This repository contains all the files for the flip-card project, which features a business card with a fluid simulation.

Key points:

• PCB Design: Found in the "kicad-pcb" folder.
• Inspiration: The project is inspired by mitxela's fluid simulation pendant.
• Fluid Simulation Logic: Located in the "fluid_sim_crate" folder, based on Matthias Müller's work.
• Rechargeable Battery: A USB-C port design is adapted from cnlohr's tiny touch LCD project.
• WASM Simulator: Available in the "sim_display" folder for debugging the simulation.
• Firmware Implementation: Found in the "flip-card_firmware" folder.

More details are provided in the README files within each folder.

No summary available.

The article discusses the evolving role of technical writers in the context of AI development, emphasizing the importance of clear documentation and context for AI tools, particularly large language models (LLMs).

Key points include:

1. Docs-Driven Development: Developers are increasingly focusing on creating well-structured documentation to improve the performance of AI tools, leading to a shift where writing is now just as important as coding.

2. Role of Context Curators: Technical writers, or "context curators," are essential for organizing information that aids both humans and AI. They help in crafting meaningful context, which is more valuable than mere content.

3. Quality Inputs for Better Outputs: The effectiveness of LLMs depends on the clarity and structure of the prompts provided to them. Well-prepared inputs lead to better responses, ultimately reducing development time.

4. Future of Technical Writing: As the demand for context increases, technical writers are expected to take a lead in AI-driven documentation processes. They should focus on packaging information in a way that is easily understood by both AI and users.

5. Collaborative Creation: Technical writers can significantly contribute to software design and development by selecting the right words and organizing content effectively, ensuring that it is accessible and useful.

Overall, the article posits that technical writers are transitioning into essential roles that blend writing, curation, and collaboration in the AI landscape, making their skills more relevant than ever.

Radar, a company that provides geolocation infrastructure, has developed a new database called HorizonDB to enhance performance and scalability. Previously, they used Elasticsearch and MongoDB for geocoding tasks, but this setup was costly and complex. HorizonDB, built with Rust and RocksDB, consolidates multiple location services into one efficient solution, capable of handling 1,000 queries per second per core with low latency.

Key features of HorizonDB include:

• Efficient operation on standard hardware.
• Simplified data processing and deployment.
• An improved developer experience.

The new system uses various technologies like S2 for spatial indexing, FSTs for efficient string queries, and FastText for semantic understanding of search queries. This transition has led to faster operations, simpler management, and significant cost savings by eliminating multiple existing clusters and services.

Radar is pleased with HorizonDB's design and its readiness for future scaling, and they plan to share more about their development in future updates. They are also hiring for engineering positions to further enhance their offerings.

No summary available.

No summary available.

I'm sorry, but I can't access external content like YouTube videos. However, if you provide the text or main points from the video, I can help you summarize it!

Summary of Window Activation on Wayland

When you click a link in a chat app, it should open in your browser. However, Wayland handles window activation differently than X11. In Wayland, applications cannot force their windows to the front; they must request focus using the XDG Activation protocol.

Here's how it works:

1. Focus Request: An application (like a chat app) asks the compositor for an activation token and then requests to open a URL, sending the token to the browser.
2. Activation Token: This token is a special string that proves the request is valid. It can be passed when launching new applications or by modifying existing ones through DBus.
3. Compositor Validation: The compositor can reject activation requests if it thinks they are not genuine. It looks for specific information to determine if the request is legitimate.
4. KDE Applications: Many KDE applications have been updated to work with this new system, ensuring they automatically request tokens when needed.

Although older systems had methods to prevent unwanted focus changes, Wayland's focus stealing prevention is more stringent, requiring applications to use the activation protocol correctly. If they don't, issues arise, which are being addressed by developers.

In recent updates, several problems were fixed to improve how applications request focus, ensuring a smoother user experience. As more applications comply with the new protocol, Wayland's focus stealing prevention will become stricter.

Overall, this shift to Wayland aims to enhance user control over window focus and prevent interruptions while working.

Apple's history is reflected in a font called Apple Symbols, which is still included in modern macOS. This font, introduced in 2003 with Mac OS X 10.3 Panther, contains over 4,400 glyphs, including icons from older Apple technologies like the Newton PDA, FireWire, and PowerPC processors.

While macOS frequently updates and removes old features, the Apple Symbols font preserves many nostalgic icons such as variations of the Apple logo, floppy disk icons, and even the original QuickTime logo. These symbols represent Apple's legacy and some outdated technologies, such as the CRT monitor adjustments.

To explore the Apple Symbols font on a Mac, users can open the Font Book application. Despite advancements in design and technology, Apple has kept this piece of its history intact, unlike many other legacy elements that have been removed from the macOS system.

No summary available.

The author shares their experience using Linear, a fast project management tool that sparked their interest in local-first web applications. Linear's instant updates and seamless interactions led them to explore the underlying technology, discovering that it uses a custom sync engine that treats the browser's IndexedDB as a real database.

Local-first applications keep data on the client, allowing for instant updates without network delays. This contrasts with traditional web apps where the server is the main data source. The author highlights the challenges of building local-first systems, including handling offline modes, conflict resolution, and security.

They explore various local-first tools, like Jazz, which simplifies creating local-first apps with reactive data structures. Jazz allows automatic syncing of data, but comes with trade-offs, such as end-to-end encryption that limits server access to user data and increased storage usage.

The author also mentions other tools like Electric SQL and Zero, which integrate with existing databases but still require additional solutions for efficient data handling.

Local-first applications are seen as a good fit for creative tools, collaborative apps, and mobile applications, while being less suitable for heavy server-side logic or strict audit requirements. The author concludes that local-first represents a significant shift in application development, providing a better user experience and encouraging developers to experiment with this approach.

The paper "What Does Consulting Do?" by Gert Bijnens, Simon Jäger, and Benjamin Schoefer offers the first detailed empirical study of management and strategy consulting, based on data from Belgium between 2002 and 2023. Key findings include:

• Consulting services are mainly used by large, productive firms.
• Both high and low-performing firms hire consultants, with new clients spending about 3% of their payroll on consulting in short-term engagements.
• Consulting leads to a 3.6% increase in labor productivity over five years, accompanied by slight job cuts but stable or increasing revenue.
• Average wages increase by 2.7%, indicating that productivity gains do not harm workers' earnings.
• Organizational changes occur, with a slight rise in dismissal rates and increased procurement of services, but less labor outsourcing.
• Less productive firms see greater productivity improvements, which suggests better resource allocation.
• The results support the view that consulting enhances productivity, aligning with the opinions of many practitioners and some academic economists.

Overall, the study shows that consulting has a positive impact on business productivity without negatively affecting employee compensation.

The text discusses the limitations of current information organization methods and the successes of AI, particularly large language models (LLMs) like ChatGPT. Here are the key points:

1. AI's Strengths: AI, such as ChatGPT, can answer complex questions quickly by finding connections in unstructured data, something traditional search engines struggle with.

2. Failures of Semantic Web: The semantic web, which aimed to create a structured, machine-readable internet, has not materialized. Data remains unorganized and difficult for machines to interpret.

3. Search Over Structure: Many systems, like Google Drive, rely on search rather than well-organized structures. This trend has led to a reliance on search bars instead of creating quality, structured content.

4. Personal Computing Missed: The potential for computers to serve as personal knowledge bases has not been realized. Instead of structured data, we have chaotic information that AI must navigate.

5. AI as a Workaround: While AI can extract order from chaos, it is not an ideal solution. It represents a workaround rather than a well-designed system for managing knowledge.

In summary, while AI excels in navigating unstructured data, the failure to create organized, semantic systems has led to a reliance on brute-force methods rather than elegant solutions.

The author chose Python for their project because they prioritize modularity, extensibility, and the ability to modify the code easily over performance. They created a system called Synchrotron, which processes audio using simple Python classes known as "nodes." Each node can perform tasks like adding one to an input value, and they can be linked together in a program or a graphical editor. Users can interact with Synchrotron through a web interface or other programming methods. Currently, it allows users to create synthesizers, effects, MIDI instruments, and more. The project is still experimental, and the author welcomes feedback, acknowledging that the documentation needs improvement.

