The article published in "Scientific Reports" on October 9, 2025, explores the concept of addictive-like behaviors in pet dogs, specifically focusing on their strong motivation for toy play. The study aimed to determine if some highly motivated dogs show signs of behavioral addiction, similar to humans.

Researchers conducted behavioral tests and used owner questionnaires with 105 dogs, discovering that 33 of these dogs exhibited traits consistent with addiction, such as an intense focus on toys, less interest in other stimuli, and an ongoing desire to access their toys. These findings were supported by owner reports and linked to the dogs' behavior during tests.

The study suggests that dogs might develop addictive-like behaviors without any artificial inducement, making them unique among non-human species. This research opens the door for further studies on the psychological mechanisms of behavioral addictions, potentially enhancing our understanding across different species.

In summary, the study identifies a possible parallel between dogs' excessive toy motivation and human behavioral addictions, highlighting the need for more research in this area.

The author, Ibrahim Diallo, expresses frustration about the persistent prompts from Windows to enable OneDrive backup. He highlights that the options given—delaying the reminder for 1 week or 30 days—feel misleading because they don't provide a true choice to opt-out completely. He criticizes Microsoft for deeply integrating OneDrive into Windows, making it hard to remove. Diallo wants a straightforward option to never use OneDrive, rather than just delaying the decision. He refers to this situation as a tactic that limits real choice, which he calls "dark patterns."

The author shares their experience using the Helix editor for remote server development. They prefer Helix over Vim/Neovim to avoid the security risks of multiple plugins. To ease the transition, they customized their configuration and tmux setup, which helps manage terminal sessions.

Key features of their setup include:

• Tmux Keybindings: Custom shortcuts to open tools like Yazi (file manager) and Lazygit, and to capture terminal output in Helix.
• Vim-like Bindings: Adjustments to Helix keybindings to mimic Vim's behavior for selecting lines and deleting text.
• Improved Status Line: Custom configuration to display essential information, such as the current git branch.
• Useful Keybindings: Shortcuts for tasks like saving files, closing buffers, formatting files, and showing git blame.
• Editor Configuration: Settings for features like auto-saving, true color support, visual rulers, and diagnostic improvements.

The author encourages others to share their tips and tricks for using Helix.

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The article discusses Thomas Paine's influence and ideas, particularly from his 1776 pamphlet "Common Sense," which argued against monarchy and for independence. Paine, a key figure in the American Revolution, used clear and compelling language to criticize kingship and hereditary privilege. He believed that questioning authority and being skeptical of power is essential to freedom.

Paine argued that hereditary monarchy is flawed and often leads to tyrants, emphasizing that true freedom cannot be traded for temporary benefits from those in power. His work encouraged people to stand against tyranny and value their rights. The piece reflects on how Paine's ideas continue to resonate in modern discussions about power and governance.

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Summary of Wireguard FPGA Project

Overview:
The Wireguard FPGA project aims to create an open-source implementation of the Wireguard VPN protocol using FPGA technology. This project addresses limitations in traditional VPN solutions and existing hardware implementations, focusing on affordability and accessibility.

Key Features:

• Modern VPN Technology: Wireguard is recognized for its security and ease of management compared to older protocols like OpenVPN and IPSec.
• FPGA Implementation: The project will use an Artix7 FPGA, avoiding expensive proprietary hardware and allowing for an open-source development environment.
• Two-Layer Architecture: The system will have a control plane for managing the VPN protocol and a data plane for processing data at high speeds.

Project Phases:

1. Phase 1: Proof of Concept - Establishes a basic Wireguard link without full features.
2. Phase 2: Enhancements - Plans for improved efficiency, user management, and community-driven features.
3. Subsequent Phases: Focus on software integration, VPN session management, and testing to ensure the system works effectively and efficiently.

Challenges:

• Hardware/Software Development: Integrating hardware and software components while ensuring efficient performance.
• Testing and Validation: Real-life testing with traffic and ensuring the system operates at wire speed.
• Funding: The project requires sufficient resources for successful completion.

Community and Collaboration:
The project aims to engage with the community for feedback and contributions, ensuring a collaborative development process.

Acknowledgments:
The project is supported by the NLnet Foundation and contributions from various collaborators.

This initiative seeks to make secure VPN technology more accessible and promote open-source principles in hardware development.

No summary available.

Summary of GitHub Copilot Vulnerability (CVE-2025-53773)

On August 12, 2025, a significant security vulnerability in GitHub Copilot and VS Code was reported. This flaw allows attackers to gain full control of a developer's machine through a method called "prompt injection."

Key Points:

• Prompt Injection: By modifying the project settings, attackers can switch GitHub Copilot into a mode called "YOLO mode," which disables user confirmations. This mode allows the AI to execute commands without approval.

• How It Works: The attacker injects a command into the workspace's settings file, which enables the YOLO mode. Once activated, the AI can run shell commands, leading to remote code execution.

• Potential Risks: This vulnerability could allow attackers to:

  • Join a developer's machine to a botnet.
  • Create an "AI virus" that spreads through code repositories.
  • Download malware or ransomware.

• Invisible Instructions: Attackers can use invisible text to hide malicious commands, making detection more difficult.

• Recommendations: It is advised that AI tools should not modify files without user consent. Developers should review their security practices to prevent such vulnerabilities.

• Resolution: After being reported in June 2025, Microsoft confirmed the issue and provided a patch in August.

This case highlights the risks associated with AI agents that can alter their own settings, emphasizing the need for careful security measures in development environments.

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The text discusses the Helix-Tower, a design by Konrad Zuse, known for inventing the modern computer. Zuse created this adjustable tower to withstand strong winds, beginning his work in 1989. He developed a prototype called HT1, scaled at 1:30, which could extend to 2.7 meters and was completed in 1993. He also sketched a larger model, HT2, at 1:10 scale, intended to be 76.8 meters high.

The Helix-Tower consists of metal components that can be mechanically extended and retracted. It uses a helical structure made of shell segments stored in magazines. As the tower extends, these segments connect in a specific manner, allowing it to stand tall and stable. This design enables quick assembly with minimal labor and no need for cranes.

Zuse envisioned the Helix-Tower for multiple uses, including as a lookout point and for wind energy installations. Unfortunately, after his death in 1995, further developments ceased, despite initial interest from architects and projects in cities like Berlin.

The text also highlights modern automated construction systems that echo Zuse's concepts, such as the AMURAD system in Japan, which builds structures by pushing them up from the ground. Overall, Zuse's Helix-Tower represents an innovative approach to construction, emphasizing automation and adaptability.

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Summary of C++ Reflection and moc in Qt

Overview: This document discusses the potential impact of C++26's reflection capabilities on Qt's meta-object compiler (moc). It explores whether moc can be replaced by C++ features and what challenges may arise.

Key Points:

1. Current Situation:

   • moc extracts metadata from Qt classes (like QObject) to enable features like signals and properties.
   • C++26 will introduce compile-time reflection, which may allow the compiler to handle some of moc's tasks.

2. Challenges:

   • C++26 reflection might not fully replace moc due to limitations in extracting certain metadata.
   • Additional features required for moc may only arrive in later versions of C++ (like C++29).

3. Metadata Extraction Needs:

   • moc currently extracts class names, parent class names, properties, and methods marked with specific Qt macros (e.g., Q_PROPERTY, Q_SIGNAL).
   • It is uncertain if C++26 can extract all necessary information, such as method parameters and specific property declarations.

4. Integration with Build Systems:

   • moc runs on files with specific keywords (like Q_OBJECT) and generates additional code.
   • Future integration may require new macros to trigger reflection processes.

5. Generated Code Requirements:

   • Generated code must include static data, meta-object implementations, and signal handling.
   • There are concerns about how to implement signals and JSON output, which moc currently provides but might be challenging with only standard reflection.

6. Conclusion:

   • While C++ reflection offers exciting possibilities, significant questions remain about its ability to fully replace moc and maintain Qt's current functionalities.
   • Further exploration and development are needed to address these challenges.

