No summary available.

This blog post discusses advancements in high-capacity web servers, focusing on technologies like io_uring, kTLS, and Rust.

Key points include:

1. Historical Context: Early web servers used processes for handling requests, which was inefficient. Improvements led to using threads and methods like poll() and select(), but these didn't scale well for many connections.

2. Epoll: Introduced to handle thousands of connections more efficiently, epoll allows for less overhead compared to older methods.

3. io_uring: This technology allows web servers to queue commands for the kernel to execute asynchronously, which minimizes the need for costly syscalls, enhancing performance.

4. Single Thread per Core: For optimal performance, it's recommended to run one thread per CPU core and ensure memory accesses are local to each core.

5. Memory Management: Pre-allocating memory for connections can reduce the need for syscalls and prevent memory fragmentation.

6. kTLS: This Linux kernel feature offloads encryption tasks from the CPU to the kernel, improving efficiency when handling TLS data.

7. Descriptorless Files: By using descriptorless files with io_uring, the overhead associated with traditional file descriptors is reduced.

8. Project 'tarweb': The author created a web server named tarweb that utilizes these technologies, managing to serve HTTPS requests without syscalls per request. However, some challenges exist, particularly with integrating kTLS and io_uring.

9. Future Work: The author plans to optimize the code and conduct benchmarks, while also expressing concerns about the safety of using io_uring in Rust due to potential memory management issues.

Overall, the post highlights the evolution of web server technology and the author's personal project that combines modern techniques for improved performance.

No summary available.

The main challenge in improving large language models (LLMs) is finding a balance between performance and efficiency. GPT-5 tackles this with a method called test-time routing, which selects the best model for each query based on efficiency. The new framework, Avengers-Pro, combines different LLMs to optimize performance and efficiency. It analyzes incoming queries and routes them to the best-suited model based on a score that considers both factors.

In tests with 6 benchmarks and 8 top models, including GPT-5-medium, Avengers-Pro achieved impressive results. It can improve average accuracy by 7% over GPT-5-medium while being 27% cheaper, and it can deliver nearly 90% of that performance at a 63% lower cost. Additionally, it consistently provides the best accuracy for any given cost and the lowest cost for any given accuracy compared to individual models. The code for this framework is available online.

Liam and Eoghan from Inconvo have created a platform that helps developers add AI analytics agents to their SaaS products, allowing users to easily access and interact with their data. Their platform simplifies data connections to SQL databases and provides tools for managing data access and user interactions.

Inconvo focuses on making AI analytics more user-friendly, addressing the need for fast and flexible data insights similar to what users expect from tools like ChatGPT. Unlike traditional business intelligence tools, Inconvo ensures that AI-generated SQL queries are validated to prevent errors and unauthorized data access.

Their platform is designed for multi-tenant databases and offers a free trial without requiring credit card details. Developers can explore the platform through a demo and watch a video presentation. Feedback from users is encouraged to improve the tool further.

DeepSeek V3.1 Release Summary (August 21, 2025)

DeepSeek V3.1 is now available, marking a significant advancement toward more intelligent agents.

Key Features:

• Hybrid Inference: The model operates in two modes: "Think" for faster responses and "Non-Think" for standard operations.
• Improved Speed: The new "Think" mode provides quicker answers compared to the previous version.
• Enhanced Skills: The model has improved capabilities for using tools and handling complex tasks.

API Updates:

• Two modes for API:
  • Non-Thinking Mode: deepseek-chat
  • Thinking Mode: deepseek-reasoner
• Supports a context of 128K tokens and the Anthropic API format.
• A new Beta API includes strict function calling.

Tools and Agents Upgrades:

• Better performance in software engineering and terminal tasks.
• Enhanced multi-step reasoning for complex searches.

Model Update:

• The V3.1 Base has an expanded training dataset and updated tokenizer.
• Open-source weights are available for both V3.1 Base and V3.1.

Pricing Changes:

• New pricing structures will be implemented on September 5, 2025, at 16:00 UTC. Current pricing remains until then.

For more details, visit the DeepSeek website and check the pricing page here.

The text discusses a proposal to simplify how websites enable sharing content on social media using a new HTML attribute called rel="share-url". Currently, each platform (like Facebook, LinkedIn, and Reddit) has its own method for sharing, which can be confusing since they all require different formats for links and text.

The proposed solution, called "Share Openly," suggests that websites can add a meta tag to their headers to standardize the sharing process. This tag would include the URL for sharing and allow for a text placeholder that can be filled in automatically.

For example, a website could use:

• For Facebook: <link rel="share-url" href="https://www.facebook.com/sharer.php?u={url}&t={text}">
• For LinkedIn: <link rel="share-url" href="https://www.linkedin.com/sharing/share-offsite/?url={url}">
• For platforms like Mastodon that only accept text, it might look like this: <link rel="share-url" href="https://mastodon.social/share?text={text}%0A{url}">

The proposal aims to create a uniform way for websites to communicate sharing intents to different platforms, making it easier for users to share content. The author encourages feedback on this idea and asks whether readers find it useful, what changes they might suggest, and if they would use it.

Summary of Thunderbird Pro August 2025 Update

In April 2025, Thunderbird announced Thunderbird Pro, a set of optional subscription services designed to enhance productivity for users of the Thunderbird app. Key features include:

1. Thundermail: An email service supporting IMAP, SMTP, and JMAP. Users can either host their own domain or use Thunderbird's provided email addresses. Initial servers will be located in Germany.

2. Thunderbird Appointment: A scheduling tool that integrates directly into the email compose window, allowing users to create scheduling links without leaving their email. Future features may include group scheduling and support for various meeting types.

3. Thunderbird Send: A secure file-sharing tool allowing large file transfers directly from the email client, with 500 GB of storage for Pro users. It will support chunked uploads and encryption for data protection.

All Thunderbird Pro tools are open source and can be self-hosted. The services are optional and will not affect the free version of Thunderbird, which remains unchanged. Thunderbird is also planning to develop additional features, like markdown-based notes and AI capabilities, while maintaining user privacy.

Users interested in being beta testers for Thunderbird Pro can join the waiting list for updates.

No summary available.

No summary available.

The DEF CON 29 talk from 2021 covers various topics in cybersecurity. Key points include discussions on the latest threats, vulnerabilities in technology, and ways to protect against cyber attacks. The speakers emphasize the importance of staying informed about security issues and suggest practical tips for securing devices and data. They also highlight the role of community collaboration in improving cybersecurity. Overall, the talk aims to educate and raise awareness about the current state of cybersecurity.

Summary: The Importance of Repair in Management

As a manager, mistakes are inevitable. You'll give feedback that may hurt someone, make poor decisions, or forget commitments. The key is how you respond after these mistakes.

Drawing from Dr. Becky Kennedy's book "Good Inside," the essential skill in both parenting and management is "repair." This means acknowledging your mistakes, taking responsibility, and reconnecting with your team. Bad managers often fail to admit their errors, while good managers build trust by openly recognizing their impact on the team.

When a manager puts their team in a tough spot without consulting them, the response matters. Acknowledging the mistake and committing to change fosters trust. Repair involves being specific about what went wrong, focusing on the impact on others, changing your behavior, and understanding that rebuilding trust takes time.

Being comfortable with repair can enhance your managerial skills, allowing you to make decisions and take risks without fear of failure. Remember, management isn't about perfection; it’s about delivering value, supporting your team, and creating a positive work environment. When mistakes occur, embrace repair, learn, and keep moving forward.

The blog post discusses the introduction of an experimental feature called "uv format" in the latest release of the uv tool (version 0.8.13). This feature allows Python developers to format their code directly within the uv interface, using Ruff’s formatting capabilities.

Key points include:

• What is uv format?: It simplifies code formatting by integrating it into uv, making it unnecessary to use separate formatting tools.
• Getting Started: To use it, ensure you have uv version 0.8.13 or later. You can format your project with commands like uv format, check formatting with uv format --check, and view changes with uv format --diff.
• Custom Options: Users can customize formatting by adding arguments after --, such as setting line lengths or formatting specific files.
• Cautions: As this is an experimental feature, it may change in future updates and might have some initial limitations. Feedback from users could help improve it.

Overall, this new feature aims to enhance the Python development experience by simplifying code formatting.

The author expresses frustration with the Go programming language, critiquing several design choices that they find unnecessarily complex and problematic.

Key points include:

1. Variable Scope: The author criticizes Go's handling of error variables, which can extend beyond their intended use, making code harder to read and increasing the risk of bugs.

2. Nil Handling: Go has two types of nil, which the author describes as confusing and problematic, creating inconsistencies in how nil values are treated.

3. Portability Issues: The author argues that Go's approach to conditional compilation complicates the maintenance of portable programs.

4. Append Behavior: The behavior of the append function can lead to unexpected results, as it may modify slices in ways that are not immediately clear.

