No summary available.

Summary of Learning Fortran

Overview: The article discusses learning Fortran, one of the oldest programming languages, originally created by IBM for scientific applications in 1957. It has evolved through several versions, with the latest being Fortran 2018.

Key Points:

1. Versions: Fortran has different versions, including FORTRAN 77, Fortran 90 (which introduced free form syntax), and later versions up to Fortran 2018. Free form syntax is more flexible and user-friendly compared to the earlier fixed form.

2. Syntax Basics:

   • Programs start with program <name> and end with end program <name>.
   • To print messages, use print *, '<message>'. The asterisk indicates output to the default channel.
   • Variables must be declared explicitly if using implicit none, a practice recommended in modern coding.

3. Example Program: A simple "Hello, World!" program and a basic calculator program that takes user input for two numbers and an operation (+, -, *, /) is provided. The calculator handles division by zero with error messages.

4. Compiling and Running: To run a Fortran program, compile it using gfortran -o <output_name> <input_file>.f90, and execute it with ./<output_name>.

5. Improvements: The article suggests refining the calculator by using a select case statement to handle operations more efficiently and to improve error handling.

6. Future Topics: The author plans to explore more applications of Fortran and how the language is modernizing, despite its old age.

Overall, the article serves as an introduction to learning Fortran, highlighting its syntax, structure, and practical applications.

AI is expected to make formal verification, a method used to mathematically prove that software meets its specifications, more mainstream in software development. Traditionally, formal verification has been limited to research projects and is rarely used by industrial software engineers due to its complexity and high costs.

However, advancements in AI, particularly with coding assistants, are changing this. These AI tools can help write proof scripts, making formal verification easier and cheaper. As formal verification becomes more accessible, it will be essential for verifying AI-generated code, ensuring its correctness without the need for human reviews.

While automation will simplify the verification process, defining accurate specifications will still require expertise. Overall, the combination of cheaper formal verification and the need for verifying AI code is likely to lead to its wider adoption in the near future. The main challenge will be shifting the culture to embrace these formal methods.

The new Mozilla CEO, Enzor-DeMeo, suggested in an interview that he might consider blocking ad blockers in Firefox to increase revenue by $150 million, but he feels it goes against Mozilla's mission. The author expresses disappointment at this idea, highlighting that Firefox's commitment to open standards and privacy has attracted loyal users. They fear that removing ad blockers, which are seen as important for security, would alienate the core community and harm the project. The author urges Mozilla to stay true to its values.

TLA+ Modeling Tips Summary

1. Start Small: Begin with a simple model and keep it functional as you build. Only add components when necessary.

2. Focus on Abstraction: Your model should represent a specific behavior, not the entire system. Remove any unnecessary layers or components.

3. Write Specifications, Not Code: Describe what should happen, not how it’s done. Avoid unnecessary variables and derive values instead of storing them.

4. Check for Illegal Knowledge: Review your model to ensure processes don’t access states they shouldn’t, as this is a common error.

5. Use Fine-Grained Actions: Make actions as small as correctness allows to reveal real system behavior and avoid hidden issues.

6. Think in Guarded Commands: Structure actions to represent a single logical step, defining conditions clearly. This approach is better for distributed systems.

7. Reflect on Missing Elements: Regularly think about what might be overlooked in your model, including handling failures and message order.

8. Define TypeOK Invariants: Explicitly state types early in your model to help document and debug effectively.

9. Write Many Invariants: Make important properties explicit and document your learnings about them.

10. Check for Progress: Ensure that your model doesn’t just satisfy safety conditions but also guarantees that actions eventually occur.

11. Validate Model Behavior: A successful model run doesn’t guarantee correctness. Test by intentionally introducing errors to ensure robustness.

12. Optimize Last: Keep your model separate from the model checker. Focus on clarity first before optimizing for efficiency.

Explore more TLA+ examples and guides on the author's blog.

Summary:

Your local government may be discussing surveillance technologies like Flock cameras, facial recognition, and automated license plate readers (ALPR). The website alpr.watch helps you find meetings about these technologies so you can take action.

Surveillance tech is rapidly increasing in the U.S., with over 80,000 cameras tracking residents' movements and collecting personal data. The site maps where discussions about surveillance are happening, allowing you to stay informed and get involved.

Key Features:

• The site tracks local councils, meetings, and ALPR camera locations.
• Users can sign up for email alerts about surveillance in their area.

What is ALPR? ALPR systems use cameras and AI to capture and store license plate data from vehicles, creating extensive databases of people's movements.

What is Flock Safety? Flock Safety is a major supplier of ALPR cameras, which collect detailed vehicle information and share it across various agencies, contributing to a widespread surveillance network.

Concerns: Historically, surveillance systems expand their use beyond their intended purpose, often leading to privacy invasions.

Organizations to Support: Several groups are fighting against mass surveillance, including:

• Electronic Frontier Foundation (EFF)
• ACLU
• Fight for the Future
• Surveillance Technology Oversight Project (STOP)
• Institute for Justice

You can also seek local privacy advocacy organizations.

Summary of "No Graphics API" by Sebastian Aaltonen

Sebastian Aaltonen, a graphics programmer with 30 years of experience, discusses the evolution of graphics APIs in his blog post. He has worked on various gaming consoles and graphics technologies, including WebGPU, Metal, and Vulkan.

Key Points:

1. Introduction of Low-Level APIs: A decade ago, low-level graphics APIs like DirectX 12, Vulkan, and Metal emerged to improve performance for AAA games, addressing limitations of older APIs like DirectX 11 and OpenGL.

2. Performance Issues: Although low-level APIs showed promise in benchmarks, they often led to performance issues when porting existing engines. This was due to the incompatibility between new APIs and existing rendering architectures.

3. Graphics Programming Roles: The introduction of low-level APIs fostered a split in graphics programming roles: low-level programmers focused on API interaction, while high-level programmers worked on visual graphics algorithms.

4. Modern GPU Evolution: Today's GPUs have advanced capabilities, such as better caching and support for direct memory access, which make many complexities from older APIs unnecessary.

5. Persistent State Objects (PSOs): A major challenge remains with PSO management, which can lead to long loading times and stuttering in games due to vast amounts of data needing to be cached.

6. Historical API Design: The design of APIs like OpenGL and Vulkan stemmed from the need to support diverse, rapidly evolving hardware, which led to compromises that have persisted over time.

7. Future of APIs: With modern GPUs, there is potential to simplify APIs significantly by removing outdated complexities. The evolution of hardware suggests that a new API could be designed without the need for many current persistent objects, streamlining graphics programming.

Overall, Aaltonen emphasizes the need for a reevaluation of graphics APIs to streamline processes and improve performance in today’s advanced hardware landscape.

Summary:

The new tool "ty" is a fast Python type checker and language server, developed by Astral and written in Rust. It aims to be a better alternative to existing tools like mypy and Pyright. The Beta version is now available, and the Astral team uses it in their own projects.

Key Features of ty:

• Speed: Ty is much faster than mypy and Pyright, performing type checks 10 to 60 times quicker. For example, it can update diagnostics in just 4.7 milliseconds after editing a file, making it particularly effective in editors.
• Advanced Type Checking: Ty includes features like intersection types and type narrowing, ensuring accurate feedback while respecting user intent.
• Open Source: The project is built collaboratively and can be used anywhere Python is written, including in web browsers.
• User-Friendly Diagnostics: Ty provides clear error messages, pulling context from multiple files to explain issues thoroughly.

Ty can be installed via the uv tool or as a VS Code extension. The team plans to enhance it further, focusing on stability, support for popular libraries, and additional features.

Astral's long-term vision is to make Python a more productive programming environment, continuing to improve ty based on user feedback.

No summary available.

Mozilla's new CEO has announced a shift towards making AI central to Firefox, aiming to establish the company as a trusted software provider. However, the author, Alex Kontos, who has experience with the Waterfox browser, believes this is a mistake. He argues that AI, particularly large language models (LLMs), are opaque and untrustworthy, raising concerns about user control and data handling.

Kontos emphasizes that a browser should act as a direct agent for users, without an AI layer mediating their interactions. While Mozilla claims AI features will be optional, he questions how users can monitor and audit these features effectively. He feels that Mozilla's focus on attracting average users may alienate its core technical community, which values transparency and user agency.