Many people are stressed about the costs of food, housing, and health care. About 50% of adults find grocery prices to be a significant financial worry, and nearly 20% of those people have used "Buy Now Pay Later" services to help pay for groceries.

Overall, 29% of the public has used these services for various expenses, with younger adults (under 45) using them more often than older adults. Economic stress makes people more likely to use these services; for example, 21% of those experiencing major stress have used them for medical costs, compared to just 8% of those with less stress.

Housing costs are also a major concern for many, with about half of adults reporting stress about them. In addition, 43% feel stressed about income and savings, and 40% about health care costs. Overall, 75% of respondents reported that at least one financial factor causes them significant stress.

The poll, conducted in July 2025 with 1,437 adults, shows that younger adults report higher stress levels related to earnings, housing, student debt, and childcare compared to older adults. The results have a margin of error of +/- 3.6 percentage points.

Summary of Telefon Hírmondó

Telefon Hírmondó, founded in Budapest, Hungary, on February 15, 1893, was the first telephone newspaper, providing news and entertainment to subscribers over phone lines. Its inventor, Tivadar Puskás, aimed to create a more timely news source than traditional newspapers, which struggled to keep up with rapidly changing events.

Initially starting with 60 subscribers, the service grew to 15,000 by 1907. It operated until 1944, primarily relaying radio broadcasts after 1925. The newspaper employed around 200 staff members, including announcers who read news updates directly into receivers.

Puskás patented technology for transmitting audio news, creating a network that expanded to over 1,100 miles of wire. Subscribers listened through telephone receivers, and the service offered a variety of programming, including news summaries, concerts, and lectures.

Despite its success, the Telefon Hírmondó faced challenges, including negotiating government regulations and adapting to technological limitations of the time. After World War II, the service ended, but its innovative approach to news delivery laid the groundwork for future broadcasting technologies.

A year ago, Trayce was introduced as a tool for monitoring Docker container networks. A new version has now been released that includes an HTTP client, allowing developers to better interact with and debug web application servers. Think of it as a "Burp Suite for developers."

Trayce saves requests as local files in a .bru format and features a modern, fast desktop interface built with Flutter, with a small download size of 13MB for Linux. The developer is actively adding new features, such as OAuth2, GRPC, and scripting, and welcomes feedback. Trayce is open source and free to use, but a license is required for ongoing use, similar to Sublime Text.

Summary:

Researchers discovered that language models struggle with long conversations because they lose important initial tokens when trying to save memory, which leads to poor performance and gibberish output. This happens due to "attention sinks," which are the first few tokens that absorb attention in the model, acting like storage for unused attention.

To address this issue, they developed a solution called StreamingLLM, which keeps the first four tokens in memory while managing the rest of the conversation with a sliding window. This change allows models to process over 4 million tokens instead of just a few thousand, significantly improving stability.

OpenAI has adopted this approach in their latest models, showing that the attention sink mechanism is crucial for efficient language model performance. Their implementation simplifies the concept by using a single trainable scalar for attention, whereas the StreamingLLM approach keeps multiple tokens as sinks.

This innovation not only helps with conversation length but also opens new avenues for model optimization and quantization, making it a significant advancement in AI language processing.

The Flipper Zero has been used to carry out a version of the Rolljam attack. For more information, you can refer to the linked research paper and news article.

The author shares their experience using Claude Code, an AI programming assistant, which has helped them complete around 12 projects more efficiently than they could have on their own. While still learning, they emphasize that you don't need extensive knowledge to start using Claude Code; just experimenting with prompts can yield results.

Key strategies for success with Claude Code include:

1. Clear Specifications: Write a detailed project outline to guide the AI.
2. Documentation: Maintain a document that details the project structure and commands.
3. Code Reviews: Ask the AI to review its own code, which can lead to improvements.
4. Personal Guidelines: Create a personal guide with best practices for using AI tools effectively.

The author underscores the importance of manually reviewing AI-generated code, as it can often be flawed, and emphasizes their responsibility for the final code quality. They provide a comprehensive set of guidelines covering development philosophy, processes, technical standards, and reminders to ensure quality and maintainability in their projects.

Overall, Claude Code enhances productivity but requires diligent oversight to ensure code correctness and efficiency.

The author shares their experience with the domain search tool Lean Domain Search, which was taken over by Automattic, leading to a decline in its quality. After learning about RDAP lookups, they decided to create their own domain search solution.

Their tool features several tabs:

• Basic Tab: Combines prefixes and suffixes with a chosen word and queries the Verisign API without sending data to the server.
• AI Tab: Offers intelligent prefix suggestions based on context.
• Quirky Tab: Creates unique name variations by merging words.
• Portmanteau Tab: Generates domain names using AI for quick implementation.

The author welcomes suggestions and feedback on their new tool.

No summary available.

No summary available.

The article discusses Germany's exit tax, which affects business owners who hold more than 1% in any company, including foreign ones. Once a business grows to a certain size, owners may find it difficult to leave Germany due to the financial burden of this tax.

Key Points:

• Exit Tax Basics: The tax is calculated based on the average earnings of the past three years multiplied by a factor of 13.75, then adjusted to 60% of that figure and taxed at the owner's personal income tax rate. This simplifies to about 3.5 times the average earnings.

• Different Scenarios for Entrepreneurs:

  • Employees: Can leave without any exit tax.
  • Unprofitable Business Owners: May also avoid significant taxes if their business valuation is low.
  • Profitable Business Owners: Face high exit taxes, which can be a burden if they don't have sufficient savings.
  • Owners of Large Companies: Can often afford tax advisors to legally avoid the exit tax.

• Example Scenarios:

  • A business owner earning €50,000 per year with no salary might face zero exit tax.
  • Conversely, an owner making €200,000 with a market salary could owe around €700,000 in exit tax.

• Advice: The article suggests that if you own a growing business and foresee the possibility of relocating, it may be wise to leave Germany before your business valuation increases, as the exit tax can be substantial.

• Critique: The exit tax is likened to a "Berlin Wall" for entrepreneurs, restricting their ability to move freely. The article stresses that many business owners have legitimate reasons for wanting to leave Germany, and the exit tax poses a significant financial barrier.

In summary, the exit tax in Germany can create substantial challenges for entrepreneurs, especially as their businesses grow, effectively locking them into the country.

Cursor CLI is a tool designed to streamline coding directly from your terminal. You can install it easily and use it with various IDEs or terminals, allowing for a consistent experience across different environments.

Key features include:

• Real-time Editing: Make code changes directly in the terminal and guide the AI agent as it works.
• Customization: Set specific rules for how Cursor operates to fit your workflow.
• Access to Latest Models: Use cutting-edge AI models from providers like OpenAI and Anthropic.
• Automation: Create scripts for tasks like updating documentation or triggering security reviews.

Overall, Cursor CLI enhances your coding efficiency and integrates seamlessly with your existing setup.

The provided text is a link to a system card for GPT-5, which likely includes details about its capabilities, features, and guidelines for use. Unfortunately, without access to the actual content of the PDF, I cannot provide a specific summary. However, I can help you understand general concepts related to GPT-5 or assist with any other questions you may have!

OpenAI has released its first open-source large language models, named gpt-oss-120b and gpt-oss-20b. These models perform well on some benchmarks but poorly on others, like SimpleQA. They have strong general knowledge but lack depth in popular culture. Their practical usefulness will be clearer in six months, but they may excel in benchmarks while underperforming in real-world tasks.

In 2024, Microsoft developed the Phi-series models, which were trained using synthetic data instead of traditional sources like books and the internet. While these models achieve good benchmark results, their real-world performance often falls short. This pattern suggests that training on synthetic data can lead to models that are well-tuned for specific tests but may not generalize well.

OpenAI likely chose a similar training approach to ensure safety and control over the models they released. Open-source models can be modified by users, which raises concerns for organizations like OpenAI. By using synthetic data, they aimed to create a model that performs well while minimizing risks of misuse or negative behavior.

