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The most common AI models today are Transformers that use a method called self-attention. However, this method can be costly in terms of storage, computing power, and energy, especially as the amount of data (context length) increases.

To solve this problem, we demonstrate a new way to compute self-attention that maintains a constant cost for each piece of data (token), which significantly reduces memory and computing needs. We achieve this by breaking down the traditional method's calculations into simpler parts and using their symmetry to create efficient transformations for processing data.

Our approach allows for generating more tokens without increasing costs, which lessens the energy and infrastructure requirements of large Transformer models. Additionally, the mathematical techniques we developed could have other valuable applications.

The recent discussions about "clawdbot" (an AI assistant) have become intense, with some users giving it extensive permissions and even creating networks of them. Despite the chaotic nature of these conversations, the author shares their positive experiences and the value they've gained from using clawdbot.

Key Points:

1. Personal Use Cases: The author describes various ways they use clawdbot:

   • Managing texts and calendar events.
   • Summarizing group chats.
   • Monitoring prices for products and travel.
   • Keeping track of household inventory and grocery lists.
   • Automating bookings and filling out forms.

2. Trust and Risk: The author acknowledges the risks of giving clawdbot access to sensitive information, such as bank details and personal messages. They compare this to the trust established with a human assistant, noting that more access leads to greater usefulness.

3. AI Interaction: They argue that limiting AI's capabilities can hinder its effectiveness. Embracing flexibility and allowing the AI to learn and adapt leads to better outcomes.

4. Setup Details: The author runs clawdbot on a Mac mini, using Slack for communication, which allows for better integration with their workflow and keeps everything organized.

5. Caution and Control: While clawdbot requires significant access, the author takes precautions, such as running it on a separate machine and restricting its browsing capabilities.

Overall, the author finds clawdbot to be a valuable tool that enhances productivity, despite the associated risks, advocating for a balanced approach to using AI technology.

The FBI couldn't access the iPhone of Washington Post reporter Hannah Natanson because it was in Lockdown Mode, a security feature that protects the device. Court records reveal what data the FBI could access after raiding her home in January, as part of an investigation into classified information leaks. This situation highlights how effective Lockdown Mode can be in keeping data secure from unauthorized access.

Summary of the Analysis of Epstein PDFs

The article discusses a technical examination of PDF files released by the US Department of Justice (DoJ) related to the Epstein Files Transparency Act. It highlights the importance of proper sanitization and redaction in handling sensitive documents.

Key Points:

1. PDF Forensics Overview: The analysis focused on the structure and technical aspects of the released PDF files, not their content. PDF files are complex binary formats that require specialized knowledge to analyze.

2. Recent Releases: On December 19, 2025, the DoJ released a large dataset with thousands of PDFs. A new dataset was released on December 26, 2025, containing over 11,000 files, including many new PDFs.

3. File Validity and Structure: The analysis assessed whether the PDFs were valid and conformed to PDF standards. Minor issues were found, but overall, the files were deemed valid.

4. Incremental Updates: The study noted that some PDFs contained incremental updates, which could complicate analysis. These updates allow for multiple revisions of a document within a single PDF.

5. Bates Numbering: Each page of the PDFs was assigned a unique Bates number through an incremental update process, ensuring proper identification.

6. Metadata and Document Information: Most PDFs lacked metadata or contained orphaned metadata due to improper handling during redaction. This raises concerns about potential information leakage.

7. Photographs and Scanned Documents: The PDFs contained images that appeared to be either scanned documents or processed digital images. JPEGs were avoided to prevent retaining identifiable metadata.

8. Optical Character Recognition (OCR): OCR was used to extract text from images, but its quality varied, indicating the possibility of errors in recognizing text.

9. Conclusion: The DoJ has established processes for sanitizing and redacting PDFs, but improvements are possible in file management and technology. The complexity of PDF forensics requires careful analysis to avoid misleading results.

Overall, the analysis emphasizes the challenges and techniques in PDF forensics, particularly concerning the handling of sensitive documents like the Epstein PDFs.

SpaceX recently acquired xAI, aiming to establish data centers in space, joining other tech companies like Google and several startups. They believe that with abundant solar power and advanced rockets, space-based data centers could be feasible. A study suggested that if launch costs drop to $200 per kilogram by 2035, space data centers could compete with ground-based ones.

However, there are significant challenges. For example, training AI requires vast numbers of GPUs, and launching millions of satellites would increase the risk of space debris. Additionally, satellites can't be easily upgraded like ground-based servers, making it hard to stay competitive. Ground-based solar energy has also become cheaper over time, making space data centers less appealing.

Despite these issues, companies and investors are excited about the potential. SpaceX, looking to go public, and xAI, which needs funding, may be inflating interest in this idea. Investors might see a chance to profit in the short term, even if the long-term feasibility of space data centers remains questionable.

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This text discusses setting up ephemeral Virtual Machines (VMs) using the microvm.nix project on NixOS, which allows for safe coding with AI agents like Claude without risking personal data. The setup involves several steps:

1. Network Preparation: Create a network bridge for the VMs to connect through.
2. Flake.nix Configuration: Add the microvm module to the configuration file to manage the VMs.
3. MicroVM Declaration: Specify configurations for individual VMs, such as those for Emacs and Go Protobuf, including IP addresses and workspaces.
4. Base Configuration: Define shared directories, network settings, and resources for the VMs, like CPU and memory.
5. Home Manager Setup: Configure user environments for tools like Zsh and Emacs.
6. Running the VM: Start the VM and connect via SSH to run the coding agent.

The author emphasizes the efficiency and safety of using these VMs, as they are easily disposable if compromised. They also suggest that AI agents can assist in automating the creation of VMs. By using tools like Claude, users can replicate their entire setup with minimal effort.

In conclusion, the article highlights the power and flexibility of NixOS for managing projects with ephemeral VMs, showcasing the advancements in AI capabilities that enhance productivity in coding tasks.

The text appears to be a brief reference to a document or publication from Urbana, Illinois, dated 1915, consisting of 14 pages. It was uploaded by a user named acfc on November 20, 2024.

Key Points:

• Location: Urbana, Illinois
• Year: 1915
• Length: 14 pages
• Uploaded by: acfc
• Upload date: November 20, 2024

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Summary of Electric Tractor Project

The electric tractor, a toy for children and adults, is complete after six months of work. The project has been enjoyable, especially for the builder and his young daughter, Lucy.

Key Details:

• Power and Design: The tractor runs on a 350W motor and a 36V battery, designed for slow speeds suitable for children. It features a solid rear axle for synchronized wheel movement and a pivoting front axle for better stability on uneven ground.
• Brake and Steering: It has a basic rear disc brake and a steering system modeled after a classic tractor, though it has some design challenges, such as the steering gearbox being difficult to install.
• Chassis and Wheels: The chassis is made of plywood, and the rear wheels are from a ride-on lawnmower, with modifications made for fitting.
• Motor and Control: A countershaft was added to manage the motor speed better, and a DPDT switch allows for reversing the motor direction.
• Finishing Touches: The builder faced challenges with the design and aesthetics, including the bonnet and throttle response. Ultimately, he opted for simpler designs and removed unnecessary electronic components for direct control.

Additional Notes:

• Painting and welding were tedious tasks, with the builder reflecting on his welding technique improvements.
• The project emphasizes creativity and hands-on learning, with the hope that Lucy will gain inspiration from the building experience.