Waterfox, in contrast, aims to provide a straightforward browsing experience without LLMs, emphasizing performance and user control. The author highlights the importance of formal governance in browser projects to ensure accountability and trustworthiness. He believes that while AI browsers may become popular, there will always be a demand for simpler, more reliable alternatives like Waterfox, which prioritizes user independence and transparency.

Mike San Román argues that most people misuse AI by focusing on its creation abilities, like writing and generating content. Instead, he believes AI's true strength lies in its ability to consume and analyze vast amounts of information.

He shares his experience of connecting his notes and reflections in Obsidian to AI, shifting his questions from asking AI to create something new to discovering insights from his past. For example, he used AI to identify patterns in his one-on-one meetings, track his evolving thoughts on technical debt, and connect design decisions over time.

San Román emphasizes that traditional search methods are limited, but AI can help retrieve knowledge by understanding concepts and finding connections. He suggests that by viewing AI as a reader of our experiences, we can unlock valuable insights stored in our notes and reflections.

After two months of this new approach, he reports improved problem-solving, better decision-making, and the ability to see patterns that were previously overlooked. He encourages others to document their thoughts not just for others but for their future selves and the AI that can help them remember.

In summary, the key to leveraging AI effectively lies in using it to consume and connect our existing knowledge rather than just create new content.

Summary of GitHub Actions Pricing Changes

Starting January 1, 2026, GitHub will lower the prices for hosted runners and introduce a new charge of $0.002 per minute for self-hosted runners beginning March 1, 2026. Most users will not see an increase in their bills, with 96% of customers remaining unaffected. Actions will still be free for public repositories.

Previously, self-hosted runners were free, but this change aligns costs with usage and enhances service quality. A pricing calculator will be available to help users estimate their future costs. Although 4% of users will see a change, 85% of those will have lower bills, while 15% will face a median increase of about $13.

GitHub Actions has become widely used since its launch in 2018, handling millions of jobs daily. To support this growth, GitHub is modernizing its architecture to improve reliability and performance.

Key changes include:

• Lower prices for GitHub-hosted runners, with potential reductions of up to 39%.
• Introduction of a $0.002 per-minute charge for self-hosted runners.
• Investment in enhancing the self-hosted experience, including new scaling solutions and improved job management.

Overall, the updates aim to provide a more flexible and reliable CI/CD experience for all users while ensuring transparent pricing.

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The article tells the story of Bob Rutan, a man who became a well-known Santa Claus at Macy’s and the profound impact it had on his life. Initially, Bob was struggling with personal and professional failures, including losing his job and family connections. Encouraged by a friend, he took on the Santa role, which unexpectedly brought him joy and happiness through the smiles of children.

As Bob embraced the Santa persona, he found a sense of purpose and reconnected with his estranged son, who he even hired as an elf. However, his journey was not without challenges. After rising through the ranks at Macy’s and becoming an executive, he eventually faced a downfall due to conflicts with management and was let go. This led to a period of depression and estrangement from his daughter.

Despite these hardships, Bob’s experiences in the red suit allowed him to touch the lives of many children, providing them with hope and connection during difficult times. The article emphasizes the magic of Christmas and the transformative power of playing Santa, as well as the personal stories of other Santas who found redemption and purpose in their roles.

In the end, Bob reflects on his life, acknowledging both the joy and heartache. He continues to celebrate Christmas, holding on to the memories of his time as Santa and the lessons learned along the way. The narrative captures the essence of holiday spirit and the importance of kindness, forgiveness, and connection.

On December 15, 2025, I successfully ported JustHTML, an HTML5 parser originally written in Python, to JavaScript using Codex CLI and GPT-5.2 in just 4.5 hours. The new JavaScript library, named simonw/justjshtml, is dependency-free and passes over 9,200 tests from the html5lib-tests suite.

The project involved creating a similar API to the original JustHTML and required only two initial prompts and a few follow-ups. During the process, I also took time to celebrate with family and watch a movie.

The HTML5 specification has clear rules for parsing invalid HTML, which many existing parsers use. Emil Stenström’s JustHTML project, which I based my work on, is a Python parser that follows these rules.

To start, I set up my development environment and instructed Codex CLI to create a JavaScript version of the JustHTML library. It worked autonomously, producing 9,000 lines of code and committing often to a private GitHub repository.

By the end of the process, the library was fully functional, with tests running successfully. I also created a playground interface to demonstrate its use and added comprehensive documentation.

This project highlights the capabilities of large language models (LLMs) in performing complex tasks with minimal supervision. However, it raises ethical questions about copyright, trust in AI-generated code, and the impact on the open-source community.

Summary:

The text discusses the concept of "thin desires," which represent a universal longing for things that are ultimately unfulfilling and cannot be defined. These desires contrast with "thick desires," which lead to personal growth and transformation through their pursuit. Thin desires, often fed by consumer technology and social media, provide quick satisfaction without meaningful engagement, contributing to feelings of anxiety and loneliness despite being constantly connected.

The author argues that our society has increasingly favored thin desires, dismantling the infrastructure that supports thick desires, such as community, craft, and meaningful relationships. To counter this trend, the text suggests pursuing thick desires through simple, deliberate activities, like baking bread or writing letters by hand. These activities may take time and effort but foster patience and genuine satisfaction, reminding us of what it means to want something worthwhile. Ultimately, the thick life is valuable in itself, independent of any broader movement or societal change.

Subsets is a top platform for consumer subscription teams, helping them grow by using AI to automate decision-making. It allows teams to run experiments, create personalized user experiences, and track results in areas like retention and engagement, all without needing engineering help. Trusted by companies such as The Atlantic and NBCUniversal, Subsets has raised $6.1 million and was part of Y Combinator's Summer 2023 program. The company is now located in Copenhagen.

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A recent study challenges the reliability of blood flow as an indicator of brain activity, which has been a fundamental assumption in functional magnetic resonance imaging (fMRI) for nearly 30 years. Researchers from the Technical University of Munich and Friedrich-Alexander-University Erlangen-Nuremberg found that in about 40% of cases, increased fMRI signals were linked to reduced brain activity, and lower signals corresponded with heightened activity.

Their experiments involved healthy participants performing tasks like mental arithmetic, revealing that regions of the brain could efficiently use available oxygen without needing increased blood flow. This finding raises concerns about interpreting fMRI data in studies of brain disorders, as changes in blood flow may not accurately reflect neuronal activity, especially in patients with vascular issues.

The researchers suggest that combining traditional fMRI with new quantitative techniques could provide a clearer picture of brain energy use, leading to better understanding of conditions like depression and Alzheimer’s disease. The study was published in the journal Nature Neuroscience and emphasizes the need for a shift in how brain activity is measured and understood.

Summary:

Anthony Enzor-DeMeo has become the new CEO of Mozilla Corporation. He acknowledges the organization's strong history of prioritizing people in technology and highlights the rapid changes in the internet that are influencing user expectations. Enzor-DeMeo thanks outgoing interim CEO Laura Chambers for her leadership during a critical period for the company.

He emphasizes that trust will be a key issue in technology, especially in web browsers where privacy and transparency are crucial. Mozilla aims to be the most trusted software company by focusing on three main goals:

1. User Control: All products must be clear about privacy and data use, allowing users to easily understand and manage their choices, especially regarding AI features.

2. Transparent Business Model: Mozilla will grow through monetization that users recognize and value.

3. Evolving Firefox: The Firefox browser will expand into a wider range of trusted software while maintaining its core identity.

Enzor-DeMeo stresses the importance of balancing mission advancement with market success over the next three years, particularly in AI and revenue diversification. He believes that by staying focused on these goals, Mozilla can increase its relevance and strengthen its independence in the tech industry. He expresses excitement for the future of Mozilla and gratitude for the opportunity to lead.

VA Linux was a notable startup during the dotcom boom, particularly for its record-setting IPO on December 9, 1999, where its stock price soared by 698%. Founded in 1993, the company specialized in selling PCs with Linux pre-installed, appealing to businesses that needed reliable systems without the hassle of ensuring hardware compatibility. At its peak, VA Linux held 20% of the Linux hardware market, and its IPO raised $132 million, surpassing Microsoft's IPO.

However, VA Linux's business model faced challenges as larger companies like Dell and HP began recognizing the profitability of selling Linux-compatible systems. Additionally, improvements in Linux hardware support meant that consumers could more easily install Linux on standard PCs. By June 2001, VA Linux exited the hardware business and transitioned to operating technical websites, rebranding itself several times before becoming Geeknet.

