The text explains that you are seeing a challenge on a website because it uses a system called Anubis to protect against AI bots that scrape data. Anubis uses a method similar to Proof-of-Work to make it harder for these bots to access the site, especially when they operate at large scales. This method is intended to slow down scrapers while allowing legitimate users to access the site.

To get past the challenge, you need to enable JavaScript in your browser, as some privacy plugins might block it. The goal of Anubis is to find better ways to identify bots without inconveniencing real users.

Summary of iPhone 15 Pro's Depth Maps and Image Processing

Since 2017, iPhones have used depth maps created by LiDAR and other technologies to enhance images. These depth maps are stored in HEIC files, which can contain multiple images and metadata. The HEIC format has been the default for iPhone images since 2017, although JPEG can be used if depth data isn't needed.

Finn Jaeger, a VFX expert, is working on a project called "HEIC Shenanigans" to extract images and metadata from HEIC files and convert them to EXR format, a high-dynamic range image format used in visual effects.

Key Points:

• System Setup: The author uses a powerful computer with an AMD Ryzen 9 CPU, 96 GB of RAM, and runs Ubuntu on Windows.
• Installation: Necessary tools and libraries for image processing are installed, including Python and OpenEXR.
• Image Example: An HEIC image from an iPhone 15 Pro is used to demonstrate the extraction and conversion process.
• Extraction Process: A Python script extracts various components from the HEIC image, resulting in multiple files, including metadata and depth maps.
• Conversion to EXR: The image and its associated depth maps are converted to EXR format using a series of command-line tools from the OpenImageIO project.

The final EXR file combines the base image, HDR gain map, and depth map, enhancing the image's usability in professional settings. The author offers consulting services for related projects.

Summary of "Why I Wrote the BEAM Book"

The author wrote The BEAM Book after a decade of experience maintaining Klarna's core system, realizing that even a brief pause in the BEAM (the Erlang virtual machine) could disrupt millions of transactions. The book aims to help engineers address such issues efficiently.

Project Background:

• The project began in 2012 with a simple DocBook file and evolved over time, facing multiple challenges, including abandoned contracts with publishers and technical difficulties with file management.
• After several setbacks, the author finally moved the project to GitHub in 2017, where community contributions helped improve the content significantly.

Purpose and Content:

The book is designed for those building or managing Erlang or Elixir systems, especially at scale. It covers essential topics, including:

• Process management and scheduling
• Memory management and garbage collection
• Data representation in the BEAM
• Compilation and execution of code
• Debugging tools and performance tuning
• System architecture of the BEAM

Key Lessons Learned:

• Persistence is crucial despite setbacks.
• Setting boundaries and time for focused writing aids progress.
• Public feedback and community involvement are valuable.
• It’s important to define project scope and prioritize essentials.
• A real deadline can spur completion.

Final Notes:

The paperback version of The BEAM Book is now available on Amazon. The author encourages readers to provide feedback and contribute to the project's GitHub repository. For teams interested in deeper learning, hands-on workshops are also offered.

Get smart code suggestions while you type, including multi-line completions that are customized for your specific codebase.

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The IRS has released most of the Direct File software code on GitHub as open-source, making it available to the public. This release is part of their commitment under the SHARE IT Act and aims to increase transparency and build trust with taxpayers. The Direct File team believes that sharing their code will allow for independent evaluation of their work and ensure that every taxpayer can benefit from available tax provisions. The initiative is seen as a step toward making tax filing more accessible and secure. The author, who recently left the IRS, expresses hope that more IRS software will be made available in the future.

AdamCAD is an AI-powered CAD platform that quickly generates 3D designs. Here are the main features:

• Text to CAD: Users can describe their desired 3D model using text prompts.
• Refine & Export: The platform generates a 3D model and provides parameters for further refinement.
• Image to 3D: Users can convert any image into a 3D model in seconds.
• Integration: AdamCAD works with popular CAD software used by professionals.

Examples of what users can create include parts for engines, phone stands, key holders, and more. AdamCAD aims to simplify the design process using natural language.

Summary:

In the late 1980s, a team at Inria developed an important computer vision algorithm called the "Efficient Chain-Linking Algorithm." This innovative code, now preserved by Software Heritage, was designed to efficiently process images by linking pixel edges to create smooth outlines. The project, led by Gérard Giraudon and his colleagues, was a response to the limitations of early computer memory, which required clever coding to minimize data storage while maximizing performance.

The algorithm could only hold three lines of an image in memory at a time, reading and processing the image line by line. This method allowed it to create contour chains with minimal memory use, a significant achievement given the technology of the era. Although modern computer vision techniques have advanced, this algorithm remains relevant for its efficiency, demonstrating the importance of resourcefulness in early computing.

The preservation of this legacy software is part of a broader initiative to archive important codes from Inria, ensuring that the history and innovations of computer vision are shared with future generations.

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Venture capital funding is driving a global increase in worker surveillance technology, especially in countries with minimal regulation. A report by Coworker.org highlights the rise of startups creating tools to monitor and manage workers, often using artificial intelligence. These technologies, which include biometric tracking and productivity monitoring, are prevalent in gig work and increasingly entering traditional workplaces.

The report indicates that many workers feel their autonomy is diminished when managed by algorithms instead of people. In regions like Latin America, where labor laws are less strictly enforced, these tools are often tested before being deployed elsewhere. Workers report feeling constantly monitored, leading to stress and uncertainty about their jobs.

Current uses of these surveillance tools include:

1. Timekeeping Systems: Platforms that track attendance through geolocation and biometrics.
2. Identity Verification: Tools that use biometric checks to confirm worker identity.
3. Performance Monitoring: Software that scores workers based on tracked metrics.
4. Predictive Analytics: Platforms that automate HR functions and analyze employee data.
5. Gig Economy Tracking: Apps that manage workers primarily through their smartphones, often making them feel like they have little control over their work.

Despite the existence of data protection laws in some countries, enforcement is inconsistent, leaving many workers unaware of how their data is being used.

Google Cloud has launched general availability (GA) for GPU support in Cloud Run, enhancing its serverless platform for running AI workloads. Key features include:

• Pay-per-second Billing: Users are charged only for the GPU resources they actually use, down to the second.
• Scale to Zero: Cloud Run automatically reduces GPU instances to zero when not in use, saving costs for unpredictable workloads.
• Fast Startup: Applications can scale from zero to an active GPU instance in under five seconds, enabling quick responses.
• Streaming Support: Users can build interactive applications with support for HTTP and WebSocket streaming.

NVIDIA L4 GPUs are now accessible without needing to request quotas, making it easier to implement GPU acceleration. Cloud Run with GPU support is backed by a Service Level Agreement (SLA) for reliability.

The GPUs are available in five global regions, facilitating low-latency deployments across the US, Europe, and Asia. Users can also take advantage of Cloud Run jobs for batch processing tasks like model fine-tuning and media processing.

Early users report significant cost savings and improved efficiency. Overall, Cloud Run with GPU support aims to simplify AI application deployment and enhance performance for developers.

Interested users can start with $300 in free credits to explore these capabilities.

Summary: How We Reduced the Impact of Zombie Clients

Samantha Frank discusses the issue of "zombie clients"—abandoned or misconfigured servers that repeatedly request digital certificates from Let’s Encrypt, wasting resources. These clients keep asking for certificates even when they can’t successfully validate their requests, often due to outdated domain names or changes in infrastructure.

Let’s Encrypt noticed that many of these requests came from accounts that consistently failed to validate, leading to increased resource use. To address this, they introduced rate limits to manage excessive requests without punishing users. The new approach includes pausing specific account-hostname pairs that repeatedly fail validation, allowing other valid requests to proceed normally.

Since implementing these measures, they paused over 100,000 pairs, resulting in a 30% drop in failed requests without inconveniencing active users. They also added a self-service option for users to unpause their accounts if needed. Feedback from users and developers is encouraged to improve the system further.

Overall, Let’s Encrypt aims to manage resources efficiently while minimizing disruption for valid users, emphasizing the importance of proactive monitoring to avoid forgotten requests.