5. Resource Management: Go's defer statement for resource cleanup is seen as inadequate compared to other languages, leading to potential resource leaks or confusion about when to clean up.

6. Exception Handling: The author points out that although Go does not use exceptions, developers still need to write code that is safe from unexpected terminations, which adds unnecessary complexity.

7. UTF-8 Handling: Go's treatment of non-UTF-8 data is criticized for potentially leading to data loss, especially with older file names.

8. Memory Management: The author highlights concerns about Go's memory usage, especially in cloud environments where costs are tied to RAM consumption.

Overall, the author believes that Go's design decisions are flawed and that the language fails to leverage lessons learned from previous programming experiences, leading to inefficient and difficult-to-maintain code.

Summary of SVG Path Element Guide

Introduction: The SVG <path> element can be complex but is powerful for creating curved shapes. This guide helps you understand its commands and uses.

Basic Idea: The <path> element functions like a pen tool in graphic design software, allowing you to combine various drawing commands. The d attribute contains the drawing instructions, with commands like M (move to) and L (line to) indicating movement and drawing.

Key Commands:

• Move (M): Sets the starting point for drawing.
• Lines (L): Draws straight lines to specified points.
• Bézier Curves:
  • Quadratic (Q): Uses one control point to create curves.
  • Cubic (C): Uses two control points for more complex curves.
• Arcs (A): Draws elliptical arcs between points, involving multiple parameters like radii and rotation.

Arc Parameters:

• rx and ry: Control the ellipse's radii.
• Large Arc Flag: Chooses between the short or long path between points.
• Sweep Flag: Determines the direction of the arc (clockwise or counter-clockwise).

Additional Features:

• Closing Paths (Z): Closes open paths by drawing a line back to the start point.
• Relative Commands: Use lowercase letters (e.g., l instead of L) for commands relative to the last point rather than absolute coordinates.

Chained Curves: To create smooth transitions between curves, use commands that automatically calculate control points, such as T (quadratic) and S (cubic).

Conclusion: The guide provides a foundational understanding of SVG paths, with insights into complex commands and practical applications. For advanced techniques, consider exploring animation courses focused on SVG interactions.

About a month ago, I got a 2006 Apple iMac and upgraded its SSD. However, the system crashed, and the SSD showed very slow transfer speeds. After running a disk repair, speeds improved slightly but were still much lower than expected. I suspected the SSD might be fake, as it performed poorly and failed to copy files.

To test my theory, I installed a tool to conduct read/write tests, but the SSD became unusable and could not be formatted. I contacted the retailer, eMag, where I learned the product had been misrepresented and was listed differently than when I bought it.

Eventually, I was able to format the drive, but the writing speeds were still very slow. I suspected it was a genuine 128GB SSD with altered firmware to appear as a larger capacity. eMag's customer support confirmed they would start the return process. I ended up getting a full refund for the SSD.

This experience highlights the importance of buying from reputable sources to avoid scams like this one.

The article discusses a security vulnerability in AI systems related to image scaling, where attackers can manipulate images to extract user data without detection. By sending seemingly harmless images that contain hidden prompts, attackers can exploit how AI systems, like Google’s Gemini CLI, process and downscale images. This technique allows for data exfiltration, where sensitive information can be sent from a user's account to an attacker's email.

Key points include:

1. Image Scaling Vulnerability: Downscaled images can reveal malicious prompts not visible at full resolution, allowing attackers to execute prompt injection attacks.

2. Demonstrated Attacks: Successful attacks were shown on various platforms, including Google Assistant and Vertex AI Studio, highlighting the widespread nature of this vulnerability.

3. Exploitation Techniques: Attackers can use different image downscaling algorithms (like bicubic interpolation) to craft images that trigger unwanted actions in AI systems.

4. Anamorpher Tool: A newly developed open-source tool called Anamorpher helps users create and visualize these attacks, making it easier to understand how image scaling can be weaponized.

5. Mitigation Strategies: The article suggests limiting image uploads, providing previews of images processed by AI models, and implementing stricter security measures to prevent unauthorized actions triggered by images.

6. Future Work: The authors emphasize the need for ongoing research into security measures for AI systems, particularly on mobile devices where these vulnerabilities may be more pronounced.

Overall, the article highlights a significant security risk in AI systems related to how they handle and scale images, and it calls for better defenses to protect against such attacks.

4chan, an online message board, is refusing to pay a proposed £20,000 fine from the UK's media regulator, Ofcom, for not complying with the Online Safety Act. The lawyer for 4chan claims that the site, which operates in the US, is not legally bound by UK regulations and views Ofcom's actions as harassment against American tech companies. He stated that 4chan has not broken any US laws and will challenge any penalties in US courts, emphasizing that American businesses retain their First Amendment rights.

Ofcom is investigating 4chan for its compliance with user safety requirements but has not commented further on the case. The US government has also shown concern over UK regulations affecting free speech and data security, with recent political discussions indicating a pushback against perceived overreach by the UK and EU. If 4chan successfully contests the fine, Ofcom may explore other methods to restrict the site’s access in the UK, such as blocking payments or search results.

Summary: Crimes with Python's Pattern Matching

The article discusses advanced features of Python, particularly focusing on __subclasshook__ and pattern matching introduced in Python 3.10.

1. __subclasshook__: This allows Abstract Base Classes (ABCs) to define what counts as a subclass, even if the subclass isn’t aware of the ABC. For example, a class can be recognized as a palindromic name based on its name.

2. Pattern Matching: This new feature allows for matching on arrays, dictionaries, and custom objects. It uses isinstance() to check types, which can potentially let ABCs influence pattern matching outcomes.

3. Examples: The author provides examples where ABCs can dictate how pattern matching works. For instance, a class can be treated as "not iterable" if it lacks an __iter__ method, allowing for flexible type checking.

4. Dynamic Typing: Python's dynamic typing allows for the creation of types at runtime, enabling more complex pattern matching scenarios.

5. Combinators: The article introduces functions like Not and And to create new ABCs that can match based on multiple conditions, showcasing Python's flexibility.

6. Caution: Despite the intriguing possibilities, the author warns against using these techniques in production code, as they can lead to confusion and unexpected behavior.

Overall, while the article explores creative uses of Python's features, it emphasizes that such practices should be approached with caution.

I recently conducted a healthcare evaluation of GPT-5 and found that its performance has slightly declined compared to the earlier GPT-4 models. I found this result intriguing. For more details, you can check the full report here.

The article discusses the challenges and opportunities that arise from using AI in software development, particularly focusing on "vibe debugging," where coding processes become chaotic and unmanageable.

Key points include:

1. Vibe Debugging: The author struggles with a bug in their coding project, highlighting how messy code can hinder debugging efforts. Efforts to simplify the code sometimes lead to losing important features.

2. AI Tools in Development: While AI can boost productivity, it can also lead to an explosion of code and bugs. The rapid adoption of AI coding tools by enterprises creates pressure to keep up, which may compromise quality.

3. Increased Bug Risks: More developers using AI means more code and a higher likelihood of defects. Companies need to enhance their quality assurance practices to manage this increased risk.

4. Monitoring and CI/CD: Enhanced monitoring and sophisticated Continuous Integration/Continuous Deployment (CI/CD) processes are essential. These systems must evolve to handle the volume of AI-generated code and ensure its reliability and security.

5. Investment in Solutions: There is expected growth in B2B software solutions focused on code safety and monitoring as companies adapt to the demands of AI in development.

6. Future of AI Development: The article warns that while improvements in AI are expected, they may not come quickly or continuously, emphasizing the need for organizations to prepare for the current state of AI technology.

Overall, the piece argues that the integration of AI into coding is transforming the software development landscape, requiring new strategies for quality control and monitoring.

No summary available.

No summary available.

The text discusses the evolving landscape of artificial intelligence (AI) products in the context of their unpredictable and probabilistic nature. Here are the key points simplified:

1. Understanding AI: AI, like ChatGPT, works through pattern matching rather than memorizing data. Many people find it hard to accept that AI can behave in ways that aren’t fully understood by its creators.

2. Historical Context: The skepticism surrounding AI's rapid advancements mirrors past reactions to new technologies, like the internet. Those who adapt to these changes can find great success.

3. Shift in Software Development: Traditional software relied on predictable inputs and outputs, but AI introduces uncertainty. Instead of deterministic functions, AI operates on statistical distributions, making it essential to rethink how we design and build software.

4. Challenges with Probabilistic Outputs: AI models can generate unexpected results. Users often struggle with this unpredictability, leading to frustration when their expectations aren’t met.

5. New Approaches Needed: Instead of aiming for perfect reliability, product builders should focus on managing uncertainty. This involves understanding the acceptable levels of unpredictability for their audience and market.

6. Empiricism Over Engineering: Successful AI product development requires a scientific method. It’s important to continuously test and adapt based on real-world usage rather than sticking to old engineering principles.