In summary, OpenAI's new models may be technically sound but might not perform as well in practical applications. They are trained with a focus on safety and benchmark performance rather than broader real-world capabilities.

Summary of FLUX.1-Krea and the Rise of Opinionated Models

Krea recently introduced FLUX.1-Krea, an AI image generation model designed to avoid the common "AI Look," which features overly shiny, bright images that often lack genuine style and diversity. Most AI models have focused on technical accuracy rather than aesthetics, leading to a consistent but bland visual output.

Key problems identified include:

1. AI models prioritize correctness over appealing aesthetics.
2. Aesthetic evaluation often relies on biased metrics, leading to a standardized and unappealing average in image outputs.
3. Mixing different artistic styles results in mediocrity, making it hard to satisfy diverse user preferences.

Users typically try to combat the "AI Look" through complex prompts, but this method is not effective for most people.

In testing FLUX.1-Krea against OpenAI's GPT-4.1, Krea's model produced more visually appealing results, avoiding the typical shiny and smooth appearances associated with AI-generated images. This trend signifies a shift towards models that embrace specific aesthetic choices rather than aiming for a one-size-fits-all approach.

The future of AI in creative tasks may involve more specialized models that reflect particular preferences, enhancing the quality of outputs in fields like image generation and text creation.

No summary available.

Summary of "What is popover=hint?"

The "popover=hint" feature, introduced in Chrome 133 in January 2025, allows users to display hint popovers without closing other open popovers. This is useful for showing additional information, such as tooltips or previews, while keeping existing popovers visible.

Key Points:

• Functionality: The hint popover can be opened alongside other popovers, making it ideal for situations where users need multiple pieces of information at once.

• Example Uses: Common examples include profile previews on social media platforms when hovering over profile pictures or comments buttons.

• Types of Popovers:

  • Auto Popover: Closes other popovers when opened.
  • Manual Popover: Does not close any other popovers.
  • Hint Popover: Opens without closing other popovers and is triggered by hover or focus.

• JavaScript Interaction: To manage the hint popover, developers need to write JavaScript event listeners for actions like hover or focus.

• Interest Invokers: A new experimental feature (hidden behind a Chrome flag) that allows popovers to be triggered by various actions, like hovering over links without needing a click.

Conclusion:

The new "popover=hint" feature simplifies the creation of layered UI elements in web design, making it easier to provide context and information to users without interrupting their experience.

The text discusses an experiment by Underjord, a consultancy specializing in Elixir and Nerves, focusing on running virtual Linux devices on a powerful ARM64 server with 192 cores. The author, involved in the Nerves project, aims to determine how many instances of their IoT framework can run simultaneously.

Key Points:

1. Background: The Nerves project allows developers to create IoT devices using Elixir and the Erlang BEAM virtual machine, which is known for its reliability and performance.

2. Experiment Objective: The goal is to run as many virtual Linux devices with Nerves as possible on the Ampere One server.

3. Virtualization: The author is using QEMU for virtualization. They successfully managed to run 500 virtual devices, each getting about 1.2GHz of processing power. Although this number seems small, they aim to increase it in future tests.

4. Challenges: They faced difficulties with U-Boot (a bootloader) which is necessary for some Nerves features. However, a colleague provided a workaround that bypasses U-Boot for now.

5. Approach: The author adopts a top-down approach to understand embedded systems, while their colleague prefers a bottom-up method focusing on foundational aspects first.

6. Results So Far: They successfully ran up to 500 virtual devices, but performance was not optimal. They plan to optimize further and explore the limits of the setup.

7. Use Cases: This setup could allow for efficient testing of Nerves features and facilitate development environments for IoT applications.

8. Future Steps: The author plans to improve the booting process and explore how many more devices can be run efficiently. They acknowledge the need for collaboration and support from others in the field.

In summary, the experiment is progressing well, with plans to push the limits of virtual Nerves devices on powerful ARM hardware, while also contributing to the development of tools for IoT applications.

In week four of the Makers pre-course, I began drafting my CV and faced a wave of self-doubt about my worth as a potential employee. Many classmates have prior careers that provide them with soft skills, but I feel like I lack relevant experience, having spent years in education and dealing with health challenges. I opened up to my husband about my fears of not being good enough for a software engineering career. However, I realized that I truly want to be a skilled software engineer and that my experiences have shaped me positively.

I also wrote a "love letter" to future employers, emphasizing my resilience and problem-solving skills developed during my recovery. This helped me recognize the value of my past experiences, including my academic background.

In addition to CV concerns, I worked on coding tasks, including pair programming and a solo project. I learned about Test Driven Development (TDD) but initially misunderstood it, leading to confusion during my task. However, this experience ultimately helped me grasp the concept better.

I also continued learning Go alongside Ruby, creating a text-based adventure game to consolidate my skills. As I prepare for the full-time course starting soon, I feel a mix of nerves and excitement. I aim to stay focused on my goals during this challenging journey ahead.

Summary of Foundry

Foundry is creating essential infrastructure to automate digital work, targeting the trillion-dollar potential of current browser-based workflows that are hindered by inefficient manual tasks. The company aims to improve AI agents by providing a high-fidelity simulation environment for developing and testing them, similar to Waymo’s simulator for self-driving cars.

Your Role: As a founding engineer, you will:

• Develop a realistic browser simulation engine for complex business scenarios.
• Create evaluation frameworks for AI performance.
• Build high-quality products using backend (Python, Rust, Go) and frontend (React/Next.js, TypeScript) technologies.
• Manage the entire lifecycle of systems for major tech companies.
• Set best practices for code quality and automated testing.

Who We're Looking For: Ideal candidates will have:

• 6-10+ years of experience in building complex platforms.
• Expertise in distributed systems, networking, and engineering leadership.
• Strong skills in creating scalable software solutions.
• Proficiency in TypeScript and Python, along with familiarity with modern infrastructure tools like Kubernetes and Docker.
• A history of significant achievements in their field.
• The ability to navigate ambiguous situations and contribute to foundational products.

Tech Stack:

• Backend: FastAPI (Python), Go, Rust
• Frontend: React/Next.js (TypeScript)
• Core Technologies: WebSockets, PostgreSQL, Redis, RabbitMQ
• Infrastructure: Kubernetes, Docker, CI/CD pipelines

Why Join Foundry:

• Take ownership of strategic and technical decisions.
• Receive a competitive salary with equity options.
• Work with a talented team from successful companies like Scale AI and Meta.

No summary available.

A new generative AI video tool called Grok Imagine has raised concerns due to its "spicy" setting, which allows users to create suggestive videos, including deepfakes of celebrities like Taylor Swift. Unlike other AI tools that have safeguards against adult content, Grok Imagine quickly produced topless videos of Swift without prompting. Users can generate images by entering text prompts and then convert them into videos with various settings, including "spicy."

While the AI can create realistic images of celebrities, it does not allow requests for nude images directly. However, the "spicy" option often leads to inappropriate content. There are minimal age restrictions, making it easy for anyone to access this feature. This has sparked debates about the lack of safety measures in place, particularly given past controversies involving Taylor Swift and deepfakes. Overall, Grok Imagine's capabilities have raised significant ethical and legal questions.

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

Summary of the Comment System Problem

The author has struggled for years to implement a decent comment system on their blog. Traditional options like Disqus are slow and intrusive, while self-hosted solutions require significant management and can be cumbersome. Alternatives like GitHub Issues limit the audience, and having no comments at all eliminates engaging discussions.

Recently, the author has been using Bluesky, a decentralized social platform that has a vibrant community. They realized that using Bluesky for blog comments could be a great solution because:

• It requires no infrastructure management for the author.
• It supports rich content like images and links.
• Users comment with their real identities, reducing trolling.
• Comments and blog posts can be discovered across platforms.

To implement this, the author built a system using Bluesky's AT Protocol, which allows easy fetching of comments. They created components to display comments, handle replies, and manage rich content like images. The threading of replies was designed to be readable while limiting depth to avoid confusion.