The right to repair is now a law in Washington, thanks to support from various advocates and organizations. Governor Bob Ferguson signed two bills that allow people in Washington to access tools, parts, and information to fix their own electronics, appliances, and wheelchairs. This law emphasizes that owners should have control over how their items are repaired.

Advocates, including groups focused on consumer rights and environmental issues, worked together for years to pass this law. They highlighted the importance of including wheelchairs in the right-to-repair legislation through personal stories shared at the state capital.

Additionally, U.S. Secretary of Defense Pete Hegseth recently issued a memo encouraging the Army to include right-to-repair provisions in its contracts. He emphasized the importance of allowing the military to maintain its equipment without relying solely on external suppliers.

The right to repair movement is growing, with all 50 states considering similar laws. Washington is now the eighth state to pass such legislation, showing significant progress in empowering individuals to fix their own belongings.

MCP Server Boilerplate Overview

This is a boilerplate template for creating remote Model Context Protocol (MCP) servers using Cloudflare Workers. It includes OAuth authentication and PostgreSQL database integration.

Key Features:

• OAuth 2.1 Provider: Custom user registration and login.
• PostgreSQL Integration: Complete database setup for user management and OAuth tokens.
• Serverless Deployment: Utilizes Cloudflare Workers for global edge distribution.
• MCP Tools Framework: Modular tools for user context.
• Custom Routes Framework: Simple system for adding REST API endpoints.
• User Interface: Responsive and customizable login/registration pages.
• Security: Incorporates JWT tokens, bcrypt hashing, and PKCE support.
• Mobile Compatibility: Works on various devices.
• Developer Friendly: Built with TypeScript and includes features like hot reload and error handling.

Quick Start

1. Setup: Clone the repository and install dependencies. Choose a PostgreSQL hosting option (Neon, Supabase, Railway, or local).
2. Configuration: Edit environment variables for database connections and security keys.
3. Cloudflare Setup: Log in to Cloudflare and initialize the database.
4. Test: Run the development server and check available tools.

Example Tools Included:

• Basic math operations
• User information retrieval
• Personalized greetings
• AI image generation
• User statistics

Customization:

• The OAuth consent screen can be fully customized using HTML, CSS, and JavaScript.

Deployment:

• Set up production secrets and deploy to Cloudflare.
• Optionally configure a custom domain.

Development:

Includes scripts for development, type checking, and deploying. Follow best practices for adding new features and testing.

This boilerplate makes it easy to build robust applications using the MCP protocol with a focus on security and performance.

Swift is a versatile programming language designed for multiple platforms. Here are the key points:

• Performance: Swift is fast and efficient, compiling directly to native code for high performance and predictable memory management.

• Expressiveness: It allows developers to write clear and concise code, supporting various programming styles like object-oriented and functional programming.

• Safety: Swift prioritizes memory safety, reducing bugs and vulnerabilities by ensuring safety checks at compile time.

• Interoperability: It works well with C and C++ code, allowing developers to gradually integrate Swift into existing projects without needing a complete rewrite.

• Adaptability: Swift can be used across a wide range of applications, from embedded systems to cloud services.

• Open Source: Swift is open for contributions, and developers can get involved through its community and GitHub.

Overall, Swift combines speed, safety, and flexibility, making it suitable for various programming needs.

Merlin Bird ID is a free app that helps you identify birds you see or hear. Here are its key features:

1. Sound ID: This feature listens to bird songs and calls around you, offering real-time suggestions for identification. It works offline, so you can use it anywhere.

2. Photo ID: You can take a picture of a bird or choose one from your camera roll. The app will provide possible matches. This feature also works offline.

3. Bird ID Wizard: By answering three simple questions about a bird, you can receive a list of potential matches. This tool is useful for bird watchers of all experience levels.

4. Save My Bird: Each time you identify a bird, you can save it to your digital life list, helping you keep track of your birding experiences.

5. Explore Nearby Birds: The app allows you to create custom lists of birds based on your location and time of year.

Merlin is enhanced by community-contributed content and expert tips, making it a reliable and comprehensive birding resource.

Summary of DiffX - Next-Generation Extensible Diff Format

Diff files are commonly used by software developers to show changes between text files, like added or removed lines. Most developers are familiar with Unified Diffs, but these formats have limitations. They don't standardize important aspects like encodings, metadata, or how file paths are represented, making it hard for tools to interpret them consistently.

Unified Diffs aren't able to represent multiple commits, binary patches, or arbitrary metadata effectively. As a result, the development world needs a more structured diff format.

Introducing DiffX: DiffX is a proposed new format that builds on Unified Diffs. It aims to provide:

• Standard rules for parsing diffs.
• Structured storage for metadata associated with diffs, commits, and files.
• The ability to represent multiple commits in one diff file.
• Compatibility with existing tools and parsers, while allowing future extensions.
• Support for binary diffs and knowledge of text encodings.

DiffX is designed to be backward-compatible and user-friendly, ensuring that existing tools can still work without major changes. It addresses the shortcomings of current diff formats while maintaining flexibility for future needs.

For more information, you can explore the DiffX File Format Specification or check out example DiffX files. Implementations like "pydiffx" are already available, and DiffX is being integrated into tools like Review Board to improve diff handling.

On June 4, 2025, Langfuse announced that it is open sourcing all remaining product features under the MIT license. This decision aims to help the community develop LLM applications more quickly and provide feedback on the platform. Key features now available include evaluations, annotation queues, prompt experiments, and the playground.

Langfuse's goal is to create an open-source LLM Engineering Platform that fosters trust and collaboration within the developer community. By making previously commercial features freely accessible, Langfuse hopes to enhance developer engagement and accelerate adoption of its platform.

Langfuse has always been open source at its core, and this expansion reflects its commitment to flexibility and integration with various models. The commercial aspects will now focus on enterprise-level security and support.

There are over 8,000 active self-hosted Langfuse instances, indicating strong community interest. Users are encouraged to upgrade to the latest version and follow the self-hosting guidelines to maximize the platform's capabilities.

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The text discusses the patterns of technological revolutions, highlighting that each major economic change is driven by a new way of converting value, from agriculture to artificial intelligence (AI). These revolutions consist of a series of innovations rather than a single invention and are characterized by seven key components:

1. Core Conversion: A new capability that transforms one type of value into another.
2. Scaling Infrastructure: Systems that make this conversion efficient and cost-effective.
3. Spatiotemporal Compression: Tools that reduce the costs of distance and time in economic interactions.
4. Key Resources: Essential inputs needed for the core conversion.
5. Economic Mode: The main way value is created and captured during each revolution.
6. Centralization/Decentralization Arc: Initial centralization for efficiency, followed by decentralization as technologies evolve.
7. Administrative Innovations: Standards and tools that support the revolution across different areas.

The text outlines six major revolutions, from agriculture (around 10,000 BCE) to the current fourth industrial revolution (IR4), which focuses on AI. Each revolution builds upon the previous one, creating a foundation for future innovations.

Key takeaways include the importance of understanding core value conversions and the infrastructure needed to support them. The discussion emphasizes that investments should be made in standards and digital infrastructure to ensure equitable access and reduce inequality.

Looking ahead, the text notes that quantum computing is a supportive technology within the current revolution and suggests that future policy should focus on creating open standards, improving digital infrastructure, and addressing inequalities to maximize the benefits of emerging technologies.

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The Connecticut Senate has passed a significant bill to reform the state's towing laws, which have not been updated in over a century. This change comes after an investigation revealed that current laws favor towing companies, often harming drivers.

House Bill 7162 aims to protect consumers by making it harder to tow vehicles from private property and easier for drivers to retrieve their cars after being towed. Key provisions include:

• Tow companies must accept credit cards and cannot tow vehicles immediately for minor violations, like expired permits.
• Towing companies must provide notice before towing vehicles and cannot begin vehicle sales until 30 days after towing.
• The law requires tow companies to document the condition of vehicles before towing and allows drivers to retrieve their belongings from towed cars, even if they haven't paid the fees.