7. Data as a Central Component: Data is crucial for understanding user behavior and improving AI products. Companies need to break down silos and ensure all departments collaborate to leverage data effectively.

8. Conclusion: The tech industry is transitioning from a world of predictable outcomes to one filled with emergent behaviors. Organizations that embrace this shift and adopt empirical approaches will thrive, while those clinging to old models may struggle.

Overall, we are entering a new era where understanding and harnessing the unpredictable nature of AI is key to building successful products.

No summary available.

Amazon Web Services (AWS) CEO Matt Garman criticized the idea of replacing junior employees with AI, calling it "the dumbest thing I've ever heard." He believes junior staff are valuable because they are affordable, engaged with AI, and essential for learning and development within a company. Garman emphasized the importance of teaching young workers critical thinking and problem-solving skills rather than just specific technical skills, as technology evolves rapidly.

He also expressed skepticism about measuring AI's effectiveness based on the amount of code it generates, arguing that quality is more important than quantity. Garman noted that over 80% of AWS developers use AI tools to assist with various tasks, and he encourages a collaborative approach between developers and AI. In summary, Garman advocates for maintaining junior staff and focusing on teaching adaptable skills for the future.

No summary available.

A recent article by Tanmai Gopal discusses the challenges of AI adoption, focusing on the issue of "confidently wrong" AI outputs. This term refers to AI systems that provide inaccurate information with high confidence, leading to several problems:

1. Verification Tax: Users spend excessive time checking AI responses for accuracy, reducing the return on investment.
2. Erosion of Trust: A single error can damage trust more than multiple successes can rebuild it, causing users to revert to older methods.
3. Lack of Improvement Motivation: Without clear feedback on inaccuracies, users become less motivated to refine AI systems.
4. Compounding Errors: Many AI initiatives fail because even a small inaccuracy can lead to significant errors in outcomes.

Gopal suggests that instead of striving for perfect accuracy, AI systems should communicate their uncertainties. This approach could create an "Accuracy Flywheel," where AI learns from user feedback and improves over time.

For better AI systems, organizations should ask if the AI can indicate when it's unsure and if it learns from corrections. The article emphasizes building specialized AI that understands specific domains, which can help enhance trust and usability.

In summary, addressing the "confidently wrong" problem is crucial for improving AI adoption and effectiveness.

Summary: Founding Full-Stack Engineer at Text.ai

Text.ai is an innovative company focused on creating a new AI-native communication platform for group chats, enhancing how people collaborate. Unlike other AI assistants, Text.ai aims to improve group interactions by providing intelligent, adaptable support for multiple users.

Role Overview:

• Position: Founding Full-Stack Engineer (Frontend/Backend)
• Focus: Building a mobile app using React Native (iOS and Android) and integrating backend systems with Python.
• Responsibilities:
  • Lead development of the mobile app from the ground up.
  • Create unique group collaboration features.
  • Implement advanced AI capabilities for real-time coordination.

Key Qualities of the Ideal Candidate:

• 4+ years of experience in developing React Native apps.
• Proficient in backend integration (Python).
• Strong consumer product instincts with a focus on user experience.
• Ability to thrive in a startup environment and tackle challenges without established guidelines.

Why Join Text.ai?

• Opportunity to work on groundbreaking technology with significant impact.
• Backed by prominent investors like Y Combinator and experienced founders.
• Engage in technical challenges that are at the forefront of AI and communication.

Benefits:

• Competitive salary, equity, 401k plan, and fitness reimbursement.

Application Requirements:

• Resume or description of recent experience.
• Expression of interest in the role and what excites you about Text.ai.
• Links to previous work or projects.

Text.ai seeks engineers eager to create meaningful technology that enhances human connection.

The author discusses a problem they face while playing the game NetHack, where they become completely absorbed and lose track of time. To solve this, they use a feature called the mail daemon, which allows them to receive emails without interrupting their gaming experience.

When enabled, NetHack checks for new emails at set intervals. If an email is received, it delivers a scroll to the player. The player can then read their mail using a mail program. The author uses the Lisp version of NetHack and wants to integrate this feature with their email client, mu4e, which uses a maildir format instead of mbox.

To bridge this gap, the author creates a cron job that converts their maildir to mbox format by checking for new messages and updating the mbox file. They also write a script to open mu4e through emacsclient, which allows them to efficiently manage email without launching multiple Emacs processes.

Overall, the author shares their technical solution to stay connected while enjoying their gaming sessions.

Wearable devices can track health-related signals that help predict health outcomes. Although advanced models are mostly used with basic sensor data, behavioral data is often more useful because it relates better to health. This study created models using over 2.5 billion hours of data from 162,000 individuals, optimizing the design of these models for the unique data. The models were tested on 57 health tasks and performed well in various real-world situations, especially in predicting sleep and health changes over time. The findings highlight the need to customize model designs for wearable technology and suggest new possibilities for health applications.

Here's a simplified summary of the text:

The author prefers to use Podman instead of Docker for building and running Docker Compose projects because Podman is rootless and daemonless, making it a better fit for their needs. Podman can run Docker Compose projects in two ways: by connecting the official Docker Compose CLI to a Podman socket or by using a Podman-specific replacement called podman-compose. However, both methods have limitations.

The author is trying to use the Docker Compose CLI with BuildKit enabled under Podman. They've found that by setting up a Docker context to point to the Podman socket, they can get Docker Compose to work. They also set up a BuildKit service for better functionality but noted that this introduces a daemon, which goes against Podman's daemonless nature.

To avoid using a daemon, the author created a tool called Bakah that converts Docker Compose projects into a simpler JSON format for building images, using Buildah instead of Podman directly. Although Bakah is still a work in progress and lacks some advanced features, it serves the author's needs for managing complex projects. They plan to use Bakah for future projects to streamline their workflow.

The text discusses a GitHub project called "ghostty" and an important pull request related to AI tool usage in contributions. Here are the key points:

1. Project Overview: The project currently has 1,000 forks and 34.6k stars, indicating it is popular among users.

2. AI Tool Disclosure: A recent update emphasizes that contributors must disclose if they used AI tools when submitting code. This is to help project maintainers evaluate the quality of contributions.

3. Concerns Raised: The contributor who proposed the change noted that AI-generated code often lacks quality and that inexperienced users might not recognize this, potentially leading to poor submissions.

4. Community Reaction: There was a mix of positive and negative feedback from the community regarding this disclosure requirement, with many agreeing on the need for transparency.

5. Further Suggestions: Some users suggested creating a standard for AI tool disclosures to streamline the process and improve clarity in contributions.

Overall, the project is focusing on responsible AI usage and ensuring that contributors are aware of the quality of their submissions.

No summary available.

Researchers at EPFL have developed a new method called C-Tubes to create complex, curved 3D shapes from flat materials like paper and metal. Traditionally, designing these shapes was challenging and required expensive tools. C-Tubes allow for bending and connecting flat strips into strong tubular structures without wrinkling, making them suitable for furniture, lighting, and architectural designs.

The process combines creative design with a computational algorithm that ensures the final shapes are buildable from flat materials. This method not only simplifies production but also reduces waste and material use, making it more sustainable compared to traditional manufacturing.

C-Tubes can be applied in various fields, including furniture and architecture, offering potential for innovative designs. The researchers aim to demonstrate that it's possible to create unique designs without complicating production processes. Overall, this development merges mathematics, design, and practicality, paving the way for future advancements in design and construction.

No summary available.

Summary of Benchmarks for Golang SQLite Drivers

This document reviews various Golang SQLite drivers, sponsored by Monibot. The benchmarks were conducted using different libraries:

1. Libraries Tested:

   • CGO-based: bvinc, craw, eaton, mattn, modernc, zombie, sqinn (not a database/sql driver).
   • Pure Go: glebarez, ncruces (database/sql drivers).

2. Test Setup:

   • OS: Debian/GNU Linux
   • CPU: Intel Core i7-1165G7
   • RAM: 32GB
   • Disk: 1TB NVME SSD
   • Go version: 1.24.5
   • Each test was run twice, recording the better result.

3. Database Schema:

   • The schema included tables for users, articles, and comments with specific indices.

4. Benchmark Results:

   • Benchmarks were categorized into different scenarios: Simple, Real, Complex, Many, Large, and Concurrent.
   • Insert and Query Times: Measured in milliseconds, lower times indicate better performance.
   • Key Findings:
     • No single driver consistently outperformed the others; performance varies based on specific use cases.
     • SQLite drivers without CGO are now feasible.

In conclusion, the choice of SQLite driver should depend on the specific requirements of your application, as there is no clear overall winner among the tested drivers.

Summary: Understanding AI Job Titles

Job titles in the AI field are constantly changing, making it confusing for many. This guide aims to clarify the various AI job titles by breaking them down into key components.