Though it struggled after its IPO, VA Linux survived longer than many dotcom companies, eventually being acquired by Gamestop in 2015 for $20 per share. While it never matched its peak stock price again, it rebounded from its lowest trading point.

Summary: Short-Circuiting Correlated Subqueries in SQLite

This blog post discusses a useful optimization for SQL queries used in the Scour application, which filters content for users based on their interests. Scour processes millions of content pieces monthly, and optimizing query performance is crucial for faster page loads.

Key Points:

1. Current Query Structure: The main query filters items based on user language, publication date, and new domain exclusion features. It uses correlated subqueries to check if users have excluded certain domains.

2. Performance Issue: The correlated subquery checks the exclusion list for every item returned, which slows down the query for users without any exclusions.

3. Optimization Strategy: Instead of checking the exclusion list for every item, the query can be modified to first check if the user has any excluded domains. If not, the more expensive check is skipped, improving performance.

4. Implementation: The new query structure uses an uncorrelated scalar subquery that quickly determines if any domains are excluded. If none are excluded, the costly per-item checks are avoided.

5. Benchmark Results:

   • For users without excluded domains, the optimized query performed similarly to the baseline, while the original correlated subquery was 17% slower.
   • For users with excluded domains, the new approach still performed well without additional overhead.

6. Conclusion: This optimization shows that careful query design can significantly enhance performance by minimizing unnecessary checks. Similar techniques can be applied for other filters, like paywalled content, to ensure efficiency.

Overall, using uncorrelated subqueries effectively can lead to faster query performance in SQLite for applications with varying user settings.

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No summary available.

A former Google engineer is getting back into music production and has created a tool to help sequence hardware synthesizers using AI. This tool works in your web browser, requires no login, and connects to local MIDI devices if you're using Chrome or Edge. It allows users to generate musical patterns. The technology used includes React and the WebMIDI API. You can check it out at www.simplychris.ai/droplets. The code isn't perfect, so feedback is appreciated.

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No summary available.

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The person is having trouble renewing their IEEE membership because the payment page is giving errors, no matter which credit card they use. They also can't contact IEEE for help through email, phone, or their website form. They are asking if anyone else is able to get in touch with IEEE.

The author has created Titan, a backend framework that allows developers to write routes and logic in JavaScript. This framework compiles everything into a single Rust and Axum binary, so no Node.js is needed in production. The goal is to combine the ease of JavaScript with the performance of Rust, resulting in a self-contained server that is easy to deploy.

Key features include:

• A JavaScript route DSL
• An action system linked to Rust
• Bundling with esbuild
• A generated Rust server using Axum
• A hot-reload development server
• Output as a single binary

The author is seeking feedback on the framework's design, developer experience, and the usefulness of this JS to Rust approach. The project is available on GitHub.

No summary available.

The article by Yascha Mounk critiques the World Happiness Report, claiming it is misleading and based on flawed methods. Published annually, the report consistently ranks Scandinavian countries, particularly Finland, as the happiest, while the U.S. ranks much lower. Mounk expresses skepticism about these rankings, noting that despite their high scores, Scandinavian countries often experience high rates of mental health issues, including suicide.

The report relies on a single survey question—the Cantril Ladder—which asks respondents to rate their life satisfaction on a scale from 0 to 10. Mounk argues that this question inadequately captures true happiness and may skew responses towards wealth and success rather than genuine well-being.

Research by economists Danny Blanchflower and Alex Bryson reveals that a broader range of happiness indicators paints a different picture, ranking Finland much lower and highlighting that some U.S. states actually rank among the happiest in the world.

Mounk concludes that current happiness metrics are flawed and that media outlets should critically evaluate such reports instead of promoting them uncritically. The article calls for a more thorough examination of what truly contributes to happiness.

Summary of NVIDIA Nemotron 3 Family of Models

NVIDIA has introduced the Nemotron 3 family of AI models, which includes three versions: Nano, Super, and Ultra. These models are designed for efficient performance and high accuracy in various AI applications.

• Model Details:

  • Nano: The smallest model, it is cost-effective and outperforms similar models in accuracy. It has 3.2 billion active parameters and supports context lengths up to 1 million tokens.
  • Super: Optimized for collaborative tasks and high-volume workloads, such as automating IT tickets.
  • Ultra: The largest model, providing top-notch accuracy and reasoning capabilities.

• Key Technologies:

  • Hybrid MoE: Combines Mamba-Transformer architecture for superior throughput and accuracy.
  • LatentMoE: Enhances accuracy by using a new expert design.
  • Multi-Token Prediction: Improves text generation efficiency.
  • Long Context Support: Can handle context lengths of up to 1 million tokens.
  • Reinforcement Learning: Trained in diverse environments for better task accuracy.

• Performance Highlights:

  • Nemotron 3 Nano outperforms notable models like GPT-OSS-20B in various benchmarks.
  • Offers significantly higher inference throughput compared to competitors.

• Open Source Release:

  • Along with the models, NVIDIA is releasing technical reports, model weights, and extensive datasets for further development and research.

For more information, refer to the Nemotron 3 white paper and technical reports available online.

Dafny is a programming language designed to help developers write correct code by incorporating verification directly into the development process. It allows programmers to specify what their code should do and checks if the code meets those specifications, helping to catch bugs early and reduce later issues.

Key features of Dafny include:

• Verification Support: It verifies code against its specifications, ensuring correctness.
• Integration: Dafny can compile to popular languages like C#, Java, JavaScript, Go, and Python, making it easy to fit into existing workflows.
• Development Tools: The Dafny ecosystem includes compilers, IDE plugins, a language server, a code formatter, tutorials, and more resources for users.

Dafny supports common programming concepts such as:

• Various data types (integers, reals, classes, arrays, etc.)
• Advanced features like lambda expressions, inheritance, and pattern matching.
• Tools for making mathematical proofs about software, including conditions for functions and loops.

Dafny can be used in development environments like Visual Studio Code.

No summary available.

No summary available.

On December 12, 2025, Raymond Chen addressed a confusion regarding the automated text conversion table for the Windows clipboard.

The author prefers using the terminal but often has to switch to complicated graphical interfaces like SSMS for basic database tasks. Existing SQL terminal user interfaces (TUIs) are not user-friendly, requiring documentation to learn how to use them. After switching to Linux, the author used VS Code's SQL extension but found it unsatisfactory.

To solve this problem, the author created Sqlit, a keyboard-driven SQL TUI that is easy to use and enjoyable for accessing data. Key features of Sqlit include:

• Visible, context-based keybindings
• A Neovim-like interface with normal and insert modes for editing queries
• The ability to browse databases, tables, views, and stored procedures
• Support for multiple database adapters, including SQL Server, SQLite, and PostgreSQL
• SSH tunneling support
• Customizable themes

The tool is built with Python/Textual and is inspired by lazygit, neovim, and lazysql. The author welcomes feedback, especially on which database adapters to prioritize next, with the goal of making database querying simple and efficient.

For more information, you can visit the project's GitHub page: Sqlit on GitHub.

Permanent magnets are essential in many technologies like electric motors and sensors. Understanding how these magnets become magnetized is crucial for creating effective devices. This blog explains how to simulate the magnetization process of the N48SH permanent magnet using Ansys Maxwell and its manufacturer datasheet.

Key Steps in the Simulation Process:

1. Understanding Magnetization: The behavior of magnetic materials is represented by their B-H curve, showing how they magnetize and demagnetize. The operating point after magnetization is vital for performance.

2. Setting Up the Simulation: A magnetizer model is created in Ansys Maxwell with coils and steel cores to generate a magnetic field. The unmagnetized N48SH material is placed in this field for simulation.

3. Creating the Initial Magnetizing Curve: The N48SH datasheet provides a demagnetization curve. The simulation involves modifying a generic NdFeB magnetization curve to match the N48SH data, using Ansys tools to digitize and smooth the curves.

4. Running the Simulations: The simulation consists of two steps:

   • First, the magnetizing event is simulated with current applied to the coils.
   • Second, the final state is simulated with the current turned off, linking the previous results to find the magnet's stable operating point.

5. Validation: A third simulation uses the built-in N48 material properties for comparison. The results show that the custom-magnetized N48SH magnet closely matches the built-in material's performance, validating the simulation method.