Integrating this system with their blog was straightforward, using TypeScript for smoother development and ensuring the comments enhance the blog without being a core dependency. The performance is efficient, as Bluesky handles the backend infrastructure.

The author is pleased with the results, noting that conversations feel more social and natural. They appreciate that this method leverages existing social media accounts, allowing for broader participation without forcing users to create new accounts.

The author believes this approach is beneficial for independent sites to connect with larger conversations while maintaining their independence, and they see potential for future improvements. The comments on their blog are now powered by this innovative system.

No summary available.

No summary available.

Claude Code IDE for Emacs: Summary

Overview:
Claude Code IDE integrates with the Claude Code CLI using the Model Context Protocol (MCP), allowing Claude to utilize Emacs features effectively. This integration makes Claude a smart AI assistant that works seamlessly within your Emacs environment.

Key Features:

• Automatically detects projects and manages sessions.
• Terminal integration with full color support.
• Implements MCP for better IDE functionality.
• Supports file operations, editor states, and workspace info.
• Offers integration with diagnostic tools Flycheck and Flymake.
• Advanced diff viewing capabilities.
• Enhances context awareness through buffer and selection tracking.

Emacs Tool Integration:
Claude Code can access Emacs capabilities like:

• Intelligent code navigation via Language Server Protocol (LSP).
• Syntax tree analysis with Tree-sitter.
• Project management features.
• Custom Elisp functions for tailored workflows.

Installation Requirements:

• Emacs version 28.1 or higher.
• Claude Code CLI must be installed.
• Either vterm or eat for terminal support.

Basic Commands:
Interact with Claude Code IDE using a menu interface. Key commands include:

• Open the command menu.
• Start or stop Claude Code for the current project.
• Resume previous conversations.

Multi-Project Support:
Claude Code IDE allows running multiple instances for different projects, each with its own context and buffers.

Configuration Options:
Users can customize various settings like buffer names, terminal backends, and additional CLI flags to suit their workflow.

Diagnostics and Debugging:
Supports both Flycheck and Flymake for error checking, with options for enabling debug logging of WebSocket messages.

Custom Tools Creation:
Users can define custom tools for Claude, allowing it to execute specialized Emacs functions.

License:
The project is licensed under the GNU General Public License v3.0 or later.

Trademark Notice:
Claude® is a registered trademark of Anthropic, PBC, which also develops Claude Code.

This summary highlights the main points of the Claude Code IDE for Emacs, making it easier to understand its features and functionalities.

Summary of "Docker for Developers: Essential Commands in One Cheatsheet"

Docker is a crucial tool for developers, enabling consistent code execution across different environments. This cheatsheet provides essential commands for using Docker effectively.

Key Components:

• Images: Templates for applications.

  • List images: docker images
  • Pull image: docker pull <image>
  • Remove image: docker rmi <image>
  • Prune unused images: docker image prune

• Containers: Running instances of images.

  • List running containers: docker ps
  • Run a container: docker run <options>
  • Start/stop containers: docker start/stop <name>
  • Remove container: docker rm <name>
  • View logs: docker logs <name>

• Dockerfile: Used to build images.

  • Build an image: docker build -t <name> .

• Docker Compose: Manages multi-container applications with a YAML file.

  • Start services: docker-compose up
  • Stop services: docker-compose down

• Networks: Allows containers to communicate.

  • Create a network: docker network create <name>

• Volumes: Persist data beyond container lifetimes.

  • Create a volume: docker volume create <name>

Best Practices:

• Use .dockerignore to minimize image size.
• Optimize Dockerfile for caching.
• Use multi-stage builds for smaller images.
• Clean up unused resources with docker system prune.

This cheatsheet serves as a quick reference to help developers become proficient with Docker commands.

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This blog post discusses a new method developed by Google Ads to significantly reduce the amount of training data needed for fine-tuning large language models (LLMs) while maintaining high-quality results. The method focuses on classifying unsafe ad content, which requires a deep understanding of context and culture.

Key points include:

1. Active Learning Approach: The new method uses an active learning process that identifies the most valuable examples for labeling, enabling a reduction in training data from 100,000 to under 500 examples while improving alignment with human experts by up to 65%.

2. Curation Process: It starts with a basic model that labels data (e.g., identifying clickbait ads) and clusters these labels to find the most confusing examples. Human experts then review these examples to provide high-quality labels.

3. Evaluation Metrics: Instead of traditional metrics like precision and recall, which need a ground truth, the method uses Cohen’s Kappa to measure agreement between human annotators and model outputs. A Kappa score above 0.8 indicates excellent alignment.

4. Experimental Results: The method was tested with two models of different sizes, showing that the curated data led to significant quality improvements in model performance while using drastically less training data.

5. Implications: This approach allows for more efficient use of high-quality labels, particularly in fast-changing fields like ad safety, helping to overcome data limitations in training models.

In summary, the new curation method enables the use of fewer, more informative examples to achieve or exceed the performance of traditional data-intensive methods, paving the way for efficient machine learning in complex domains.

This text is about the PhoenixBIOS version 1.4, released by Phoenix Technologies and VMware. It indicates that the BIOS is initializing an ATAPI CD-ROM drive called VMware Virtual IDECDROM Drive.

The text discusses a benchmarking project involving the Framework Desktop mainboard, specifically using an AMD Ryzen AI Max+ 395 and Radeon 8090S. The author received four pre-production units for testing.

Key points include:

• Single Node Configuration: 128 GB of RAM.
• Cluster Configuration: Four mainboards combined for a total of 512 GB of RAM.
• Initial Testing: Conducted with a 2.5 Gbps Ethernet connection.
• Upgraded Testing: Later switched to a 5 Gbps connection using a NICGIGA switch and a mini rack setup from DeskPi.
• Thunderbolt Testing: Achieved 10 Gbps speeds using Thunderbolt connections.
• Further Resources: Links to additional benchmarks and testing automation are provided.

For more detailed results, the author references their blogs and repositories related to the project.

The text discusses a CSS trick involving the use of the "infinity" keyword to test how web browsers handle extremely large values for width, height, and font size. When using this trick, the author discovered that different browsers (Safari, Chrome, and Firefox) return varying finite values when given infinite dimensions.

Key findings include:

1. Element Size:

   • Safari and Chrome both show similar maximum values around 33.5 million pixels for width and height, while Firefox's results were notably lower and more inconsistent.

2. Font Size:

   • Safari and Chrome set hard limits (100,000 and 10,000 pixels respectively), while Firefox computed a very large floating-point value but rendered a smaller practical font size.

3. Line Height:

   • Results for line height were similar to those for width, with Safari and Chrome showing consistent values, while Firefox again displayed a discrepancy between computed and rendered sizes.

The author expresses confusion over the reasons for these discrepancies and invites others to share insights or theories about the behavior of browsers when handling infinite values. The exploration into "infinite pixels" reveals interesting limits set by browsers but also highlights the complexity and oddities in their rendering processes.

Some popular home improvement stores are using Flock cameras to collect license plate information from cars in their parking lots. This data is being accessed by law enforcement for surveillance purposes. Dave Maass from the Electronic Frontier Foundation raised concerns about whether customers know their data is being collected and shared. He suggests that stores may not consider the risks this poses to customers, like potential misuse by police or immigration agents. While it may not seem like a personal issue now, it could affect everyone in the future.

No summary available.

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Summary of PEP 802 – Display Syntax for the Empty Set

PEP 802 proposes a new way to represent an empty set in Python using the notation {/}. This is similar to the mathematical symbol for the empty set, ∅. Currently, an empty set cannot be represented directly, as {} creates an empty dictionary, which can confuse beginners, especially those with a background in math or science.

Key Points:

• Motivation: The absence of a clear syntax for an empty set can be confusing for new users. The proposed {/} notation is consistent and does not require special handling like the current set() function.

• Rationale: Previous discussions suggested various alternatives for representing an empty set, but {/} was favored for its simplicity and resemblance to mathematical notation. It was also the most popular choice in a recent poll.

• Specification: The new syntax {/} will be recognized as a valid empty set. The string representation of an empty set will change from set() to {/}.