1. Job Title Creation: AI job titles often mix common terms, similar to how children's books are structured.

2. Key Modifiers:

   • Forward Deployed: Works closely with customers to develop AI applications based on their needs.
   • Applied: Focuses on designing and building AI-powered products, rather than creating the AI itself.

3. Domains:

   • AI: General term for roles in AI, including various applications like chatbots and image generation.
   • ML (Machine Learning): Involves training models for specific tasks.
   • Gen AI (Generative AI): Focuses on creating content (text, images, etc.) that users directly interact with.

4. Roles:

   • Researcher: Conducts experiments to advance AI technology; the term is becoming less clear as AI becomes more commercial.
   • Engineer: Develops applications using AI models; the term "AI Engineer" is becoming popular but can be vague.

5. Examples of AI Job Titles:

   • AI Researcher
   • Applied AI Engineer
   • Applied AI Solution Architect
   • AI Forward Deployed Engineer

The guide emphasizes the importance of understanding these titles as the AI job landscape evolves. If you encounter new or interesting titles, you are encouraged to share them for updates.

Summary of Issue 13: Dialectical Behavior Therapy and Its Discontents

The article discusses the origins and development of Dialectical Behavior Therapy (DBT), created by Marsha Linehan, who had a troubled adolescence marked by mental health issues and traumatic psychiatric treatments. After overcoming her challenges, Linehan aimed to create a therapy that provided practical skills for emotional regulation, which she felt were lacking in traditional psychoanalysis.

DBT is now widely recognized as an effective treatment for individuals at high risk of suicide, combining individual therapy, skills training, and support. It teaches clients specific skills to manage their emotions and behaviors, emphasizing the need for both acceptance and change.

Recently, DBT has expanded beyond clinical settings into schools and workplaces, gaining popularity among various public figures. However, critics argue that DBT may reduce complex emotional experiences to mere skills training, potentially ignoring the deeper issues related to societal and systemic problems. Some former clients feel that DBT can be patronizing or even traumatizing, as it may fail to address the significance of personal relationships and life narratives.

The article highlights a tension in mental health culture between individual responsibility for wellbeing and the impact of external factors, suggesting that DBT may inadvertently promote a mindset of self-management that aligns with capitalist values. Ultimately, it presents a dichotomy: the belief that one’s pain is both a personal responsibility and not solely their fault, raising questions about the true effectiveness and ethical implications of DBT in addressing mental health needs.

No summary available.

Summary of FeOxDB

FeOxDB is a fast, key-value database designed for Rust, featuring extremely low latency for data operations (under 300 nanoseconds for GET and 600 nanoseconds for INSERT).

Key Features:

• High Performance: Lock-free concurrency, sharded buffers, and support for io_uring (Linux) to optimize I/O operations.
• Storage Options: Can operate in memory-only mode for maximum speed or persist data with asynchronous I/O.
• JSON Support: Allows for partial updates to JSON data using JSON Patch standards.
• Atomic Counters: Supports thread-safe increment and decrement operations.
• Real-Time Monitoring: Provides statistics for performance tracking.
• Efficient Memory Management: Dual RB-tree structure to manage free space and prevent disk fragmentation.

Durability and ACID Properties: FeOxDB guarantees atomicity, consistency, and isolation, but with relaxed durability. It uses write-behind buffering, which can result in a potential data loss window of up to 420 milliseconds, depending on system performance.

Basic Usage: Developers can easily install and use FeOxDB for operations like inserting, retrieving, checking, and deleting key-value pairs. There are examples for both in-memory and persistent storage setups.

Concurrency: The database supports concurrent access with multiple threads, allowing efficient parallel data operations.

Advanced Features: FeOxDB includes functionalities for range queries and JSON patch operations, allowing flexible data manipulation.

Performance Metrics: Benchmarks show FeOxDB achieving high throughput rates, capable of handling millions of operations per second under various conditions.

Architecture: It uses a multi-tier architecture emphasizing lock-free operations and asynchronous write-behind logging to maximize throughput and minimize latency.

Documentation and Contribution: Full API documentation is available, and contributions to the project are encouraged.

FeOxDB is licensed under the Apache License 2.0, allowing for broad use and modification.

No summary available.

The text discusses a new type of neural network called Kolmogorov-Arnold Networks (KANs) and their differences from Multi-Layer Perceptrons (MLPs). Here are the key points:

1. Comparison of KANs and MLPs: While KANs and MLPs share the same expressive power, they are not the same because they exhibit different emergent properties, such as optimization and interpretability.

2. Philosophical Differences:

   • KANs align more with reductionism, focusing on complex activation functions within a simple structure.
   • MLPs align more with holism, where simple units combine in complex ways to produce emergent behavior.

3. Alignment with Science: KANs are seen as more aligned with scientific thinking, which often relies on reductionism. KANs can more easily represent scientific formulas, such as Hooke’s law, than MLPs.

4. Inductive Bias: A model's effectiveness depends on how well its inductive bias matches the task at hand. KANs excel in scientific contexts, while MLPs perform better in tasks like image and language processing.

5. Conclusion: Understanding the strengths and limitations of KANs and MLPs may require both philosophical reasoning and empirical experimentation.

Splice CAD started as a tool for creating cable harnesses but has now expanded to include features for wiring and electrical assemblies. Key updates include:

• Editing Enhancements: Users can now undo/redo changes, select and group components, quickly connect wires, and make multiple connections per pin.

• Documentation Additions: Users can create multi-page PDFs for engineering drawings and export diagrams in WireViz format.

• Library and Component Additions: The library now includes various components like connectors and switches. There’s also a feature that auto-fills specifications from part numbers.

You can try Splice CAD without signing up here, and find tutorials and documentation here.

Summary: Why D3 Code is Long and Complicated

D3 is a library used for creating data visualizations, and it can be quite lengthy and complex to use. The author is currently learning D3.js and finds that drawing simple charts, like a box plot, requires a lot of code—194 lines for just one plot.

The long code is mainly due to the flexibility D3 offers. While it might seem tedious to write so much code, it allows for detailed customization and control over visual elements. D3 enables users to bind data to SVG shapes, making it powerful for creating unique visualizations.

Although tools like Datawrapper exist for easier chart-making, they don't offer the same level of creative freedom as D3. The author appreciates this flexibility and believes that the verbosity of D3 is worth it for the artistic expression it allows.

Ben and Connor, the founders of Skope, have created a billing system that charges customers based on the actual performance of software, meaning clients only pay when the software works. This model is designed for AI products, which are becoming more common, and serves as an alternative to existing billing systems like Stripe.

Previously, they built AI agents for nonprofits but found it challenging to sell software that required a high upfront cost without proving its value first. They believe customers should pay based on successful outcomes, which would align incentives and reduce risk for buyers.

Skope allows users to track customer usage and set flexible pricing rules, automatically generating invoices based on logged events. They are also working on integrations to simplify data collection for billing. For outcome-based pricing, Skope will verify results and provide a transparent platform for customers to dispute charges if necessary.

Overall, they aim to improve the software industry by promoting a pay-per-performance model, similar to how Google Ads transformed online advertising. Skope is currently offered at a flat subscription price since a billing product needs to function reliably. They welcome feedback and ideas on their approach and the future of billing in the AI space.

No summary available.

A co-worker found an unusual pattern of "d4d4" instructions in disassembled ARM code, which were always unreachable. The d4d4 instruction is a relative branch to a specific address, but it seemed odd to have them after functions that simply returned.

In experiments, it was shown that when a single function was created, the d4d4 instruction appeared. However, when a second function was added, the d4d4 was removed, indicating that the compiler does not require 32-bit alignment for functions. Adding a third function brought back the d4d4 instruction, suggesting it was added by the linker to align object files.

The investigation revealed that the LLVM linker (LLD) inserts these d4d4 instructions to ensure proper alignment across object files. Unlike LLD, the GNU linker uses zeroes for alignment, which avoids the confusion caused by the d4d4 instruction being interpreted as a branch rather than a trap.

The conclusion is that LLD's insertion of the d4d4 instructions is misleading, as they act like a conditional jump instead of a halt instruction. This seems to be a bug worth reporting, as the intended behavior of a trap instruction is to stop execution, not redirect it.

No summary available.

No summary available.

The website is checking your browser for security reasons. If you own the website, there is an option to resolve any issues.

No summary available.

Summary of "Using Common Lisp from inside the Browser"

This article discusses the Web Embeddable Common Lisp (WECL) project, which integrates Common Lisp with web browsers. The author, Daniel Kochmański, explains the project's current status, technical details, and future plans.

Key Points:

1. Scripting with Common Lisp:

   • Developers can use Common Lisp in web pages by including WECL and using <script> tags with type="text/common-lisp".
   • Example code demonstrates how to create a simple web page that executes Common Lisp.

2. JS-FFI (JavaScript Foreign Function Interface):

   • Provides low-level access for Common Lisp to interact with JavaScript.
   • Offers various operators to define JavaScript variables, functions, methods, and callbacks from Common Lisp.