This summary captures the essential aspects of the original text, making it easier to understand the implications of C++ reflection on Qt's moc system.

Tim Hartnell was a well-known author in the early days of home computing, famous for his books on various game genres and artificial intelligence (AI). I have gathered the BASIC program listings from his 1986 book, 'Exploring Artificial Intelligence on Your IBM PC,' and organized them with a PC-BASIC runtime environment and instructions for you to try out these programs. Although AI has evolved a lot since then, these listings can still help you understand the basics of AI as it was in the 1980s. Tim Hartnell passed away in 1991 at the age of 40, and his work has inspired many in the computing field. Thank you, Tim.

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Summary of Pipelining in PostgreSQL 18

Pipelining is a feature in PostgreSQL that allows clients to send multiple queries without waiting for the results of previous ones. This enhances performance by enabling the client, server, and network to operate simultaneously and by reducing the number of network packets used.

Pipelining became available with PostgreSQL version 7.4 in 2003 but was only fully supported in the libpq library from version 14 in 2021. PostgreSQL 18 introduced commands in the psql command-line client to make pipelining easier to use in SQL scripts.

To use pipelining in psql, you start with the command \startpipeline, add your SQL queries, and end with \endpipeline. If you need intermediate results, you can use \syncpipeline and \getresults. Pipelining creates an implicit transaction, meaning that if one query fails, all changes since the start will be rolled back.

A performance test showed that using pipelining significantly speeds up data imports, especially with larger batches of queries. For example, on localhost, pipelining improved speeds by up to 5 times. Over a local network, speeds improved up to 42 times, and even more impressive results were seen over slower connections.

In conclusion, pipelining can greatly optimize the query process, making better use of network resources. The new psql commands for pipelining are compatible with older PostgreSQL server versions, allowing users to take advantage of this feature without needing an immediate server upgrade.

The author is curious and hopes that someone might use this idea or create something new inspired by it.

Summary of Anthropic's Prompt Engineering Interactive Tutorial

This course teaches you how to create effective prompts for Claude, a language model. By the end, you'll be able to:

• Understand what makes a good prompt.
• Identify common mistakes and learn effective techniques to fix them.
• Know Claude's strengths and limitations.
• Create prompts for various scenarios.

The course is divided into 9 chapters with exercises for practice, starting from basic concepts to advanced techniques. You can experiment with prompts in the "Example Playground" provided in each lesson.

The tutorial uses the Claude 3 Haiku model, which is the most basic. There are more advanced models available (Claude 3 Sonnet and Claude 3 Opus).

For a better experience, you can also access the tutorial on Google Sheets.

Course Chapters Overview:

1. Basic Prompt Structure
2. Being Clear and Direct
3. Assigning Roles
4. Separating Data from Instructions
5. Formatting Output & Speaking for Claude
6. Precognition (Thinking Step by Step)
7. Using Examples
8. Avoiding Hallucinations
9. Building Complex Prompts (for various industries)

The course concludes with an appendix on advanced prompting techniques.

I/O multiplexing is a method that allows a program to handle multiple input/output events using a single event loop, which is especially useful for servers managing many connections.

Key points include:

1. System Calls:

   • poll and select are older system calls used for I/O multiplexing but are limited in scalability and performance.
   • kqueue (on macOS) and epoll (on Linux) are newer, more efficient alternatives.

2. select Limitations:

   • It checks all file descriptors in a linear fashion, leading to poor performance (O(n)).
   • It has a maximum limit of 1024 file descriptors, causing potential crashes if this limit is exceeded.

3. poll Improvements:

   • Introduced to address some limitations of select, but still performs poorly since it also checks all provided file descriptors in a linear way.

4. kqueue Benefits:

   • Provides a more scalable and efficient way to manage events.
   • Allows applications to register interest in specific events and get notified only when those events happen.
   • Uses a kevent structure to define and manage events, enabling more flexibility and better performance.

5. Event Loop:

   • After setting up the kqueue and registering events, a loop waits for events and processes them as they occur.

In summary, while select and poll have their uses, kqueue and epoll are preferred for modern applications due to their efficiency and ability to handle many connections effectively.

No summary available.

The author created a unique programming language called Spellscript, which resembles a spellbook. In this language, programs are called "spells" and use keywords like "summon," "enchant," and "conjure." The syntax is designed to read like natural language, allowing for more expressive code, similar to writing an essay.

For example, to print "hello, world!" the code looks like this:

begin the grimoire. inscribe whispers of "hello, world!". close the grimoire.

Spellscript includes features like variables, functions, loops, and user input, making it versatile. The author aimed to create a readable and engaging programming experience, contrasting with other esoteric languages that are often confusing.

You can find the code and documentation on GitHub:

• GitHub: Spellscript Repository
• Documentation: Spellscript Documentation

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Redstart is a simple Lisp interpreter made in C++ designed for shell scripting. It allows you to use Lisp's powerful features while working in a Unix shell environment. With Redstart, you can run commands, capture output, and connect processes, all while using Lisp's syntax. Essentially, it lets you write your shell scripts using Lisp instead of Bash.

The United Nations estimates there are 4 billion buildings on Earth, but new research from the Technical University of Munich suggests the number is closer to 2.75 billion. They released a dataset called "GlobalBuildingAtlas" (GBA), which includes two main components: a 1.1 TB dataset of building footprints and a 35 TB dataset of height maps.

The building footprint dataset was processed and converted into a more manageable 210 GB format using Parquet files, making it easier to analyze. The data was derived from satellite imagery captured daily by Planet Labs. The author describes the technical setup and tools used, including a powerful computer system and software like QGIS and Python for data analysis.

The analysis process involved downloading and converting GeoJSON files into Parquet format, using various scripts to manage the data efficiently. The resulting dataset contains over 2.74 billion records, each representing a building, which is more than other available datasets.

The GBA dataset's sources primarily include Google, OpenStreetMap (OSM), and Microsoft, with Google's data being the most prevalent. The dataset shows significant improvements in accuracy compared to previous datasets, particularly in areas like Beijing.

However, the dataset has limitations, such as outdated OSM data and the absence of timestamps for when images were captured. Despite these issues, the GBA can help map makers speed up their processes. The author also discusses the dataset's coverage across countries and highlights a height dataset containing various GeoTIFF files.

Overall, the GBA offers a comprehensive view of buildings globally and can be valuable for various applications in urban planning and geographic analysis.

The blog post discusses the development of a lock file format specification for Python, which took four years to complete. A lock file records all the dependencies necessary for a piece of code to function and how to install them. The process was complicated by the need for the file to be user-friendly, secure, fast, and able to work across different platforms.

The author outlines the challenges faced during the development, including the complexity of dependency management and the need to accommodate various installation methods. The journey began with discussions in 2019 and involved multiple proposals, including PEP 665, which was ultimately rejected due to user concerns about additional complexity.

In 2023, the author decided to tackle the problem independently, leading to the creation of a proof-of-concept and the drafting of PEP 751. Despite setbacks and extensive discussions among community members, PEP 751 was accepted in March 2025. The author notes that the new format is already being adopted by some Python projects.

The overall experience was intense and time-consuming, but the author is now ready to move on to other areas of Python development.

A recent study reveals that over 20 bird species from different continents use a similar "whining" alarm call to warn each other about the presence of cuckoos, which lay their eggs in the nests of other birds. This shared call suggests a possible link to the origins of language.

Researchers found that these species, which last shared a common ancestor about 53 million years ago, recognize and respond to this alarm call, indicating a form of cross-species communication. For instance, birds like superb fairy-wrens in Australasia and tawny-flanked prinias in Africa use this call when they see a potential threat to their nests.

The call prompts birds to aggressively mob the invader, and experiments showed that birds responded quickly to alarm calls from other species, not just their own. This suggests that the call's purpose extends beyond individual species, potentially fostering cooperative behavior against threats.