The bill received broad bipartisan support and is expected to be signed into law by Governor Ned Lamont. It aims to create a fairer towing process and address issues highlighted by investigative reporting, which showed that many drivers faced financial hardship due to predatory towing practices.

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Summary of "Consider Knitting"

The article encourages readers, especially those in tech fields, to consider knitting as a fulfilling hobby. The author, a software developer, shares how he discovered knitting after feeling a strong need for tactile experiences during the pandemic. He emphasizes that knitting is a fiber art that involves various techniques and materials, allowing for creative expression and personal satisfaction.

Key points include:

1. Tactile Experience: Knitting engages the sense of touch, providing a satisfying, hands-on experience that contrasts with the screen-focused nature of coding.

2. Skill Development: Knitting has a manageable learning curve, making it accessible for beginners. Once basic skills are learned, there are countless patterns and techniques to explore, offering endless opportunities for growth.

3. Creative Freedom: Unlike linear activities, knitting allows for personal choice in projects and styles. You don’t have to follow a specific path, making it a flexible and enjoyable pursuit.

4. Structured Yet Relaxing: Knitting strikes a balance between structure and freedom, allowing for both focused and mindless projects, depending on your mood.

5. Meaningful Gifts: The author reflects on the emotional value of creating handmade items, which carry personal significance and can deeply touch loved ones.

6. Recommendations: For those interested in trying knitting, the author suggests starting with basic supplies and encourages patience through the initial learning challenges.

Overall, knitting is portrayed as a rewarding, creative outlet that can fit into various lifestyles and provide both joy and a sense of accomplishment.

Click-V Summary

Click-V is a RISC-V emulator built using ClickHouse SQL, making ClickHouse Turing complete. The project is primarily a backup and not yet user-friendly for developers.

How It Works:

• The emulator responds to an INSERT INTO clickv.clock (_) VALUES () command, triggering a series of materialized views and tables that simulate reading and writing from memory and registers.
• It uses a User Defined Function (UDF) for external machine access, reading/writing data in a custom binary format.

Performance:

• The emulator has performance issues due to a bug in ClickHouse's key-value storage logic, relying on Redis for memory/registers. Currently, it runs at about 17 Hz, which is slower than expected.

Setup Instructions:

1. Set up ClickHouse v24 and a Redis server.
2. Run SQL statements from /sql/click-v.sql.
3. Load your RISC-V program.
4. Use the clock command to run the emulator.

Monitoring Commands:

• Check program instructions, registers, memory, and console output with various SQL SELECT commands.

Components:

• ClickHouse: The main engine required for the emulator.
• ClickOS: An optional program for handling system calls to access host resources.
• Memory Management: Uses Redis for storing registers/memory but has performance limitations.
• RISC-V Instruction Test Suite: A set of unit tests for validating instruction compliance and performance.

Architecture Overview:

• Includes components like Clock, Program Counter, Memory, Registers, Instructions, and Syscalls, each serving distinct functions within the emulator's operation.

Syscalls:

• The ecall instruction enables communication with the operating system for tasks like printing output and rendering graphics.

Overall, Click-V is a complex emulator that implements a RISC-V architecture within ClickHouse, but it currently faces performance challenges and is still in development.

The author shares their positive experience with the interview process at Mapbox, especially appreciating the request to write a blameless postmortem. A postmortem is a document that analyzes what went wrong in an incident to learn from it without assigning blame. The author emphasizes that this type of exercise reveals important qualities in programmers, such as communication skills, empathy, and critical thinking.

In preparing their postmortem, the author reflects on a sailing incident from 2015, where a shroud detaching from the mast caused the mast to break. They acknowledge multiple root causes, including a lack of thorough inspection of the boat's rigging and poor decision-making under pressure. The author concludes that they learned valuable lessons about equipment maintenance, the compounding nature of failures, and the importance of practicing decision-making in high-pressure situations.

Overall, the exercise highlighted the significance of learning from mistakes and improving both technical and decision-making skills.

The article discusses the installation process of NetBSD using its installer, sysinst, in 2025. This is the third part of a series that previously covered installers for FreeBSD and OpenBSD.

Key points include:

1. Background: The author, not very familiar with NetBSD, decided to explore its installer after discussing installation difficulties with a developer at a conference.

2. Installation Process: The author installed NetBSD 10.1 twice—once using a graphical console and once via a serial connection.

3. Installer Features:

   • The installer is menu-driven and presents language and keyboard layout options, limited to English and a few other languages.
   • The installation process includes selecting the disk, partitioning options, and installing the OS components.

4. User Experience Issues:

   • Some screens lack helpful explanations for newcomers, making navigation and understanding tasks more challenging.
   • Partitioning features can be confusing, especially regarding how to edit or delete partitions.
   • The installer does not clearly indicate successful actions or provide options for modifying choices easily.

5. Network Configuration:

   • The network setup process could be clearer, particularly regarding interface selection and configuration options.
   • Redundant prompts during configuration were noted as unnecessary.

6. Conclusion: Despite encountering many issues, the author appreciates the workflow and certain features of sysinst. However, they highlight significant problems that need to be addressed to improve the installation experience for new users.

7. Next Steps: The author plans to review DragonFly BSD’s installer in the next article.

Overall, while the author found some aspects of NetBSD's installer well-designed, many areas require improvement for better usability, especially for those less familiar with the system.

This text appears to be a list of groups that may need information: current students, staff, alumni, businesses, and donors. Each group likely has specific needs or interests related to the organization.

The text discusses the challenges and misconceptions surrounding the development of Artificial General Intelligence (AGI), particularly in relation to generative AI models. Here are the key points simplified:

1. Misconception of AGI: The success of current AI models has led some to believe that achieving AGI is close, but these models don't truly understand intelligence as humans do. They work by leveraging existing hardware rather than embodying true intelligence.

2. Limitations of Current Models: Generative AI, particularly through a multimodal approach (combining different types of data), is unlikely to lead to human-level AGI. Human-like intelligence requires an understanding of the physical world, which these models lack.

3. Need for Physical Understanding: True AGI must be able to handle tasks grounded in physical reality (like repairing a car or cooking) rather than just manipulating symbols. Current AI models often fail to learn a comprehensive understanding of the world and rely on superficial heuristics.

4. Issues with Language Models: Language models like LLMs (Large Language Models) may show impressive linguistic skills but do not genuinely understand semantics or pragmatics. They can generate well-formed sentences without grasping their meaning because they often rely on syntax alone.

5. Critique of Scale Maximalism: The approach of scaling up models (using more data and computational power) has been effective but doesn’t necessarily lead to true AGI. A better path might involve integrating different modalities of knowledge and treating intelligence as an embodied process.

6. Importance of Structure: The text argues against the idea that AI should be structure-agnostic. Significant advancements in AI have often come from making informed assumptions about how intelligence should be structured.

7. Future Directions: For AGI to be achieved, a more thoughtful integration of different cognitive processes and modalities is needed. This could involve creating systems that process various types of information (like text and images) in a unified way, rather than treating them separately.

In conclusion, the text emphasizes that building true AGI requires a deeper understanding of intelligence that goes beyond current approaches, focusing on physical interaction and integrated cognitive processes.

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Deep learning, especially with models like Transformers, is highly valued in research, particularly in predicting enzyme functions. A recent study published in Nature Communications used a deep learning model to predict the functions of 450 unknown enzymes from a dataset of 22 million. This paper gained significant attention and citations.

In contrast, another study published as a pre-print on bioRxiv critically examined the first paper and found many errors, including hundreds of incorrect predictions. This highlights the challenges in assessing AI results without deep expertise in the field.

Enzymes are vital for biological reactions and are classified by Enzyme Commission (EC) numbers. The first study aimed to predict these numbers for unknown enzymes using machine learning. Although the methodology seemed sound, the model produced many erroneous results, including claims of novelty that were already known. For example, it incorrectly classified the function of certain genes based on flawed reasoning.