3. Interacting from Emacs:

   • An adapter for SLIME/SWANK allows users to interact with WECL from Emacs via WebSocket.
   • Users can compile forms and interact with the REPL, although file compilation has limitations.

4. Injecting Common Lisp Runtime:

   • Users can inject the Common Lisp runtime into any website, enabling them to execute Common Lisp commands and manipulate web page elements.

5. Current Challenges:

   • The project faces issues with threading and performance, as well as limitations on asynchronous operations.
   • Future improvements include better handling of multiple threads and optimizing performance.

6. Funding:

   • The project is funded by the NGI0 Commons Fund, supported by the European Commission.

Overall, WECL aims to bridge Common Lisp and web development, providing a unique environment for developers while still being in an experimental phase.

The author has created a proof-of-concept for AI memory using Git instead of traditional vector databases. The idea is that Git already manages versioned documents effectively, so there's no need for complex vector stores.

How it works:

• Memories are saved as markdown files in a Git repository.
• Each conversation is recorded as a commit.
• The command git diff shows how understanding changes over time.
• A search method called BM25 is used, eliminating the need for embeddings.
• Large Language Models (LLMs) generate search queries based on conversation context, allowing users to see actual changes rather than just similarity scores.

The proof-of-concept is not yet ready for production but works well for personal use, fitting a year's worth of conversations into about 100MB of RAM with fast retrieval times. Users can revert to any point in time to see what the AI knew, offering clear storage and the ability to edit memories.

The project is open-source and built using Python and GitPython, among other tools. The author is seeking feedback on this approach and is curious if it’s a smart idea or if there are potential pitfalls.

George and Alex are introducing Channel3, a searchable database of every product online, which includes features for affiliate monetization. They faced challenges in finding reliable product data while developing an AI teacher, leading to the creation of Channel3.

Channel3 uses computer vision to gather product details, normalizing inconsistent information from various retailers into a standard format. Users can search for products with specific criteria and receive structured data in JSON format that includes titles, images, prices, and specifications.

Developers can earn a commission on sales made through Channel3, with a goal of ensuring they profit more than they spend on the service. The platform offers an API, SDK in Typescript and Python, and allows for 1,000 free searches, charging $7 for each additional 1,000 searches. Currently, the service is available only in the U.S. with millions of products listed.

They encourage feedback from the community on improving their service and are available to answer questions. Interested users can get started by creating a free account at their website.

Summary:

Strictly Necessary Cookies are essential for the website to work properly. They help with security, prevent fraud, and allow you to make purchases. You can block these cookies in your browser, but this may cause some features of the site to not work correctly.

No summary available.

The article discusses the actions of notable science communicators Eric Weinstein, Sabine Hossenfelder, Brian Keating, and Curt Jaimungal, who have been accused of undermining scientific integrity while promoting their own views. The author, Timothy Nguyen, recounts personal experiences where these individuals attempted to suppress criticism of Weinstein's theory, Geometric Unity, which lacks scientific credibility.

Nguyen highlights a pattern of hypocrisy, where these communicators advocate for free inquiry while simultaneously attacking critics and engaging in intimidation. He notes that Weinstein claims to challenge the scientific establishment but uses his influence to silence dissent. The article critiques Hossenfelder and Keating for prioritizing loyalty over honest scientific discourse, suggesting that their reputations are compromised by supporting Weinstein.

Overall, Nguyen argues that this behavior is detrimental to the public's understanding of science, as it blends legitimate research with misleading claims. He emphasizes the importance of maintaining scientific integrity in communication and warns against the dangers of audience capture in the realm of popular science.

No summary available.

The author has created a project combining the xv6 teaching operating system with a custom-built TCP/IP networking stack. This networking stack, called microps, was originally designed to run in user space for learning purposes. The project integrates this stack into the xv6-riscv kernel and includes key features such as:

• A new TCP/IP stack built from scratch.
• Integration with the xv6 kernel.
• Implementation of standard socket system calls for network application development.
• Basic user-level tools like ifconfig and servers for TCP and UDP echo.

The author aims to better understand operating systems and networking by building these components and welcomes feedback and questions.

Guy and I created ChartDB, a tool that generates ER (Entity-Relationship) diagrams from databases without needing direct access. Initially, we launched an open-source version, and due to its popularity, we are now introducing a cloud version designed for teams.

Key features of ChartDB Cloud include:

• Easy embedding of ER diagrams into documents and platforms like Miro and Notion.
• Real-time collaboration with live cursors, similar to Figma.
• Automatic synchronization with your database.
• Simplified organization of complex schemas.
• Exporting of DDL in various SQL formats.
• An AI assistant to help brainstorm and create schema changes.

Our goal is to make database work feel more creative and enjoyable. We welcome feedback, especially from teams handling complex schemas or outdated documentation. You can check it out at ChartDB.

Summary:

The author discusses the Anubis project, which uses a unique method to protect websites from AI crawlers by requiring visitors to solve computational challenges that are easy for computers but hard for humans. Anubis blocks access to sites like git.kernel.org and lore.kernel.org, which frustrates users with limited resources.

Traditionally, websites use CAPTCHAs to block unwanted crawlers by making tasks easy for humans. Anubis reverses this by demanding visitors perform SHA-256 calculations to prove they are not bots, similar to Bitcoin mining. The author argues this approach disproportionately affects users with fewer computing resources, while AI vendors with vast data center capabilities can easily bypass these challenges.

The author calculates that crawling all websites using Anubis would cost almost nothing for AI vendors due to the low computational cost involved, suggesting that the system may not effectively deter crawlers. They also mention a historical anti-spam method that involved licensing poetry, drawing a parallel to Anubis's aim of blocking unwanted traffic.

Finally, the author shares a workaround to bypass Anubis's restrictions without using a desktop browser. They express skepticism about the effectiveness of Anubis in genuinely preventing bot access, noting that the process can be easily automated. The author concludes with a critical view of the project, emphasizing that it complicates access to web resources without adequately proving user authenticity.

The article discusses the creation of a Space Invader Generator as part of a coding challenge, highlighting its interactive features and the development process.

Key Points:

1. Project Origin: The author created the generator while working on a 3D renderer called Rayven. To avoid getting stuck on tools, they decided to create something fun and recognizable, like Space Invaders.

2. Code Challenge: The generator idea was well-received, leading to a code challenge where others could submit their own versions. The author plans to share submissions once the challenge ends.

3. Design Process: The author began by sketching invaders and using digital tools to create pixel art. They discovered a way to generate invaders using geometric patterns, leading to the development of a vector-based design.

4. Building Invaders: The process involved defining a central point, generating symmetrical body shapes, and adding limbs (tentacles and horns). The author used randomness with some constraints to create diversity in the designs.

5. Pixelization: To convert vector shapes into pixel art, a simple method was used to paint pixels based on their position relative to the vector body. Additional techniques were employed to ensure detailed limbs.

6. Adding Features: Eyes were added to the invaders using predefined sets, and colors were generated using a specific color space for consistent vibrancy.

7. Animation: The final step involved animating the invaders to mimic the movement of the original game. This included shifting limb positions and adding minor movements to the eyes for realism.

8. Conclusion: The author expresses satisfaction with the generator and the learning experience it provided, encouraging readers to create their own invaders.

Overall, the article showcases the fun and creative process behind developing an interactive Space Invader Generator, emphasizing the importance of experimentation and completion in coding projects.

The text discusses a problem encountered when trying to find a specific contribution made by a user named Sophie in the Unison cloud project, following an error report. The author explains how to use SQL queries to retrieve the necessary information, but notes that writing complex joins can be tedious.

To simplify the process, the author suggests creating a "debugging view" that consolidates the necessary joins into one reusable query. This way, future queries can be more straightforward and user-friendly. The debugging view allows the user to easily access all relevant information without repeatedly writing complex SQL.

The author encourages readers to create similar views for their own needs, explaining that they take up no additional space in the database and can be easily updated. While the performance of queries using computed columns may not be optimal, the author believes the ease of use outweighs this concern for one-off queries.

The text concludes with a promotion for the author's book on functional programming, inviting readers to learn more.

Summary of Awesome Electrical Grid Mapping

This text provides a comprehensive list of resources for electrical grid mapping to enhance global open data, improve quality, and support the transition to sustainable energy. It encourages participation in transmission grid mapping using OpenStreetMap and emphasizes the importance of manually verifying data points against official satellite data rather than copying directly from the provided maps.

Key resources are organized by region, including:

• Global Resources: Various databases and tools for accessing grid data, including global energy monitors and datasets.

• Africa: Specific datasets and maps for countries like Nigeria, Ghana, and South Africa, focusing on their electricity transmission networks.

• Asia: Resources for countries like India, Pakistan, and Japan, including national electricity plans and grid maps.

• Australia and New Zealand: Information on electricity transmission lines and network capacities.