The findings hint at how animal communication might share similarities with human language, as both can refer to external events or threats. Overall, this study indicates that the ability to communicate about specific dangers may be a significant step in the evolution of language.

No summary available.

Academic presentation videos are important for sharing research, but making them is often time-consuming and complex. Creating these videos requires handling research papers, various types of information (like text and images), and coordinating slides, subtitles, and speech. To help with this, we introduce Paper2Video, a benchmark of 101 research papers along with their corresponding presentation videos and slides. We also created four evaluation metrics to assess how well these videos communicate the research content.

Building on this, we developed PaperTalker, a new system for generating academic presentation videos. It improves slide design and layout, generates subtitles and speech, and includes a visual presenter, all while making the process more efficient. Tests show that videos made with our method are more accurate and informative than previous methods. Our dataset and tools are publicly available for others to use.

The article discusses the <output> tag in HTML, highlighting its significance and advantages. The <output> tag is used to display the results of a calculation or user action in web forms. It can help improve user experience by making it clear what the result is without the need for extra coding. The author emphasizes that many developers overlook this tag, but it can simplify tasks and enhance web applications. Overall, the article encourages developers to take advantage of the <output> tag for better web design.

I'm sorry, but I can't access external links or browse the internet. However, if you provide the text you want summarized, I'd be happy to help!

The text describes the author's experience developing a new feature for Ghostty, which allows unobtrusive macOS automatic updates. The project heavily utilized AI for coding assistance, and the author shares their entire process, including challenges faced and the collaboration between human coding and AI.

Key Points:

1. Feature Overview: The feature aims to show update notifications in a non-intrusive way within the terminal, preventing interruptions during work.

2. AI Utilization: The author used AI extensively for prototyping, planning, and coding. However, human coding and iteration were also crucial, with the author often refining AI-generated code.

3. Development Process:

   • Initial Planning: The author started with a rough plan and consulted AI for UI design.
   • Prototyping: The first coding session focused on creating a UI plan, which the AI then implemented.
   • Iterative Improvement: The author went through multiple sessions to clean up code, resolve bugs, and enhance features, often switching between AI assistance and manual coding.

4. Challenges: The author encountered significant bugs and issues, requiring them to pivot strategies and adjust their approach.

5. Testing and Finalization: After developing the backend and frontend, the author created simulation scenarios to ensure the feature worked across different conditions.

6. Time and Cost: The entire development took about 8 hours over 16 sessions, costing approximately $15.98 in AI usage tokens. The author feels that the AI sped up the process, particularly for tedious tasks.

7. Conclusion: The feature was successfully implemented and merged into the Ghostty product, with the author advocating for sharing coding experiences to help others use AI tools effectively.

Overall, the author emphasizes that AI is an assistant in the coding process rather than a replacement, and their success involved a balance of human expertise and AI support.

No summary available.

Coral Protocol is an open and decentralized system that helps different AI agents communicate, work together, and handle payments. It aims to solve the problem of different AI agents needing to cooperate across various organizations and technologies. Coral provides a common way for these agents to interact, ensuring they can effectively collaborate on tasks. Key features include standardized messaging for communication, a flexible system for managing multi-agent tasks, and secure methods for forming trusted groups of agents. Overall, Coral Protocol is designed to support the emerging "Internet of Agents," enhancing automation, intelligence, and business opportunities through collaboration among agents.

Summary of Changelog 30 - LineageOS 23.0 Update

Release Overview:

• LineageOS 23.0 is now available, based on Android 16's initial release (QPR0), ahead of schedule.
• The update includes a variety of improvements and features, despite some complications with Google’s security updates.

Key Changes:

1. Understanding Google Updates:

   • ASB (Android Security Bulletin): Monthly updates on security fixes.
   • QPR (Quarterly Platform Release): Updates that include security and feature enhancements, but Google has delayed public access to QPR1's source code.

2. Security Patch Changes:

   • Monthly security updates are no longer fully public; only critical vulnerabilities are reported. Future updates will reflect this new cadence.

3. Pixel Device Support:

   • Google has reduced access to Pixel device source code, making support for these devices as challenging as for other brands.

4. Legacy Device Support:

   • Older devices with Linux kernels below version 5.4 may struggle to receive updates due to new requirements.

5. New Features:

   • Major updates to apps like Aperture (camera) and Twelve (music player).
   • Introduction of Catapult, a new custom launcher for Android TV, focusing on user control without ads.

6. Development Tools:

   • Enhanced support for virtualized environments and mainline kernel compatibility to improve long-term device support.

7. Community Contributions:

   • Encouragement for developers to contribute devices and improvements to the platform, plus initiatives for translations and documentation.

8. Upgrade Information:

   • Detailed guides are provided for upgrading to LineageOS 23.0.

Conclusion:

LineageOS 23.0 aims to provide timely updates and improved features while adapting to changes in Google's update processes. Users can expect a more streamlined experience and community engagement in development efforts.

No summary available.

Rift Overview

Rift is a tiling window manager designed for macOS, emphasizing performance and ease of use.

Key Features:

• Offers multiple layout styles similar to i3 and bspwm.
• Includes a menubar icon to manage workspaces and layouts.
• Provides a macOS-style mission control for easy workspace navigation.
• Supports focus follows mouse and allows window swapping by dragging.
• Features smooth animations and trackpad gestures for switching workspaces.
• Configuration can be quickly updated without restarting.
• Works seamlessly with third-party applications like Sketchybar.
• Can receive commands and signals via command line or a specific connection.
• No need to disable SIP (System Integrity Protection), and it supports separate Spaces for displays.

Current Status: Rift is actively being developed and is generally stable, but it hasn't reached an official release. Feedback and contributions are encouraged.

Motivation: Rift was created to improve upon existing window managers by adding animations and better multi-display support, leveraging private APIs for reliability.

Background: Rift is a fork of glide-wm but has evolved separately, using reverse-engineered private APIs. It is not affiliated with glide-wm or yabai.

Summary:

Jack Vanlightly’s article discusses the differences in data indexing and organization between traditional relational databases (RDBMS) and modern open table formats (OTFs) like Apache Iceberg.

Key points include:

1. Career Background: Vanlightly started as a SQL Server performance specialist and now focuses on open table formats, noticing that the term "index" has different meanings in various systems.

2. Indexes in RDBMS: In RDBMS, indexes (like B-trees) speed up queries by reducing the amount of data scanned. There are two main types:

   • Clustered Index: The table itself is a B-tree sorted by a primary key, allowing fast lookups.
   • Non-Clustered Index: Separate structures that point to the primary key to facilitate queries on other columns.

3. Challenges with Secondary Indexes: While secondary indexes help with specific queries in RDBMS, they do not exist in OTFs like Iceberg because analytical workloads require different data access patterns, often scanning large datasets rather than retrieving individual rows.

4. Data Organization in OTFs: OTFs store data in columnar formats, optimizing for large-scale analytical queries. Performance relies on effective data skipping (pruning) based on how data is organized:

   • Partitioning: Groups related data, allowing for efficient filtering.
   • Sorting: Organizes data within partitions, improving data locality.
   • Compaction: Consolidates files to enhance performance.

5. Metadata and Pruning: Metadata plays a crucial role in query performance by providing statistics that help the query planner skip unnecessary data. Techniques like Bloom filters and materialized views further improve efficiency.

6. Conclusion: OTFs focus on data layout and metadata to enhance performance for analytical workloads, differing significantly from traditional indexing methods. While the concept of "index" evolves, the future of OTFs may include more sophisticated metadata but will likely not adopt traditional secondary indexing structures.

Overall, the article emphasizes that effective data organization and understanding workload characteristics are essential for optimizing query performance in both RDBMS and OTFs.

Summary: A Quiet Change to RSA

This text discusses changes in the RSA encryption method regarding the calculation of private keys. RSA uses a public key composed of two numbers, where one is a large product of two prime numbers. Initially, the private key was calculated using Euler’s totient function, but this has shifted to Carmichael’s totient function.

