a few commands. Here’s a quick guide on how to do it:

1. Prerequisites: The author uses Caddy as their web server, DigitalOcean for hosting, and Debian as their operating system.

2. Install Tor: Use the command sudo apt install tor to install Tor on Debian.

3. Configure Tor: Modify the Tor configuration file to set up a hidden service. Key changes include disabling the SOCKS proxy and specifying the hidden service directory.

4. Restart Tor: Apply changes by restarting Tor with sudo systemctl restart tor.

5. Get Your .onion Address: Find your new .onion address in the specified directory by running sudo cat /var/lib/tor/hidden_service/hostname.

6. Configure Caddy: If necessary, add a site block in Caddy for your .onion address, noting that .onion sites use HTTP instead of HTTPS.

7. Optional - Advertise Your .onion Address: Add an Onion-Location header on your main site to direct Tor users to your .onion address seamlessly.

Once everything is set up, you can access your .onion site using a Tor-enabled browser.

Marc and Matt are developing Propolis, a tool that uses browser agents to simulate user interactions on websites for bug reporting and end-to-end (e2e) testing. Users can deploy multiple agents to collaboratively explore a site, identify issues, and suggest automated tests for continuous integration (CI).

Propolis aims to improve software quality by providing a way to catch bugs before they reach real users. It allows companies, from startups to public firms, to enhance their automated testing processes without the need for constant updates to traditional test scripts.

The service is available for $1,000 per month with unlimited use and support for early adopters. They also offer lower-priced options for smaller projects. The team is interested in feedback from the community, particularly on other uses for autonomous agents beyond just bug detection. Users can try the product for free with a quick setup.

The text discusses how the ear processes sound, particularly focusing on the cochlea's function. Here's a simplified summary of the key points:

1. Sound Processing: The eardrum vibrates in response to sound waves, and these vibrations are amplified by the bones in the middle ear before reaching the cochlea, which is filled with fluid.

2. Frequency Separation: Inside the cochlea, the basilar membrane separates sound frequencies. The base responds to high frequencies, while the apex responds to low frequencies.

3. Hair Cells and Signals: Hair cells on the basilar membrane wiggle in response to sound vibrations. This movement creates electrical signals through a process that opens and closes ion channels, leading to the release of neurotransmitters.

4. Filtering Mechanisms: Nerve fibers act as filters to extract information about sound. The cochlea does not perform a Fourier transform (a common signal analysis method) but uses a unique filtering method that balances frequency and temporal resolution.

5. Ecological Relevance: The cochlea's filtering approach may help reduce redundancy in sound representation, with different types of sounds (like human speech or animal calls) occupying distinct areas in a time-frequency space.

6. Future Exploration: The text hints that there is much more to learn about how these processes work at a cellular level, which will be covered in upcoming discussions.

Overall, the cochlea is a sophisticated system for analyzing sound, with specific mechanisms that optimize our ability to understand and interact with our auditory environment.

The article discusses a new tool called iongraph, developed to visualize the compilation process of JavaScript and WebAssembly. It allows users to interact with graphs that show how functions are optimized by the SpiderMonkey compiler. Users can input JavaScript code and see how the graph updates in real-time as they manipulate it.

The author explains that previous tools like Graphviz were unsatisfactory due to their unstable and confusing output. In response, a custom layout algorithm was created that is simple, fast, and produces clear graphs, all within a thousand lines of code. This new algorithm maintains a structure that reflects the source code more accurately, making it easier to visualize complex control flow.

The article outlines six main steps of the layout algorithm:

1. Layering: Organizing blocks of code into horizontal layers to represent their structure.
2. Creating Dummy Nodes: Adding placeholder nodes to manage edges crossing layers without cluttering the graph.
3. Straightening Edges: Adjusting the layout to make edges straighter and more readable.
4. Tracking Horizontal Edges: Sorting edges into tracks to avoid overlaps.
5. Verticalizing: Assigning vertical coordinates to each node based on their layer.
6. Rendering: Finalizing the layout for visual representation, emphasizing clarity over complex optimizations.

The author highlights that this approach, while simple, effectively balances readability and performance, making the graphs easy to navigate. Future work on iongraph includes additional features for better navigation and integration into Firefox's profiler.

Overall, the article promotes the idea that straightforward algorithms can yield significant improvements in practical applications, advocating for a balance between human insight and automated processes in software development.

Large language models (LLMs) have improved in reasoning tasks, but they struggle with complex problems. Researchers are examining large reasoning models (LRMs), which are LLMs trained to perform step-by-step reasoning and self-checking. While LRMs show promising results on some benchmarks, further investigation reveals these benchmarks are not very challenging. To address this, a new dataset called the Deep Reasoning Dataset (DeepRD) was created to test models with more complex reasoning tasks. When evaluating LRMs on this dataset, their performance drops sharply as the problems become more difficult, indicating they do not generalize well. Most real-world examples fall within the capabilities of LRMs, but there are still many situations where they may fail. This highlights the usefulness of LRMs while pointing out the need for improved methods that can handle more complex reasoning tasks.