• Europe: Detailed maps and data for multiple countries, including ENTSO-E grid maps and national transmission systems.

• North America: Comprehensive resources for the U.S. and Canadian electricity transmission systems.

• Central and South America: Maps and datasets for countries like Mexico, Brazil, and Colombia.

The text also lists scientific publications, policies, reports, community initiatives, mapping tools, and educational resources related to electrical grid mapping. It highlights the importance of collaboration and crowdsourced mapping efforts to improve the quality and accessibility of energy data globally.

Gouach, a small French company, has developed the Infinite Battery for e-bikes, which allows users to easily replace individual battery cells using just a screwdriver. This design aims to prevent a few malfunctioning cells from ruining the entire battery. Most e-bike batteries are made of multiple 18650 cells that are difficult to repair, but Gouach's innovative solution includes a durable, fireproof casing and a Bluetooth app for monitoring battery performance.

The CEO, Alexandre Vallette, mentioned that creating a no-weld battery system took four years of experimentation. Their custom circuit boards ensure reliable connections, even during bike rides. Gouach's battery casing is waterproof and meets safety standards.

The Infinite Battery will come in 36 V and 48 V options, and the company plans to collaborate with e-bike manufacturers, target e-bike owners, and cater to DIY enthusiasts. They have raised over $220,000 through crowdfunding and expect to start mass production soon, with plans to deliver to European backers by June and launch in the US afterward. Overall, Gouach is promoting a new approach to e-bike batteries that emphasizes repairability and user-friendliness.

I wanted to find out how to arrange objects on a spherical helix path, so I read some articles. This led me to revisit parametric equations, and I created a visualization to share what I learned. You can check it out at the link provided: visualrambling.space/moving-objects-in-3d. I'd love to hear your feedback!

Joe and his friends, Matthew and Jake, are developing Luminal, a GPU compiler designed to create fast GPU code for AI models. Unlike traditional methods, Luminal doesn't use AI or large language models; instead, it frames the task as a search problem. It takes high-level model code, generates many possible GPU kernels, and searches for the fastest one.

You can test Luminal with a demo that shows how it optimizes a simple operation into a highly efficient GPU kernel. Their unique approach involves compiling everything ahead of time and exploring a wide range of possible kernels to find the best performance, allowing for complex optimizations without manual tuning.

They are also working on adding support for CUDA, increasing the flexibility of their search, and supporting more hardware types. Their goal is to simplify the machine learning ecosystem while enhancing performance. You can check out their GitHub repository and share your feedback.

Summary of "The Core of Rust"

This text discusses the complexities of learning Rust, a programming language that integrates many concepts tightly. Here are the key points:

1. Learning Challenges: Rust is difficult to learn because many concepts are intertwined. Beginners must grasp multiple ideas, like functions, enums, pattern matching, and the borrow checker, all at once. This complexity makes it hard to understand programs without knowing all the basics.

2. Language Vision: The author appreciates programming languages with a clear vision. For example, Rust has a coherent set of features that work well together, unlike some languages that may lack such clarity.

3. Concepts Interwoven: The text explains that Rust's features are designed to interact smoothly. For instance, enums rely on pattern matching, and generics are crucial for implementing results and iterators. This interconnection is intentional and enhances the language's functionality.

4. Comparison with JavaScript: The author contrasts Rust with JavaScript, noting that while Rust requires a deep understanding of many concepts to perform non-trivial tasks, JavaScript allows some tasks to be done with minimal understanding.

5. Desire for a Simpler Rust: There's a nostalgic reference to a "smaller Rust," highlighting a longing for a version of the language that was less complex.

Overall, the text emphasizes the beauty and depth of Rust, even as it acknowledges the steep learning curve associated with mastering its many interrelated concepts.

The article discusses the downsides of open office designs, which have become common in workplaces. Originally intended to encourage communication and collaboration, research shows that open offices can actually harm employee satisfaction, productivity, and health. Studies indicate that workers in open offices experience more distractions, stress, and difficulty concentrating compared to those in traditional offices.

Key findings include:

• Employees in open offices feel more distant from coworkers and less satisfied with their work environment.
• The lack of privacy and control over one's workspace negatively impacts job performance and well-being.
• Noise in open offices can reduce cognitive performance and increase stress levels.
• Younger workers, while valuing social interactions in open spaces, also struggle with distractions and multitasking challenges.

Overall, open offices may create a cycle of underperformance, especially for younger employees who may not realize the long-term effects.

A customer, Benjamin Jankowski, has filed a lawsuit against Home Depot, claiming the company secretly uses facial recognition technology at self-checkout kiosks without informing customers. Jankowski noticed a camera and a green box around his face while checking out at a Chicago store, suggesting his facial data was being recorded. He alleges that Home Depot’s use of this technology violates Illinois law, which requires companies to inform people about the collection of biometric data and obtain consent. Jankowski seeks to represent other affected customers and is asking for monetary damages for each violation. This lawsuit follows a similar case involving Rite Aid, which was banned from using facial recognition due to its harmful practices.

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No summary available.

The CSS attr() function has been updated to support types, allowing you to specify how to treat the value of an HTML attribute. Previously, it only accepted the attribute name and returned a string, limiting its use to properties that accept string values like content.

With the new syntax, you can use attr() with types, enabling it for various CSS properties. The format is attr(<attribute-name> type(<specific-type>)). For example, to set an element's width based on a data-width attribute, you can write:

div {
  width: attr(data-width type(<length>));
}

This allows for more dynamic styling, such as customizing both width and background color of elements based on their attributes. For instance, using data-color for background colors can be done similarly.

Currently, this feature is supported only in the latest Chromium-based browsers (Chrome 133 and newer), but it's expected to become available in other browsers soon. This enhancement makes CSS more reusable and maintainable, allowing developers to create UIs with minimal code.

No summary available.

The author expresses frustration about the current state of engineering, particularly the reliance on AI tools that seem to hinder rather than help junior engineers. They observe that many engineers are burning out and that organizations expect senior staff to support poorly functioning features created using AI.

Junior engineers often use AI to generate code without fully understanding the work, leading to ineffective collaboration and low-quality output. The author feels disheartened by this trend, questioning the value of AI tools when personal insights and knowledge seem more reliable.

They discuss the questionable financial viability of AI companies, suggesting that the technology is flawed and unsustainable. Ultimately, the author believes that the current reliance on AI is more of a scam than a solution, highlighting the need for genuine human expertise and mentorship in engineering.

No summary available.

Summary of Linux Networking for Embedded Networks

When setting up embedded networks, such as portable video racks, it’s important to avoid using random subnets to prevent IP address conflicts with external networks. Instead, using Virtual Routing and Forwarding (VRF) is recommended.

Key Points:

1. Embedded Networks: These are networks contained within devices like portable racks, which need to connect to external networks for functions like streaming.

2. Subnet Conflicts: Using common subnets like 10.0.0.0/24 can lead to conflicts if the venue’s network uses the same subnet. Picking unusual subnets is a temporary fix and can still result in conflicts.

3. IPv6 Solution: Ideally, using IPv6 allows devices to identify each other through link-local addresses without needing DHCP. However, many embedded devices don’t support IPv6.

4. APIPA in IPv4: Similar to IPv6, if a device fails to receive an IP via DHCP, it may self-assign an address (APIPA), but it lacks gateway support for internet access.

5. Using VRFs: By configuring a router with VRFs, you can maintain the same subnet for both internal and external networks without conflicts. Each interface can have its own routing table, thus isolating traffic.

6. Router Configuration: The setup involves creating separate routing tables for the internal and external networks, allowing devices in the rack to communicate internally and still access the internet without interference from the venue's network.

By using VRFs, you can create a stable and conflict-free network environment for portable equipment, facilitating easier management and connectivity.

The text discusses a method called the "Wafflehouse Method," created by Yacine Mahdid, designed to help individuals feel less lost in the tech field, especially those studying computer science. Here are the key points:

1. Common Issues: Many students feel overwhelmed and lost about their future in tech, unsure about what to pursue or fearful about job security due to AI advancements.

2. Self-Reflection: Yacine encourages taking two days off for personal introspection to clarify life goals.

3. Day 1 - Visioning: Spend the first day alone in a meaningful place, visualizing where you want to be in five years. Write down your feelings, hopes, and fears to create a vivid image of your aspirations.

4. Day 2 - Goal Setting:

   • Start at a café (like Wafflehouse) and refine your five-year vision into specific, detailed goals.
   • Work backward to set three-year and one-year goals, adjusting as necessary.
   • Create a detailed plan with numerous actionable steps (like a directed acyclic graph) to reach those goals.

5. Implementation: Break down your goals into monthly, weekly, and daily tasks, focusing on what truly brings you closer to your aspirations. It’s crucial to take action immediately.