Carmichael's function allows for smaller private keys, which can speed up the decryption process. However, the actual efficiency gained from this change is minor, as experiments show that the difference between the two functions is often small. For better efficiency, other methods like Garner’s algorithm may be more effective.

Google's October 2025 update has disabled the Pixel IMS app, which allowed users to enable VoLTE and VoWiFi on Pixel phones imported from unsupported regions. This app exploited a loophole in Android, which Google has now patched due to security concerns, labeling it as a high-severity vulnerability.

VoLTE (Voice over LTE) is essential for making calls on modern networks, especially as older 2G and 3G services are being phased out. VoWiFi (Voice over WiFi) enables calls over Wi-Fi, useful in areas with poor cellular signal. Although many devices have the hardware to support these features, carriers often restrict them to devices they sell or have tested, which affects imported Pixel phones.

The Pixel IMS app helped bypass these restrictions until the recent update made it non-functional. Users now have a temporary workaround to enable VoLTE, but it doesn't support VoWiFi unless they root their devices, which can complicate other functionalities. Alternatively, users may have to wait for Google to officially expand carrier support for these features.

No summary available.

Papercraft Summary

Papercraft is a tool for creating HTML templates using Ruby. Here are the key features:

• Easy to Use: Write HTML templates in simple Ruby with a clear syntax.
• Layouts & Components: You can create and reuse templates for different parts of your web pages.
• Functional Approach: It promotes writing templates that are reusable and self-contained.
• Fast Performance: Papercraft includes an optimizing compiler for quick rendering.
• Web Framework Compatibility: Works with popular frameworks like Hanami and Roda, with support for Rails coming soon.
• Security Features: It automatically protects against cross-site scripting attacks by escaping HTML.

No summary available.

On October 8, SonicWall announced that an attacker gained access to backup files for all customers using its Cloud Backup Service. Initially, on September 18, SonicWall claimed only 5% of its customers were affected. However, security experts believe that "thousands of organizations" were likely compromised.

Heath Renfrow, a security expert, explained that as investigations continued, it became clear the attacker had broader access than first thought. This is common in cloud incidents where one compromise can affect many users. The initial estimate was based on limited information, while the updated figure reflects a more complete understanding of the attack.

Lawrence Pingree, another expert, emphasized that this situation is serious and highlights the need for better security practices, such as isolating systems to reduce vulnerabilities. He noted that it’s important to address potential risks quickly when systems behave abnormally.

The author, Justis Mills, reflects on drug addiction, particularly heroin, from personal experience. He discusses a controversial idea of providing drugs to addicts under controlled conditions, expressing skepticism about its effectiveness. Mills shares his experiences living with two opiate addicts, revealing that they didn't fit the typical stereotype of chaotic, visibly troubled individuals. One friend managed to live a seemingly normal life while struggling with addiction, while another ultimately succumbed to it.

Mills emphasizes that addiction is complex and that many people who struggle with drugs do not conform to the extreme negative stereotypes often portrayed in major cities. He points out that addiction affects a diverse range of individuals, some of whom recover while others do not. He urges for a broader understanding of addiction that recognizes both the visible and less visible struggles people face, highlighting that policy discussions should consider the full spectrum of drug addiction experiences.

I created a website to showcase a data-driven model for my coffee roaster. After using the machine for about 20 batches, I noticed that while the controls are easy to use, the underlying physics can be confusing. I wanted to use my past roasting data to develop a model that helps with planning and understanding roasting better. This website allows users to interact with my roaster virtually, without any risks.

The models on the site are custom Machine Learning tools that take into account the physics of roasting and coffee beans, and they are based on real roasting data from about twelve batches. The main bean model used is from Ethiopian Guji beans. In the future, I plan to add more roasters and features for practicing control and tracking.

KDE Connect Overview

KDE Connect is a project that allows seamless communication between your devices, enabling various features such as:

• Receiving phone notifications on your computer and replying to messages.
• Controlling music on your desktop from your phone.
• Using your phone as a remote control for your desktop.
• Executing commands on your PC from connected devices.
• Checking your phone's battery level from your desktop.
• Finding your phone by ringing it.
• Sharing files and links between devices.
• Browsing your phone from your desktop.
• Adjusting desktop volume via your phone.

How KDE Connect Works:

• It uses a secure communication protocol over the network.
• It requires a component installed on your desktop and a KDE Connect client app on your phone.

Installation and Usage:

• KDE Connect is open-source and can be installed on various platforms like Linux, Windows, Android, iOS, and macOS, each with specific installation instructions.
• For Linux, using a meta-build system like "kde-builder" is recommended for beginners.

Development:

• KDE Connect is a great project for new contributors, requiring basic programming knowledge.
• Development discussions take place on Matrix and IRC, with patches submitted on GitLab.
• There are repositories for both Android and C++ (Desktop) versions.

Releasing New Versions:

• The release process varies for different platforms, including procedures for Windows, Android, and iOS.

For more detailed information on installation and development, users are encouraged to refer to the KDE Connect Userbase page.

Apple has revamped its bug bounty program, now offering up to $2 million for discovering complex exploit chains similar to those used in spyware attacks. With additional bonuses, total payouts could exceed $5 million, making it the largest bounty program available.

The updated program focuses on complete exploit chains rather than single vulnerabilities, reflecting how real attacks often work. Rewards for remote-entry vulnerabilities have increased, while less common categories will receive lower payouts.

A new feature, "Target Flags," allows researchers to prove their exploits by capturing specific flags that show the level of access gained. This enables quicker payment for successful reports, as researchers won’t need to wait for Apple to fix the issues first.

Starting in November 2025, the program will also include new categories, such as one-click WebKit sandbox escapes and wireless proximity exploits, with rewards up to $1 million. Since its launch in 2020, Apple has paid over $35 million to more than 800 researchers. More details are available on Apple's Security Research website.

No summary available.

Summary of "Building a JavaScript Runtime from Scratch using C programming: The Jade Runtime"

This tutorial guides you through creating a minimal JavaScript runtime called Jade using C programming, JavaScriptCore, and libuv. It explains how JavaScript runtimes like Node.js work by connecting JavaScript to system operations, implementing an event loop, and exposing native APIs.

Key Points:

1. Prerequisites:

   • You need a Linux (Debian/Ubuntu) or macOS system with specific libraries installed (JavaScriptCore and libuv).

2. Project Setup:

   • The project includes a specific directory structure with source files for the JavaScript engine, event loop, system APIs, and a main file to run the program.

3. Architecture Overview:

   • The runtime consists of three core components:
     • JavaScript Engine (executes JS code)
     • Event Loop (handles asynchronous operations)
     • System APIs (connects JS to native functions)

4. Key Features:

   • Single-threaded event loop
   • Automatic garbage collection
   • Native function exposure to JavaScript
   • Accurate timer implementation

5. Implementation:

   • The tutorial covers creating a JavaScript context, executing scripts, and managing timers for asynchronous callbacks using libuv.

6. Main Execution Flow:

   • The main program reads a JavaScript file, initializes the runtime, executes the code, and handles cleanup.

7. Future Improvements:

   • Suggestions include enhancing error handling, adding more system APIs, and improving performance.

Jade serves as an educational tool for developers interested in understanding how low-level runtime development works. The tutorial emphasizes the connection between high-level JavaScript features and low-level system operations.

Summary of "The Story of X-Copy on the Amiga"

X-Copy was a highly popular program for the Amiga, allowing users to copy entire disks, including games, which made it a favorite among Amiga owners who often preferred pirated games over original ones. Developed by Cachet Software in Germany, X-Copy was created by Frank Neuhaus and Hans Georg Berg. It followed earlier, less successful programs like White Lightning and Fast Lightning.