The second paper revealed that many predictions from the first study were either repeated, not novel, or incorrect. This emphasizes the need for careful evaluation and domain expertise in AI research. It also raises concerns about the current research incentives that favor flashy AI models over thorough data verification.

The author suggests that more investment should be made in thorough scientific research, rather than solely focusing on high-profile AI solutions, to improve the quality and reliability of research outputs.

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Ephe is a simple tool that helps you manage your daily tasks and thoughts using Markdown. Unlike traditional todo apps, which can be complicated, Ephe offers a single, clean page to help you focus on your day. For more information, you can check the guide.

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OpenAI's ChatGPT is introducing new features aimed at business users, including integrations with various cloud services like Dropbox, Google Drive, and SharePoint. These integrations enable ChatGPT to access company documents and provide tailored responses, making it easier for analysts to create reports using company resources.

Additionally, ChatGPT now offers meeting recording and transcription capabilities, which can generate notes with time-stamped citations and suggest action items. Users can ask questions about their meeting notes, similar to how they interact with documents. This feature competes with tools like ClickUp and Zoom.

OpenAI is also rolling out deep research connectors for platforms like HubSpot and select Microsoft and Google tools, allowing users to compile detailed research reports using data from these sources. Furthermore, businesses can utilize the Model Context Protocol (MCP) for enhanced research capabilities, available to Pro, Team, and Enterprise users.

With these enhancements, OpenAI aims to encourage more businesses to adopt ChatGPT in their operations. The number of enterprise subscribers has grown to three million, reflecting strong interest in its offerings.

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In his blog post, Geoffrey Huntley discusses the changing landscape of software engineering in relation to AI, particularly Large Language Models (LLMs). He argues that LLMs reflect the skill of their operators, meaning that even experienced software engineers may need to adapt their skills to remain relevant in the AI-driven environment.

Huntley highlights the challenge companies face in identifying skilled operators, noting that traditional interview processes are failing due to the potential for candidates to cheat using AI tools. He advises against banning AI in interviews, as this could deter top talent and lead to "shadow AI," where employees use AI covertly.

To effectively assess candidates, Huntley suggests asking detailed questions about LLMs, including their functionalities and the candidate's hands-on experience. He emphasizes the importance of observing how candidates interact with LLMs during interviews, looking for signs of genuine skill, curiosity, and problem-solving abilities.

Huntley also mentions the need for a balance between technical skills and cultural fit in potential hires. Ultimately, he recognizes that while observing candidates' interactions with LLMs can be revealing, it also makes the hiring process more complex and costly.

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Summary of "Destination: Jupiter" by Andrew Liptak

On January 7, 1610, Galileo Galilei first observed Jupiter through a telescope and discovered its four largest moons: Callisto, Europa, Ganymede, and Io. This marked a significant shift in our understanding of the solar system, showing that celestial bodies could orbit other planets, similar to how Earth's moon orbits our planet.

Since then, Jupiter has fascinated writers and scientists alike. Ancient civilizations, like the Babylonians and Greeks, studied the planets, and in the 16th century, Nicolaus Copernicus proposed the heliocentric model of the solar system, which Johannes Kepler further developed. Galileo’s findings supported these theories.

As science fiction emerged in the 19th century, authors began to imagine space travel to Jupiter, often depicting it as a vibrant and mysterious world. In the 20th century, interest in Jupiter grew with the advent of the space race and NASA missions. Probes like Pioneer and Voyager provided groundbreaking insights into Jupiter's atmosphere and its moons, revealing potential subsurface oceans that could harbor life.

Today, missions like Juno and the upcoming Europa Clipper aim to deepen our understanding of Jupiter and its moons. These discoveries not only advance science but also continue to inspire new science fiction stories about life and exploration in our solar system.

Summary of Advanced Time Manipulation with GDB

This article explores advanced features of the GNU Debugger (GDB) for time manipulation, particularly for debugging code more efficiently. The author, Guinevere Larsen, builds on a previous article about basic time travel with GDB to show how to create time loops and change past states during debugging.

1. Understanding Time Loops: Time loops allow developers to repeatedly test code until a bug is identified. By setting breakpoints at specific lines in the code, GDB can automate the testing process, recording executions and restarting when a bug does not occur.

2. Example Code: The article uses a simple game code that checks hit chances. The author demonstrates how to set breakpoints and use GDB commands to automate testing, helping to track down sporadic bugs.

3. Changing the Past: GDB restricts changing the past to maintain the integrity of execution logs. However, a workaround exists where developers can stop recording and change values in the past, allowing them to alter the program's future execution.

4. Combining Techniques: The author suggests combining time loops and past state changes to improve debugging efficiency, especially in cases where starting the program takes a long time.

5. Reverse Debugging: The article concludes by highlighting the versatility of reverse debugging in GDB, encouraging readers to explore more about breakpoints and other debugging techniques.

Overall, this article aims to enhance debugging skills using GDB's advanced features for manipulating time and execution history.

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The author is leaving the tech industry, possibly for good, and plans to change the focus of their blog. They will write about a wider range of personal interests, such as their hobby farm, wilderness trips, and emergency medicine, rather than just tech topics.

After 25 years in tech, the author feels burnt out and disillusioned by the industry's negative impacts, despite enjoying their last job. They have considered leaving since 2016 but felt hesitant due to financial stability. Now, they feel ready to make a change, acknowledging that it's a personal decision and not criticizing those who stay in tech.

The author plans to train as an EMT and volunteer with a local Search and Rescue team, possibly becoming a Paramedic in the future. They will continue engaging with the tech community but want to write for themselves again, shifting away from the tech leadership focus they maintained since 2020. Overall, the author is excited about this new direction and the freedom to explore different topics in their writing.

Summary of Quarkdown

Quarkdown is a flexible typesetting system based on Markdown, enabling users to create print-ready books or interactive presentations effortlessly. It enhances Markdown with scripting capabilities, allowing for complex documents and dynamic content.

Key Features:

• Versatility: Quarkdown can compile projects into various formats, including HTML and PDF.
• Scripting Support: It allows users to define functions and variables directly within Markdown, enhancing its functionality.
• Library Support: An expanding library includes layout builders and math functions, making it powerful and customizable.
• Fast Compilation: Quarkdown offers quick processing times and live previews for ease of use.

Installation and Setup:

• Requires Java 17 or higher and supports all major operating systems.
• Users can create projects easily using a prompt-based wizard or by manually creating .qmd files.

Compilation Options:

• Users can compile their documents using various options, including automatic reloading and PDF generation.

Contributions and Community:

• Contributions are encouraged, and a mock document is available for users to explore Quarkdown's features.

Overall, Quarkdown combines the simplicity of Markdown with advanced capabilities for document creation and design.

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Meta and Yandex have been accused of secretly tracking Android users through their apps, like Instagram and Facebook, without users' consent. Researchers from Radboud University and IMDEA Networks discovered that these companies were collecting data on users' web browsing activities, even in incognito mode, by using scripts that bypass Android's security measures.

Experts expressed concern that this practice undermines privacy controls available on modern browsers and mobile platforms. Google confirmed that Meta and Yandex's actions violated privacy principles and stated it was investigating the issue.

Meta is currently looking into the matter and has paused the tracking feature while discussing it with Google. Yandex claimed it complies with data protection standards and does not collect sensitive information.

The tracking has been ongoing for several months for Meta and since 2017 for Yandex, affecting thousands of websites. In response, Google has started making changes to prevent such tracking and is in contact with the involved companies. Other browsers like Firefox and DuckDuckGo are also taking steps to address the issue.

No summary available.

Summary of Covert Web-to-App Tracking on Android

A recent disclosure revealed a new tracking technique by Meta (Facebook) and Yandex that may impact billions of Android users. This method involves native apps like Facebook and Instagram silently listening on local ports to collect data from mobile browsers.

Key Points:

1. Tracking Method:

   • Meta and Yandex apps can capture users' browsing data by listening on specific local ports (localhost). They receive cookies and metadata from scripts embedded on websites.