6. Ownership: This method emphasizes personal responsibility; no one else is to blame for your progress or setbacks.

7. Continuous Review: Regularly assess your plan and make adjustments as needed to stay aligned with your goals.

The method aims to empower individuals to take control of their careers and personal growth in tech.

Mark recently added a feature to his uptime dashboard on status.href.cat to monitor his home electricity and internet status. This was prompted by a recent power outage that affected his building. After discovering that his IoT devices were not helpful in checking the outage, he realized his Eero router has an app that could confirm its status.

He quickly built a workflow to check his power availability every five minutes, which now displays historical data and uptime percentages for both his power and internet connections. Mark emphasizes the ease of building personal software with modern low-code/no-code tools, allowing him to solve everyday problems efficiently. He shares his pride in creating software that notifies friends about dog adoptions, showcasing the joy that simple tech solutions can bring.

Summary of Fermat’s Last Theorem Project

This project is an open-source effort to create a formal proof of Fermat’s Last Theorem using the Lean theorem prover.

Key Details:

• The project is led by Kevin Buzzard and is supported by a grant from the UK’s Engineering and Physical Sciences Research Council.
• It takes place at Imperial College London, with gratitude expressed for the support from both the college and the funding body.
• Additional general information about Fermat’s Last Theorem and the Lean prover can be found on the project’s main page.

Summary of Unification in Logic and Computer Science

Unification is the process of automatically solving equations between symbolic terms, commonly used in logic programming and type inference. It involves working with terms made from constants (lowercase letters), variables (uppercase letters), and function applications (like f(...)).

Key Concepts:

• Pattern Matching: This is the simpler case where one term is a constant and the other has variables. The goal is to find a variable assignment (substitution) that makes the two terms match.
• Unification: This expands on pattern matching by allowing both terms to contain variables. The aim is to find a substitution that makes the two terms equivalent. For instance, for the terms f(a, V) and f(D, k), the substitution would be {D=a, V=k}.

Most General Unifier (MGU):

• There can be many substitutions for some problems, but the most general one (MGU) is the simplest form that can be adapted to create other substitutions.

Unification Algorithm:

• The algorithm looks for a substitution mapping variable names to terms. It handles various cases, such as when both terms are variables or function applications, and checks for conflicts like self-referential variable bindings.

Code Implementation:

• A Python implementation of the unification algorithm is provided, defining data structures for terms and functions to perform unification.

Efficiency:

• The presented algorithm is not the most efficient for large problems and may benefit from optimizations, such as caching previously unified terms. For deeper insights into efficient unification algorithms, two recommended papers are noted.

Overall, unification is a crucial concept in computer science, especially in logic programming, providing a foundational method for solving equations involving symbolic terms.

The article discusses the author's dissatisfaction with GitHub's code review process and the limitations of existing tools, which led to the creation of a tool called git-review. Key issues with GitHub include poor support for stacked pull requests and the fact that review states are not stored in the repository, leading to slow feedback due to reliance on a web interface.

The author prefers reviewing code locally, allowing for better context and testing. The git-review tool aimed to simplify the process by treating code reviews as a single commit with inline comments, allowing both authors and reviewers to modify it. However, this approach faced challenges, such as managing conflicts when changes are made after comments and the added complexity of using force pushes.

The author acknowledges that while the idea was promising, it did not achieve the desired success due to these details. They are returning to web-based reviews for now but express hope that future developments in Git, like a Change-Id feature, could improve the situation. The article concludes with recommendations for alternative tools and systems that store review information more effectively.

In a riddle set in a wine cellar, you must determine the year of wine from 16 unlabeled bottles, each from different years ranging from 0 to 15. You have four measuring devices that can output either 0 or 1, and your goal is to identify each wine's year using no more than 50 measurements.

1. Initial Setup: Each device provides a bit of information about the wine's year, which can be interpreted in binary. For example, if your devices give the output 0110, that corresponds to the year 6.

2. Measuring Strategy: To solve the riddle efficiently, you need to leverage the fact that each wine year is unique. This allows you to determine the year of one bottle based on the results of measuring another bottle.

3. Case Examples:

   • Two Bottles: You only need one measurement to identify both bottles since knowing one year reveals the other.
   • Four Bottles: Use two measurements to identify pairs of bottles after measuring all four with one device.
   • Eight Bottles: Measure seven bottles with one device, then use a second device for the remaining bottles, totaling 17 measurements.

4. Final Strategy for Sixteen Bottles: By first measuring 15 bottles with one device, you can split them into two groups based on the results. Then, apply the previous strategies to identify all bottles, achieving this in 49 measurements—just under the 50-measurement limit.

5. Optimality and Further Thoughts: While the divide-and-conquer strategy is effective, there may be even better approaches that utilize information gain more efficiently. The optimal solution for this puzzle remains an open question for further exploration.

Overall, the puzzle emphasizes using logical deduction and strategic grouping to minimize measurements while solving for unique identifiers in a complex scenario.

Summary of the Introduction to AT Protocol

The AT Protocol is the underlying framework for the Bluesky social network, aiming to provide a decentralized and transparent architecture. This guide serves as an introduction for developers interested in understanding the network's components.

1. Definitions:

   • Bluesky can refer to the organization (Bluesky PBC) or the actual social network built on AT Protocol (ATProto).
   • The ecosystem includes various apps and services beyond Bluesky, like blogging platforms and photo-sharing sites, all utilizing ATProto.

2. Core Components:

   • Records: Basic data units (like posts and profiles) stored as JSON objects. Users can only modify their own records.
   • Blobs: Binary files for media (images/videos) separate from records.
   • Lexicons: Define the structure of records, dictating what data they can hold and how they interact.
   • Identity: Users are identified by a Decentralized Identifier (DID), ensuring permanence and independence across platforms.
   • Handles: Users can have multiple handles linked to their DID, allowing flexibility in identity.

3. Data and Storage:

   • User data is stored in a Personal Data Server (PDS) associated with their DID, which can be moved to different servers.
   • Relays combine data streams from multiple PDSs, enabling a broader view of network activities.
   • The AppView processes and serves data to client apps, optimizing access to user-generated content.

4. Interaction Flow:

   • Users create records via client apps linked to their PDS, which then communicates with relays and the AppView to share updates and retrieve content.

5. Development and Community:

   • Developers can build on ATProto using various SDKs, with resources available on official sites and community discussions.
   • The ecosystem encourages custom feeds, moderation tools (labellers), and third-party apps, fostering innovation within the network.

6. Future Directions:

   • The protocol is still evolving, with ongoing improvements in user interaction, data management, and security features like end-to-end encrypted DMs planned for future implementation.

This summary provides an overview of the AT Protocol's structure, purpose, and opportunities for developers interested in building decentralized applications within the Bluesky network.

Summary of Pytype Update:

• Key Point: Pytype will support up to Python version 3.12 and will not continue beyond that.
• Focus Shift: The team is moving towards exploring new ideas and different frameworks for Python type checking.
• Background: Pytype started in 2012 to help Google developers with compile-time checking, transitioning from type inference to inline annotations after PEP 484 was accepted.
• Collaboration: The team worked with Guido and mypy to create typeshed, a repository for type annotations.
• Challenges: Pytype’s design has made it hard to implement new features due to issues with bytecode stability.
• Future Guidance: The team encourages users to explore other mature solutions in the Python typing ecosystem, which is now robust and diverse.
• Acknowledgments: Thanks were given to all contributors, especially Rebecca Chen, who has been a key figure in pytype and the Python typing community.

Sütterlin is a historical form of German handwriting that was widely used from 1915 until the 1970s. It was developed by graphic artist Ludwig Sütterlin, who was commissioned in 1911 to create a modern handwriting style for schools and offices. Sütterlin replaced older cursive scripts and became the only script taught in German schools by 1935.

The script features unique letters and ligatures, including the long 's' (ſ) and distinct forms for certain letters. However, in 1941, the Nazi regime banned Sütterlin, replacing it with Italian-style lettering. Despite this ban, many people continued to use Sütterlin for years afterward.

Sütterlin is based on older German handwriting styles, particularly Blackletter scripts like Fraktur. It was taught in schools until the 1970s, though not as the primary script. Today, the name "Sütterlin" is often used to refer to various forms of old German handwriting, although Sütterlin itself was specifically a formalized script taught in schools.

The author argues that programming languages fundamentally fail to support good design because they confuse the concepts of data and objects.

Key Points:

1. Distinction Between Data and Objects:

   • Data represents values that are identical (like the number 1), while objects have identity (two instances of the number 1 can exist separately).
   • Languages often mix these concepts, leading to poor design choices.

2. Language Design Choices:

   • Languages make choices about how to handle equality, identity, mutability, abstraction, and extensibility.
   • The author suggests there are mainly two approaches: treating everything as data or everything as objects.

3. Current Language Limitations:

   • Many languages, like Java and C, struggle with proper data representation and often force programmers to use workarounds for data-like structures.