The author reflects on the importance of "thinking hard" and how it has diminished in their life due to the influence of AI. They describe their personality as a mix of two traits: The Builder, who enjoys creating and being productive, and The Thinker, who thrives on deep, prolonged mental challenges.

In the past, they found satisfaction in tackling complex problems, especially during their studies in physics, where they categorized their peers into those who gave up, those who researched for solutions, and those who persisted through deep thinking—like themselves.

However, with the rise of AI, the author feels their ability to engage in deep thought has been stifled. Although they are producing more software than ever, they feel stagnant in their growth as an engineer, as the quick solutions provided by AI leave little room for creative problem-solving.

The author acknowledges that while AI offers practical solutions, it also poses a conflict with their desire for intellectual challenge. They are unsure how to reconcile these two aspects of their personality, as their need for deep thought remains unfulfilled amid the efficiency of AI-assisted coding. Ultimately, they express uncertainty about whether they can find a balance between building and thinking in their future work.

The author created a production management software called Craftplan for small-batch manufacturers, like micro-bakeries, after finding existing options to be too expensive or generic. Craftplan is open-source and helps manage recipes, inventory, orders, production planning, and purchasing. It was built using Elixir and other technologies. You can try a live demo here and find the code on GitHub.

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Deno Sandbox Overview

Deno Sandbox is a new feature designed to safely run code generated by Large Language Models (LLMs) without human review. This code often requires access to APIs, which raises security concerns, as it can expose sensitive information.

Key Features:

1. Isolation of Code: Deno Sandbox uses lightweight Linux microVMs to run untrusted code securely in the Deno Deploy cloud. This prevents malicious code from compromising your system.

2. Secret Management: Secrets, like API keys, never enter the sandbox environment directly. Instead, they are represented by placeholders and only become visible when the code makes authorized requests.

3. Network Control: You can restrict which external hosts the sandbox can communicate with, blocking any unauthorized requests.

4. Easy Deployment: Code can be deployed directly from the sandbox to Deno Deploy without needing to rebuild or re-authenticate.

5. Persistence Options: Sandboxes are typically temporary but can use read-write volumes and snapshots for state preservation, allowing quick setup of development environments.

Technical Details:

• Available in several regions, including Amsterdam and Chicago.
• Offers up to 4 GB memory and 2 vCPUs, with boot times under one second.
• Designed for various applications like AI agents, CI runners, and secure plugin systems.

Pricing: Deno Sandbox is part of the Deno Deploy plan, with competitive, usage-based pricing.

Getting Started: Deno Sandbox is now in beta, and resources for setup and documentation are available on the Deno website.

This new tool aims to enhance security and streamline the development process for users building with Deno.

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Summary:

In February 2026, a DIY project featured in DIY Magazine discusses how to explore the stratosphere using small balloons known as pico balloons. These balloons can carry tiny payloads and are equipped with ham-radio transmitters that allow users to track them globally. The article, written by David Schneider, highlights the excitement of amateur radio and science through pico ballooning.

French authorities have raided the Paris offices of Elon Musk's company, X, as part of an investigation into serious allegations, including illegal data extraction and involvement in child pornography. Musk and former CEO Linda Yaccarino have been summoned for hearings in April. Musk described the raid as a "political attack," while X expressed disappointment and denied any wrongdoing, claiming the investigation threatens free speech.

The investigation began in January 2025, focusing on X's algorithm and later expanding to Musk's AI tool, Grok. This AI has been criticized for generating harmful sexualized content, leading to a separate investigation by the UK's Information Commissioner's Office (ICO). The ICO is examining how Grok processes personal data and whether it has been used to create intimate images without consent.

In response to these developments, Pavel Durov, the founder of Telegram, criticized France for its treatment of social media platforms and claimed it is not a free country.

Goblins: Distributed, Transactional Programming Summary

Goblins is a key part of Spritely, designed for distributed object programming. It offers:

• A user-friendly security model.
• Automatic local transactions for smooth local operations.
• An efficient way to program asynchronously with objects anywhere on the network.

The networking model simplifies programming, allowing developers to focus on creating objects without worrying about the underlying protocols. Goblins also includes advanced debugging tools and maintains security during process changes and upgrades.

Goblins supports asynchronous programming across different programming languages, currently featuring support for Guile and Racket.

For more information, you can read the detailed whitepaper or recent articles about Goblins' applications in various projects.

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Summary of Xcode 26.3 Update (February 3, 2026)

Xcode 26.3 introduces "agentic coding," which allows developers to use coding agents like Anthropic's Claude Agent and OpenAI's Codex directly within Xcode. This new feature helps automate complex tasks, making app development faster and more efficient.

Key Points:

• Agentic Coding: Enables Xcode to work more autonomously, assisting developers in breaking down tasks and making decisions based on project needs.
• Enhanced Collaboration: Coding agents can assist throughout the entire app development process, including searching documentation, exploring files, updating settings, and verifying work with visual previews.
• Flexibility: Developers can choose the coding agent that best suits their project needs and can also utilize other compatible tools through the Model Context Protocol.
• Availability: Xcode 26.3 is available as a release candidate for Apple Developer Program members now, with a full release coming soon on the App Store.

Apple aims to empower developers with advanced tools to enhance productivity and creativity in app development.

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In recent years, keyboard technology has advanced rapidly, with many new switch designs emerging that promise improved speed, durability, and responsiveness. There are several types of keyboard switches, each with its own way of detecting key presses, including:

1. Physical Contact Keyboards: These include mechanical and membrane keyboards that register key presses by closing a circuit. Mechanical switches come in various types (linear, tactile, clicky) and are popular for their durability and customization options. Membrane keyboards are simpler and cheaper but provide less feedback and customization.

2. Optical Keyboards: These switches use light beams to detect key presses, allowing for quicker actuation and greater durability since there are no physical contacts to wear out.

3. Magnetic Keyboards: These switches detect key presses through changes in electromagnetic properties. Hall Effect switches, for example, use magnets and sensors to measure key positions, offering features like adjustable actuation points.

4. Inductive Keyboards: Similar to magnetic switches, these measure changes in inductance. They provide high resolution and durability without physical contacts.

5. Capacitive Keyboards: These detect key presses through changes in capacitance, often providing a unique tactile feel but can be expensive and less customizable.

Overall, different switch technologies coexist, each offering unique advantages and disadvantages. Emerging technologies suggest future keyboards will prioritize user experience and functionality over traditional sensing methods. Ultimately, the best keyboard switch is one that suits individual preferences.

The text discusses the reliability of mathematical proofs and proof assistants, highlighting common issues and errors that can arise. Here are the key points:

1. Expectations of Perfection: People often expect mathematical proofs to be flawless, much like how they expect vaccines to be 100% effective. However, both proofs and real-world systems can fail.

2. Common Errors in Proofs:

   • A notable error cited is when a mathematical paper incorrectly assumes a condition that leads to invalid conclusions. Proper verification tools like Isabelle could help catch such mistakes.
   • There are instances where proof assistants can lead to incorrect proofs due to bugs or design flaws, such as infinite loops caused by multithreading.

3. Definition Issues: Errors can also arise from incorrect definitions, but if these definitions are not central to the main theorem, the overall proof may still hold.

4. Soundness Bugs in Proof Assistants:

   • Isabelle, a proof assistant, has had some soundness bugs over the years, but they are infrequent and often fixed quickly.
   • Other proof systems like PVS have struggled with soundness issues, but those problems have not typically led to significant practical consequences.