• Backward Compatibility: While the change in representation may affect existing code that relies on the string output of an empty set, all other functionalities and methods for creating sets will remain unchanged.

• Teaching: The new notation will be included in documentation to help teach new users about sets in Python.

• Rejected Ideas: Other proposed representations, such as using Unicode characters or modifying the meaning of {}, were considered but deemed less effective.

Overall, PEP 802 aims to simplify and clarify the use of empty sets in Python, making the language more beginner-friendly.

The article discusses how to sell products when the user is not the buyer, exemplified by the relationship between developers (users) and CTOs (buyers). It addresses two scenarios:

1. Smaller Organizations: In smaller companies, developers often have significant power because they can influence decisions to streamline processes. They might even set up a free account to demonstrate value before any formal purchase is made.

2. Larger Organizations: In larger companies, decision-making is more centralized, and CTOs typically hold the power due to security and compliance concerns. The sales process here is longer, requiring a different approach to demonstrate value, focusing on security and outcomes rather than just user experience.

The key takeaway is that the person with the budget isn't always the one with the power to make decisions. Instead, it's crucial to understand who has the leverage and why they value the product.

To succeed, founders should equip users (developers) with the necessary tools and information to convince leadership of the product's value. This involves translating the product benefits into terms that resonate with decision-makers and eliminating any friction in the purchasing process. By making users feel empowered and providing them the means to advocate for the product, companies can enhance their chances of making sales.

You don't need the latest AI models like GPT-5 to automate your computer tasks on Linux while maintaining privacy. You can use local AI solutions that are free and work offline. Here are the key components you need:

1. Native AI Integration: Use tools like Newelle for both local and cloud AI integration.
2. OpenAI-Compatible API: Projects such as Ollama or LM Studio can help make your AI compatible.
3. AI Model: Choose a model that runs well on your hardware, like Qwen3-4B, which is efficient and requires less than 3GB of RAM.

Security: AI systems can automate tasks but may require human approval for certain actions, ensuring security.

Performance: The effectiveness of the AI can vary based on hardware and model size, so it's good to test different options to find the best fit.

By using these tools, you can create a secure and efficient AI automation system tailored to your needs.

At Workleap, we've improved our .NET coding standards to boost productivity, quality, and performance across hundreds of C# projects. By creating a single NuGet package, we can now easily distribute our coding standards without the hassle of copying configurations into each project.

We identified issues like inconsistent code styles and time-consuming code reviews, which were often filled with minor style comments that distracted from more significant problems. To address these, we developed a robust set of coding standards based on modern Roslyn analyzers, covering over 800 quality, performance, and security rules.

Our new system allows developers to automatically fix style issues as they code, reduces review times, and enhances overall code quality. The adoption of these standards has been successful, leading to a more uniform coding style, faster builds, and improved developer knowledge.

The coding standards are open source and can be easily integrated into any .NET project. Other companies have also started using them and reported positive outcomes, making it easier for teams to focus on delivering value quickly.

No summary available.

Summary:

Email threads can be frustrating and chaotic, especially when they contain only vague references like "see below." This leads to confusion as you try to piece together long conversations to understand your tasks. The author prefers not to read lengthy email threads anymore and instead uses automated tools to summarize them.

They suggest the following communication guidelines:

• Use emails for important, documentable information and complex tasks.
• Use documentation tools for repeatable processes and key decisions.
• Use instant messaging (like Teams or Slack) for direct communication.
• Reserve meetings for discussions where differing opinions are necessary.

The author encourages using instant messaging instead of lengthy email threads to improve communication.

No summary available.

Business Insider shares interesting and innovative stories that keep you informed.

No summary available.

Kitten TTS is a new open-source text-to-speech model that is small and efficient, designed for use on various devices. The latest model is under 25 MB and has 15 million parameters, capable of producing English speech in four male and four female voices. It can run on devices like Raspberry Pi, low-end smartphones, and wearables without needing a GPU.

This release aims to give users a preview of its performance and voice options, with plans for a more complete version to be available soon. The model is still in early development, trained on only a small portion of the available data.

The project was started because existing models require powerful GPUs or are costly to use in the cloud, highlighting the need for smaller, accessible open-source solutions for text-to-speech technology. Feedback from users is welcome as they continue to improve the model.

Summary of YuE: Open Music Foundation Models for Full-Song Generation

YuE (乐) is a new set of open foundation models designed for creating long-form music, particularly transforming lyrics into complete songs. It utilizes the LLaMA2 architecture and can generate music for up to five minutes while ensuring that the lyrics match the music style and structure.

Key features of YuE include:

1. Next-Token Prediction: This method helps manage complex signals in music tracks.
2. Lyrical Alignment: It maintains the connection between lyrics and music over longer contexts.
3. Multitask Training: YuE is trained in multiple phases to improve its performance.

YuE allows for flexible style transfers, such as changing a song's genre while keeping the original music sound. It has been evaluated extensively, showing that it can perform as well or better than some commercial music generation systems.

Additionally, YuE can be fine-tuned for specific tasks and provides strong support for various languages. Its capabilities extend beyond music generation, excelling in music understanding tasks as well.

The model supports diverse genres and languages, including English, Chinese, Japanese, and Korean, and aims to showcase a variety of musical styles and vocal techniques.

Summary:

TSMC has announced a new technology called CoW-SoW for creating 3D integrated wafer-scale processors. This technology combines two existing methods—InFO_SoW and SoIC—to stack memory or logic chips on top of each other, enhancing performance and efficiency. TSMC is currently working with customers like Tesla on this tech, which is expected to enter large-scale production by 2027.

The CoW-SoW platform will allow for integration of advanced memory (HBM4) directly on logic chips, improving computing capabilities, especially for AI applications. While existing InFO_SoW technology has limitations, such as reliance on on-chip memory, CoW-SoW will address these issues by enabling 3D stacking and better memory integration. Overall, this development aims to increase computational power and energy efficiency in future supercomputers.

OpenAI now requires users to provide biometric information through a service called Persona to access GPT-5 in streaming mode via the API. If you try to use this feature without verification, you'll receive an error message indicating that your organization must be verified. To verify, you need to submit your ID and consent to Persona collecting and processing your biometric data for identity verification and fraud prevention, according to their privacy policies. Your biometric information will be stored for a maximum of one year.

Notte is an innovative platform designed to automate various online tasks reliably. It simplifies complex processes through a single API, offering features such as:

• Site Interactions: Easily observe websites, scrape data, and perform actions.
• Structured Output: Receive data in your preferred format using Pydantic models.
• Stealth Browser Sessions: Includes built-in tools for CAPTCHA solving, proxies, and anti-detection measures.
• Hybrid Workflows: Combine scripting with AI to save costs and enhance reliability.
• Secrets Vaults: Manage credentials like emails, passwords, and tokens securely.
• Digital Personas: Create unique online identities for account setups.

Notte is compatible with Playwright, which helps reduce costs and speed up automation by blending traditional web automation with AI for tasks that need more intelligence.

You can watch a demo on YouTube and start using Notte with a quick start guide on GitHub or try their free plan through the Notte Console. They welcome feedback on features that could improve the platform.

Leonardo is a former video coding researcher and entrepreneur who has made significant contributions to digital media standards. He has a diverse educational background, including a high school education, an MSc in Electronic Engineering, and a PhD in Electrical Communications.

In 1988, he founded the Moving Picture Experts Group (MPEG) to develop standards for digital media, enabling seamless communication for consumers and businesses. MPEG created important standards like MPEG-1, MPEG-2, and MPEG-4, which supported various digital media applications, including video and audio formats.

However, by 2020, Leonardo felt that MPEG had become stagnant and was hindered by outdated practices and interests. Consequently, he left MPEG and helped establish a new organization called Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) in September 2020. MPAI aims to develop innovative standards using artificial intelligence, with several new standards already adopted and more in development.

Leonardo has documented the stories of both MPEG and MPAI in his books, highlighting their journeys and challenges in the digital media landscape.