2. Privacy Bypass:

   • This tracking method bypasses common privacy measures, such as clearing cookies or using Incognito Mode, enabling organizations to link web activity to individual identities.

3. Technical Details:

   • The Meta Pixel script sends the _fbp cookie to the native app using a communication technique that was largely undetectable through standard debugging tools.
   • Yandex apps similarly use local ports to send device identifiers back to their servers.

4. Impact and Scope:

   • Meta Pixel is present on over 5.8 million websites, while Yandex Metrica is on nearly 3 million. Many sites may trigger these tracking methods automatically, even without user consent.

5. Recent Changes:

   • Following the disclosure, Meta stopped using this tracking method as of June 3, 2025. This indicates the disclosure's impact in raising awareness and prompting immediate action.

6. Risks:

   • The method poses risks, such as third-party apps potentially intercepting users' browsing history. A proof-of-concept showed that malicious apps could exploit this vulnerability.

7. Browser Responses:

   • Major browsers are working on patches to mitigate these privacy issues. However, more comprehensive measures are needed to address the underlying vulnerabilities of localhost access.

8. User Awareness:

   • Users may not be aware of these tracking practices, which can occur even when they are not logged into relevant apps or have cleared browsing data.

This disclosure highlights significant privacy concerns regarding mobile tracking and the need for better protections against unauthorized data collection.

As wind farms grow, a phenomenon known as "wind theft" is emerging, where one wind farm can reduce the wind available to another, impacting energy production. This occurs because turbines slow down the wind behind them, creating a wake that can extend over 100 kilometers. If one wind farm is positioned upwind of another, it can cut the downwind farm's energy output by over 10%.

This issue is becoming more critical as countries expand offshore wind energy to meet climate goals. Disputes are arising between developers regarding the effects of wakes, especially in crowded areas like the North Sea. Research projects, like one in the UK, aim to better understand these effects to help with planning and reduce conflicts.

The increasing size of turbines also contributes to the problem, as larger blades can create longer wakes. Experts are calling for cooperation between countries to manage wind as a shared resource, similar to how marine resources are regulated, to avoid legal issues and ensure efficient energy production. Overall, better understanding and planning are crucial for the successful expansion of offshore wind energy.

The IRS has made the code for its free tax filing software, Direct File, available as open source on GitHub. This decision comes amidst efforts by the Trump administration and lobbyists, including those from Intuit (the company behind TurboTax), to eliminate the program. Although the software might be at risk, the open-sourcing allows others to build upon it, offering a chance for new, free tax filing tools. The move to open source was required by the SHARE IT Act, aiming to promote public scrutiny and improvement of the software. However, the code still depends on internal IRS systems to function.

The Go Blog discusses ongoing concerns about error handling in the Go programming language, particularly its verbosity. Developers often find themselves writing repetitive code to check for errors, which can clutter their programs. For example, a function that sums two numbers has extensive error handling that detracts from the main logic.

The Go team has been aware of these complaints for years and has attempted to address them through various proposals, starting in 2018. Early attempts included a "check and handle" mechanism and a "try" function, both of which faced backlash for their complexity and impact on control flow. Subsequent proposals, including one inspired by Rust's "?" operator, also failed to gain sufficient support.

The blog outlines that despite numerous community suggestions and discussions, no consensus on improving error handling syntax has emerged. Given the lack of agreement and the potential disruption any changes could cause, the Go team has decided to halt efforts to change the syntax for error handling for the foreseeable future.

The article emphasizes that while the current method may seem verbose, it effectively serves its purpose. The team believes that introducing new syntax could create more issues than it solves. They acknowledge the persistent complaints but suggest focusing on refining existing error handling practices instead of pursuing new syntactic changes. Overall, the Go team looks forward to exploring new opportunities to improve the language while putting error handling discussions on hold.

Summary:

Many companies now offer APIs that work with OpenAI's Completions and Chat Completions, such as Deepseek, xAI, and others. However, OpenAI views Completions as outdated and is focusing on its new Responses API, even though it will continue to support the Chat Completions API.

The existing Chat Completions API lacks several advanced features that other providers have implemented in different ways, leading to confusion for developers. For instance, the way to include an assistant prefix varies across providers, making it difficult to know how to use these features without trial and error.

To improve the situation, there is a push to create a standardized version of the OpenAI completions APIs. This would help developers by providing a consistent experience and a recommended SDK for providers, while still being compatible with the current OpenAI SDK.

If you're a developer or provider interested in this initiative, you can reach out via email or Twitter/X.

3D Model Playground Summary

The 3D Model Playground is an interactive web application that allows users to control 3D models with hand gestures and voice commands in real-time. It is built using technologies like Three.js, MediaPipe for hand tracking, and the Web Speech API for voice recognition.

Key Features:

• Change interaction modes by saying "drag," "rotate," "scale," or "animate."
• Use finger pinching to manipulate the 3D model.
• Import new 3D models by dragging and dropping them onto the page (supports GLTF format).

Requirements:

• A modern web browser with WebGL support.
• Access to a camera and microphone.

Technologies Used:

• Three.js for rendering 3D graphics.
• MediaPipe for tracking hand gestures.
• Web Speech API for recognizing voice commands.
• HTML5 Canvas for visual feedback.
• JavaScript for real-time interactions.

Getting Started:

1. Clone the repository:

   git clone https://github.com/collidingScopes/3d-model-playground
   

2. Navigate to the project directory:

   cd 3d-model-playground
   

3. Serve the project (e.g., using Python):

   python -m http.server
   

4. Open your browser and go to http://localhost:8000.

License: MIT License

Credits:

• Three.js: threejs.org
• MediaPipe: mediapipe.dev
• Rosebud AI: rosebud.ai
• Quaternius 3D models: quaternius.com

Contact Information:

• Instagram: @stereo.drift
• Twitter: @measure_plan
• Email: [email protected]
• GitHub: collidingScopes

Donations: If you find the tool useful, consider supporting Alan with a donation for his open-source software projects.

Fusarium Overview

Fusarium is a large group of fungi found mainly in soil and associated with plants. Most Fusarium species are harmless and help decompose organic matter, but some can produce harmful toxins that affect crops and, subsequently, human and animal health. The main toxins include fumonisins and trichothecenes.

Key Points:

• Classification: Fusarium belongs to the kingdom Fungi and is part of the Nectriaceae family. It includes many species, some of which are significant plant pathogens.

• Plant Pathogens: Certain Fusarium species, like Fusarium graminearum, can cause serious agricultural issues like barley head blight, leading to substantial economic losses. Fusarium oxysporum is known for causing Panama disease in bananas, which threatens banana cultivars globally.

• Human Health: While most Fusarium species are harmless, some can lead to infections in humans, particularly in those with weakened immune systems. Conditions like nail infections and eye infections can occur.

• Food Uses: Fusarium venenatum is used to produce a meat substitute called Quorn. However, some individuals may have allergies to it.

• Historical Context: Fusarium has been involved in severe health crises, such as a contamination incident in the Soviet Union during the 1930s that caused many deaths. It has also been researched for potential use in biological warfare.

• Cultural Impact: Fusarium fungi pose a risk to historical artifacts, such as the cave paintings in Lascaux, due to their potential to cause damage.

In summary, while many Fusarium species play beneficial roles in the environment, some can be harmful to plants, animals, and humans, making them an important subject of study in agriculture and medicine.

No summary available.

The article discusses a new app called Sky, which brings AI automation to Mac computers. It highlights that the creators of Sky previously worked on Apple's automation tools but left due to Apple's lack of support for such innovations. The author expresses frustration about Apple's failure to utilize this talent and questions why Apple has not developed similar automation features themselves.

Sky is described as a polished app that enhances the Mac user experience by understanding user needs and automating tasks effectively. The author believes that Sky outperforms anything Apple has created in this area, pointing to Apple's internal issues and outdated practices as reasons for their shortcomings.