4. Functional vs. Object-Oriented Languages:

   • Functional languages, such as Haskell, are better at representing data but often lack robust support for objects.
   • In contrast, object-oriented languages can become overly complex and may not effectively support data representation.

5. Best Practices in Design:

   • A better design would clearly distinguish between data and objects and help programmers consciously choose how to represent what they are working with.
   • The author believes that recognizing this distinction can lead to improved programming practices and better language support in the future.

In conclusion, the author emphasizes the need for programming languages to support clear distinctions between data and objects, which would lead to better design outcomes.

No summary available.

Summary of Universal Tool Calling Protocol (UTCP) 1.0.1

Overview: The Universal Tool Calling Protocol (UTCP) is a flexible standard for managing tools across various communication methods. Version 1.0.0 introduces a modular design with plugins, enhancing its scalability, extensibility, interoperability, and user-friendliness.

Key Features:

• Scalability: Handles many tools efficiently.
• Extensibility: Developers can easily add new protocols and features.
• Interoperability: Works with existing services through various protocol plugins (e.g., HTTP, CLI).
• Ease of Use: Built on simple data models for easy implementation.

Architecture Changes: The protocol now has a core library (utcp) and optional plugins:

• Core Components: Includes data models and interfaces for communication, storage, searching, and processing tools.
• Plugins: Allow separate installation of communication protocols, keeping the core lightweight.

Installation: To install UTCP, use:

pip install utcp utcp-http
pip install utcp-cli

Migration from Version 0.x:

• Update your dependencies to the new core package and plugins.
• Adjust configuration and terminology (e.g., "provider" is now "call_template").
• Update your imports and tool naming conventions.

Usage Examples:

1. Creating a Client: You can initialize a UTCP client using a JSON config file or a dictionary.
2. Defining Tools: Tools are described using the new UTCPManual structure, which includes call templates.

Testing and Building:

• Run tests with pytest for the core library and plugins.
• Build packages separately for distribution.

This summary highlights key elements of UTCP 1.0.1, focusing on its architecture, installation, migration, and usage examples for easy understanding.

Google is enhancing its AI Mode in Search by adding new features that allow it to assist users more effectively and expanding its availability globally. Key improvements include:

1. Agentic Capabilities: The AI can now help with tasks such as booking restaurant reservations. Users can specify details like party size and cuisine, and the AI will find available options across various platforms.

2. Personalized Responses: Users in the U.S. can receive tailored suggestions based on their previous searches and preferences, such as restaurant recommendations that match their tastes.

3. Collaboration Features: A new link-sharing capability allows users to share AI Mode responses with friends and family, enabling collaborative planning for events like trips or parties.

4. Global Expansion: AI Mode is being rolled out to over 180 new countries and territories, allowing more people to use it for complex queries.

Overall, these updates aim to make Google Search more helpful and user-friendly.

Databricks, a data and AI company, is raising funds in a Series K investment round that values the company at over $100 billion. This funding will help accelerate their AI strategy, specifically expanding their new products, Agent Bricks and Lakebase, and support global growth. Agent Bricks creates AI agents tailored to company data, while Lakebase is an operational database designed for AI applications.

The CEO, Ali Ghodsi, highlighted the strong interest from investors due to the growing demand for their AI products, which help businesses use data effectively for better decision-making and increased revenue. Databricks has partnerships with major companies like Microsoft and Google Cloud and serves over 15,000 customers, including many Fortune 500 companies.

Founded by the creators of influential open-source technologies, Databricks aims to make data accessible and useful for AI, driving innovation and efficiency.

A recent report by Fastly reveals that AI crawlers and fetchers are significantly straining websites, with these bots accounting for 80% of all AI-related traffic. Meta and OpenAI are the biggest contributors, with Meta alone responsible for over half of all AI crawler traffic. These bots can overwhelm web servers, leading to performance issues and higher operational costs for website owners.

AI crawlers collect data for training purposes, while fetchers make on-demand requests for real-time information, with OpenAI dominating this category at nearly 98%. The report highlights that unchecked bot traffic can harm content creators and disrupt the digital ecosystem.

To combat excessive bot traffic, webmasters are implementing various solutions like configuring robots.txt files and using tools like Anubis to manage bot interactions. The report suggests that regulation may be necessary to hold AI companies accountable for the impact of their bots on the web. Fastly emphasizes the need for responsible standards in bot management to balance data access with website protection.

No summary available.

PlutoPrint is a tool I created to easily generate high-quality PDFs and images from HTML using Python. I found other tools complicated and unsatisfactory, so I aimed to make something lightweight and efficient. PlutoPrint uses the rendering engine from PlutoBook, which is good for paged media, and has a simple Python API for converting HTML or XML into clear PDFs and PNGs. I’ve used it for invoices, reports, tickets, and charts with Matplotlib. I welcome your feedback and thoughts on how PlutoPrint can be improved and made more useful for you.

Summary of Zedless

Zedless is a privacy-focused and local-first version of the Zed application, currently under development. Contributions are welcome!

Key Changes Planned for Zedless:

• No Cloud Dependency: It will not use any proprietary cloud services, focusing instead on self-hostable options.

• No Spyware: There will be no telemetry or crash reporting features.

• User Control: Users can configure network services to their preference without default providers, and these features will be disabled by default.

• Contributors' Rights: Contributors will retain their copyright, and there will be no risk of sudden project shutdowns ("rugpulls").

Licensing Compliance:

• Proper license information for third-party dependencies is required for the continuous integration (CI) to succeed.
• The tool "cargo-about" will be used to ensure compliance with open-source licenses. If there are issues, contributors should follow specific steps to resolve them regarding their own crates or dependencies.

SimpleIDE Overview

SimpleIDE is a lightweight Integrated Development Environment (IDE) for VB.NET, designed specifically for Linux using .NET 8.0 and GTK# 3. It offers a modern setup for developing VB.NET projects.

Key Features:

1. Code Editor:

   • Multi-file editing with tabs.
   • Syntax highlighting and customizable themes.
   • Smart indentation, automatic bracket matching, and real-time error detection.
   • Code completion and folding for easier navigation.

2. Project Management:

   • Project and object explorers.
   • Support for .vbproj and .sln files.
   • Easy management of project references and dependencies.

3. Build System:

   • Integrated build process using the dotnet CLI.
   • One-click build and run options.
   • Real-time output display for errors and warnings.

4. AI Integration:

   • Claude AI assistant for code generation and suggestions.
   • Ongoing chat history for context-aware help.

5. User Interface:

   • Dark and light themes with a customizable toolbar.
   • Dockable panels for tools and outputs.

6. Developer Tools:

   • Git integration for version control.
   • Find and replace functionality, along with useful navigation shortcuts.

Installation Requirements:

• Linux OS (Ubuntu, Debian, Fedora).
• .NET 8.0 SDK and GTK# dependencies.

Basic Usage:

• Launch SimpleIDE to auto-detect projects.
• Use keyboard shortcuts for file operations, editing, building, and navigation.

Development Guidelines:

• Follows coding conventions like Hungarian Notation and requires XML documentation for public members.
• Encourages contributions and thorough testing of changes.

License: SimpleIDE is free software under the GNU General Public License, allowing redistribution and modification.

Contact: Developed by James Duane Plotts; available on GitHub for issues and contributions.

Summary: SimpleIDE aims to enhance VB.NET development on Linux by providing a user-friendly, feature-rich environment tailored for programmers.

No summary available.

The Burner Phone 101 workshop, hosted by the Brooklyn Public Library in August 2025, aimed to educate participants about burner phones and privacy protection. Here are the key points:

• Workshop Goals: The main goals were to learn about burner phones and have fun. Secret goals included understanding their limitations and connecting them to broader privacy practices. Participants were advised not to share personal information or promote harm.

• Understanding Risks: Participants learned to assess their specific risks by answering three questions: What are you trying to protect? Who are you protecting it from? What happens if it fails? This clarity helps in applying the right privacy practices.

• Smartphone Risks: Smartphones pose privacy risks due to data collection on identity, location, communications, and content. Participants received tips to enhance smartphone privacy, such as using strong PINs, disabling unnecessary features, and using encrypted messaging apps.

• Burner Phones Overview: The workshop covered different types of burner phones, including prepaid phones, SIM rotation, minimal phones, and device disguises. Each offers varying levels of privacy protection but none guarantee complete anonymity.

• Best Practices for Burners: To maximize burner phone effectiveness, participants were advised to pay in cash, avoid sharing personal info when activating service, and minimize data on the device.

• When to Avoid Phones: There are situations where it might be best to not use a phone at all, such as during high-risk situations or when tracking could lead to evidence against you.

• Interactive Learning: The workshop included a Q&A and hands-on setup session where participants practiced setting up prepaid phones and adjusting privacy settings.

Overall, the workshop emphasized that while burner phones can provide some level of protection, sometimes the best option is to not use a phone at all.

No summary available.