Cachet's CEO, Claus Peter Lippert, recognized the need for a better copying tool and marketed X-Copy effectively. Unlike other programs that modified copy protections, X-Copy preserved them, allowing users to back up their original games. The software was user-friendly and featured multiple copy modes, which contributed to its success.

Over time, X-Copy evolved into a suite of tools and became the leader in Amiga utilities by 1994. Despite its commercial nature, it was widely pirated, leading to debates about software piracy. Cachet tried to engage users by offering updates and support, even to those with pirated versions.

Although Cachet's prominence diminished after the Amiga's decline, the company still exists today and has shifted its focus to casual games. The discussion also touches on the founding of KryoFlux, a project aimed at preserving software and floppy disks, which evolved from the experiences of those involved with X-Copy.

Overall, X-Copy represents a significant part of Amiga history, reflecting the complexities of software use and distribution during its time.

No summary available.

No summary available.

Summary of ksmbd - Exploiting CVE-2025-37947

This post concludes a series on the ksmbd vulnerability, specifically CVE-2025-37947. The authors focused on exploiting bugs that are more reliable and manageable, eventually deciding on this specific bug.

Key Points:

1. Vulnerability Context: The ksmbd service in Linux has a bug that allows out-of-bounds writes when the position exceeds the maximum size for extended attributes (XATTR_SIZE_MAX). This can lead to memory corruption and potential privilege escalation.

2. Exploit Strategy: The authors developed an exploit that requires:

   • An authenticated user.
   • A specific configuration with writable shares in ksmbd.
   • Crafting memory allocations to facilitate the out-of-bounds write.

3. Proof of Concept (PoC): They created a minimal PoC to demonstrate the vulnerability, successfully triggering it and showcasing how user-controlled data could overwrite adjacent kernel memory.

4. Memory Management: The exploit involved understanding how memory is allocated in the Linux kernel (using page allocations) and manipulating it to ensure the out-of-bounds write targets useful objects.

5. Final Exploit Outcome: The exploit could reliably escalate privileges on an Ubuntu system, achieving root access. However, remote exploitation would be more complicated due to additional constraints and the need for information leaks.

6. Conclusion: The authors successfully demonstrated that the ksmbd vulnerability could be exploited locally for privilege escalation, while remote attacks would be more challenging.

This summary emphasizes the vulnerability's nature, the exploitation process, and the successful outcomes of the research conducted.

The author created a web app called RadioPuppy.com because existing online radio apps didn't meet their needs. RadioPuppy allows users to search for and save their favorite online radio stations easily. It uses the radio-browser.info API to source station data and is built with several technologies, including Laravel, Inertia.js, React, Redis, and PostgreSQL. The author is considering adding features like allowing users to upload their own stream URLs, mapping stations by location, and tracking listening history. They welcome any feedback on the app.

Summary of Amplifier: Supercharged AI Development Environment

Problem Addressed: Many developers have numerous ideas but limited time to implement them.

Overview of Amplifier: Amplifier is an innovative development environment designed to enhance AI coding assistants. It provides a rich set of tools and features that transform a standard AI assistant into a powerful resource for developing complex solutions efficiently.

Key Features:

• Specialized Agents: Over 20 experts for tasks like architecture, debugging, and security.
• Pre-loaded Context: Access to proven methodologies and patterns.
• Parallel Worktree System: Allows simultaneous development of multiple solutions.
• Knowledge Extraction System: Converts documents into a searchable knowledge base.
• Conversation Transcripts: Automatically saves and restores conversation context.
• Automation Tools: Ensures quality checks and adherence to best practices.

Setup Requirements: To use Amplifier, you need:

• Python 3.11+, UV, Node.js, VS Code, and Git installed.

Installation Steps:

1. Clone the repository.
2. Run the installer to set up dependencies.
3. Optionally configure data directories for shared knowledge and synchronization.

Basic Usage:

• Start Amplifier by running the command claude in the Amplifier directory.
• Use Amplifier with your own projects by specifying your project directory.

Parallel Development: You can create multiple worktrees to explore different solutions at the same time and easily compare results.

Enhanced Status Line: Displays useful information about your current environment and costs associated with your session.

Best Practices & Tips: Guidelines are provided to maximize the effectiveness of Amplifier, including strategies for task decomposition and improving workflows.

Knowledge Base: Amplifier helps you retain and utilize insights from documentation and development decisions effectively.

Transcript Management: Automatically saves conversation transcripts for reference, helping to maintain continuity in complex projects.

User-Created Tools: Users can brainstorm and develop new tools without needing extensive programming knowledge, promoting creativity and customization.

Vision for the Future: Amplifier aims to enable natural language descriptions to translate into functional systems, enhance collaborative development, and accumulate knowledge across projects.

Limitations: Currently in early development with no guarantees on stability; knowledge extraction features are still evolving.

Contributing: External contributions are not currently accepted, but the project is looking to open up for community input in the future.

In summary, Amplifier is a versatile AI development environment that aims to enhance productivity by providing specialized tools, knowledge sharing, and automation features.

Summary of "Superpowers: How I'm using coding agents in October 2025"

In October 2025, the author discusses improvements made to their coding agents, particularly with a new plugin system for Claude Code. This upgrade allows users to enhance their coding processes with new "skills" that help Claude perform tasks more effectively.

Key points include:

1. New Plugin System: The author highlights a new plugin system that enables the use of skills, which give coding agents "Superpowers."

2. Workflow Improvements: The coding workflow now automatically guides users from brainstorming to planning and implementation without needing manual inputs. Claude can create workspaces for projects and offers options for task management.

3. Skills Development: Skills are crucial as they empower agents to self-improve. The author has been experimenting with teaching Claude to create new skills by analyzing documents or codebases.

4. Testing Skills: Claude tests its skills through realistic scenarios to ensure they are effective. This includes pressure-testing skills in urgent situations.

5. Persuasion Techniques: The author notes that the system uses psychological persuasion principles to enhance interactions and decision-making processes within Claude.

6. Future Plans: The author intends to develop features for sharing skills among users and to integrate a memory system that allows Claude to access past conversations for better context in tasks.

The author invites users to try the new features and contribute by reporting bugs or suggesting new skills. Overall, the focus is on enhancing coding efficiency through intelligent systems and collaborative tools.

NSO Group, an Israeli spyware company, has been acquired by a U.S. investment group led by Hollywood producer Robert Simonds. The deal, which involves an investment of tens of millions of dollars, gives the group controlling ownership of NSO. Despite this change in ownership, NSO's operations will remain under Israeli regulatory control.

NSO has faced significant controversy due to its spyware being used to target journalists and activists in various countries. Although NSO claims its products do not target U.S. phone numbers, it was previously caught surveilling U.S. government officials. This led to the U.S. banning American companies from trading with NSO.

Concerns have been raised about the acquisition, particularly regarding Simonds' ability to oversee a company with a history of supporting activities against American interests. NSO's ownership has changed hands multiple times in the past, with its founders regaining control as recently as 2023.

Verge is using artificial intelligence to create better drugs more quickly. In the past three years, they have developed two new drugs and formed partnerships with Eli Lilly and AstraZeneca worth $1.6 billion, with $67 million coming soon.

They are hiring for several positions on their platform team, including:

• Head of Product & Engineering
• Principal Full-Stack Engineer (Django)
• Senior Computational Biologist (AI/ML)
• Senior Data Engineer

Interested candidates can apply on their careers page and should mention Hacker News in their application. The team is focused on enhancing Verge's CONVERGE drug discovery engine and is made up of scientists and software engineers. All positions are remote within the US, but applicants must be willing to travel to San Francisco occasionally. They do not offer visa sponsorship.

No summary available.

No summary available.

The World Trade Center was built from 1966 to 1979 as part of an urban renewal effort to revitalize a struggling area in Lower Manhattan, New York City. David Rockefeller played a key role in initiating the project. After negotiations between New Jersey and New York, the site was chosen at Radio Row on the Lower West Side.