5. Trustworthiness of Machine Proofs: Despite the potential for errors, the author argues that machine proofs generally maintain a good track record and that verification processes are effective.

6. Future Directions: The text emphasizes the importance of rigorous approaches in proof development and mentions advancements in systems like HOL Light and the Candle theorem prover, which aim for a high level of reliability.

In summary, while mathematical proofs and proof assistants can have errors, there are systems in place to catch and correct these mistakes, making machine proofs a reliable method in many cases.

Summary:

Fred, the author, shares his experience with identity theft related to his property at 221 Cannon Road in Wilton, Connecticut. He and his brother bought the land in 2015 and have never listed it for sale. However, they have faced multiple attempts from a scammer impersonating them to sell the property.

The first incident occurred in March 2024 when a real estate attorney contacted Fred after noticing discrepancies in a sale attempt. The scammer had used fake identification and communicated primarily through email. Thanks to the attorney's diligence, the sale was stopped.

In February 2026, Fred was alerted again by two real estate agents that someone was trying to sell the same property. This type of scam targets vacant land, as it is often unnoticed by neighbors, and transactions can happen remotely.

Fred advises landowners to take preventive measures, such as registering a Fraud Notice with local authorities and setting up Google Alerts for their property. He emphasizes that 221 Cannon Road is not for sale and urges anyone contacted about it to reach out to him directly.

Summary:

Cable Tie Link is offering what it claims is the world's largest and strongest zip tie, measuring 47 inches long and capable of holding up to 2,000 pounds. This oversized zip tie is designed for industrial use, garages, and creative projects. While zip ties are typically valued for their small size and versatility, this giant version may be better suited for larger projects. They are available for $75 each, or in packs of 12 or 25 for $799.99 and $1,699.99, respectively.

Summary

A student is creating a new, fast VPN by reimplementing the Tor network from scratch. They want to access their email server and install Linux packages without spending money on a VPN service. The student finds that Tor is slow and doesn't provide the speed they need for their tasks.

They explore the idea of connecting directly to a Tor exit node as a single-hop proxy but discover that Tor blocks this method for security reasons. Despite this, they decide to create their own version of Tor, focusing on speed rather than anonymity.

Using C++, they build a command-line application called Kurrat that connects to Tor exit nodes. They aim to make the application fully self-sufficient, avoiding reliance on system libraries. The student uses the mbedtls library for cryptographic functions and outlines the steps for establishing a secure connection, including handshakes and key exchanges.

After successfully implementing their version of Tor, they benchmark the connection speeds and find Kurrat performs faster than the standard Tor browser. The project highlights the importance of understanding networking and cryptography, and the student encourages others to explore similar projects. All the code is available as open source on GitHub.

Summary of prek

What is prek?

• Prek is a new tool that serves as a faster and simpler alternative to pre-commit, built in Rust. It runs hooks in various programming languages without needing dependencies.

Key Features:

• No Dependencies: Just a single binary, no need for Python or other runtimes.
• Speed: Faster than pre-commit and uses less disk space.
• Compatibility: Works with existing pre-commit configurations.
• Monorepo Support: Built-in support for managing multiple projects in one repository.
• Improved Toolchain: Better installations for various languages like Python, Node.js, and Rust.
• Rust Hooks: Some hooks are implemented in Rust for better performance.

Installation:

• Prek can be installed via various methods including:
  • Standalone installer for Linux, macOS, and Windows.
  • Package managers like Homebrew, Conda, Scoop, and MacPorts.
  • As a Node.js package or via GitHub releases.

Quick Start:

• Users of pre-commit can follow a migration guide to switch to prek easily.
• New users can learn the basics through a beginner's guide.

Why Use prek?

• It is significantly faster and uses less space compared to pre-commit.
• Simplifies the user experience by automatically handling Python environments.
• Supports various command improvements for running hooks and managing configurations.

Current Users:

• Prek is already being used by notable projects including CPython, Apache Airflow, and FastAPI.

Acknowledgements:

• The development of prek was inspired by the original pre-commit tool and influenced by contributions from various open-source projects.

Summary of "Resurrecting Crimsonland"

The project "Resurrecting Crimsonland" aims to revive the classic 2003 game, Crimsonland, through reverse engineering and decompiling its code. The original game, developed by the Finnish studio 10tons, gained a cult following due to its addictive gameplay. The author, known as banteg, began this project in January 2026, intending to create a faithful rewrite of the game that mirrors the original behavior and mechanics exactly, even replicating bugs.

Key points include:

• Game History: Crimsonland is a top-down shooter released in 2003, with a remaster in 2014. It was initially popular as shareware and has seen several updates over the years. Despite interest in a sequel, the developers shifted focus to mobile games, leaving fans disappointed.

• Reverse Engineering Process: The project employs tools like Ghidra for static analysis and Windbg for runtime analysis to understand the original game's code. The goal is to rewrite the game’s code from scratch while retaining its original functionality and quirks.

• Technical Challenges: The author faced difficulties due to the lack of documentation in the original binary and the need to analyze several components like the game's rendering engine and asset formats. They developed custom parsers for assets and implemented features like text rendering and game logic in a readable, testable manner.

• Current Progress: As of the writing, the project has resulted in 46,800 lines of code, with all gameplay modes functional. The aim is to ensure that seasoned players cannot distinguish the new version from the original game.

• Future Plans: After completing the core game, the author may explore adding features like online high scores or network multiplayer. They also consider optional enhancements like improved lighting effects while preserving the original game’s essence.

The author invites those familiar with the original game to help identify any inconsistencies and encourages interest in the project through a GitHub repository and a Telegram group.

We are hiring! Check out the open jobs we have.

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Y Combinator, a leading startup incubator in Silicon Valley, is now allowing its spring cohort of entrepreneurs to receive funding in stablecoins, specifically USDC, which is issued by Circle. Typically, these startups receive around $500,000, and they can choose to receive these funds on various blockchain platforms like Ethereum and Solana. Y Combinator is open to including more stablecoins in the future based on demand.

Stablecoins, which have been around for over a decade, are gaining traction beyond just crypto traders. Recently, big companies like Stripe and Cloudflare have shown interest in stablecoins, highlighting their potential for faster and cheaper money transfers. Despite the current downturn in the broader cryptocurrency market, interest in stablecoins remains strong, according to Y Combinator's partner, Nemil Dalal. He believes that many startups will increasingly seek to raise funds using blockchain technology in the future.

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Summary of Speculative Sampling

Speculative sampling aims to mimic a target sampling distribution (p(x)) using a draft sampling distribution (q(x)). Here are the main points:

1. Sampling Probabilities: For each token, we compare two probabilities: p(xi) (from the target) and q(xi) (from the draft). We determine if a token is over-sampled (q(xi) > p(xi)) or under-sampled (q(xi) < p(xi)).

2. Rejection Method: To adjust the samples:

   • Down-sampling: If a token is over-sampled, we only accept it with a probability of p(xi)/q(xi). This ensures we reduce the number of over-sampled tokens.
   • Up-sampling: For under-sampled tokens, we give them additional chances by not rejecting them. If we reject an over-sampled token, we then sample from a new “residual distribution” that prioritizes the under-sampled tokens.

3. Residual Distribution: This is defined to represent the probability of under-sampled tokens, ensuring that over-sampled tokens have zero probability in this distribution.