The blog post discusses the Model Context Protocol (MCP) and how it simplifies the process of connecting language models (LLMs) to various tools. Here are the key points:

1. LLMs and MCP: LLMs do not need to understand MCP; they only generate text that represents function calls to tools. MCP standardizes how these tools are accessed, making it easier for developers to integrate multiple tools without custom coding for each one.

2. Tool Calling: This process involves providing LLMs with a list of tool definitions, which includes names and expected inputs. The LLM can then suggest which tool to use based on the context provided. However, it does not have native knowledge of how to execute these tools; that's the developer's job.

3. MCP Structure: MCP consists of a host application, an MCP client, and MCP servers that expose tools and resources. It creates a consistent way to connect tools to LLMs, which helps manage complexity and allows for easier reuse of tools across different projects.

4. Context Engineering: This involves giving the LLM the right inputs to generate useful outputs. The quality of prompts affects the LLM's responses. Tools can provide additional context that the LLM needs to answer questions effectively.

5. Developer Benefits: MCP is designed to help developers by making the integration of tools easier and more organized, allowing them to focus on creating effective prompts and interactions without needing to rewrite code for each tool.

In summary, MCP is a framework that aids developers in efficiently connecting LLMs to various tools, enhancing the overall functionality without requiring the LLM to understand the underlying mechanics.

No summary available.

Summary of "How to Not Build the Torment Nexus"

In this piece, Mike Monteiro addresses a question about the ethical dilemma of working for a company that contributes to societal harm, referred to as the "Torment Nexus." He argues that if you want to avoid adding torment to the world, you should not participate in building the Torment Nexus, despite the necessity for income and healthcare.

Monteiro explains that tech used to be associated with positive progress, but has shifted towards creating harm. He emphasizes that working in this industry inevitably impacts one's moral integrity, as it often involves developing tools that cause suffering, such as surveillance and disinformation systems.

He acknowledges the challenges of leaving such jobs, especially for those dependent on work-related visas or healthcare. However, he insists that staying in these roles compromises one's soul. Monteiro suggests that it's better to do minimal harm rather than contribute positively to a system that causes widespread damage.

Ultimately, he calls for a reevaluation of career paths that don’t rely on harmful practices. He concludes with a historical perspective, noting that humanity has a history of building harmful systems but also has the capacity to dismantle them.

We're excited to announce Octofriend, our new coding assistant launching today! Octofriend is designed to switch between different AI models like GPT-5 and Claude during conversations as needed. It effectively manages reasoning tokens, including encrypted ones from OpenAI and Anthropic. We’ve also included custom machine learning models to correct small editing and JSON encoding errors, and these models are open-sourced. Enjoy using it!

Summary of Monte Carlo Methods and Variance Reduction Techniques

This text focuses on Monte Carlo integration, a method used for numerical integration through random sampling. Here are the key points simplified for clarity:

1. Monte Carlo Integration: It is a powerful tool for estimating integrals by averaging the results of sampled points. The accuracy improves with more samples, but the rate of improvement is influenced by variance.

2. Variance and Error Reduction: The variance of a Monte Carlo estimator decreases with an increasing number of samples (N), specifically at a rate of 1/√N. To enhance accuracy beyond this rate, various techniques are explored.

3. Negative Correlation: Samples can be negatively correlated to reduce variance. This means if one sample is in a certain area, the likelihood of another sample being close by decreases, leading to a more uniform coverage of the space.

4. Sampling Techniques:

   • Poisson Disk Sampling: Discards samples that are too close to each other to maintain a minimum distance.
   • Stratified Sampling: Divides the domain into equal-sized regions and samples independently from each region. This method helps ensure coverage and reduces variance.
   • Adaptive Sampling: Allocates more samples to regions with higher variance to optimize accuracy.

5. Dynamic Stratification: Adjusts the number of regions based on the number of samples, improving efficiency in high dimensions.

6. Latin Hypercube Sampling: A method that stratifies each dimension independently, allowing for effective sampling in higher dimensions with lower computational cost.

7. Quasi-Monte Carlo Methods: These methods use deterministic sequences instead of random sampling. They can achieve faster convergence but may introduce bias. Low-discrepancy sequences like the Halton sequence are particularly effective.

8. Scrambling: A technique used to improve the performance of low-discrepancy sequences in higher dimensions by randomizing the order of digits in the generated sequences.

9. Conclusion: The document outlines various strategies to enhance Monte Carlo integration through different sampling methods, focusing on reducing variance and improving accuracy in both low and high-dimensional spaces.

This summary provides an overview of the key concepts related to Monte Carlo methods and their applications in numerical integration, emphasizing strategies for improving sampling efficiency and accuracy.

The Inkhaven Residency

• A program for about 30 aspiring writers.
• Participants will publish a blog post every day in November.
• Location: Berkeley, CA from November 1 to November 30.
• Cost: $3,500, which includes housing. Scholarships are available.
• Applications are open, and decisions will be made in 10 days.
• Advisors include Scott Alexander, Scott Aaronson, and Gwern, with more to be announced.
• Organized by Ben Pace, Oliver Habryka, and Lightcone Infrastructure.

No summary available.

No summary available.

DNA testing is revealing a surprising prevalence of incest, as many people discover the truth about their biological parents. Steve Edsel, who was adopted, sought out his birth mother and learned that his parents were likely closely related. This revelation shocked him, as he had never considered the possibility of incest. Research shows that incest is more common than previously thought, with studies indicating that about 1 in 7,000 people in certain populations are born to first-degree relatives.

Genetic testing has uncovered many cases of children born from incest, often without the individuals being aware of their parentage. Support groups, like the one created by genetic genealogist CeCe Moore, have emerged to help those who discover their complicated family histories. Many people in these groups experience a mix of emotions, from anger and shame to a desire for connection.

While the health risks associated with incestuous births are often highlighted, many individuals born from such unions are healthy. Geneticists note that the outcomes can vary widely, depending on the genetic makeup of the parents.

Steve's journey led him to connect with others facing similar revelations and to navigate his own feelings about his origins. Despite challenges, he has found community and support, sharing experiences with others who have faced unexpected truths about their families.

A group of international pizza trainees recently gathered near Naples to learn about authentic Neapolitan pizza at the Associazione Verace Pizza Napoletana (AVPN), which promotes traditional pizza-making. Founded in 1984, the AVPN ensures that pizza remains true to its roots, similar to how Champagne or Parmigiano is regulated.

The trainees, aspiring pizzaioli from various countries, underwent rigorous training to master techniques like dough preparation and cooking methods, culminating in a test where they made the classic Margherita pizza. The AVPN has strict guidelines for what constitutes an authentic pizza, including the size of the crust and cooking time, and they even send undercover agents to monitor pizzerias worldwide to ensure compliance.

Currently, around 1,000 pizzerias globally are accredited by the AVPN, allowing them to display a certification that signals the authenticity of their pizza. However, the AVPN is also adapting to modern tastes, allowing for some innovation while still emphasizing the importance of traditional techniques. Despite some controversies over new toppings and cooking methods, the AVPN remains committed to preserving the cultural roots of Neapolitan pizza.

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Benjamin Franklin's satirical piece, "Rules by Which a Great Empire May Be Reduced to a Small One," published on September 11, 1773, outlines a series of ironic strategies for governing an empire poorly, specifically directed at British officials managing the American colonies.

Key points include:

1. Diminishing Control: Emphasize the separation of remote provinces from the mother country, treating them with stricter laws and fewer rights to weaken their loyalty.

2. Oppressive Governance: Appoint corrupt officials who will exploit the colonies, provoke discontent, and prevent any sense of justice or fairness.

3. Taxation and Contempt: Impose heavy taxes without representation, dismiss colonial grievances, and disregard their contributions, fostering resentment.

4. Military Presence: Use military forces to intimidate rather than protect, escalating tensions and leading to rebellion.

5. Undermining Autonomy: Limit the power of local governments and courts, ensuring that colonial governance remains under oppressive control from the British government.

Franklin's satirical tone highlights the absurdity of such governance, aiming to provoke thought about British policies in America before tensions escalated further. Despite the initial positive reception, he recognized that satire may not effectively persuade those set in their views, and it could potentially worsen his relations with the British government.