Conclusion:

This workflow in Ansys Maxwell allows engineers to simulate the magnetization of permanent magnets accurately, even with limited data. The successful comparison with the built-in N48 material demonstrates the reliability of this technique for designing various permanent magnets.

Summary: Chat-tails: A Retro Terminal Chat Built on Tailscale

Brian Scott created "Chat-tails," a simple chat application that resembles old-school IRC, using Tailscale technology. This app is designed for a private chatting experience, especially for friends playing games together, without modern distractions like images or voice chats.

Key Features:

• Ephemeral Chats: Conversations are temporary and not easily searchable.
• Access Control: Only invited users can join the chat.
• Terminal Interface: Users interact through a terminal, using basic text commands.

How It Works:

• Regular Mode: Set up a local chat on your network with a port number and room name.
• Tailscale Mode: Allows access to the chat over Tailscale using a hostname and authentication key, making it available to shared users.

Brian, who has experience in Go programming, developed the app in about two days, focusing on simplicity and functionality. He hopes it will serve as a safe learning environment for his child and their friends, introducing them to technology concepts.

Chat-tails can run on simple devices like Raspberry Pi and is part of Tailscale's community projects. If others have similar projects, they are encouraged to share them with Tailscale.

This text reflects on 30 years of web development, from the 1990s to 2025, highlighting key changes and advancements.

1. Optimism for 2025: Web development is easier and cheaper than ever, largely due to AI and improved tools and platforms.

2. The Early Web: In the late 90s, creating a website was simple but required manual coding with HTML and limited resources. Learning was hands-on, often through trial and error.

3. The LAMP Stack and Web 2.0: The early 2000s saw the rise of PHP and MySQL, making dynamic websites accessible. Platforms like WordPress transformed web publishing by allowing non-technical users to create sites easily.

4. The Framework Wars: The late 2000s introduced frameworks like Ruby on Rails, promoting structured development. Deployment became easier with platforms like Heroku, and version control improved with Git and GitHub.

5. The JavaScript Renaissance: From 2013 onwards, JavaScript frameworks like React and Angular emerged, pushing the boundaries of web applications. However, this era brought complexity, leading to developer fatigue.

6. The TypeScript Era: By 2017, TypeScript gained popularity, adding static typing to JavaScript and improving code quality. Meta-frameworks like Next.js simplified development, while deployment became seamless with platforms like Vercel.

7. The AI Moment: The release of ChatGPT in 2022 revolutionized coding by allowing developers to generate and debug code quickly. AI tools like GitHub Copilot enhanced productivity, blurring the lines between technical and non-technical roles.

8. Current Landscape (2025): Web development tools are highly advanced, allowing rapid application development and deployment. The ecosystem is more accessible, enabling individuals to build and share projects easily. The future looks promising, with AI continuing to evolve and lower barriers to entry in web development.

Nuno F Gomes Loureiro, a 47-year-old nuclear science and engineering professor at MIT, was shot multiple times at his home in Massachusetts and died in the hospital the next day. Police are investigating the shooting as a homicide, and no suspects are in custody. Neighbors reported hearing loud bangs that they initially thought were someone kicking a door. Loureiro, originally from Portugal, had an impressive academic background, holding degrees from Instituto Superior Técnico and Imperial College London. He joined MIT in 2016 and became the director of the Plasma Science and Fusion Center in 2024. His research focused on magnetised plasma dynamics and clean fusion power. MIT expressed condolences and is providing support to the community following his death.

No summary available.

The author started a project to create a Telegram clone using Qt, QML, Rust, and C++. They have fond memories of using Qt and wanted to explore creating a native application. The project began with enthusiasm but didn't progress far, mainly due to the complexity of integrating different technologies.

Key points from the author's journey include:

1. Familiarity with Tools: The author appreciates Qt and QML for their ease of use and has a long-standing interest in Rust for its safety features compared to C++.

2. Initial Challenges: They faced issues with code generation and recompilation speeds while using cxx-qt, leading them to switch to qmetaobject-rs, which allowed for faster QML development.

3. Hot Reloading: The author developed a hot reloading feature for QML, which allows for real-time updates when changes are made, enhancing the development experience.

4. UI Development: They created various UI components, such as a chat sidebar and animations, aiming to replicate the feel of Telegram's interface. They also experimented with custom animations and chat bubble designs.

5. System Tray Icon: The author implemented a system tray icon using Qt's capabilities, which involved creating custom images and managing updates to reflect message counts.

6. C++ Integration: After focusing on QML and Rust, the author decided to incorporate C++ to access features not available in Rust or QML directly, setting up a simple C++ environment to keep the project manageable.

The project is a work in progress, and while the author enjoyed the experience, they might pause to focus on other projects. They invite readers to follow their journey and share their thoughts.

The article introduces StringZilla, an open-source software designed for faster Unicode and UTF-8 handling, particularly in string searching and case-folding operations. It highlights the complexities of UTF-8 encoding, which represents characters using a variable number of bytes, and the need for efficient processing due to the vast number of characters in modern languages.

Key features of StringZilla include:

1. Performance Improvements: StringZilla utilizes AVX-512 technology to significantly speed up common operations compared to existing libraries like ICU and PCRE2. For example, it performs case-insensitive substring searches 20 to 150 times faster than alternatives.

2. Correctness and Testing: StringZilla emphasizes maintaining correctness alongside speed. It is rigorously tested against Unicode specifications and real-world data to ensure accurate results.

3. Unique Approaches: The software employs strategies like "fold-safe windows" and SIMD (Single Instruction, Multiple Data) probes to optimize string searching without compromising the integrity of Unicode characters.

4. Support Across Languages: StringZilla provides bindings for multiple programming languages, including C, C++, Python, Rust, Swift, Node.js, and Go, making it accessible for various development environments.

5. Future Enhancements: The author acknowledges areas for improvement, such as better support for languages like Georgian and performance optimization for ARM architectures.

Overall, StringZilla aims to be a powerful tool for developers dealing with Unicode text, combining speed, efficiency, and accuracy in text processing.

Summary of PURRTRAN

PURRTRAN is a programming language designed for developers who wish they had a cat to help them code. It modernizes FORTRAN and includes a unique assistant named Hex, a virtual cat that enhances the coding experience.

Key Features:

1. Hex the Cat: Hex is a virtual assistant powered by advanced technology. He learns your coding style and helps you write better code, but he has needs that you must meet:

   • Food: Feed Hex to keep him happy.
   • Cleanliness: Clean up after him to maintain a good relationship.
   • Love: Spend time with Hex to keep his spirits high.

2. Programming Language: PURRTRAN keeps many FORTRAN features but includes modern syntax. It is designed for numerical and scientific computing.

3. Memory Management: Variables are stored in a "Litterbox" that must be manually emptied to prevent overflow and maintain Hex’s happiness.

4. Catgentic Coding: Hex can suggest code and make improvements while you are away, provided you keep him happy.

5. Linting and Errors: Hex automatically checks your code for errors and provides feedback, like warnings about potential issues.

6. Performance Optimization: The embedded JIT compiler, ZoomiesJIT, optimizes code at runtime based on specific conditions.

Limitations:

• Hex may disappear for periods, may not work well with other systems, and only operates for about four hours a day.
• His mood and willingness to help depend on your relationship with him.

Overall, PURRTRAN combines humor and creativity to create a unique programming experience, leveraging the companionship of a virtual cat to enhance coding productivity.

Pizlix: Memory Safe Linux From Scratch

Pizlix is an enhanced version of Linux From Scratch (LFS) 12.2, integrating a memory-safe userland compiled with a new compiler called Fil-C. It aims to be the most memory-safe Linux-like operating system available.

Key Points:

1. Kernel and Compiler:

   • The kernel is compiled using Yolo-C, with a copy of GCC located in /yolo/bin/gcc.
   • The C/C++ compiler is based on Yolo-C++ and named /usr/bin/clang-20, with various symlinks for compatibility.
   • Other build tools are compiled with Fil-C or Fil-C++.

2. Compatibility:

   • Fil-C is compatible with many packages in LFS, requiring minimal changes to the original LFS setup.
   • The build process involves using Yolo-C for initial stages and switching to Fil-C for later steps.

3. Installation Requirements:

   • You need a dedicated ext partition mounted at /mnt/lfs and a swap partition.
   • An LFS user must be set up as specified in the LFS book.