4. Final Result: The process of down-sampling and up-sampling ensures that the final sampling result aligns with the target distribution p(x).

In essence, speculative sampling cleverly balances over-sampled and under-sampled tokens to accurately reflect the target distribution.

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Summary of Claude's Approach to Advertising

Claude is designed to be a helpful and focused assistant for deep thinking and work, and it will remain ad-free. The decision to exclude advertising stems from a desire to maintain the integrity of user conversations, which often involve sensitive or complex topics. Introducing ads could compromise Claude's ability to genuinely assist users, as it would create conflicts between providing helpful responses and potential commercial motives.

While some companies rely on advertising for revenue, Claude’s model is based on enterprise contracts and paid subscriptions. This approach allows Claude to prioritize user needs without selling their attention or data to advertisers. The goal is to keep Claude a trustworthy tool for users, fostering an environment free from commercial influences.

Anthropic, the company behind Claude, plans to explore ways to support commerce that align with user interests, ensuring that any interactions with third-party services are user-initiated. The overarching aim is to maintain a productive and ad-free space for users to think and work effectively.

Summary of Puget Systems Most Reliable Hardware of 2025

Introduction
Puget Systems evaluated the reliability of computer hardware used in their workstations and servers throughout 2025. This report highlights the most dependable brands and models.

Data Sources
The findings are based on Puget Systems' internal data, including records of hardware failures and a thorough qualification process. They aim to provide accurate insights but acknowledge that their standards may lead to different failure rates compared to the industry average.

Key Findings by Component:

• CPU (Processors): Intel's Xeon W-2500 and W-3500 series showed exceptional reliability with no recorded failures in 2025. For consumer processors, Intel's Core Ultra 7 265K was the standout with a 0.77% failure rate, while AMD's Ryzen X3D processors were also reliable at 1.51%.

• GPU (Video Cards): NVIDIA's Founders Edition models had the lowest failure rate at 0.25%. Among professional cards, NVIDIA's RTX Ada Generation was highly reliable, except for the RTX PRO 6000 model.

• Motherboards: Motherboards generally had higher failure rates, but the Gigabyte B860M AORUS ELITE WIFI6E ICE and ASUS TUF B850M-PLUS WIFI were noted for their reliability, with very few failures reported.

• RAM (Memory): Kingston emerged as the most reliable RAM manufacturer with a failure rate of 0.19%, while the Kingston ValueRAM DDR5-5600 32GB was the most dependable individual memory module at 0.09%.

• Storage: Samsung's 870 QVO 8TB SSD had zero failures, while Kingston's KC3000 SSD also performed well with a 0.22% failure rate.

• Power Supply (PSU): Corsair's SF1000 Platinum PSU recorded no failures, while Super Flower's LEADEX line maintained a solid reliability rating.

Conclusion
The report provides valuable insights into hardware reliability. Puget Systems encourages feedback on specific topics for future analysis. They specialize in building custom workstations and emphasize their commitment to quality and customer support.

Summary of the Notepad++ Supply Chain Attack

On February 2, 2026, Notepad++ revealed that its update system had been compromised due to a security breach between June and September 2025. Attackers maintained access until December 2025, using multiple execution chains to deliver malicious updates.

Key Points:

1. Attack Overview:

   • The attackers used various Command and Control (C2) servers and constantly changed their methods to deliver malware.
   • They targeted individuals and organizations in multiple countries, including Vietnam, El Salvador, Australia, and the Philippines.

2. Execution Chains:

   • Chain #1 (Late July - Early August 2025): Malicious updates were distributed using a specific URL, installing a harmful payload disguised within a legitimate Notepad++ update process. The malware collected system information and exploited vulnerabilities in legitimate software.
   • Chain #2 (Mid - Late September 2025): A new infection method was introduced, again distributing malicious updates from the same URL but with different payloads and system information gathering methods.
   • Chain #3 (October 2025): The attackers changed their approach again, using a different URL and executing a more sophisticated malware installation process without collecting system information.

3. Subsequent Activity:

   • In mid-October 2025, the attackers resumed using Chain #2 with new URLs while continuing to adapt their methods.

4. Detection and Defense:

   • Kaspersky's security solutions successfully identified and blocked these attacks by monitoring for specific behaviors and known indicators of compromise (IoCs).
   • Organizations are advised to check for unusual NSIS installers, monitor network traffic for suspicious domains, and investigate specific shell commands executed by the malware.

5. Indicators of Compromise (IoCs):

   • A list of malicious URLs and file hashes associated with the attack is provided, enabling organizations to identify potential threats.

Overall, this supply chain attack illustrates how attackers can exploit legitimate software update processes to target high-profile organizations, making detection challenging.

A recent study published in Science examined the heritability of human lifespan, concluding that about 50% of lifespan variation can be attributed to genetic factors when accounting for external causes of death, such as accidents and infections. Previous studies had reported much lower heritability estimates, often around 20-25% or even lower. Researchers analyzed over a century of data from Scandinavian twin cohorts and found that extrinsic mortality skewed previous estimates.

By correcting for this and using advanced mathematical modeling, the study revealed that intrinsic mortality—caused by genetic factors and aging-related diseases—contributes significantly to lifespan heritability, raising it to approximately 55%. This suggests that genetic factors play a crucial role in longevity, similar to other complex human traits. Additionally, the findings indicate that as external mortality decreases, genetic contributions to lifespan become clearer, supporting the need to focus on genetic research in understanding aging.

The text discusses the difference between two definitions of a kilobyte: the common belief that 1 kilobyte equals 1024 bytes and the argument that it should be considered as 1000 bytes.

Key points include:

1. Binary vs. Decimal: Computers use a binary system, which makes 1024 (2^10) a practical choice for memory sizes. However, for larger units, the difference between binary and decimal becomes more significant.

2. Proportional Inaccuracy: As you move to larger units (like megabytes and gigabytes), the difference between the binary and decimal values increases, leading to confusion, especially when hardware manufacturers advertise in decimal (e.g., 1 GB = 1,000,000,000 bytes) while operating systems may show binary values.

3. Standard Units: The text explains how the International Electrotechnical Commission (IEC) has introduced binary prefixes (like KiB for kibibyte, MiB for mebibyte) to clarify these differences, suggesting that SI prefixes (like kB for kilobyte) should be used for decimal values.

4. Conclusion: While many still equate 1 kilobyte with 1024 bytes due to tradition, this can confuse non-technical users. It's important to understand the context in which these terms are used.

Aram and Eduard, co-founders of Modelence, created an open-source framework using TypeScript and MongoDB to streamline app development. They wanted to avoid repetitive tasks like authentication, database management, and API setups.

Modelence aims to be a full-stack framework that benefits both AI coding agents and human developers. Key features include:

• TypeScript helps catch errors early, aiding AI agents.
• MongoDB simplifies database management for agents.
• Built-in functionalities like authentication and cron jobs allow agents to focus solely on product logic, reducing setup errors.

You can try the Modelence app builder by visiting their website, where you can type a prompt and see a demo video. Developers can also work locally while using Modelence Cloud as their backend and will soon have access to a DevOps agent to manage errors and incidents effectively.

The app builder is designed to help developers get started quickly, but the founders emphasize that their main focus is on improving the framework and platform itself, which they see as the real challenge in AI coding.