The piece raises concerns about Apple's disconnect with user expectations and its slow response to integrating automation and AI into its products. The author is skeptical about Apple's future plans, especially regarding their upcoming WWDC, and suggests that Apple needs to improve its approach to automation and AI to remain relevant. Ultimately, Sky serves as a benchmark for Apple's failures in delivering on the potential of AI for Mac users.

Summary of "Implementing a Forth"

The text discusses the author's experiences with creating different versions of the Forth programming language. None of these versions are fully finished for commercial use, but they provided valuable learning experiences about Forth and programming concepts.

Key Points:

1. Starting with Forth: If you're interested in creating your own Forth, consider beginning by porting an existing version, such as JONESFORTH. This can help you understand the language better and know when you've completed your work.

2. Creating a Minimal Forth: Think about how small you can make the core of your Forth. The challenge is not just to minimize it, but to make it interesting. Many examples of tiny Forth implementations exist, ranging from 1,000 bytes to even just 46 bytes.

3. Target Programs: Design your Forth to run a specific small program. The author shares examples of his Forth-like languages that were built to execute simple programs, emphasizing the importance of having a clear goal for your project.

Resources: The author lists valuable resources for learning about Forth, including the source code of JONESFORTH and notable articles like Brad Rodriguez’s "Moving Forth" series.

Overall, the text encourages experimentation with Forth while providing guidance on how to get started. Happy programming!

The "You Will" campaign was an advertising initiative by AT&T that started in 1993, featuring commercials directed by David Fincher and narrated by Tom Selleck. Each ad began with "Have you ever..." and concluded with "…you will. And the company that will bring it to you: AT&T." The campaign showcased futuristic technologies, predicting innovations like grocery checkout machines, telemedicine, intelligent assistants, videoconferencing, GPS navigation, and home automation.

One of the campaign's notable achievements was the first web banner ad sold on HotWired in 1994, asking users if they had ever clicked a specific spot. While many predictions were accurate, they were largely realized by new Silicon Valley companies rather than AT&T alone. The campaign received several awards, including the David Ogilvy Award for effectiveness.

No summary available.

We introduce a new approach to understand how much a language model "knows" about specific data points and to measure the model's capacity. Previous research has had difficulty separating memorization from generalization. In our study, we define two types of memorization:

1. Unintended memorization - knowledge about a specific dataset.
2. Generalization - knowledge about the overall data-generating process.

By removing generalization, we can measure total memorization, which helps estimate model capacity. Our findings suggest that GPT-style models have a capacity of about 3.6 bits for each parameter. We observed that as we train models on larger datasets, they memorize information until they reach their capacity. After that point, a phenomenon called "grokking" occurs, where unintended memorization decreases, and generalization improves. We trained many transformer models, ranging from 500,000 to 1.5 billion parameters, and developed scaling laws that connect model capacity and dataset size to the ability to infer membership in the data.

The text discusses the role of computers in art, particularly in a piece by Frieder Nake from 1971. Here are the key points:

1. Emergence of Computer Art: Computers began to influence artistic creation around the 1960s, leading to public exhibitions and discussions about their impact on art.

2. Debate on Artistic Value: There is ongoing debate in the art world about whether computer-generated works should be considered "art." Nake believes that computer art has not advanced the field of art significantly compared to traditional methods.

3. Critique of the Art Market: Nake argues that art dealers, rather than artists, dictate trends in the art world, similar to fashion industries. He views computer art as a passing trend rather than a meaningful innovation.

4. Limitations of Computer Art: He points out that access to technology and programming knowledge limits "real" artists from creating impactful computer art. He criticizes the idea that merely using computers will lead to significant artistic breakthroughs.

5. Alternative Focus: Instead of producing more art, Nake suggests that computers should be used to explore and understand new forms of communication and aesthetic experiences. He advocates for projects that address societal issues rather than just creating aesthetically pleasing objects.

6. Future Directions: Nake proposes several research areas, such as studying the alienation of artists from their work due to technology and investigating how aesthetic information can be applied in various aspects of life.

In summary, Nake argues for a critical approach to the use of computers in art, emphasizing the need for meaningful exploration rather than simply creating new artistic fashions.

Lingo.dev is an open-source toolkit that helps make web and mobile apps multilingual using AI for localization and translation. It includes three main tools:

1. Lingo.dev CLI: A command-line tool for fast and accurate translations of apps and markdown content.
2. Lingo.dev CI/CD: An integration for GitHub, GitLab, and Bitbucket that automatically updates translations when new content is added.
3. Lingo.dev Compiler: A new tool that allows React apps to support multiple languages at build time without changing existing components.

The Lingo.dev Compiler uses your LLM API key to automatically translate your app into different languages. The project is community-driven, encouraging contributions and discussions on Discord. There is also support for multiple languages in the documentation, and users can add more languages if needed.

The article discusses how to implement optimized locking mechanisms in Linux, focusing on spin locks and futexes.

Key Points:

1. Mutex Concept: A mutex (mutual exclusion) allows only one thread to access a critical section of code at a time. If another thread tries to access it while it’s locked, it must wait.

2. Spin Lock: The simplest locking method involves a "spin lock," where a thread continuously checks (or "spins") until it can acquire the lock. An example implementation in C uses an atomic boolean to track if the lock is held.

3. CPU Usage Issue: Spin locks can lead to high CPU usage, especially if a thread holds the lock for a long time (e.g., sleeping in the critical section), as other threads waste resources spinning.

4. Futex System Call: The futex syscall provides a more efficient way to handle waiting threads. Instead of spinning, it can put threads to sleep until the lock is available, using operations like FUTEX_WAIT and FUTEX_WAKE.

5. Futex Implementation: A futex-based lock uses a 32-bit integer to manage states (available, locked, or locked with waiters). It checks conditions before putting threads to sleep, aiming to reduce unnecessary system calls.

6. Performance Comparison: The article compares spin locks and futex locks through tests. It shows that while futex locks reduce CPU usage significantly, simple spin locks can be faster in scenarios with low contention and quick lock acquisitions.

7. Improving Futexes: The article suggests enhancements to futex locks to avoid unnecessary syscalls when there are no waiting threads, improving performance further.

8. Conclusion: The article concludes that while futexes are generally more efficient under high contention, spin locks can outperform them in simpler cases. It also hints at future explorations into hybrid locking approaches that combine both methods for optimal performance.

Overall, the text provides insights into locking mechanisms in concurrent programming, highlighting the trade-offs between different implementations.

No summary available.

Tellico Overview

• Automatic Data Fetching: Tellico can search various online data sources, allowing you to save time by not having to enter information manually.

• Customization Options: It provides pre-defined collections for popular items like books and video games, and you can modify these or create your own collections.

• Built on Qt & KDE: Tellico uses the Qt and KDE Frameworks for better desktop integration and a consistent look and feel.

Garlic Decompiler Summary

Garlic Decompiler is a Java decompiler written in C that converts .class and .jar files into Java source code.

Key Features:

• Decompiles .class files, .jar files, and .war files.

Requirements:

• CMake version 3.26 or higher is needed; no other dependencies are required.

Installation:

1. Clone the repository: git clone https://github.com/neocanable/garlic.git
2. Navigate to the directory: cd garlic
3. Build the project:
   • cmake -B build
   • cmake --build build
4. Run the decompiler: ./build/garlic

Usage:

• To decompile a .class file, use: garlic /path/to/jvm.class
• To decompile a .jar file:
  • Basic: garlic /path/to/file.jar
  • Specify output: garlic /path/to/file.jar -o /path/to/save
  • Set thread count: garlic /path/to/file.jar -t 5 (default is 4).

Additional Features:

• Similar to javap, but faster and without certain attributes.
• Debugging options are available by modifying the main function in the source code.

License:

• Licensed under the Apache 2.0 License.

Summary of "Sid Meier's Pirates! - In-depth Written Amiga Review With Pics"

The blog post reviews "Sid Meier's Pirates!" a classic video game originally released in 1987 for the Commodore 64 and later for the Amiga in 1990. The Amiga version is praised for its unique graphics and gameplay. The game combines action, adventure, and simulation elements, allowing players to choose their paths as pirates in various historical contexts.