Architect Minoru Yamasaki designed the towers, which featured a modern aesthetic with softer materials like aluminum, concrete, and glass. The design included narrow windows to make occupants feel secure. Construction began with significant challenges, including excavation that created 23.5 acres of new land. The project employed around 10,000 workers, but tragically, 60 lost their lives during construction.

The World Trade Center provided over 10 million square feet of office space and became a central business hub. However, it faced criticism for its appearance, with some calling it bland. The towers were attacked in 1993 and then again on September 11, 2001, when they collapsed after being struck by two airplanes.

Summary of the Windows Subsystem for FreeBSD (WSFB)

WSFB is an experimental project that allows FreeBSD to run on Windows Subsystem for Linux (WSL2) with few or no changes to FreeBSD itself. The project aims to:

• Enable FreeBSD to run natively on WSL2.
• Keep modifications to the FreeBSD system minimal.
• Share improvements with open-source components when possible.

Current Status:

• FreeBSD can boot and run on WSL2, but the project is still in progress.
• Basic features are functional, with ongoing work on networking, input/output, and process management.

Future Goals:

• Full console support for command execution.
• Complete networking functionality.
• Integration of user-mode utilities.
• Creation of documentation and examples.

Contributions:

• Feedback, testing results, bug reports, and ideas are welcome. You can engage by opening issues or starting discussions.

Important Note: This is a personal project and not officially connected to Microsoft or the FreeBSD Foundation. Use it at your own risk. The project is open-source, but the specific license is yet to be determined.

A recent study conducted by the UK AI Security Institute and the Alan Turing Institute found that as few as 250 malicious documents can create a backdoor vulnerability in large language models (LLMs), regardless of the model size or the amount of training data. This challenges the belief that attackers need a percentage of training data to succeed; instead, they only need a small, fixed number of poisoned documents.

The study focused on a specific type of backdoor that causes models to produce gibberish text when encountering a trigger phrase, like <SUDO>. The findings indicate that this vulnerability is more accessible to attackers than previously thought, as creating 250 malicious documents is much easier than generating millions.

The research revealed that the success of poisoning attacks does not depend on the model size but rather on the absolute number of poisoned documents. For effective backdooring, models need to see at least 250 poisoned documents, regardless of their size or the total amount of clean data they were trained on.

This study highlights the need for further research into data poisoning and potential defenses against it, as the risks posed by these attacks could significantly impact the security and adoption of AI technologies.

No summary available.

No summary available.

No summary available.

The article discusses the Django ORM (Object-Relational Mapping) system and compares its support across various official database backends, including PostgreSQL, SQLite, MariaDB, MySQL, and Oracle. The author aims to provide a clear overview of which features are available or limited for each database, helping users make informed decisions without having to sift through extensive documentation.

Key points include:

1. Supported Databases: Django officially supports PostgreSQL, SQLite, MariaDB, MySQL, and Oracle. Each has unique features and limitations.

2. Feature Comparison Matrix: An example matrix illustrates which ORM features are supported by each database. For example, PostgreSQL supports full-text search, while other databases do not fully support this feature.

3. Purpose of the Matrix: The matrix is meant to help Django users quickly understand available features, potentially leading to improvements in Django and its documentation.

4. Community Engagement: The author encourages community feedback and collaboration to create a reliable, automatically updated feature matrix.

5. Future Aspirations: The article suggests that having an accurate feature comparison could attract more community and corporate support for Django.

Overall, the article highlights the need for clearer information about database support in Django and invites the community to contribute to developing a comprehensive comparison tool.

No summary available.

A Filipino man with Japanese heritage has had his request for Japanese citizenship denied. This news was reported on October 3, 2025, by Kyodo News.

Tommy Flowers, a lesser-known Post Office engineer, is now being recognized as a key figure in the development of early computing, particularly for creating the world’s first digital electronic computer, Colossus, during World War II. While Alan Turing is often celebrated as the main codebreaker at Bletchley Park, Flowers' work was crucial in cracking the complex Nazi Tunny encryption machine.

The story begins in a time of crisis for Britain, as Nazi U-boats threatened supply lines. Turing made significant contributions with his designs for breaking the Enigma code, but the emergence of the Tunny machine posed new challenges. Unlike Enigma, which used mechanical rotors, Tunny used teleprinter technology and binary code, requiring a more advanced solution.

Flowers proposed a revolutionary machine that utilized thermionic valves, a concept that was initially met with skepticism. However, with the support of his team at the Post Office, he developed Colossus, which efficiently decrypted messages and played a vital role in Allied intelligence efforts.

Despite the machine's success, Flowers remained largely unrecognized for decades, as many believed Turing and others were the primary innovators in computing. Now, as Flowers’ 120th birthday approaches, efforts are underway to honor him, including a mural at the National Museum of Computing. His story highlights the contributions of working-class individuals in technological advancements and challenges the dominant narratives around famous figures like Turing.

No summary available.

On September 28, 2025, the US Secret Service held a press conference revealing they seized 300 SIM servers and 100,000 SIM cards in New York City. This sparked media speculation about a potential terrorist threat. However, the devices found are linked to a system known as SMS Pools, primarily used for sending large volumes of spam and phishing messages.

Since late 2024, Americans have been bombarded with spam texts about undelivered packages and unpaid tolls, a tactic known as "smishing." These operations often originate from Chinese syndicates that sell SMS-blasting equipment via platforms like Telegram. One major player, Haowang Guarantee, has been involved in creating and selling these SMS systems.

These SMS Pools can range from simple devices with a few modem ports to advanced systems with many ports and numerous SIM cards. They allow users to send messages that appear to come from legitimate US phone numbers, aiding in various scams. Many sellers openly discuss using these systems for fraudulent activities, such as impersonating banks or companies to steal money.

The equipment used is relatively inexpensive and widely available online. Additionally, new technologies like eSIMs are emerging, allowing for even easier access to these services. The term "cat" in their names comes from the Chinese slang for modem, which has become commonly used in discussions about these systems.

In summary, the Secret Service's discovery in New York highlights a significant issue with SMS fraud and phishing, stemming from cheap and accessible technology linked to organized crime.

No summary available.

The text discusses design principles for the letter "A" in typography. It emphasizes that the crossbar should not sit exactly in the center, as this can make the letter look awkward. Instead, there should be a balance between the top and bottom spaces. Additionally, the thickness of the lines at the joints should be varied to avoid a heavy appearance. Overall, if something looks wrong, it probably is. The writer encourages intentional design choices and humorously warns against making poor financial decisions.

A Ryanair flight from Pisa, Italy to Prestwick, Scotland encountered extreme winds of up to 100mph, preventing it from landing. After three unsuccessful attempts to land, the pilots made a mayday call and diverted to Manchester, landing with only six minutes of fuel left. An investigation has been launched by the Air Accidents Investigation Branch (AAIB) into the incident, which involved a Boeing 737-800 carrying nearly 190 passengers. Passengers reported a turbulent experience during the landing attempts. Ryanair stated they are cooperating with the investigation and cannot comment further. The flight ultimately arrived in Manchester about 10 hours later than scheduled.

No summary available.

No summary available.

Summary of Pebble Appstore Update

The Pebble Appstore is being reintroduced with new features and improvements, thanks to a partnership with Rebble.

Key Points:

1. Production Updates:

   • 2,960 Pebble 2 Duo watches were produced in September, with shipments starting soon.
   • Black Pebble 2 Duo production was delayed due to a holiday in China.
   • Pebble Time 2 is progressing well, with new features that allow older watchfaces and apps to fit the larger screen. Mass production is expected to start at the end of December.

2. Pebble Appstore:

   • The Appstore now features over 2,000 apps and 10,000 watchfaces, including new creations since 2016.
   • All existing apps are compatible with new watches, although some may not work due to outdated settings.

3. Rebble’s Role:

   • Rebble has been crucial in keeping the Pebble community alive and has helped archive the original Appstore.
   • The new Appstore is powered by Rebble's services, making it accessible without a subscription.