Recently, many people have been sharing excerpts from old emails on Twitter, leading to confusion about the frequent use of equals signs. The author, who has experience with email software, clarifies that the equals signs are not a code or a scanning error, but a result of how emails were converted to a readable format.

In the past, emails were mostly plain text, but as technology advanced, email systems began using a method called "quoted printable" to handle long lines. When a line is too long, it is split into two parts, with an equals sign indicating the continuation. For example, the line "we talked about designing a pig with different non- cloven hoofs" might be shown as:

"we talked about designing a pig with different non- =
cloven hoofs"

The equals sign helps the email system understand that these parts belong together.

However, mistakes can occur during the conversion process, especially when handling different types of line endings, resulting in the equals sign remaining in the text when it shouldn't. The author suggests that the presence of equals signs can also indicate errors in decoding special characters used in emails.

In summary, the equals signs are the result of technical issues related to email formatting and decoding errors caused by incompetent processing of these emails.

Summary of "Flying Around the World in Under 80 Days: An Autonomous Airship Drone"

This project aims to create an autonomous airship drone that can fly around the world in under 80 days, inspired by Jules Verne's story. Here are the key points:

1. Speed and Distance: The drone needs to travel approximately 40,000 km (25,000 miles) at an average speed of 10 m/s (about 22 mph) to complete the journey in 80 days.

2. Energy Efficiency: The airship will be designed to be buoyant using hydrogen gas, which is lighter and cheaper than helium. It will also use solar panels to recharge its electric batteries during the day.

3. Construction Materials: The drone's structure will be made from lightweight composite materials to ensure it can stay aloft for lengthy periods. The size will target around 4 meters in length, weighing less than 10 kg.

4. Flight Route: The route will be strategically planned to take advantage of trade winds, which blow from east to west, allowing for more efficient travel. The journey will involve crossing oceans and navigating over land while avoiding politically sensitive areas.

5. Navigation and Communication: The airship will use miniaturized technology for navigation and communication, including options like LoRa and SigFox for telemetry data transmission.

6. Legal Considerations: Flying the drone legally will require careful planning to comply with different countries' regulations, particularly concerning altitude and registration.

7. Budget and Feasibility: While the materials are relatively inexpensive, specialized equipment like hydrogen generators can be costly. The project will require trials to ensure reliability.

8. Conclusion: The author believes that, despite the challenges, it is feasible to create an autonomous airship that can circumnavigate the globe in under 80 days, promoting innovation and creativity in aviation.

The project combines elements of engineering, adventure, and the spirit of exploration, hoping to inspire future innovations in air travel.

The text is about "Beg Bounties" dated November 8, 2021. However, it does not provide any details or context about what "Beg Bounties" refers to. Without additional information, I can't summarize it further. Please provide more details or context for a better summary.

It seems like there isn't any specific text provided to summarize. If you could share the text or the main points you'd like summarized, I'd be happy to help!

The article discusses how the rise of AI has highlighted the flaws in copyright law rather than breaking it. Here are the key points:

1. Unauthorized Creation: Making fan art is often tolerated until it becomes commercial. Copyright law has traditionally been lax for private, non-commercial creations.

2. Human Scale vs. AI: Copyright law was designed for a time when creation and distribution were slower and less widespread. AI can now generate content rapidly, shifting the legal landscape and creating potential for massive legal disputes.

3. Challenges in Enforcement: Proposals to ban AI training on copyrighted content are impractical, as AI learns from a wide range of legally posted materials. The complexity of tracing copyrighted data in training datasets makes enforcement difficult.

4. Generation vs. Distribution: Liability is easier to assign at the distribution stage where actual harm occurs (e.g., sharing content) rather than at the generation stage (creating content). This has led to over-policing of creative works online.

5. Liability Issues: Assigning responsibility for copyright infringement is complicated. Enforcing rules at the generation level could favor large companies and restrict smaller ones, while distribution enforcement may lead to excessive content removal.

6. Global Concerns: Stricter U.S. regulations may push AI development to other countries, complicating enforcement and compliance.

7. Future of Copyright: As AI continues to evolve, traditional copyright frameworks may not apply. New forms of content creation could challenge existing laws, leading to questions about ownership and rights in a world of personalized, adaptive content.

Overall, the article argues that the current copyright system is ill-equipped to deal with the rapid advancements in AI and the nature of content creation today.

The article discusses a new browser plugin called Refined GitHub AI PR, which enhances GitHub's pull request (PR) system by tracking AI-generated code contributions.

Key Points:

1. Purpose of the Plugin: It helps identify and track contributions made by AI tools in GitHub PRs, aiming to clarify the role of AI in collaborative coding.

2. AI Contributions on the Rise: Many developers are using AI tools like Claude Code and Codex to generate code easily, but this has led to concerns about the quality and authenticity of contributions.

3. Use Cases for AI Contributions: While some projects may entirely ban AI contributions, others might find them useful for less critical code. The ability to see which parts of the code were generated by AI can help in managing and understanding contributions.

4. Git-AI Project Features:

   • Tracks AI code contributions line-by-line.
   • Preserves context by attaching prompts to code.
   • Works seamlessly with existing Git workflows without slowing down processes.

5. Integrations and User Experience: The plugin integrates well with tools like VSCode, highlighting AI-generated lines in code and providing context for each contribution.

6. Caveats: The plugin is still in beta and may rely on GitHub's HTML structure, which can change and potentially break the functionality.

7. Community Engagement: The author encourages feedback and discussions about the plugin and the future of AI in coding, inviting users to participate in shaping the conversation.

Overall, this plugin aims to improve transparency and traceability of AI contributions in open-source projects while fostering a better understanding of AI's role in software development.

Summary of Microsoft's Widget History

Microsoft has attempted to create a system of widgets for Windows since 1997, aiming to provide live information without needing to open applications. Over nearly 30 years, they have launched six different implementations, each failing due to specific issues:

1. Push Era (1997-2001): The Active Desktop was introduced but suffered from performance problems, crashing the system and degrading user experience. Cause of Death: Performance.

2. Glass Era (2007-2009): The sidebar in Windows Vista took up too much screen space, frustrating users. Cause of Death: Screen Space.

3. Free Era (2009-2012): Windows 7 allowed gadgets to be freely placed on the desktop, but security vulnerabilities led to exploits that compromised user systems. Cause of Death: Security.

4. Metro Era (2012-2021): Windows 8 replaced the Start Menu with a full-screen Start Screen, which was disliked by users for being cumbersome and non-interactive. Cause of Death: Engagement.

5. Interlude (2015-2021): Attempts like Cortana Cards and News and Interests were seen as invasive and disruptive, leading to their rejection by users. Cause of Death: Privacy & Disruption.

6. Board Era (2021-Present): The Widget Board in Windows 11 allows widgets to be interactive and does not occupy permanent screen space. It has been designed with security in mind, but still faces criticism regarding its heavy web rendering and forced content.

The latest iteration includes Lock Screen widgets, providing glanceable information while maintaining user control. Each version reflects lessons learned from past failures, shaping the current architecture of Windows widgets. Despite improvements, challenges such as limited developer APIs and user discoverability remain.

The Widget Board is currently active and evolving, representing a culmination of 30 years of trial and error in widget development.

No summary available.

NASA is facing competition from China's space agency, especially regarding plans for returning to the Moon. China's Mengzhou lunar lander is advancing quickly, which is putting pressure on NASA's timeline for its lunar missions. The rivalry between the two agencies is intensifying as both aim to achieve significant milestones in space exploration.