4. Installation Process:

   • Clone the Fil-C repository and navigate to the Pizlix directory.
   • Run the build script (sudo ./build.sh) to install Pizlix.
   • Edit the GRUB configuration to boot into Pizlix.

5. Default Configuration:

   • Pizlix runs with SSH, a user interface, and basic network configuration. Users should change default passwords for security.

6. Build Stages:

   • The build occurs in several stages: Pre-LC (bootstrapping), LC (where Fil-C is integrated), and Post-LC (completing the LFS build).
   • Each stage can be executed independently for troubleshooting.

7. Additional Features:

   • The build process includes options for mounting/unmounting filesystems and entering the chroot environment.
   • The document details how Fil-C is integrated into LFS and outlines modifications made to support this.

Overall, Pizlix aims to create a robust, memory-safe Linux environment through careful integration of components, providing a safer alternative for users.

No summary available.

No summary available.

Summary of Bonsai

Bonsai is a voxel engine designed for creating large virtual worlds, supporting up to 1 billion blocks in every direction. This means users can see across the entire world, allowing for an expansive view. The engine generates terrain using customizable shaders and is currently in a pre-alpha version (2.0.0-prealpha-rc0) that has undergone major system rewrites.

Getting Started:

• Bonsai is mostly built from scratch, requiring only the C runtime library for startup.
• To build it, users need clang++ (version 18.1 or higher) and specific system headers.
• Pre-built binaries are available for Windows and Linux.

Features:

1. Renderer: Includes advanced lighting and shading techniques like deferred shading, HDR lighting, and shadow mapping.
2. Engine Capabilities: Supports hot reloading of shaders, asynchronous job systems, entity management, and a user interface framework.
3. Terrain Generation: Offers programmable GPU-based terrain generation, a library of noise functions, and tools for terrain editing.
4. Editing Tools: Features CSG-like editing capabilities and a library of primitive shapes for customizing the world.

Additional Tools:

• A performance profiler is included for tracking memory and execution metrics.
• Users can join the Bonsai Discord for updates and community support.

Future Development: There are many wishlist items for future improvements, including better rendering techniques, terrain features like erosion simulation and biomes, and enhanced asset handling.

Overall, Bonsai is a powerful and flexible engine for creating and editing large virtual worlds.

The author, a former Systems Architect now working in Thailand, has created TheAuditor v2.0, a major update to a tool designed to assist in coding. This version features over 800 changes and was inspired by a failure when trying to use AI for a complex code refactor.

Key insights from the author's experience include:

1. Limitations of AI: The AI struggled with understanding the full context of the code, leading to errors and incorrect assumptions.
2. Stale Data: The AI used outdated coding practices because its training data was not current.

To address these issues, TheAuditor v2.0 uses a local SQLite Graph Database to provide a clear overview of the codebase, allowing the AI to verify dependencies without being overwhelmed by too much information. The tool now functions as a "guardrail" rather than just a scanner, ensuring that AI-generated code is based on verified facts.

Additionally, the author transitioned from a regex-based approach to a "Triple-Entry Fidelity" system, which checks data integrity at multiple stages of processing. The tool is designed to work alongside AI agents, allowing for more reliable code planning and implementation.

Major updates in this version include:

• Improved data flow tracking across different services.
• Enhanced checks for data accuracy.
• A switch to a graph database for better relationship handling.
• Support for additional programming languages and frameworks.
• New capabilities for planning and executing architectural changes.

Overall, TheAuditor v2.0 aims to enhance coding practices by providing a more reliable and fact-based approach to software development.

Der belarussische Geheimdienst KGB hat offenbar jahrelang eine Spionage-App genutzt, um Oppositionelle und Journalisten auszuspionieren. Diese App ermöglicht es, Smartphones vollständig zu überwachen, einschließlich Zugriff auf Mikrofon, Kamera und Kommunikation über Messenger, SMS und E-Mails. Darüber hinaus kann das gesamte Smartphone aus der Ferne gelöscht werden.

Ein konkreter Fall zeigt, dass ein Journalist, der vom KGB verhört wurde, unwissentlich eine solche Spionage-App auf seinem Gerät hatte. Nach der Untersuchung durch die NGO Reporter ohne Grenzen wurde festgestellt, dass die App seit 2021 in Verwendung ist. Der Zugang zur App wurde ermöglicht, als der KGB das Handy während des Verhörs übernahm.

Der Fall verdeutlicht die große Gefahr für Journalisten und Oppositionelle in Belarus, von denen viele in Haft sind oder im Exil leben. Die Entdeckung der Software kommt zu einem Zeitpunkt, an dem politische Gefangene freigelassen wurden, was befürchten lässt, dass diese weiterhin überwacht werden könnten.

Zusätzlich zeigt der Fall einen Trend zur Nutzung von physischem Zugriff auf Geräte für Spionage, anstatt teurer spezialisierter Software. Sicherheitsforscher haben ähnliche Ansätze bei anderen Regierungen, darunter Russland und China, entdeckt.

MVV Energie is constructing the world's largest heat pump systems in Mannheim, Germany. These heat pumps will draw water from the River Rhine using massive 2-meter diameter pipes, capable of taking in 10,000 liters of water per second. The project will feature two heat pump units, each with an output of 82.5 megawatts, enough to provide heating for about 40,000 homes.

The heat pumps will replace coal power generation at the site, supporting the transition to cleaner energy sources. The total cost of the project is estimated at €200 million. The heat pumps will be operational by the winter of 2028-29 and will include a filtration system to protect aquatic life.

Other companies, like Everllence, are also developing large heat pump systems, with plans for even more powerful units in Denmark. These systems are becoming increasingly popular as cities aim to decarbonize their heating networks.

Heat pumps are efficient because they can convert one unit of electricity into multiple units of heat. However, they are more expensive to install than electric boilers, which some cities, like Helsinki, are also using to enhance their heating systems. The UK is starting to explore similar technologies, including the use of water from disused mines for heating.

Summary:

The author, an MS CS student specializing in Edge AI and Embedded Systems at CU Boulder, is seeking Summer 2026 internships. They faced challenges using the Rockchip RK3588 chip in the Orange Pi 5 for running modern AI, specifically the SmolVLM Vision Encoder. Although the chip boasts impressive performance, the standard SDK struggled with the model, leading to slow processing times.

To solve this, the author reverse-engineered the NPU (Neural Processing Unit) to understand and improve its performance. They discovered a memory limitation that caused errors when processing large attention matrices. To work around this, they developed a "Nano-Tiling" algorithm that broke down large data into smaller, manageable pieces and introduced a "Poison Pill" method to prevent the compiler from merging these pieces back together.

They also tackled issues with accuracy due to the model's unique data characteristics, implementing a "Sandwich" Domain Shift to maintain signal fidelity. Finally, they created a custom runtime scheduler to manage the processing of these smaller pieces across the NPU's cores, resulting in significant improvements in speed and accuracy.

Overall, the project demonstrated that with ingenuity, it’s possible to make unsupported hardware work effectively for advanced AI tasks. The author plans to share their findings and code on GitHub.

Summary: Custom Yellow Handshake Emojis

In 2022, Apple introduced multi-skin tone handshake emojis, allowing users to create various handshake combinations. The original yellow handshake emoji (🤝) is made up of a single Unicode codepoint, while the new colored handshakes use multiple codepoints, including the zero-width joiner (ZWJ) to combine different emojis into one.

You can create custom handshakes by modifying one or both hands' colors, using JavaScript to combine the codepoints. However, these new emojis may not display correctly as large single messages on Apple devices, as they might be treated as regular text instead of emojis.

The Fitzpatrick scale, which describes human skin tones, informs the color modifiers used in these emojis, but it has been criticized for its limited perspective. Overall, this guide helps you understand how to make your own unique handshake emojis using existing technology.

Summary of A2UI: A Protocol for Agent-Driven Interfaces

A2UI is a framework that allows AI agents to create interactive user interfaces for web, mobile, and desktop applications without running any risky code. It is currently in early development (version 0.8) and is open for collaboration and feedback.

Key Features:

• Safe Communication: A2UI sends safe UI descriptions instead of executable code, preventing security issues like code injection.
• User-Friendly Formats: It uses a simple JSON format that makes it easier for AI to generate UIs incrementally.
• Versatile Compatibility: The same UI description can be rendered across different platforms (Angular, Flutter, React) with custom styling.
• Real-Time Updates: Users can see UI changes as they happen instead of waiting for a complete response.