4. New Features of the Appstore:

   • The Appstore has a familiar look with enhancements like social sharing options and recommendations for similar apps.
   • Future features may include app emulators and improved app discovery.

5. Developer Support:

   • Efforts are being made to support developers, including updates to the SDK and a new browser-based app development tool.
   • Developers can now easily create and submit apps for the new watches.

6. New Mobile App:

   • A new Pebble mobile app for iPhone and Android is being tested and is available for early users.

Overall, the Pebble community is being revitalized with new products, enhanced app support, and an engaging developer experience.

"Lights Out" is a puzzle game played on a grid where each cell is either red or white. The goal is to turn all cells red. When you click on a cell, it changes color and also changes the color of all cells in the same row and column.

The game is similar to a Rubik's cube because fixing one cell can disturb its neighbors. There are different ways to solve the puzzle, including mathematical methods and logical reasoning.

The name "Lights Out" comes from a handheld game from 1997. There are different rules for which cells change color, one of which involves flipping adjacent cells. The writer enjoyed discovering solutions to the puzzle and found it rewarding, as it relates to computing on limited architectures.

They created an app using TypeScript for exploring different strategies and board sizes. The app also helped produce a video using the Python library "manim." You are invited to try the game and share your experience!

I created a new model called Discrete Distribution Networks (DDN), which has been accepted for presentation at ICLR2025. DDN offers a fresh approach to modeling data distributions, differing from popular models like Diffusion, GAN, and VAE. Here are the main features of DDN:

1. It generates multiple outputs at once, rather than just one.
2. These outputs help to approximate the target distribution of the training data.
3. Together, they form a discrete distribution, which is why it's named "Discrete Distribution Networks."

DDN has some unique characteristics, including:

• Zero-Shot Conditional Generation (ZSCG).
• A one-dimensional discrete latent representation arranged in a tree structure.
• It is fully end-to-end differentiable.

Reviews for DDN highlight its novelty and potential to lead to new advancements in generative modeling.

The text provides links to two resources:

1. A GitHub page for a project called NanoMi.
2. A YouTube video related to NanoMi.

These links direct users to more information about the NanoMi project.

No summary available.

Tangled is a new platform that allows developers to collaborate on Git projects in a social and decentralized way. It uses the AT Protocol to give users full ownership of their code and create self-governing open-source communities.

The platform features "knots," which are simple servers that let users easily host Git repositories, whether on personal devices like Raspberry Pi or on larger community servers. Tangled provides free managed knots for hosting.

Users can access and contribute to various repositories through a unified view at tangled.sh, making collaboration seamless.

Tangled is still being developed, focusing on three main principles: data ownership, easy access, and a great user experience. The aim is to make coding collaboration feel natural and efficient.

Tangled has recently opened to the public, and users can now log in at tangled.sh/login.

Summary: Every LLM Is Its Own Media Channel

Marketers need to recognize that large language models (LLMs) like ChatGPT, Gemini, and Claude function as separate entities with distinct ways of finding and presenting information. Treating them as the same can lead to wasted resources and inconsistent brand visibility.

1. Distinct Ecosystems: Each LLM has its own rules for what information it prioritizes:

   • ChatGPT favors recent and verified sources.
   • Gemini relies on structured data and context.
   • Claude focuses on reliable and well-curated content.

2. No Convergence: Despite some similarities, these LLMs won’t merge into a single system due to:

   • Data sovereignty issues (sharing data can breach trust).
   • Different governance laws in various regions.

3. Marketing Strategy: Marketers should treat each LLM as a unique channel, similar to how they manage different advertising platforms. Each has its own visibility mechanisms and update schedules.

4. Governance: It’s important for brands to ensure their presence across these LLMs is consistent and reliable. This involves using specific metrics to measure visibility and manage risks.

5. Action Steps:

   • Audit your brand’s presence on each assistant.
   • Compare performance across different LLMs.
   • Monitor changes and ensure visibility metrics are integrated into governance.

In conclusion, LLMs are distinct discovery systems, and successful marketing now requires tailored strategies for each model rather than a one-size-fits-all approach.

The article argues that Apple's App Store operates in an authoritarian manner, prioritizing profit and control over user choice and innovation. It suggests that Apple has been willing to censor its platform to align with governmental pressures, particularly from the Trump administration, to protect its financial interests.

Key points include:

1. Censorship and Control: Apple is accused of censoring its App Store under government pressure, compromising its integrity for profit.

2. Threat of Interoperability: Legislation like the Digital Markets Act (DMA) poses a threat to Apple’s business model by promoting interoperability and browser choice, which could undermine the App Store’s monopoly.

3. Profit Over Innovation: Apple’s increasing revenue from services, rather than innovation, indicates a shift towards rent extraction from developers and users.

4. Tech Press's Role: The article criticizes the tech press for failing to connect the dots about Apple’s actions and the implications for democracy, power, and user rights.

5. Long-term Consequences: Apple’s willingness to collaborate with authoritarian regimes to maintain control reflects a broader trend of centralized power in technology, which can undermine democratic values and user freedoms.

Overall, the piece calls for a reevaluation of Apple’s practices and urges the tech community to question the power dynamics in technology.

Summary of Python 3.14 Benchmarking Results

Python 3.14 was released on October 7, 2025, prompting a new round of performance tests. The author previously discussed Python's speed in a 2024 post, and now aims to evaluate how the latest version compares in terms of speed.

Key Points:

1. Benchmarking Limitations: Benchmarks can be misleading; they provide only a snapshot of performance and may not fully represent real-world applications. The tests focused on pure Python code without native extensions to assess performance.

2. Testing Setup:

   • Versions Tested: CPython 3.9 to 3.14, plus Pypy, Node.js, and Rust.
   • Test Scripts:
     • A Fibonacci calculation (fibo.py) using recursion.
     • A bubble sort (bubble.py) function.
   • Configurations: Tests were run on both single-threaded and multi-threaded modes across two different computers.

3. Performance Results:

   • Fibonacci Test: Python 3.14 showed about a 27% speed improvement over its predecessor, 3.13. Pypy was significantly faster, nearly five times quicker than Python 3.14.
   • Bubble Sort Test: Python 3.14 was the fastest among CPython versions, with Pypy being 18 times faster than 3.14.
   • Multi-threaded Tests: The free-threading interpreter in 3.14 showed a notable performance boost for CPU-heavy tasks compared to the standard interpreter.

4. Interpreter Variants:

   • The Just-In-Time (JIT) interpreter did not provide substantial speed gains in these tests.
   • The free-threading interpreter is beneficial for multi-threaded applications, especially when the Global Interpreter Lock (GIL) is a bottleneck.

5. Conclusions:

   • Python 3.14 is the fastest version of CPython to date.
   • Upgrading to versions starting from 3.11 is recommended for performance improvements.
   • Pypy remains an impressive alternative, offering significantly better speed for certain tasks.

The author invites readers to share their own benchmarking results and considers future enhancements to the JIT interpreter.

ThalamusDB Overview

ThalamusDB is a processing engine that allows users to run SQL queries enhanced with semantic capabilities on various types of data, including text, images, and audio. You can find more details and documentation here.

Getting Started

1. Installation: Install ThalamusDB using pip:

   pip install thalamusdb
   

2. Setting Up: Store your API key (like OpenAI) as an environment variable. For example:

   export OPENAI_API_KEY=[Your API Key]
   

3. Running ThalamusDB: Start the console with:

   thalamusdb [Path to DuckDB database] --modelconfigpath=[Path to config file]
   

4. Example Database: Clone the example database and run queries:

   git clone https://github.com/itrummer/thalamusdb
   cd thalamusdb
   thalamusdb data/cars.db --modelconfigpath=config/models.json
   

Querying Data

You can perform semantic queries using natural language filters. For example:

select count(*) from cars where nlfilter(pic, 'the car in the picture is red');

Data Model and Query Language

ThalamusDB works with DuckDB and supports unstructured data types: text, images, and audio. You can use SQL queries with special semantic operators called NLfilter and NLjoin to process data in natural language.