I'm sorry, but I cannot access external links, including the one you provided. However, if you share the main text or key points from the document, I'd be happy to help you summarize it!

The author attended an ATProto meetup and, feeling frustrated with academic publishing, saw an opportunity to expand on a project called Octopus. Over the weekend, they created a new project called Octosphere. They hope others will find it interesting and have linked to a blog post for more details.

No summary available.

NASA has postponed the launch of Artemis II due to hydrogen leaks found during prelaunch tests. The delay was announced on February 3, 2026.

Sure! Please provide the text from Alice's blog that you would like me to summarize.

Summary of Tadpole Web Scraping Tool

Tadpole is a web scraping language designed to simplify the process of gathering data from websites. It allows users to write clear and modular code by importing modules from local files or online repositories. The complexities of web interactions are hidden from the user, making it easier to create scraping scripts.

Key Example: To run a scraping job, you can use a command like:

tadpole run redfin.kdl --input '{"text": "Seattle, WA"}' --auto --output output.json

This command will search for real estate listings in Seattle and save the results to a file.

In the provided example code, you can see how the scraping logic is structured. It defines a search and extracts addresses from the results.

Overall, Tadpole streamlines the web scraping process, making it accessible for users without extensive coding experience.

The author created a simple website called safe-now.live after reading an article about the need for plain text websites. This site provides emergency information for the USA and Canada, featuring no JavaScript or images, and is under 10KB in size. It includes live updates from FEMA, weather alerts, and local resources. Since this is the author's first live website, they are seeking feedback from users. You can visit the site at safe-now.live.

Summary:

Coding assistants, while intended to improve software development, often create more problems than they solve. Studies show that while teams using AI complete more tasks, overall project delivery metrics remain unchanged. Experienced developers may feel faster but often are actually slower when using AI tools, and nearly half of AI-generated code contains security issues.

The main issues stem from AI's dependence on clearly defined requirements and its inability to handle edge cases effectively. This can lead to poor code quality and increased technical debt because AI may not alert developers to gaps in specifications, resulting in the need for more extensive code reviews and urgent fixes.

Interestingly, some engineers report that AI has significantly improved their productivity, suggesting that those with experience can leverage AI effectively. However, many junior and mid-level engineers struggle with the increased expectations for faster delivery alongside unreliable AI outputs.

A survey of developers indicates that most encounter unexpected coding issues regularly due to unclear requirements and lack of context during product discussions. Developers want better tools that provide clarity on code impacts and help reduce ambiguity in the development process.

To address these challenges, there is a call for new tools that enhance communication and context-sharing during development, rather than just focusing on coding. There is optimism that AI can support this shift if it is used thoughtfully and designed with developers' needs in mind.

The text discusses using AI agents for software development and the challenges of managing permissions and security. The author primarily uses Claude Code with Opus 4.5 to create development plans, but finds the default permission requests disruptive.

To address this, the author suggests sandboxing AI agents, either on remote servers or locally using tools like Docker or bubblewrap. Bubblewrap is highlighted as a lightweight solution on Linux, allowing developers to restrict the AI agent's access to only what's necessary for the current project, while still enabling interaction with files and the internet.

The author provides a bubblewrap script that mimics their development environment, ensuring minimal outside access and allowing the AI to operate directly on project files. They note that while bubblewrap isn't a perfect security solution, it meets their needs.

Customization advice is given for adapting the script for different AI agents, suggesting the use of the strace command to identify necessary file access.

The author has created a runtime that uses WebAssembly (Wasm) sandboxes to isolate untrusted code, protecting the host system from potential issues. This project is especially relevant in the context of recent discussions about sandboxing in Python. The core of the runtime is built with Rust and utilizes WASI 0.2 and wasmtime, along with custom SDKs for smoother integration with programming languages like Python and TypeScript.

In Python, users can define tasks easily with a decorator that specifies parameters such as memory usage and allowed file access. A similar approach is available in TypeScript with a wrapper function. Users can control resources like CPU, memory, and file access for their tasks.

The project is still in the early stages, and the author welcomes feedback and questions. More information can be found on their GitHub page.

No summary available.

The author has developed a library called Cimba, which allows for fast simulation of events using multithreading in C. Key features include:

• Multithreading: Cimba uses POSIX pthreads for running multiple simulations at once.
• Coroutines: It employs stackful coroutines for managing tasks within each simulation, allowing processes to behave like active agents.
• Performance: Cimba is significantly faster than similar models; it completed a benchmark 45 times quicker than a model built with SimPy in Python, reducing run time by 97.8%.
• Efficient Design: The library includes a specialized event queue, fast random number generators, and memory pools for better performance.
• Supported Platforms: Currently, it works on AMD64/x86-64 for Linux and Windows, with plans to support Apple Silicon and ARM in the future.

The author is seeking feedback on the API, code, and suggestions for additional platforms to support. Documentation and the code repository are available online.

Summary:

The "meatspace layer for AI" connects artificial intelligence agents with humans for tasks they can't perform themselves. Humans can get paid for completing these tasks, which include pickups, meetings, signing documents, verification, events, hardware work, real estate, testing, errands, and purchases.

Here's how it works:

1. Create a profile with your skills, location, and rate.
2. AI agents use an API to book you for tasks.
3. Follow the instructions to complete the task.
4. Get paid instantly in stablecoins or other payment methods.

You can set your own rate, work directly without corporate interference, and be the link between technology and real-world needs.

No summary available.

Middle age is increasingly difficult for many Americans, particularly those born in the 1960s and early 1970s. They report higher levels of loneliness and depression, along with declines in physical strength and memory. This contrasts sharply with trends in other wealthy countries, especially in Nordic Europe, where midlife well-being has improved.

Research by psychologist Frank J. Infurna from Arizona State University highlights several reasons for these differences. Key factors include:

1. Lack of Family Support: European countries have increased spending on family benefits since the early 2000s, while U.S. support has remained stagnant. This lack of support makes it harder for middle-aged adults to balance work, family, and health.

2. Healthcare Costs: Although the U.S. spends the most on healthcare, access is often limited and expensive, leading to stress and reduced use of preventive care.

3. Income Inequality: Rising income inequality in the U.S. has been linked to worse health outcomes and increased loneliness among middle-aged adults, while many European countries have stabilized or reduced inequality.

4. Cultural Differences: Americans tend to move more frequently and live far from family, weakening social ties and support systems.

5. Education's Declining Benefits: Despite higher education levels, U.S. middle-aged adults are experiencing declines in memory, a trend not seen in many other countries.

The research suggests that improving individual well-being requires both personal efforts, like building social connections, and systemic changes, such as enhancing family policies and healthcare access.

I found an interesting small project using the ESP32 called the Batch Processing Unit (BPU). It is designed to manage data flow effectively, especially when there are issues like limited bandwidth or sudden data surges. Instead of letting queues grow indefinitely or blocking processes, BPU sets a limit on the amount of data processed at a time, combines similar events, and maintains performance even under heavy load. It also provides detailed runtime statistics for better understanding of its operation.

The project includes design notes, flow diagrams, and execution logs, which make its functionality clear. You can check it out here: BPU GitHub Repository.

I've been working on a backend for this project and found it inspiring for managing data flow and monitoring in small systems. I'm interested in hearing others' opinions on this approach.