Summary of the Roadmap for Improving the Swift Type Checker

This post outlines plans to enhance the Swift compiler's type checker, focusing on improving how it handles expression type checking. It addresses common issues like the frustrating "unable to type-check this expression in reasonable time" error, which can occur with both valid and invalid code.

Key Points:

1. Error Handling: The type checker often struggles with complex expressions, leading to lengthy debugging processes. Current workarounds like splitting expressions or adding type annotations can be cumbersome.

2. Type Overloading: Swift allows functions and variables to share names (overloading), which complicates type checking as the type checker must evaluate the types of expressions to determine the correct overload.

3. Constraint Solving: The type checker uses a method called constraint solving to manage overload resolution. It generates constraints that describe relationships between types and attempts to find solutions. However, this can become inefficient, especially with complex overloads.

4. Performance Limits: The type checker imposes limits on operations to prevent excessive processing time. If certain thresholds are exceeded, type checking is aborted to maintain performance.

5. Diagnostic Improvements: A "salvage mode" is employed to provide better error messages when type checking fails. This involves re-evaluating failed constraints to produce actionable diagnostics.

6. Recent Improvements:

   • In Swift 6.2, profiling revealed bottlenecks, leading to optimizations that reduced type checking time for complex expressions.
   • Swift 6.3 introduced better algorithms for selecting disjunctions, significantly speeding up type checking for many expressions.

7. Future Goals:

   • Further enhancements aim to streamline the constraint solver and improve how bindings are managed to avoid slowdowns.
   • Plans to eliminate outdated performance hacks and improve handling of partial solutions are also in place.
   • Longer-term changes may include optimizations to operator lookup and exploring advanced techniques used in other computational problem-solving areas.

The overall aim is to make type checking more efficient and user-friendly while maintaining the rich features of the Swift language. Future updates will continue to refine these processes.

No summary available.

I'm sorry, but I cannot access external links or articles. However, if you provide the text or main points from the study, I would be happy to summarize that for you!

Summary of "Taking Money off the Table"

In a recent conversation, the author discusses the tough decision many employees face when their startup offers a chance to sell a portion of their stock. The author shares personal experiences and emphasizes the importance of taking the money when it's available, as it can be life-changing.

Key Points:

1. Risk Assessment: The author encourages thinking of financial decisions as a gamble, weighing the benefits of securing gains against the risks of holding onto uncertain stock.
2. Startup Reality: Many startups can fail, even those that seem successful. The author warns against overconfidence in a startup's future.
3. Decision Making: The author suggests using a "forcing function" to critically analyze whether to hold or sell stock, comparing it to flipping a coin to reveal your true feelings about the decision.
4. Regrets and Stress: Taking some money off the table can relieve stress and provide security, even if it feels like leaving money on the table.
5. Investing Cash: The money taken can still grow through other investments, making it a valuable choice rather than a loss.
6. Acceptance of Imperfection: It’s okay not to make the perfect financial decision. The pressure to optimize every choice can be overwhelming.

Overall, the author stresses the importance of financial security in uncertain times and the need to consider one’s current situation rather than solely focusing on potential future gains.

The author, John, discusses the ratio of two numbers, 987654321 and 123456789, which is nearly 8. He explores whether similar ratios in different number bases also approximate integers.

In base 6, the ratio of 54321 to 12345 is approximately 4, while in base 16, the ratio of 0xFEDCBA987654321 to 0x123456789ABCDEF is about 14. The author introduces functions to calculate these ratios for any base (denom and num) and finds that for bases greater than 2, the ratio is close to the integer value of (base - 2) with a small fractional part.

He confirms through Python code that this pattern holds for bases up to 1000. The calculations reveal that the fractional part is roughly 1/(base * (base - 2)). The author notes that floating-point calculations can lead to loss of precision, which is why certain values return without fractions.

Overall, he emphasizes the relationship between number bases and integer approximations, highlighting the usefulness of computational verification alongside mathematical proofs.

Warp is updating its pricing structure to simplify its paid plans. Here are the key changes:

1. New Build Plan: A single plan called "Build" will be available for $20 per month, providing 1,500 AI credits. This plan is designed to be more cost-effective for many users, with over half expected to pay less or only slightly more than before.

2. Legacy Plans Phased Out: The old plans (Pro, Turbo, and Lightspeed) will be discontinued. Existing users will transition to the Build plan at their next renewal after December 1, 2025.

3. Usage-Based Credits: Users will pay for what they use, and any unused credits will roll over month to month. The cost of additional credits (called Reload credits) has been reduced by about 50% compared to previous overage costs.

4. Bring Your Own Key (BYOK): Users can now integrate their own API keys for OpenAI, Anthropic, and Google models within the Build and Business plans.