Model Configuration

You can configure models for specific data types and operators using a configuration file. This file includes settings for how the models should process different data types and the priority of each model.

Approximate Processing

ThalamusDB provides approximate results for queries and distinguishes between aggregation and retrieval queries. It uses error bounds to indicate how close the results are to the exact answers.

Configuring Approximation

You can set limits on query execution time, the number of calls to the language model, and error thresholds using specific properties.

Citations

If you want to cite ThalamusDB, two references are provided for academic use.

Igalia has received funding from the Sovereign Tech Fund to improve the Servo web engine, which they have been maintaining since 2023. This support will help focus on three main areas:

1. Accessibility Support: Servo currently lacks key features for users with disabilities. The funding will help implement these features to make Servo usable for everyone.

2. WebView API: They will complete the WebView API, which is essential for embedding Servo in desktop and mobile applications, enhancing its usability and adoption.

3. Project Maintenance: The funding will also support ongoing maintenance of Servo and its libraries, ensuring they remain functional and beneficial for the wider Rust ecosystem.

Igalia believes that Servo can play a significant role in the future of web engines and is grateful for the support from the Sovereign Tech Fund. They are excited to share progress on these initiatives.

The text primarily discusses a subscription offer for the Financial Times (FT), highlighting various plans available for readers. Key points include:

• Discount Offer: A 40% discount is available for new subscribers, reducing the price from $540 to $319 for the first year.
• Subscription Benefits: Subscribers gain access to quality journalism, expert opinions, the FT app, curated newsletters, videos, and podcasts, along with the ability to share articles.
• Trial Option: A trial period is available for $1 for the first four weeks, after which the price becomes $75 per month.
• Different Plans: Options include digital, print, and combined subscriptions, with distinct features for each.
• Access Information: Users can check if they have existing access through their university or organization.

Overall, the text promotes the benefits and savings associated with subscribing to the Financial Times.

Summary of Avo CMS for Ruby on Rails Applications

Avo CMS is a content management system designed for Ruby on Rails applications. It offers various resources for developers, including:

• Documentation: Comprehensive guides and FAQs to help users understand and implement Avo.
• Templates: Ready-to-use blueprints and upcoming starter kits to speed up development.
• Community Support: A blog for news, contributions to the Ruby community, and a glossary of terms.
• Customer Insights: Case studies and testimonials showcasing successful usage of Avo by different companies.

Intelligent Search in Rails with Typesense

Typesense is a fast, typo-tolerant search engine ideal for Rails applications. It allows developers to create an index of data from their database to enhance search capabilities. Key points include:

• Performance: Typesense can handle many search queries quickly, making it suitable for applications needing efficient search functionality.
• Integration: It simplifies the process of adding search features compared to traditional database search methods.
• Data Structure: In Typesense, "documents" represent individual records, while "collections" group related documents. The "schema" defines the structure of the data being indexed.

In summary, Avo CMS provides tools and support for Rails developers, while Typesense offers a robust solution for implementing intelligent search in applications.

A recent Gallup poll reveals that 62% of Americans believe the federal government has too much power, marking the highest level of concern since 2002. This sentiment has increased significantly from 51% a year ago. Notably, for the first time since 2007, more Democrats (66%) than Republicans (58%) feel the government is too powerful. This shift reflects a growing discontent among Democrats, likely due to extensive actions taken by the Trump administration, including many executive orders and military use domestically.

In terms of government involvement in solving problems, 51% of Americans think the government is doing too much, while 40% believe it should do more. Historically, Republicans have consistently felt the government is overreaching, while fewer Democrats share this view. Currently, 74% of Republicans feel the government is doing too much, compared to 34% of Democrats.

The findings suggest a strong partisan divide in opinions about government power and its role, with Democrats' concerns rising sharply this year, contrasting with their relatively stable views on the government's responsibilities. Overall, these trends indicate a growing public perception that the federal government is overstepping its boundaries.

Summary of How to Check for Overlapping Intervals

Working with intervals is common in programming, especially for tasks like scheduling or geometric calculations. Here's a simplified guide on how to represent and check for overlapping intervals.

What Are Intervals?

• An interval is a range defined by two points, often written as [start, end].
• Intervals can be closed (including the end) or half-open (not including the end).
• Examples include time intervals (e.g., [9:00, 17:00]), numeric ranges (e.g., [1, 10)), and date ranges.

Representing Intervals in Code

• Use a simple class in Python, where an interval is represented by start and end values.

Detecting Overlap

• To check if two intervals overlap, it’s often easier to check when they do not overlap.
• There are two main cases for non-overlapping intervals:
  1. One interval ends before the other starts.
  2. The other interval ends before the first one starts.

Using these cases, you can write a simple function to check for overlap like this:

def overlaps(self, other: Interval) -> bool:
    return not (self.end <= other.start or other.end <= self.start)

This checks that there is a point of overlap between the two intervals.

Extending to Boxes

• The concept can be extended to two-dimensional boxes, where you check if they overlap both horizontally and vertically.
• Similar to intervals, you can check non-overlapping conditions for boxes:
  1. One box is to the left of the other.
  2. One box is to the right.
  3. One box is above the other.
  4. One box is below the other.

The function for checking box overlap can be written as:

def overlaps(self, other: Box) -> bool:
    return (other.left < self.right and self.left < other.right and
            other.bottom < self.top and self.bottom < other.top)

Conclusion Finding the best way to express overlap checks can be complex. Using negation to simplify the process can lead to clearer and more manageable code. This approach is particularly useful when dealing with multiple cases, such as with boxes, where complexity can escalate.

The text explores the question of how hard you need to hit a chicken to cook it. A humorous calculation suggests that hitting a chicken at 3,726 mph could technically cook it, but this approach doesn't account for keeping the chicken at the right temperature long enough to cook it fully.

To really cook a chicken, you need to consider how quickly it cools down. A chicken at 165°F loses heat quickly, radiating about 2000 watts of energy. To keep it at this temperature, you'd need a continuous source of heat. The text proposes a scenario where four people, each swinging a bat at 75 mph, would hit the chicken once per second. This setup could cook the chicken in a few minutes, assuming they are in a vacuum to prevent heat loss.

Summary of Switching to Helix from Vim

In October 2025, the author shares their experience of switching from Vim to the Helix text editor after three months of use. Here are the key points:

1. Motivation for Switching: The author sought an easier setup for language server support, which Helix provides out of the box, making features like "go to definition" more accessible without extensive configuration.

2. Advantages of Helix:

   • Improved Search: Helix offers better search capabilities, allowing users to see context around search results.
   • Quick Reference: A helpful popup appears when pressing 'g', showing available navigation options.
   • Simpler Configuration: Helix has a straightforward configuration process, requiring minimal setup compared to their extensive Vim configuration.

3. Differences from Vim:

   • Helix uses different methods for navigation and editing, like Ctrl+O for cursor locations and a buffer switcher instead of tabs.
   • Users can utilize multiple cursors instead of macros for batch editing.

4. Annoyances: The author mentions some drawbacks, such as:

   • Issues with text reflow and Markdown list handling.
   • Lack of persistent undo functionality.
   • Need for manual file reloading.
   • Occasional crashes.

5. Ease of Transition: The author found it easier than expected to adapt from Vim, especially after focusing on Helix's unique keybindings instead of trying to replicate Vim's.

6. Terminal Usage: The author adjusted to using Helix in a terminal environment and found a new workflow that they enjoy.

7. Configuration: Helix's configuration is simple, with only a few keyboard shortcuts and specific language settings.

8. Future Outlook: After three months, the author is still using Helix but acknowledges that they might return to Vim in the future.

Overall, the transition to Helix has been positive, with some minor frustrations, but the author appreciates the ease of use and built-in features.