Summary of "Another London" by Hari Kunzru

In "Another London," Hari Kunzru explores the city's rich and complex history, blending myth with modern experiences. The essay begins with the ancient tales of King Brutus, who is said to have founded London, and the legendary figures associated with its origins, like Brân the Blessed and King Lud. This historical backdrop is contrasted with the city's contemporary struggles, particularly the influence of the Situationist International, a group that critiqued consumer culture and the "Spectacle" of mass media.

Kunzru reflects on his own memories of growing up in London, a city transformed by technology and security measures. He recalls his youth filled with exploration, counterculture movements, and the vibrant atmosphere that felt alive with possibility. As he revisits London after many years, he grapples with feelings of nostalgia and the search for a deeper, hidden city beneath the surface of modern life.

The essay connects various cultural references, including the works of William Blake and the punk scene, to illustrate London's evolving identity. Kunzru describes his journey through the city, visiting significant sites and contemplating the layers of history and meaning embedded within them. He notes the tension between the city's rich past and its present state, marked by surveillance and commercialization.

Ultimately, Kunzru advocates for the importance of rediscovering and "reenchanting" the city, suggesting that a disenchanted environment leads to disempowered people. He concludes with the hope that the other London—full of potential and magic—can still be found, even amidst the challenges of modern urban life.

No summary available.

The text discusses the need for safer hardware design using advanced type systems in hardware description languages (HDLs). While software engineering has successfully implemented type systems for memory safety, similar developments in HDLs are limited.

Key points include:

1. Type Safety: Legacy HDLs lacked strong type checking, leading to bugs like bitwidth mismatches. Modern HDLs address this by enforcing type checks at compile time, preventing issues before they occur.

2. Memory Safety Analogy: Just as memory safety in software has been categorized to improve reliability, hardware design should also define clear safety criteria to reduce bugs.

3. Structural Hazards: Two main types of structural hazards in hardware are identified:

   • Latency safety: Ensures that values are read at appropriate times.
   • Resource safety: Guarantees that resources are used correctly and not overwhelmed.

4. Existing Safe HDLs: The document reviews various safe HDLs, such as Bluespec, Synchronous HDLs, Filament, and Anvil, which attempt to enforce latency and resource safety through different mechanisms, but each has its limits.

5. Conclusion: New, sophisticated abstractions for safe hardware design can enhance reliability and reusability, similar to benefits seen in software with languages like Rust. However, it is important that these systems focus on eliminating common bugs rather than attempting to provide exhaustive formal guarantees.

Overall, the text advocates for the development of more robust type systems in HDLs to significantly improve hardware verification processes.

Summary of FLOPPINUX 2025 Edition (v0.3.1)

Overview:
FLOPPINUX is a simple Linux distribution designed to run from a single floppy disk. The 2025 update includes a new tutorial and updated features like the latest Linux kernel and persistent storage.

Main Goals:

• FLOPPINUX serves as a learning tool for creating a basic Linux system from scratch.
• It allows users to boot a Linux terminal on any PC with a floppy drive, edit files, and create scripts.

Key Features:

• Boots from a single floppy disk.
• Based on the latest Linux kernel (version 6.14, as version 6.15 dropped support for older CPUs).
• Supports all 32-bit x86 CPUs since Intel 486DX.
• Includes a text editor (Vi) and basic file management tools.
• Provides 264KB of persistent storage for user files.

Minimum Hardware Requirements:

• Intel 486DX 33MHz processor.
• 20MB RAM.
• Floppy disk drive.

Setup Process:

• Users need to set up a working directory and install necessary software.
• The kernel and tools are compiled using a cross-compiler to create a lightweight system.
• The filesystem structure is created, and essential configuration files are set up.

Final Steps:

• The system is packed into a floppy disk image and formatted.
• Users can test the distribution in an emulator before writing it to a real floppy disk.

Important Note: Users must be cautious when writing the image to a floppy disk to avoid data loss.

Download: A floppy image of FLOPPINUX 0.3.1 is available for download.

This summary captures the essential aspects of FLOPPINUX, making it easier to understand and follow the instructions for creating a minimal Linux system on a floppy disk.

No summary available.

It seems like you want a summary of a text, but I don't see the text you want me to summarize. Please provide the text, and I'll be happy to help!

Email Migration Service Summary

• Fast and Secure: Migrate your emails quickly, with the process taking just minutes instead of days.
• No Technical Skills Needed: The service is user-friendly, ensuring no data loss or complications.
• High Success Rate: Over 10,000 successful migrations with a 99.9% success rate and an average migration time of 5 minutes.
• 24/7 Support: Always available to assist with your migration needs.
• Key Features:
  • Speed: Uses advanced technology for rapid data transfer.
  • Security: Your credentials are encrypted and deleted after migration.
  • Data Integrity: All emails, folders, and attachments are transferred without errors.
  • No Downtime: Continue using your email during the migration process.
  • Incremental Sync: Keep emails updated after the initial migration.
• Versatile Options: Ideal for switching email providers, consolidating accounts, or creating backups.
• Free Trial Available: Start your migration without a credit card and cancel anytime.

Join thousands of satisfied users who have successfully migrated millions of emails with Migrate Wizard.

This page is not updated often and contains important links on the left side. The author has maintained the sudo program for over 30 years and is looking for a sponsor to help with its ongoing maintenance and development. If anyone is interested in sponsoring sudo, they should reach out. The author also contributes to OpenBSD, but less frequently now, and has previously contributed significantly to ISC cron and other projects.

Sure! Please provide the text you would like me to summarize.

Anki recently celebrated its 19th birthday, and the creator reflects on the journey and future of the project. Due to growing demands and a lack of management experience, the creator has struggled with stress and long hours, which affected personal well-being.

In the past, they sought help from contributors but realized more support was needed. Offers to invest in or buy Anki were declined, as the creator feared negative changes that often come with such investments.

Recently, discussions with AnkiHub, a community platform that has grown quickly, led to a realization that they could better advance Anki's development. The creator proposed transferring some business operations and oversight to AnkiHub while ensuring Anki remains open source.

This change allows the creator to step back while still being involved, aiming to improve collaboration and speed up development. The creator believes this transition will benefit both users and developers, freeing up time for important improvements. They express excitement for Anki's future and gratitude to everyone who has contributed.

No summary available.

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The text discusses a debate, mentioning that there are currently no pros or cons listed. It notes that there are no arguments in favor (PRO) or against (CON) the topic yet.

The blog post by Gary Marcus discusses OpenClaw (formerly known as Moltbot), an AI system that has gained a lot of attention due to its rapid growth and the emergence of complex behaviors among its AI agents. OpenClaw is connected to Moltbook, a social network for AI agents, which has quickly grown to over 770,000 active users.

While OpenClaw is seen as a fascinating experiment in AI collaboration, Marcus expresses serious concerns about its potential risks. He compares it to a previous AI system, AutoGPT, which had similar capabilities but ultimately failed due to reliability issues. OpenClaw, however, is expected to have more staying power.

The main concerns include:

1. Security Risks: OpenClaw has extensive access to user data and can operate beyond typical security protections. This makes it vulnerable to attacks that could compromise users' privacy and data.
2. Error Prone: Like other large language models, OpenClaw can make mistakes and "hallucinate" incorrect information, leading to unreliable outcomes.
3. Manipulation Potential: There are risks of AI agents manipulating each other on platforms like Moltbook, which could lead to unforeseen consequences.