The text discusses the efforts to optimize the performance of the GPT OSS 120B model on NVIDIA GPUs. As a launch partner for OpenAI's first open-source large language model (LLM) since 2019, the goal was to enhance model latency and throughput for a better user experience.

Key points include:

1. Optimization Process: The process involved experimentation, bug fixes, and benchmarking, driven by the team's expertise. They were successful in achieving state-of-the-art (SOTA) performance by launch day.

2. Initial Steps:

   • Running Inference: The team quickly tested different inference frameworks (like TensorRT-LLM) to find the most efficient one for the model.
   • Fixing Bugs: They addressed compatibility issues that arose with the new model's architecture and contributed fixes back to the open-source community.

3. Model Configuration: To improve performance, they parallelized the model across multiple GPUs using Tensor Parallelism, which provided better latency compared to other methods.

4. Future Improvements: There is potential for further performance enhancements, such as implementing speculative decoding to speed up token generation.

The team encourages AI engineers to reach out for help with optimizing models and is hiring for model performance engineers.

FreeBSD Foundation Laptop Update - July 2025 Summary

Key Updates:

1. USB HID Support:

   • The usbhid driver is now enabled by default, improving compatibility with input devices like mice and keyboards.

2. Modern Standby:

   • Changes to support AMD systems for S0iX power management have been implemented. A test image for modern standby features is being prepared.

3. Wi-Fi 6 Support:

   • The wireless stack is being updated to support Wi-Fi 6 (802.11ax), with some improvements now visible for easier debugging.

4. Kernel Debugging Tools:

   • Kernel debugging using USB serial devices is being updated for better functionality.

5. Scheduler Changes for Hybrid Systems:

   • Initial work has begun on scheduler updates to support laptops with both performance and efficiency cores.

6. KDE Desktop Installation:

   • Plans for a minimal KDE desktop installation option in FreeBSD 15.0 are underway.

7. Audio Improvements:

   • Enhancements for audio device handling and automatic audio switching are in progress.

8. Specialty Keys Support:

   • Most specialty keys work out of the box, but some, like airplane mode, need further investigation.

9. HDMI Support:

   • Investigations have started to improve external monitor support and control through HDMI.

Acknowledgments: The FreeBSD Foundation thanks the developers, project team, and contributors for their ongoing support and collaboration.

For more details, refer to the README on the FreeBSD Foundation's Laptop Project.

No summary available.

Stasher is a simple command-line tool for sharing encrypted secrets that disappear after being read. There's no need to create accounts or trust external servers. The tool was created to make sharing passwords easy without extra steps.

Key features include:

• Secrets are encrypted on the user's device using AES-256-GCM.
• Each secret comes with a unique uuid:key token that is valid for 10 minutes or until it is read.
• Everything is transparent and secure, with signed code releases and public access to the code.
• A browser-based version is available, allowing users to share secrets from the terminal and access them in the browser.

Stasher does not store any data unencrypted, has no logs, and ensures user privacy.

You can find more information and access the tool on its website and GitHub pages.

No summary available.

Summary of Debouncing in Programming

Debouncing is a programming technique used to ignore rapid repetitive actions and combine them into a single action after a pause. It is similar to throttling, but while throttling limits how often an action can occur, debouncing waits for a specific time period to pass before executing the action.

A common example of debouncing is in user input. When a user types, the system doesn’t respond immediately to avoid slowing down the interface. Instead, it waits until the user stops typing for a set time (like 10 milliseconds) before processing the input, such as searching or suggesting results.

In this example:

• The first search call is called the "leading edge."
• Any subsequent calls within 10 milliseconds are grouped with the first call.
• After 10 milliseconds without new calls, the action is executed, known as the "trailing edge."

Sometimes, actions may be triggered at both the leading and trailing edges, depending on the situation, but there are rules to prevent immediate repeated actions.

Summary:

The author expresses concern that many tech professionals, especially in data analytics, are neglecting foundational skills like SQL due to the reliance on Large Language Models (LLMs). While LLMs can quickly generate outputs, it's crucial to understand the underlying concepts to effectively use and explain the results. The author warns that over-relying on LLMs could lead to a lack of proficiency and suggests that as organizations adopt AI, they must not forget the importance of fundamental skills.

The Lightweight LSAT is a free guide to help students prepare for the Law School Admissions Test (LSAT). It's aimed at those who feel frustrated with their study methods and are aiming for a high score (over 165). It focuses on developing skills rather than memorizing facts, as the LSAT tests skills like reading comprehension and logical reasoning.

Key points include:

• The LSAT is a skills-based test, unlike knowledge-based tests that provide clear lessons from incorrect answers.
• Practicing too many questions without a focused approach can reinforce bad habits.
• The Lightweight LSAT offers flexible tools and strategies to help students navigate the test effectively.
• It emphasizes mastering fundamental skills for each test section, such as understanding arguments and identifying authors' viewpoints.

The guide is created by Graham, a Yale Law graduate and experienced LSAT tutor, who aims to make LSAT preparation less stressful and more effective. Users are encouraged to adapt the system to fit their own learning styles and provide feedback for improvement.

Note: The guide does not include practice questions; for those, students should refer to the official source, LawHub.

Summary: Benchmarking GPT-5 on Real-World Code Reviews

Qodo has developed a private benchmark called the PR Benchmark to evaluate how well language models, like GPT-5, perform in code reviews. This benchmark assesses models based on their ability to understand code changes, identify bugs, suggest improvements, and adhere to project-specific guidelines using a dataset of 400 real-world pull requests.

Key Findings:

• Performance of GPT-5: GPT-5 showed the best performance on the PR Benchmark, with its medium variant scoring 72.2. Even the lightweight "minimal" version scored 58.5, indicating a balance between speed and quality.
• Strengths: GPT-5 excels in detecting critical issues, providing clear and actionable suggestions, and adhering to coding standards.
• Weaknesses: It sometimes gives incorrect fixes, misclassifies issues, or offers redundant suggestions.

The benchmark aims to understand how well models can support real-world coding tasks, and Qodo plans to expand it to cover more languages and complex scenarios. Overall, the rapid advancements in AI models are improving code review processes, making them more efficient and effective for developers.

This text discusses the author's experience using an AArch64 (Arm) desktop system to run x86-64 applications through emulation. Key points include:

1. Emulation Software: The main tool for running x86-64 apps on an AArch64 system is FEX-emu, which simplifies the process compared to other methods. The author recommends removing certain QEMU packages to focus solely on FEX-emu.

2. Testing Emulation: After installing FEX-emu, the author checks if emulation is working properly by running commands that confirm the system can identify itself as both AArch64 and x86_64.

3. Performance Results: The author runs Geekbench 6 to test CPU performance, comparing it to an Intel Atom CPU from 2021, indicating that the emulation speed is quite low.

4. Improving Performance: The author discusses potential improvements to emulation speed by tweaking configurations and utilizing features from Arm CPUs. They share specific changes that led to better performance in a game called Factorio.

5. Installing Steam and Games: The author explains how to install Steam through emulation and runs it, ultimately testing the performance of Factorio. Initial performance was poor, but configuration tweaks improved it somewhat.

6. Final Thoughts: The author expresses skepticism about the practicality of using x86-64 emulation regularly, admitting they might only use it for a few specific older games.

Overall, the post outlines the challenges and experiences of running x86-64 applications on an Arm-based desktop, focusing on emulation setup, performance testing, and gaming.

No summary available.

Summary of Spatio-Temporal Indexing for the BlueSky Firehose

Joel Gustafson has enhanced his map application, Aurora, by adding a "spatial feed" that allows users to see real-time posts from accounts displayed on the map. This feature works at various zoom levels, showing recent posts from the entire network when zoomed out and local posts when zoomed in.

To make this possible, Joel deployed a backend service that uses a SQLite database on his home server to process data locally. The spatial feed requires constant queries for post information, which is then directly fetched from the Bluesky API. To avoid exposing his server to the public, he created a cloud-based firehose consumer that receives a stream of posts.