Players can select different time periods and scenarios, engaging in activities such as treasure hunting, ship battles, and sword fighting. The game is noted for its open-ended structure, enabling players to set their own goals and explore the game world freely.

The author shares personal anecdotes about playing the game and emphasizes its lasting appeal, highlighting that many fans prefer the original versions over newer remakes. The review concludes that "Sid Meier's Pirates!" is one of the greatest games of all time, deserving attention from anyone interested in gaming history.

The Barrelfish Project is an operating system developed by ETH Zurich, featuring a unique "multikernel" architecture. Here are the key points:

1. Architecture: Barrelfish operates with a small kernel on each CPU core, where each core runs its own CPU driver. This setup avoids shared memory between kernels, and applications are designed to run across multiple cores using user-space libraries.

2. CPU Drivers: Each core's CPU driver handles tasks like scheduling, system calls, and interrupts. They are single-threaded and non-preemptible, meaning they execute tasks sequentially without interruption.

3. Dispatchers: These are the primary units of scheduling within the Barrelfish OS, similar to processes in Unix. Each dispatcher operates on a single core and does not migrate between cores.

4. Runtime Libraries: Barrelfish programs rely on two main libraries for functionalities such as thread scheduling, memory management, and communication.

5. Capabilities: Barrelfish uses a capability-based access control system for managing resources and permissions, enhancing security and organization within the OS.

6. Memory Management: The OS allows applications to manage their own virtual memory and respond to page faults, giving them the flexibility to handle memory directly.

7. Inter-domain Communication: Barrelfish facilitates message passing between application domains through a structured channel system, ensuring efficient communication.

8. System Knowledge Base (SKB): This service maintains and queries system state information and aids in device management and configuration.

9. Device Drivers: Drivers in Barrelfish operate as individual dispatchers, initialized with specific capabilities to manage hardware devices.

Overall, Barrelfish is designed to efficiently utilize multi-core systems while maintaining a modular and secure operating environment.

Summary: Using Your iPhone as an AirPlay Receiver with AirAP

AirAP is an app that turns your iPhone into an AirPlay receiver, allowing it to play audio from your Mac, Apple TV, or other iOS devices. This means you can stream sound to your iPhone instead of the usual way of streaming from your iPhone to other devices.

This can be useful in various situations, like listening to audio quietly at night through headphones or testing audio apps as a developer.

To install AirAP, use the TestFlight link, follow the installation instructions, and ensure your iPhone is on the same Wi-Fi network as the device you want to stream from. After launching AirAP, your iPhone will show up as an AirPlay option.

For developers, you can compile the app using Homebrew and Xcode.

AirAP was developed with the help of other projects and is compatible with Apple's technology.

The document discusses a method for enabling hot module reloading (HMR) natively in Node.js to improve development efficiency. The key points include:

1. State Preservation: Effective development requires minimizing state loss. The new Node.js --watch flags are inadequate because they discard all state when a change occurs.

2. Module Invalidation: Instead of discarding everything, the goal is to update only the changed modules and their dependencies, keeping the rest intact.

3. Improved System: The author describes how the immaculata system previously mirrored Vite's approach but had issues with duplicated logic and separate systems. By utilizing Node's built-in module hooks, a more efficient HMR can be implemented.

4. File Management: A FileTree class loads and maintains file trees in memory, using Node's native file watcher for efficiency without needing additional libraries.

5. Hooks Implementation: The useTree dual-hook allows for the retrieval of up-to-date module sources and handles versioning using timestamps.

6. Dependency Tracking: Changes in a module's dependencies automatically update the version of the parent module, ensuring that modules stay current even when only a single dependency changes.

7. Example Code: Simple code snippets demonstrate how to set up the FileTree, register hooks, and handle module imports and updates.

8. Resource Management: The document highlights the ability to clean up resources (like syntax highlighting) when modules are invalidated, ensuring a smoother development experience.

Overall, the approach allows for efficient module updates in Node.js without unnecessary reloading, enhancing the development workflow.

No summary available.

The text discusses the dangers of commiseration in management, especially when managers complain with their direct reports. Key points include:

1. Commiseration is Harmful: Complaining with team members can damage trust and create divisions within the organization. It can lead to a negative mindset and hinder collaboration.

2. Empathy as a Manager: Managers should approach grievances with a focus on finding solutions rather than just offering sympathy. They need to gather information and ensure a balanced perspective.

3. Communication Techniques:

   • Ask clarifying questions to understand the situation better.
   • Offer constructive feedback and a positive view of others instead of criticizing them.
   • Avoid phrases that imply incompetence and focus on collaboration.

4. Handling Complaints About Leadership: Instead of joining in negative talk about higher-ups, managers should steer the conversation towards how to work effectively with them.

5. Follow-Up is Essential: After addressing a complaint, managers should commit to taking action and separate emotions from the discussion to maintain professionalism.

6. Seek Support Wisely: If managers need to vent, it's best to do so with peers rather than team members to avoid endorsing negative attitudes.

Overall, the emphasis is on maintaining a constructive work environment and fostering trust within the team.

Summary: Vision Language Models (VLMs) Exhibit Significant Bias

Recent research reveals that Vision Language Models (VLMs) perform exceptionally well in familiar situations, achieving 100% accuracy in identifying and counting objects in standard images. However, they fail dramatically when faced with modified images, scoring only about 17% accuracy. This indicates that VLMs rely on memorized information rather than true visual analysis.

Key Findings:

1. Counting Failures: VLMs can accurately count familiar objects (like a dog having 4 legs) but struggle with slight modifications (like a dog with 5 legs), consistently defaulting to their memorized knowledge.
2. Confirmation Bias: The models exhibit confirmation bias, ignoring visual changes and sticking to expected answers based on prior knowledge.
3. Systematic Errors: Approximately 75% of errors made by VLMs align with their biases, suggesting they prioritize memorized facts over what they actually see.

Testing Methodology: The study used a three-step process:

• Confirm VLMs' knowledge using standard images.
• Test their performance on modified images.
• Analyze the influence of background cues on their answers.

Performance Across Domains: In various tasks (such as counting legs in animals, stripes in logos, and elements in flags), VLMs consistently underperformed when the images were altered. This demonstrates a fundamental flaw in their ability to process visual information accurately.

Implications:

• Practical Concerns: The biases of VLMs pose risks in critical fields like medical imaging and autonomous vehicles, where slight modifications can lead to significant errors.
• Research Directions: There’s a need for improved evaluation methods and training approaches that focus on visual analysis rather than rote memorization.

Conclusion: Current VLMs excel at recognizing known patterns but are fundamentally limited in their visual reasoning capabilities. As these systems are deployed in real-world applications, it's crucial to understand their limitations and work towards better models that can accurately interpret visual information.

Here’s a simplified summary of the updates:

June 3, 2025 Updates:

• Internet Access for Codex: Codex can now access the internet to install dependencies, run tests, and more, but this is off by default. Pro and Team users can enable it for specific environments with control over which websites and methods Codex can use. Enterprise access is coming soon.
• Update Pull Requests: Users can now update existing pull requests easily.
• Voice Dictation: You can now dictate tasks to Codex.
• Fixes and Improvements:
  • Added a link to the changelog in the profile menu.
  • Support for binary files improved.
  • Fixed several issues on iOS, including duplicated tasks and outdated pull request statuses.
  • Improved task handling and error messages.
  • Increased limits for task diffs and setup script duration.
  • Enhanced GitHub connection flow and re-enabled notifications on iOS.
  • Removed mandatory two-factor authentication for some users.

May 22, 2025 Updates:

• Environment Page Reworked: It's now easier to set up code execution.
• Fixes and Improvements:
  • Added buttons to retry tasks and indicators for network status.
  • Improved error messages and onboarding for teams.
  • Reduced delays in GitHub connections and task completions.
  • Updated documentation.

May 19, 2025 Updates:

• Codex in ChatGPT iOS App: You can start tasks, view differences, and push pull requests from the app while away from your desk.