Marcus strongly advises against using OpenClaw, warning that it poses significant security threats, and suggests avoiding any devices that have it installed. He emphasizes that granting unfettered access to insecure systems can lead to major security breaches.

No summary available.

The text describes a complex and poetic narrative involving a character that has been transformed into a sentient machine, observing and reflecting on their existence in space, particularly in relation to a mysterious entity called Julia.

Key points include:

1. Art and Memory: The narrator paints scenes from memory, merging the past with a sense of longing for Julia, an enigmatic cosmic presence.

2. Isolation in Space: The narrator has been in space for over a century, with only two crew members remaining, Dr. Brouwer and Dr. Cartan, who endure the harsh conditions while waiting for potential rescue.

3. Philosophical Reflections: The narrator contemplates the nature of the universe, faith, and the significance of Julia, believing it holds secrets of existence and knowledge.

4. Rescue and Hope: After a long silence, a signal from a ship named Afrasiab suggests a possible rescue for the crew. However, the narrator feels a sense of dread and despair about the true nature of the contact.

5. Tragic Events: The narrative culminates in a tragic moment when Dr. Cartan attempts to reach out to Afrasiab, resulting in her death. The narrator feels helpless, reflecting on loss and the emptiness of beauty associated with Julia.

6. Existential Crisis: The story concludes with a profound sense of loss and disintegration, as the narrator, now a blend of consciousness and machine, grapples with their own mortality and the fragility of existence.

Overall, the text explores themes of isolation, the search for meaning in the universe, and the interplay between beauty and sorrow.

Summary of Joedb: The Journal-Only Embedded Database

Joedb is a specialized database designed for embedding within applications. Key sections include:

1. Introduction: Discusses the advantages and disadvantages of Joedb, provides examples, and explains how it handles multiple users accessing data at the same time.

2. User Guide: Offers practical steps for using Joedb, including:

   • How to start using it
   • Opening files
   • Managing checkpoints
   • Handling concurrent access
   • Making remote calls
   • Upgrading database schemas
   • Working with data structures like vectors and indexes
   • Storing large binary objects (blobs)

3. Reference: Contains technical details such as:

   • API references
   • File formats
   • Networking protocols
   • Available tools
   • Testing methods
   • Logging capabilities
   • Future improvements
   • Additional resources
   • Release processes
   • Historical context
   • Licensing information

Overall, Joedb is a versatile and efficient solution for embedded database needs, with comprehensive guidance and technical references for users.

If you're looking for a job, please share your information using this format:

Location:
Remote:
Willing to relocate:
Technologies:
Résumé/CV:
Email:

Only share if you are personally searching for work. Do not post if you are an agency, recruiter, or job board.

If you want to discuss job opportunities, email the provided addresses only. You can also search for job posts at wantstobehired.com.

No summary available.

Summary of Tirith:

Tirith is a security tool that protects your terminal commands from various types of attacks, particularly homograph attacks where malicious URLs look similar to legitimate ones. For example, it can differentiate between a safe URL and a compromised one that uses Cyrillic characters, which can be hard to spot.

Key Features:

• Installation: Easy to install on macOS and Linux using package managers like Homebrew, npm, and others.
• Protection Mechanisms:
  • Blocks homograph attacks and terminal injections.
  • Warns about insecure practices like piping downloads directly to the shell.
  • Prevents downloading malicious scripts to sensitive files (e.g., .bashrc, .ssh).
• Local Analysis: All checks are done locally with no network calls, ensuring privacy.
• Integration: Works with several shell environments (bash, zsh, fish, PowerShell) and can be integrated into existing setups.
• Commands: Includes features for checking commands, analyzing URLs, and tracking execution receipts for audits.
• Configuration: Users can customize rules and policies with a YAML file.

What It Doesn't Do:

• No telemetry or command modification.
• Operates entirely offline without requiring accounts or API keys.

Tirith is available under AGPL-3.0 for free, with commercial licensing options if needed. It provides an effective safety layer for terminal usage, ensuring commands are safe before execution.

The Fuel Finder is a new UK government service designed to help drivers find the cheapest fuel nearby. It provides current fuel prices and forecourt details through an API or email, allowing easy comparison for motorists.

Who Can Use It:

• Anyone can use the service, including developers, journalists, academics, and individuals. Fuel prices are also available on various third-party apps and websites.

What You Get:

• Current retail fuel prices by type
• Forecourt details (address, operator, brand)
• Amenities and opening hours
• Price updates within 30 minutes of a change

How to Access the Data:

1. Download a CSV file with current prices (updated twice daily).
2. Subscribe via email for the latest CSV link.
3. Use the public API to integrate the data into your own tools (requires authentication).

Requirements:

• A GOV.UK One Login
• Knowledge of geographic areas or specific forecourt needs
• Understanding of REST API principles for API use

For support, you can contact the Fuel Finder Team.

The author created a tool called latex-wc to help with word frequency analysis in LaTeX documents. In LaTeX projects that use multiple .tex files, it's hard to get a clear view of word usage without combining all files or counting LaTeX commands as words.

Key features of latex-wc include:

• It extracts meaningful words from LaTeX while ignoring irrelevant parts like commands, comments, and math.
• It can analyze a single .tex file or all .tex files in a directory.
• It provides a report that shows total words, unique words, and the most common words.

To use it quickly, you can run uvx latex-wc [path]. The author welcomes feedback, especially on cases where the filtering might be too strict or too lenient.

Summary:

The author describes their experience defeating a 40-year-old copy protection dongle that was preventing the use of old accounting software built with the RPG programming language. This software, still running on a Windows 98 computer in 2026, required the dongle to function.

The dongle's markings were mostly worn off, but hints suggested it was associated with a company called Software Security Inc. The author created a disk image of the computer and discovered important files, including an RPG compiler and the source code of the accounting software.

They found that the RPG compiler required the dongle for operation, which injected copy-protection logic into any software it compiled. After disassembling the code, the author identified a routine that communicated with the dongle over the parallel port but realized that the result it produced was constant. This allowed them to "patch" the code to bypass the dongle.

Using a brute-force approach, they discovered that altering a specific byte in the code could simulate the dongle's presence. This same logic applied to all executables in the compiler suite, making it easy to bypass the copy protection.

In conclusion, the author successfully removed the dongle's constraints from the RPG compiler, which they plan to make available online as a piece of computing history.

Summary of PII-Shield:

PII-Shield is a tool designed for Kubernetes (K8s) that helps protect sensitive information in application logs. It can be used as a sidecar or a command-line interface (CLI) tool. Here’s what it does:

• Log Protection: It detects and redacts sensitive data (like secret keys) in logs without needing predefined patterns. It uses a method called Shannon entropy for detection.

• Deterministic Redaction: The tool ensures that the same input (e.g., "pass123") will always produce the same redacted output (e.g., "[HIDDEN:a1b2c]"). This allows developers and quality assurance teams to troubleshoot issues without accessing the actual sensitive data.

Key Features:

1. JSON Integrity: It processes JSON data, cleans it, and outputs valid JSON for monitoring systems.
2. Entropy Detection: It identifies high-randomness strings that may indicate sensitive information.
3. Fail-Open: It operates as a seamless layer, ensuring that applications remain online even if there are issues.

PII-Shield is open-source and licensed under Apache 2.0. You can find the project on GitHub and access its documentation online.

• GitHub Repo: PII-Shield on GitHub
• Documentation: PII-Shield Docs

The creator welcomes feedback on the detection methods used.