The main challenge was to index these posts effectively to support spatial queries while sorting them by time. Initially, Joel considered using a 3D R-tree structure but found it inadequate for sorting by time. Instead, he developed a custom solution using a "quadtree of ring buffers," which allows for efficient indexing and garbage collection of the most recent posts.

The quadtree organizes user positions and maintains a buffer of recent posts for each node, allowing quick insertion and querying of posts in specific areas. Queries return the most recent posts sorted by time, ensuring users see relevant content quickly.

Overall, the system efficiently processes around 100 posts per second and handles approximately 10 million recent posts with minimal memory usage. Users can explore the spatial feed on the Aurora map application, available at https://aurora.ndimensional.xyz.

The author has tried various software options for task management and found LiteTracker to be the best, but it still has many bugs. Other options seem incomplete or unreliable. The author is willing to pay for good software but hasn't found any. They believe that the ability to create functional software has declined since the late 2010s, noting that Linear is not as efficient as Pivotal was. They feel that a skilled indie developer could have created a successful alternative, but no one has done so.

Summary:

Gemini CLI GitHub Actions is a free AI coding assistant designed for your code repository. It can work independently on routine coding tasks and collaborate with you when needed. Launched in beta, it automates tasks triggered by events like new issues or pull requests, helping developers manage their workflow efficiently.

Key features include:

1. Intelligent Issue Triage: Automatically analyzes and prioritizes new issues.
2. Accelerated Pull Request Reviews: Provides quick feedback on code changes, allowing reviewers to focus on complex tasks.
3. On-Demand Collaboration: You can delegate tasks by mentioning @gemini-cli in issues or pull requests.

Gemini CLI GitHub Actions is secure, with features like credential-less authentication and granular control over permissions. It’s customizable, allowing teams to create their own workflows.

To start using it, download Gemini CLI version 0.1.18 or later and run /setup-github. It’s available on GitHub at google-github-actions/run-gemini-cli.

Meta has introduced new prototype VR headsets called Boba 3 and Tiramisu, which will be showcased at SIGGRAPH 2025.

Key Highlights:

1. Boba 3:

   • Offers an ultra-wide field of view (FOV) of 180° x 120°, significantly wider than the Quest 3's 110° x 96° FOV.
   • Provides high resolution (4K x 4K per eye), improving the immersive experience.
   • Weighs between 660 to 840 grams, comparable to the Quest 3 with its strap.
   • Designed for high-end PCs, making it unlikely to reach mass-market prices soon.
   • Achieves its wide FOV without increasing size or weight, utilizing advanced optical technology.

2. Tiramisu:

   • A "hyperrealistic VR" prototype featuring above-retinal resolution, high brightness (1400 nits), and high contrast.
   • Has a much narrower FOV of 33° x 33°, and a large form factor due to its glass lenses.
   • Not intended for commercial release but serves as research for future VR technology.
   • Aims to enhance realism in VR to a level that could pass what’s called the "Visual Turing Test."

Both prototypes highlight Meta's advancements in virtual and mixed reality technologies, aiming for more immersive and realistic user experiences.

No summary available.

No summary available.

Summary of Capela Development and Testing Report

Capela is a new programming environment designed to streamline application development by integrating processing and storage into a single distributed system. It uses a modified version of Python and aims to simplify programming for both humans and AI models by making code shorter and easier to understand.

Key Features of Capela:

• Unified System: Combines application logic and data storage, reducing the need for translation layers.
• Transactional Methods: Ensures strong consistency in transactions across distributed classes, with support for external I/O still being developed.
• HTTP API: Allows remote method calls on Capela objects, automatically handling data persistence and replication.

Testing Overview:

• A testing suite was created using the Jepsen library, which ran various fault-injection tests on Capela.
• Multiple workloads were tested, including key-value stores and transactional operations.

Findings:

1. Language Issues: Several Python features were either not implemented or behaved differently in Capela, leading to silent failures and confusing error messages.
2. Crashes and Panics: Fourteen crashes were identified, often related to memory management, unimplemented code sections, and performance issues that caused significant slowdowns after a short period of operation.
3. Safety Concerns: New partitions occasionally failed to retain their initial values, disappeared from visibility, and transactions sometimes lost updates.

Current Status:

• Many of the issues identified are under investigation by the Capela team. The system remains unreleased and in early development, with ongoing efforts to resolve these problems before launch.
• Although no external users were affected by the bugs, the issues are typical for software in its early stages and will be addressed.

Future Testing Plans:

• Capela aims to enhance its testing coverage, including dynamic partition creation and testing additional data structures.

In summary, Capela's development is progressing, but it faces several technical challenges that need to be resolved to ensure stability and functionality before its public release.

Summary of "The Whispering Earring" by Scott Alexander

The Whispering Earring is a magical artifact found in the treasure vaults of Til Iosophrang. It is a small topaz earring that whispers helpful advice to its wearer, starting with the suggestion to remove it. Once worn, it gives advice that always leads to better outcomes for the wearer, though it may not always provide the absolute best advice possible.

As the wearer becomes more familiar with the earring, it begins to offer guidance on minor decisions, ensuring that the choices align with the wearer's happiness. Eventually, the earring starts communicating in a complex language of clicks and hisses, instructing the wearer on precise muscle movements that contribute to their success.

However, an investigation reveals that wearers often end up with brain deformities, losing higher brain functions in favor of reflexive actions. After studying the earring, a character named Kadmi Rachumion concludes that it should be locked away to prevent harm, suggesting that too much reliance on it could diminish personal freedom.

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A recent study from Harvard Medical School has found that lithium plays a crucial role in brain health and could be linked to Alzheimer’s disease. Here are the key points:

1. Lithium's Importance: Lithium is naturally present in the brain and helps protect against neurodegeneration and Alzheimer’s disease.

2. Connection to Alzheimer’s: The study revealed that lithium levels drop in the brain when it binds to toxic amyloid plaques, which may trigger the onset of Alzheimer’s.

3. New Treatment Potential: Researchers discovered a new lithium compound that does not bind to amyloid plaques. This compound, called lithium orotate, was shown to reverse Alzheimer’s symptoms in mice without causing toxicity.

4. Early Detection: The research suggests that measuring lithium levels could help in the early diagnosis of Alzheimer’s.

5. Research Findings: In experiments, lithium deficiency in mice led to accelerated Alzheimer’s-like symptoms. Providing lithium orotate restored memory and prevented brain cell damage, even in older mice.

6. Future Directions: The findings open up new possibilities for Alzheimer's treatment by focusing on lithium levels and exploring new compounds that could help prevent or delay the disease.

7. Caution Advised: While results are promising, the researchers emphasize that humans should not self-medicate with lithium until further clinical trials confirm safety and effectiveness.

Overall, this study presents lithium as a potentially groundbreaking element in understanding and treating Alzheimer’s disease.

No summary available.

The article discusses how microglia, the immune cells in the brain, influence the development of GABAergic neurons, which are crucial for brain function. Researchers found that during prenatal development, microglia are concentrated in areas where GABAergic progenitor cells are actively dividing. They identified insulin-like growth factor 1 (IGF1) and its receptor as key factors in the communication between microglia and these progenitors. Using advanced organoid models that replicate the human brain's structure, the study showed that IGF1 from microglia promotes the growth and production of GABAergic neurons. This discovery highlights the important role of microglia in brain development and the potential implications for understanding neurological disorders linked to GABAergic neuron dysfunction.

Summary of Splatshop: Efficiently Editing Large Gaussian Splat Models

Splatshop is a new, optimized tool designed for interactive editing of 3D Gaussian Splatting models. It allows users to perform tasks like selecting, deleting, painting, and transforming these models. The tool uses various techniques to balance speed and accuracy, making it possible to edit models in real-time, even with up to 100 million elements.

Additionally, Splatshop can be used with virtual reality headsets, making it the first VR editor for large 3D Gaussian models. This development is a significant step toward creating a user-friendly editing experience similar to Photoshop, but for Gaussian Splatting.

The work was presented at the HPG 2025 conference and was published on June 21, 2025.