This summary captures the key points and improvements made in the updates.

The text discusses the concept of decentralization in historical societies, particularly during the Middle Ages, often referred to as the "Dark Ages." Here are the key points summarized:

1. Decentralization and Record Keeping: Historical examples of decentralized societies are often overlooked because they did not keep records, and modern states may also have reasons to obscure these examples.

2. Private Law in the Middle Ages: During this time, laws were based on local customs rather than the king's decrees. Both kings and lords were subject to these laws, which were considered ancient and just, and land ownership was not granted as a privilege from the king but was independent.

3. Misconception of the "Dark Ages": The term "Dark Ages" implies a period of cultural decline after the fall of Rome, but many aspects of governance were more decentralized and equitable than commonly believed.

4. Sovereignty of Free Men: In this era, free men had significant authority over their own lands, and taxes were voluntary, contrasting with the modern view of government authority.

5. Role of Law vs. Authority: The king was bound by law, and both he and the people had responsibilities to uphold it, unlike today where resisting government authority is often illegal.

6. Localism and Variation: Architectural styles and laws varied significantly by region during the Middle Ages, reflecting a strong sense of local identity and governance.

7. Understanding Serfdom: While serfdom is often viewed negatively, it involved labor obligations in exchange for protection and access to land, similar to modern economic relationships, albeit with different constraints.

Overall, the text emphasizes the complexity and nuances of governance during the Middle Ages, challenging the idea that it was a uniformly dark or regressive period.

No summary available.

The text discusses the shortcomings in treating age-related diseases, highlighting that current approved drugs do not reverse damage or significantly halt disease progression. Here are the key points:

1. General Findings: No approved drugs for age-related diseases effectively reverse damage; they often only slow decline slightly, and some show no real functional benefits.

2. Geographic Atrophy (GA): Two drugs, Syfovre and Izervay, approved in 2023, slow lesion growth but do not improve vision.

3. Idiopathic Pulmonary Fibrosis (IPF): Two drugs, nintedanib and pirfenidone, approved in 2014, slightly reduce the decline in lung function but do not improve overall prognosis.

4. MASH (Metabolic Dysfunction-Associated Steatotic Liver Disease): Resmetirom, approved in 2024, is the first drug for MASH, showing some improvement in early stages but not for advanced liver disease.

5. Alzheimer's Disease: Recent drugs like lecanemab and donanemab show statistically significant but clinically questionable benefits, with serious side effects reported.

Overall, while there are some advancements in treatments, they often do not provide meaningful improvements for patients with age-related diseases.

Summary: Migrating Apple's Password Monitoring Service from Java to Swift

Apple's Password Monitoring service, which manages billions of requests daily, was successfully rewritten in Swift, resulting in a 40% performance boost compared to its previous Java version. This migration was necessary due to Java's limitations in scalability and efficiency, particularly under high load.

The Passwords app, launched in 2024, helps users manage their passwords securely, including a feature that alerts them if their passwords are compromised. The Password Monitoring service operates privately, never revealing user passwords to Apple while checking them against known data leaks.

Swift was chosen for its performance advantages and modern features. The team found Swift's syntax easy to learn and its focus on protocols allowed for cleaner, more maintainable code compared to Java's complex inheritance structures. Swift's safety features, such as optional types, helped reduce runtime errors.

The new Swift-based service has shown significant improvements, including a smaller memory footprint and faster response times, allowing for more efficient resource use in Apple's infrastructure. Overall, the transition to Swift has proven beneficial for performance, safety, and maintainability, making it a strong choice for Apple's cloud services.

No summary available.

MonsterUI: A Simplified Approach to UI Development with FastHTML

MonsterUI is a Python library designed to help developers quickly create beautiful user interfaces for web applications using FastHTML. It addresses the common challenges of web UI development, where managing CSS and complex styling can be tedious and confusing.

Key Points:

1. The Challenge: Creating attractive web applications often involves complicated dependencies and extensive CSS. This leads to difficulties in managing styles and layouts, especially as applications grow.

2. Introducing MonsterUI:

   • MonsterUI simplifies UI development by providing pre-styled components and smart defaults, allowing developers to focus on building features rather than worrying about CSS.
   • It integrates with FastHTML and modern libraries like Tailwind and FrankenUI, offering beautiful, responsive components without needing to write CSS.

3. Core Features:

   • Theme Selection: Choose from 12 color themes with dark and light modes for consistent styling across the app.
   • Base Components: Every HTML element comes with default styling, making it easy to create buttons, cards, and more with minimal code.
   • Semantic Text Styles: Enhances standard HTML tags with modern styling for better readability and design.
   • Smart Layout Helpers: Simplifies page layouts with easy-to-use layout functions, such as stacking elements or creating grids.
   • Common UI Patterns: Provides shortcuts for frequently used elements like labeled input fields, streamlining the development process.
   • Higher-Level Components: Offers helpers for creating complex UI elements like modals and navigation bars without the need for extensive boilerplate code.
   • Markdown Rendering: Easily convert Markdown text into styled HTML with syntax highlighting.

4. Getting Started:

   • Installation is simple via pip, and a basic application can be set up quickly with predefined theming and responsive layouts.
   • The library is designed for developers to start building applications with minimal configuration and a focus on user experience.

With MonsterUI, developers can create modern web applications efficiently, ensuring both functionality and aesthetic appeal without the usual hassles of web UI development.

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Elide Gradle Plugin Overview

The Elide Gradle Plugin is an experimental tool that allows users to utilize Elide within Gradle for improved performance in dependency resolution and Java compilation.

Installation Steps:

1. Install Elide using the provided GitHub Actions setup.
2. Create a script named elide-javac in your JAVA_HOME/bin directory to use Elide's Java compiler.
3. Make the script executable.

Usage:

• Update your gradle.properties with the latest Elide plugin version.
• In settings.gradle.kts, apply the Elide plugin from the specified URL.
• In build.gradle.kts, configure the Elide settings, like enabling dependency resolution and Java compilation features.

Key Features:

• Acts as a drop-in replacement for traditional Java tools (javac, jar, javadoc).
• Offers faster dependency fetching and code compilation, potentially up to 20 times quicker for some projects.
• Supports multiple programming languages and integrates seamlessly with Gradle.

How It Works: Elide uses a native image to function efficiently, replacing Gradle's built-in tools with its optimized versions for better performance.

Important Notes:

• Elide is currently in beta; use at your own risk.
• Dependency fetching requires an elide.pkl manifest, which lists your Maven dependencies.

For more information, visit elide.dev.

Generative AI is helping software developers become more productive, but there are worries about job displacement and skill loss. Research with 21 developers revealed 12 work goals, 75 related tasks, and the necessary skills for using AI effectively. From this, five key insights were identified. Successful AI-enhanced developers need skills in four areas: using Generative AI, core software engineering, adjacent engineering, and non-engineering skills. These skills should be applied throughout a six-step task process. To prepare developers for the AI era, training programs should focus on both technical and "soft" skills in these four areas to ensure they remain competent and valuable in their roles.

The report "Plutonium Mountain" details a 17-year mission to secure plutonium left from Soviet nuclear tests at the Semipalatinsk Test Site in Kazakhstan. Between 1949 and 1991, the Soviet Union conducted 456 nuclear tests, leaving behind significant amounts of plutonium that could potentially be recovered for nuclear weapons. After the Soviet Union's collapse, scientists and military personnel abandoned the site, prompting concerns about nuclear security.

In 2012, a collaborative effort involving scientists from the U.S., Russia, and Kazakhstan culminated in securing the plutonium by filling tunnels and bore holes with concrete, significantly reducing the nuclear threat. This operation began in 1995, driven by a need to address the dangers posed by the abandoned plutonium amidst rising global concerns about nuclear terrorism.

Despite the success of this informal collaboration, which avoided formal state-to-state agreements, the operation faced challenges, including logistical issues and distrust among the countries involved. The report highlights the importance of international cooperation in nuclear threat reduction and reflects on the lessons learned for future efforts in nuclear security.