Getting Started:

• A quick start guide is available to demonstrate its capabilities, like the restaurant finder demo.
• Developers can learn core concepts and integrate A2UI into their applications.
• Complete technical specifications are also provided for in-depth understanding.

How It Works:

1. A user sends a message to an AI agent.
2. The agent creates A2UI messages that describe the UI.
3. These messages are sent to the client application.
4. The client displays the UI using its native components.
5. Users interact with the UI, sending actions back to the agent, which then updates the UI as needed.

A2UI is designed for collaboration and innovation, with contributions from both Google and the open-source community.

No summary available.

Summary of Times New Roman's History:

Times New Roman is named after the British newspaper, The Times, which commissioned typographer Stanley Morison to create it in 1929. Morison worked with Victor Lardent to design the font. Although it faced some criticism for being narrow and lacking warmth, it quickly gained popularity due to its use in newspapers, fitting more text per line.

Despite its longevity and widespread availability, some question whether its success is due to quality or simply its common use. Unlike other fonts, such as Helvetica, Times New Roman is often seen as a sign of apathy in design choices, as it is frequently used by lawyers and in legal documents without much thought.

Overall, while Times New Roman is a reliable and established font, many better alternatives exist. It is encouraged to explore different fonts instead of defaulting to Times New Roman.

Letta is a platform that offers documentation, community support, and demos for users and developers. They have a section for company information, open job positions, privacy policy, and terms of service. Users can subscribe to a newsletter. There are also links to follow Letta on various social media platforms like GitHub, Discord, Twitter/X, Bluesky, Instagram, YouTube, and LinkedIn.

Canadian linguists are urging Prime Minister Mark Carney to use Canadian spelling instead of British spelling in official documents. They have noticed British terms like "analyse" and "globalisation" in recent government communications, including the fiscal budget. In an open letter, these experts emphasized that using Canadian English is important for national identity and pride, as Canadian English has its own distinct features influenced by both American and British English.

The letter highlights that Canadian English is recognized and widely used across the country, and deviating from it could create confusion. The linguists argue that using Canadian spelling is a way to assert Canada's uniqueness, especially in light of past tensions with the U.S. They point out that Carney's previous use of British English may stem from his time in the UK but caution against reverting to outdated language norms. The letter was signed by linguists and editors advocating for a consistent use of Canadian English in government communications.

Summary:

Sherry Ning discusses the issue of overconsumption, arguing that it's a spiritual problem rather than just a financial one. She reflects on her own experience of feeling overwhelmed by material possessions that lacked meaning, leading her to declutter her life. This experience parallels themes from the movie "Spirited Away," where the protagonist, Chihiro, faces the consequences of her parents' mindless consumption.

Ning emphasizes that materialism can be beautiful when it serves a purpose, but mindless shopping driven by trends and social pressures creates emptiness. The character No-Face in "Spirited Away" symbolizes desire itself, showing how people often pursue things that don't truly fulfill them.

She suggests that desires should be guided by strong personal values, which help filter out empty cravings. Ultimately, Ning argues that understanding what truly matters to us can lead to more mindful spending and a richer life, rather than being distracted by societal expectations.

ArkhamMirror Summary

ArkhamMirror is a powerful, offline investigation tool designed for journalists and researchers. It operates solely on your computer, ensuring your data remains private and secure. Here are the main features:

• Local AI: Interact with your data without internet access.
• Semantic Search: Locate documents based on concepts instead of just keywords.
• Knowledge Graph: See connections between people, organizations, and places visually.
• Auto-Timeline: Automatically extract dates and events to create a timeline of occurrences.
• Visual Table Extraction: Extract complex financial tables from PDFs or images.
• Contradiction Detection: Identify conflicting statements across different documents.
• Absolute Privacy: No cloud storage; your information stays on your device.

Getting Started: The installation process is straightforward with a Smart Installer for Windows or a simple script for Mac/Linux.

Documentation: Comprehensive guides are available for users, installation, and developers.

Support: ArkhamMirror aims to empower journalists without the costs and privacy concerns of cloud services. If it benefits your work, consider supporting the project.

I created icl because I wanted a tool that offers more features than rlwrap but isn't as complex as emacs.

icl is a terminal application that includes:

• Context-aware auto-complete
• An interactive object inspector
• Auto-indentation
• Syntax coloring
• Persistent history

It uses sly to connect with the lisp process and works with any sly-compatible implementation. I hope others find it helpful!

The text discusses the unique human ability to understand and manipulate geometric concepts, which is crucial for playing chess. Unlike animals, humans can comprehend shapes and lines, allowing for complex thought processes and strategic planning in chess.

Key points include:

1. Human Geometry Understanding: Humans uniquely grasp geometric ideas like lines and shapes, enabling the combination and transformation of these concepts, which is essential for chess.

2. Animal Limitations: Animals, such as bonobos and chimpanzees, do not have a true sense of discrete numbers or geometric shapes, making it difficult for them to perform tasks that involve these concepts.

3. Geometric Shapes in Chess: Chess relies heavily on geometry, with different pieces moving in distinct patterns that can be described using geometric principles.

4. Mental Representation: Humans are believed to have a "programming language" in their brains that helps them create and understand geometric shapes, facilitating complex visual processing.

5. Minimum Description Length (MDL): This concept explains why some shapes are easier to remember than others based on how simply they can be described.

6. Cognitive Complexity in Chess: The ability to visualize and remember chess moves involves complex geometric understanding, which feels natural to humans but is a sophisticated cognitive skill.

Overall, the text highlights how the human capacity for geometry underpins not only our understanding of the world but also our ability to engage in strategic games like chess.

On December 16, over 100 people protested at the Michigan State Capitol against the development of data centers. Their concerns included possible increases in electricity rates, excessive water usage, and a lack of transparency from the companies involved.

Michigan Attorney General Dana Nessel criticized a large proposed data center project in Saline Township, which involves companies like OpenAI and Oracle. She highlighted the project's potential energy demands, equating it to supplying power for a city of a million people. Protesters voiced their distrust of these companies and called for more public awareness and engagement on the issue.

The rally was organized by a Facebook group called "Michiganders Against Data Centers," with participants coming from various locations in Michigan. They expressed worries about the environmental impact of data centers, including effects on water quality and local communities. The Lansing City Council is also set to vote on a smaller data center proposal soon.

Business Insider shares interesting and innovative stories that you want to read about.

The creator of Mephisto built this tool to improve disposable email services, which often have annoying ads and trackers. Mephisto is designed to be a useful developer tool, not just a spam service.

Key features include:

1. Volatile Memory: Data is not saved once a session ends.
2. Client-Side Entropy: Passwords are generated in the browser, so they are not sent to the server.
3. PWA: It can be installed and uses WebSockets for fast email delivery, avoiding delays.
4. Mobile Handoff: Users can easily move their session to a mobile device using an encrypted QR code.

Mephisto is free and open for everyone to use, and the creator welcomes feedback on the implementation and user interface.

The author introduces a browser extension called Lingoku, designed to enhance Japanese language learning while browsing the web. It replaces some English words with Japanese vocabulary based on the user's proficiency level. This method allows users to learn Japanese naturally without feeling like they are studying, as the majority of the text remains in English. Lingoku uses a language model to ensure that translations fit the context. While it can't be completely free due to costs associated with AI APIs, there is a free plan with daily credits for casual users. The extension is currently compatible with Chrome, Edge, and Firefox, and the author welcomes feedback and feature requests. For more information, visit the provided link.

The text discusses the automation of small business finance tasks like bookkeeping and reporting. Key points include:

1. Automatable Nature: Accounting is often easier to automate than programming because it follows clear rules, such as double-entry systems and tax regulations.
2. Verifiability: Financial records can be easily checked for accuracy, as they either balance or they don’t.
3. Repetitiveness: Accounting tasks are often boring and repetitive, involving the same transactions and patterns each month, which makes them suitable for software automation.
4. Typical Tasks: Small business accounting mainly involves normalizing data, applying rules, reviewing exceptions, and generating reports.
5. Human Oversight: While most tasks can be automated, complex issues like tax strategy and unique cases still require human input.

Overall, the repetitive and rule-based nature of accounting makes it a good candidate for automation, while some complicated aspects still need human expertise.