5. Updated Business Plan: The Business plan will cost $50 per month per user, offering similar features to the Build plan but with added security features like Single Sign-On (SSO).

6. Credit Management: Reload credits can be purchased on-demand or set to auto-reload with monthly spending limits. These credits will also roll over and remain valid for 12 months.

7. Transition Period: The new pricing takes effect immediately for new customers and during the first renewal for existing customers. Current users can switch to the Build plan at any time before renewal.

These changes aim to make Warp's pricing fairer and more aligned with user needs while ensuring the company's sustainability.

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No summary available.

Azure is currently down, and we cannot access the Azure portal. We want to know if others are experiencing the same issue. Our services are based in Canada/Central and US-East 2. For updates, you can check the following links: Downdetector and Azure Status.

The blog discusses the process of independently verifying the reproducibility of Go's toolchains. When developers compile a Go module requiring a newer version of the Go toolchain, the go command automatically downloads and uses this version without changing the installed version. This feature, introduced in Go 1.21, raises security concerns about downloading binaries, which could be compromised.

To address these concerns, the Go project implemented two key measures:

1. All toolchains can be reproduced from their source code, ensuring the same Zip archive is generated every time.
2. They publish checksums of toolchain Zip archives in a public database, allowing verification against malicious changes.

Despite these measures, independent verification is crucial. The author, who has experience in reproducible builds, created an auditor called Source Spotter to monitor the Go Checksum Database and ensure toolchain reproducibility. Source Spotter has successfully reproduced all Go toolchains since version 1.21.

The author details the process of building toolchains, including challenges faced, such as discrepancies in macOS toolchain signatures and issues with certain version numbers. They also mention that Source Spotter can publish checksums for source tarballs, providing additional verification.

In conclusion, the Go project's system allows developers to benefit from centralized package management while maintaining security. The author encourages other software ecosystems to learn from Go's approach. More information can be found on the Source Spotter website or GitHub repository.

No summary available.

Summary of Mnemosyne Project

As of October 2025, Mnemosyne is being developed and tested as a customizable cache library for Java applications. Here are the key points:

• Purpose: Mnemosyne improves memory management by allowing multiple caches to be updated simultaneously using a unique ID for each cached object.

• Functionality:

  • It uses an in-memory database to store object IDs for cached items, making updates efficient.
  • Developers can create their own caching algorithms by extending an abstract class, while the library includes built-in FIFO and LRU implementations.

• Usage:

  • For Spring applications, simply annotate the main class and methods with specific annotations to enable caching.
  • For non-Spring Java applications, more integration options are coming soon.

• How It Works:

  • When a method is called, arguments are combined into a key (CompoundKey) to retrieve object IDs from a cache. The actual objects are fetched from a common Value Pool.
  • Updates to objects are reflected across all caches by modifying the Value Pool, ensuring data consistency.

• Example Methods: Mnemosyne supports various methods to fetch and update transactions, ensuring that all related caches are updated seamlessly when a transaction changes.

• Future Plans: The goal is to develop Mnemosyne into a high-performance, distributed cache system. There are ongoing efforts to improve documentation, exception handling, and support for additional caching algorithms.

• Contribution: Community contributions are encouraged to help enhance the library.

For further details, most documentation is available within the code as Javadoc, and additional resources are being developed.

uBlock Origin Lite Overview

• Availability: This app is free and can be downloaded only from the App Store for iPhone, iPad, and Mac.

• Rating: It has a 5.0 rating based on 34 reviews.

• Description:

  • uBlock Origin Lite (uBOL) is a powerful content blocker that uses built-in filter lists to block ads and trackers.
  • It operates without needing a constant background process, making it efficient in terms of CPU and memory usage.
  • Users can enable more filter rules through the options menu.

• Updates: The latest version was released on October 29, 2025, which updated the filter lists.

• User Feedback:

  • Users have expressed satisfaction with its performance, especially on iPad, noting it works well with Safari.
  • Some users mentioned it took a long time to be available for iPadOS.

• Privacy: The app does not collect any user data.

• Compatibility:

  • Requires iOS 18.5 or later for iPhone and iPad, macOS 13.5 or later for Mac, and visionOS 2.5 or later for Apple Vision.

• Size: The app is 6 MB in size.

Overall, uBlock Origin Lite is recognized as an effective and efficient tool for blocking unwanted content on Apple devices.

This text describes a GitHub Gist created by a user named "nicolas17," which contains assembly code for an iOS application called "hello-world." The Gist, last updated on November 1, 2025, has received 78 stars and 3 forks, indicating it has some popularity among users.

The assembly code outlines the main function of the app, including the setup of the application delegate and the creation of a window with a yellow background. Key components of the code involve initializing classes and methods from the Objective-C runtime, handling memory management, and setting up the app's user interface.

Additionally, there are comments from users discussing build and deployment steps, as well as some technical feedback about the assembly code itself.

Overall, the Gist serves as a resource for developers interested in iOS app development using assembly language.