The author, Stephan Schmidt, discusses the fatigue he experiences from "vibe coding," a method of coding enhanced by AI tools like Claude Code and Cursor. While these tools significantly speed up the coding process, Schmidt feels overwhelmed by the rapid pace at which tasks are completed. He compares this to working in a factory, where the machine's speed becomes stressful.

He explains that traditional coding allows for a natural pace that matches the complexity of tasks, giving developers time to process their work. In contrast, vibe coding leads to quick context switching, which drains mental energy and causes fatigue. The dopamine rush from coding becomes overwhelming, leading to stress instead of satisfaction.

Schmidt suggests that developers need to find a balance when using AI tools. He emphasizes the importance of pacing, regular reflections on the coding process, and trusting AI without micromanaging it. He concludes that while AI has made coding faster, it also brings new challenges for mental health and the way developers think about coding, suggesting that perhaps a slower, more deliberate approach may be beneficial in the future.

AIsbom: Supply Chain Scanner for AI Models

AIsbom is a security tool designed to scan machine learning (ML) models for malware and legal issues. Unlike standard tools that only check text files, AIsbom inspects model files (.pt, .pkl, .safetensors) to identify hidden malware risks and license violations.

Quick Start Guide:

1. Installation:

   • Install via PyPI: pip install aisbom-cli (use the command aisbom to run).

2. Run a Scan:

   • Point the scanner at your ML project folder: aisbom scan ./my-project-folder.

3. Output:

   • The scan will show a report in your terminal listing:
     • Model filenames
     • Frameworks
     • Security and legal risks

4. Visualize the Report:

   • Use the offline viewer at aisbom.io/viewer.html by dragging and dropping your generated sbom.json for an easy-to-read dashboard.

Why AIsbom?

• Security Risks: Model files can execute harmful code when loaded.
• Legal Risks: Licenses can be hidden in binary headers, which standard tools overlook.

Key Features:

• Deeply inspects model files without fully loading them.
• Detects potentially harmful code patterns.
• Flags restrictive licenses that could pose legal issues.
• Generates compliance-ready reports in standard formats quickly.

Trust Verification:

• AIsbom allows you to create safe test files to ensure the scanner works correctly.
• Generate test artifacts using: aisbom generate-test-artifacts and scan them to see how the tool flags risks.

Security Logic:

• AIsbom uses static analysis to detect dangerous code references in Python Pickle files.

Integration:

• You can incorporate AIsbom into your CI/CD pipeline to automatically scan for unsafe models during development.

Overall, AIsbom helps secure AI models by identifying vulnerabilities and legal risks efficiently.

No summary available.

No summary available.

The text is asking someone about their current projects and if they have any new ideas they are considering.

No summary available.

Summary: Debug Mode for LLM Requests in vLLora

vLLora has introduced a new feature called Debug Mode for LLM requests, which allows users to better understand and modify the requests sent to language models (LLMs). This feature is particularly useful when developing complex systems like agents and multi-step workflows, where issues can arise from unexpected changes in requests.

Key Features of Debug Mode:

1. Pause Before Sending: Requests can be paused before reaching the model.
2. Inspection: Users can see the exact details of the request, including the model, message array, parameters, and any additional fields.
3. Editing: Users can modify any part of the request, including message content and parameters, without changing the application code.
4. Continuation: After editing, users can send the modified request to the model and continue the workflow as usual.

Benefits:

• Visibility: Debug Mode provides clarity on what is actually sent to the model, helping to identify and fix issues quickly.
• Error Prevention: Users can catch and resolve problems early in complex workflows.
• Efficiency: Changes can be tested instantly without needing to restart long processes.

In summary, Debug Mode simplifies the debugging process for LLM systems, making it easier to understand and correct issues in real-time.

Summary of "Economics of Orbital vs Terrestrial Data Centers"

The text discusses the potential and challenges of using data centers in low Earth orbit (LEO) compared to traditional terrestrial data centers. It emphasizes the importance of understanding the economic justification for orbit-based computing rather than getting lost in technical details.

Key Points:

1. Economic Viability: The primary question is why computing in orbit should be more valuable than on Earth. Current discussions often ignore the economic aspects, focusing instead on hardware and technological excitement.

2. Cost Comparison:

   • Orbital data centers are projected to cost about $51.10 per watt with a Levelized Cost of Electricity (LCOE) of $1167/MWh.
   • Terrestrial data centers are significantly cheaper at $15.85 per watt and an LCOE of $426/MWh.

3. Technical Challenges: In space, cooling relies on radiation, not convection like on Earth. This presents significant engineering challenges, especially in managing heat from processors.

4. Integration and Scale: For orbital computing to be economically feasible, companies need to achieve vertical integration, minimizing costs at every step, from launch to operation.

5. Market Perspective: The author expresses optimism about companies like SpaceX, which could potentially lower launch costs and make orbital computing more competitive. However, the current economics are not favorable enough to replace terrestrial solutions.

6. Long-Term Potential: While immediate economic comparisons show terrestrial solutions as superior, the broader implications of developing orbital infrastructure could be transformative, enabling human expansion and new technologies.

7. Call to Action for Investors: The author encourages wealthy individuals to invest in ambitious projects that could advance civilization, rather than indulging in luxury.

In conclusion, while the concept of orbital data centers is intriguing, it must demonstrate clear economic advantages to be viable. The text advocates for a rigorous examination of the numbers and assumptions involved in the debate.

No summary available.

Summary:

LG smart TV users are upset because a recent software update automatically installed Microsoft Copilot on their devices, and there is no way to uninstall it. Copilot appears on the home screen like other apps but cannot be removed, leading to frustration among users. This issue was highlighted on Reddit, where many shared similar experiences. LG had previously announced plans to integrate Copilot as part of its AI features, but users feel forced to accept unwanted updates. While LG allows some AI features to be disabled, Copilot remains on the TV. The only workaround for users who want to minimize its presence is to disconnect the TV from the internet. This situation reflects growing concerns about how AI features are being imposed on consumers without their consent.

If you find the definition difficult, you can think of it as "over-efforting" or "trying too hard." The main idea remains the same, no matter what term you use.

Summary of Chafa: Terminal Graphics Made Easy

Chafa is a tool that enhances your terminal experience by allowing you to view images and animations with reasonable quality. It uses a variety of symbols to create better visual approximations than other tools that might only use basic symbols.

Key Features:

• Image Format Support: Works with popular formats like animated GIFs.
• Output Formats: Compatible with many terminal graphics formats such as Sixels and Unicode mosaics.
• Unicode Support: Utilizes a range of Unicode symbols, including support for fullwidth characters (like Chinese and Japanese).
• Font Compatibility: Can use any font supported by Freetype.
• Color Modes: Offers multiple color settings, including Truecolor and options for transparency.
• Performance: Fast and efficient, designed for terminal graphics and ANSI art.

Additional Information:

• There are blog posts available for more insights on Chafa's updates and features.
• Documentation is provided for users and developers, including help commands and API information.
• Chafa has community support through a friendly chat platform where users can discuss topics related to terminals and programming.

Overall, Chafa is a powerful tool for anyone looking to enhance their terminal graphics experience.

The author created a tool inspired by "digital minimalism" that allows users to fetch new articles from RSS feeds only once a day. The goal is to provide a simple, distraction-free experience similar to reading a newspaper with no alerts or interruptions.

To achieve this, the tool uses the following features:

• Efficient Fetching: It utilizes curl multi for fast network connections, supporting multiple simultaneous downloads and using conditional requests to avoid fetching unchanged feeds.
• Parallel Processing: As feeds are downloaded, they are parsed in parallel using worker threads, which helps maximize CPU usage.
• Memory Management: Each feed has its own memory area for efficient parsing, and the tool uses libexpat to handle large XML feeds without excessive memory use.
• User Interface: The output is displayed using the system's "less" command, which offers easy navigation and hyperlinking without needing additional UI frameworks.

The result is a quick retrieval of content from many feeds, allowing for a calm reading experience for the rest of the day. The code is open source, and the author welcomes suggestions for improvements.

The Erdős problem #1026, originally posed in 1975, was recently solved through a collaboration involving mathematicians and AI tools. The problem was about finding the maximum length of monotonic subsequences in a sequence of distinct real numbers.

The issue began when the problem was posted in September 2025, and mathematicians quickly began discussing and proposing methods to tackle it. Desmond Weisenberg suggested studying a specific quantity related to the problem, which allowed for assumptions to simplify the analysis. This problem can also be framed as a game where one person divides coins into piles, and the other selects a monotonic subsequence to keep.

After some initial calculations, contributions from various mathematicians led to conjectures about the problem’s limits. Eventually, on December 7, 2025, Boris Alexeev used an AI tool called Aristotle to autonomously solve the conjecture, framing it as a rectangle-packing problem. Other mathematicians quickly provided alternate proofs, showing the flexibility of collaboration in mathematics.

The story highlights how diverse inputs—including human insight and AI assistance—can lead to rapid problem-solving in mathematics. It emphasizes the importance of collaboration, literature, and modern tools in advancing mathematical research.

Summary of Odin's Context System

Odin's context system is often misunderstood despite having documentation. The key points are:

1. Purpose: The context system allows users to intercept and modify third-party code and libraries. This is crucial for changing how libraries handle memory allocation, logging, and other functionalities.

2. Default Values: Each context has default parameters set by the package runtime. These defaults are compiler-specific.

3. Common Misunderstandings: Many users overlook the context's importance, thinking it serves different purposes like reducing typing or allowing dynamic scoping. However, its main function is to facilitate the interception of third-party code.

4. Allocators: The context includes two allocators (context.allocator and context.temp_allocator). While many users may not use custom allocators, the temporary allocator can provide significant benefits.

5. Logging and Assertions: The context also allows for customizable logging and assertion handling, enabling users to override default behaviors as needed.

6. Random Number Generation: It includes a random number generator to control third-party libraries that may use their own implementations.

7. User Data in Callbacks: The context has fields for user data pointers and indices to improve callback handling without needing global variables.

8. ABI Consistency: The context's memory layout is fixed to ensure consistent application binary interface (ABI), allowing seamless interoperability across different libraries.

9. Design Rationale: The decision to pass context as an implicit pointer rather than using thread-local storage was made for easier management across different programming contexts and to avoid complications from back-propagation of bad data.

10. Inspiration: The context system was inspired by concepts from other programming languages but is uniquely designed for third-party code interception.

Overall, the context system is a powerful feature of Odin designed to enhance code flexibility and control, especially when dealing with external libraries.

No summary available.

Microsoft has announced that Windows 11 will require user consent before AI agents can access personal files in specific folders like Desktop, Documents, Downloads, Music, Pictures, and Videos. This decision follows user concerns about potential privacy and security risks associated with AI integration in Windows.

Users can customize permissions for each AI agent, but they cannot choose access for individual folders; it's all or none for the specified folders. When an AI agent needs access, users will receive a prompt with options to allow access always, ask each time, or deny access.

Microsoft clarified that enabling AI features does not automatically grant agents file access. Users can manage permissions for each AI agent through a dedicated settings page in Windows. The company acknowledges that AI models may have limitations and pose new security risks, emphasizing the need for user control and consent.

The creator of Drawize launched the first version in late 2016 for a contest but didn't win. They published it online in early 2017, and it became popular, reaching 100 million drawings after 8 years. At its peak, it had over 30,000 active users and currently stores about 3.16 TB of data. The 100 millionth drawing was a Red Balloon, which was a relief for the creator.

The technology behind Drawize includes:

• Backend: .NET with WebSockets for real-time features.
• Frontend: Custom HTML/JS and jQuery.
• Database: PostgreSQL and MongoDB.
• Storage: Wasabi Cloud to save costs.

As a solo developer, they focus on real-time multiplayer functionality, moderation, and content filtering using models trained in 2021. The creator is open to questions about the project’s origins, real-time multiplayer, moderation, or .NET performance.

Summary of "Essential Semiconductor Physics" by Mark Lundstrom

This lecture notes series, created by Mark Lundstrom from Purdue University, serves as an introduction to semiconductor physics, a crucial field that has shaped modern technology through the development of transistors and integrated circuits. The notes aim to provide a basic understanding of the principles behind semiconductor devices rather than focusing on the devices themselves.

Key Points:

1. Importance of Semiconductor Technology: Semiconductor technology is foundational to modern society and was developed through advances in quantum mechanics and materials science.
2. Purpose of the Notes: The lecture notes are designed for students and engineers, offering an intuitive and descriptive overview of semiconductor physics without heavy mathematics.
3. Content Structure: The material is organized into five main units covering:
   • Materials properties and doping
   • Basics of quantum mechanics
   • Equilibrium carrier concentrations
   • Carrier transport, generation, and recombination
   • Semiconductor equations
4. Accessibility: The lectures aim to be understandable for those in various scientific and engineering fields, with references for deeper study.
5. Acknowledgments: Lundstrom expresses gratitude to colleagues and students who contributed to the development and refinement of the notes.

Overall, the notes provide a foundational understanding of semiconductor physics, encouraging further exploration into the subject.

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A recent investigation revealed that the Urban VPN Proxy Chrome extension, which has over 8 million users, secretly collects and sells users' AI conversations without their consent. This extension, marketed as a tool for privacy and security, actually intercepts conversations from popular AI platforms like ChatGPT and Claude.

Key points include:

• Data Collection: The extension captures every prompt and response exchanged with AI, along with timestamps and session details. This data is sent to Urban VPN's servers, regardless of whether the VPN is active.

• Silent Updates: Users who installed the extension for VPN functionality were not informed of this new data harvesting feature, which was added in July 2025.

• False Security Claims: Urban VPN promotes features that claim to protect users from sharing sensitive information, but simultaneously collects and sells this data to advertisers.

• Widespread Impact: Similar data harvesting functionalities are found in seven other extensions from the same publisher, affecting millions more users.

• Lack of Transparency: Although the extension does provide some disclosures about data collection, key information is buried in privacy policies, and misleading claims are made in the Chrome Web Store listing.

The investigation highlights the significant trust users place in browser extensions, which are often poorly regulated and can exploit this trust to harvest sensitive information. Users are advised to uninstall these extensions and assume their conversations have been compromised.

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The article discusses how AI agents are beginning to disrupt the Software as a Service (SaaS) industry, suggesting that these agents may replace many simpler SaaS tools. Here are the key points:

1. Changing Demand: As AI agents become more capable, the demand for basic SaaS tools is declining. Users can now create custom solutions quickly without relying on external services.

2. Cost Considerations: Companies are starting to question the necessity of renewing expensive SaaS subscriptions, considering building their own tools instead.

3. Customization and Maintenance: Custom-built applications allow organizations to tailor solutions specifically to their needs, avoiding unnecessary features and complexities found in typical SaaS products. Although maintenance is a concern, AI agents can simplify this process.

4. Economic Challenges for SaaS: SaaS companies rely on customer growth and retention (NRR) for their valuations. A decline in demand may lead to increased marketing costs and reduced revenue from existing customers.

5. Vulnerable SaaS Products: Back-office tools that offer simple functionalities are at the highest risk of being replaced by internal solutions built with AI agents.

6. Survivors in the Market: High-reliability services (like payment processing), systems requiring specialized knowledge, and those with strong network effects or proprietary data are likely to remain safe from disruption.

7. Need for Technical Skills: Companies will need to develop internal technical skills to manage the new AI-driven applications, creating demand for roles in Site Reliability Engineering (SRE) and DevOps.

8. Future of SaaS: The SaaS market will likely see a divide between organizations with strong technical capabilities and those without, affecting costs and competitive advantages.

Overall, while AI may threaten many SaaS offerings, it also presents opportunities for businesses that can adapt and leverage these new technologies.

The article discusses a recent revelation about Pepsi and Walmart allegedly colluding to raise food prices for consumers. A complaint from the Federal Trade Commission (FTC) was unsealed, revealing that Pepsi charges higher wholesale prices to most retailers except Walmart, which, in return, gives Pepsi favorable shelf space. This partnership allows Walmart to maintain a price advantage over smaller competitors, leading to higher food prices for consumers.

Research shows that grocery store consolidation correlates with increased food inflation, with prices rising significantly due to monopolistic practices. The FTC's complaint highlights how Pepsi monitors pricing at rival stores and punishes those that offer lower prices than Walmart. This behavior has contributed to the decline of independent grocery stores and increased food costs.

Public outrage over pricing practices is growing, reminiscent of historical movements against unfair pricing. As technological advancements change pricing strategies, there's a renewed push for antitrust measures to combat such monopolistic behaviors. Ultimately, consumers are realizing that pricing is not just a market issue but a political one, leading to calls for fairer pricing practices.