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A user asked how the opening logo of Universal Pictures, introduced in 1936, was created. They noted the logo's unique design compared to previous ones, featuring many moving parts and reflections. Despite their research, they found little information online.

An answer provided detailed insight into the logo's creation by Art Director Alexander Golitzen. The logo was made using plexiglass and involved filming spinning stars with special lighting to create reflective effects. The globe was filmed with the stars projected onto it, creating dynamic light patterns. This process took about six months to complete. Later, the globe was reused in the movie "This Island Earth" in 1955.

The author experienced battery drain on their MacBook Pro Silicon M1 Max, which started unexpectedly. To investigate, they used a terminal command to access power management logs but found it complicated. They created a tool to analyze the logs, but it wasn't very helpful. After further research, they discovered a tool called Sleep Aid, which simplifies viewing wake events and adjusting settings. They found that the "Wake for maintenance" option was disabled, which was causing the frequent wake-ups. By enabling this setting, the battery drain issue was resolved, and the MacBook no longer loses power overnight when unplugged.

Jeffrey Hass, a Professor Emeritus at the Jacobs School of Music, Indiana University, is associated with the Center for Electronic and Computer Music. You can find more information on their website or contact them via email. Feedback and comments are encouraged. The content is copyrighted for 2025 by Jeffrey Hass and the Trustees of Indiana University.

StreamNative AI Hub Overview:

• Ursa Engine Launch: The new Ursa Engine combines Apache Kafka and Pulsar, enabling faster, smarter, and cheaper data streaming.

• Cost Efficiency: Users can run Kafka workloads at 5GB/s for only $50 per hour, significantly less than traditional engines like Redpanda.

• Integration with Snowflake: Ursa is now integrated with Snowflake's Open Catalog for secure access to Iceberg tables.

• General Availability: Ursa is now fully available on AWS, allowing users to run production workloads without the need for ZooKeeper management.

• Key Benefits:

  • Cost Reduction: Potential total cost of ownership (TCO) reduction by up to 95%.
  • High Throughput: Offers 1000x higher throughput compared to traditional systems.
  • No Application Changes: Fully compatible with existing Kafka APIs, requiring no rewrites.

• Architecture Features:

  • Leaderless Design: Simplifies management and enhances scalability.
  • Lakehouse Native Storage: Directly writes data to low-cost storage in open formats, making it readily available for querying.

• Multi-Protocol Support: Combines Kafka and Pulsar, allowing real-time data streaming for AI models and other applications.

• Try Ursa for Free: StreamNative offers easy deployment across major cloud platforms, with a pay-as-you-go model and no credit card required to start.

Overall, Ursa aims to enhance data streaming capabilities while reducing costs and simplifying operations for businesses.

Summary:

Servo is an independent web browser engine developed in Rust, aiming to provide a fast and secure alternative to existing engines like Chromium and Gecko. Originally a Mozilla project, Servo is now managed by Linux Foundation Europe and is designed to be embeddable in various applications, not just browsers. It emphasizes multi-threaded performance and memory safety, which are crucial for modern web applications.

Currently, Servo lacks a full-featured browser, but nightly builds are available for testing. While it shows promise, it has some rendering bugs and scores 83/100 on the Acid3 test, indicating it needs improvement.

Mozilla initially incorporated Servo components into Firefox but shifted its focus after layoffs in 2020. Now, Servo is being actively developed, with support from various organizations.

The ongoing legal battle against Google could affect Mozilla's future and Firefox's reliance on Google's search engine, raising questions about the fate of Gecko and the potential for community-driven projects. Despite uncertainties, there is optimism for Servo's development and future impact in the web ecosystem.

No summary available.

Summary of Zig Profiling on Apple Silicon

If you're a developer using an Apple Silicon Mac with Zig, the available profiling tools are limited compared to Linux. Here are the main points:

Types of Profilers

1. CPU Time Profilers:

   • Statistical Sampling: Periodically samples to estimate time spent in code.
   • Hardware Event Sampling: Samples based on hardware counter overflows.
   • Instrumentation Profilers: Insert code to monitor performance at specific points.

2. Profiling Tools for Apple Silicon:

   • Samply: A sampling profiler that collects stack traces. It has a user-friendly interface and can profile both running processes and new commands.
     • Installation: cargo install samply or brew install samply.
   • Poop: A tool for comparing performance using hardware counters. It's in development and requires root access.
     • Installation: Clone the forked repo and build it with Zig.
   • Tracy: A real-time profiler that offers instrumentation features but lacks callstack sampling support on Apple Silicon.
     • Installation: Clone the Tracy repo and integrate it with your Zig project.
   • Apple Instruments: A versatile tool for CPU profiling and more, but known for a slow interface. It can also track GPU usage and other metrics.

Conclusion

While profiling tools for Apple Silicon aren’t as abundant as those for Linux, options like Samply and Tracy can be useful for performance analysis. Samply is recommended for quick checks, while Poop is better for iterative optimizations.

No summary available.

AI agents using large language models can perform complex tasks on their own, but they don't match human skills in areas like computer use and software development. Their increasing independence raises safety concerns, such as making mistakes or being misled. To improve this, we suggest using "human-in-the-loop" systems, which combine human oversight with AI efficiency to enhance productivity.

We introduce Magentic-UI, an open-source web interface designed for studying how humans and AI interact. It allows for web browsing, code execution, and file manipulation, and can be customized with various tools. Magentic-UI includes six ways for humans to engage effectively: co-planning, co-tasking, multi-tasking, action guards, and long-term memory.

We evaluated Magentic-UI in four areas: how well it completes tasks, how users interact with it, feedback from real users, and safety checks. Our results show that Magentic-UI has great potential for improving safe and efficient collaboration between humans and AI.

Summary of Dark Patterns in Online Shopping

Dark patterns are deceptive tactics used by websites and apps to trick you into spending more money or sharing unnecessary personal information. Here’s what to watch out for when shopping online:

1. Hidden Costs: Extra fees appear late in the checkout process or are made less clear. This can include pre-selected extras or automatic renewals for free trials.

2. Trick Questions: Confusing questions steer you towards choices that benefit the business, often during subscription cancellations or data collection.

3. Scarcity Cues: Tactics like countdown timers and low stock alerts create a fear of missing out, pushing you to make hasty purchases.

4. Activity Notifications: Alerts about other users' actions (like purchases) may create urgency, but they can be misleading.

5. Confirm Shaming: Language designed to make you feel bad for not agreeing to a purchase, like offering guilt-inducing options.

6. Forced Continuity: Easy subscription sign-ups but difficult cancellations, often requiring multiple steps.

7. Data Grabs: Requests for excessive personal information that may not be necessary for your transaction.

8. Disguised Advertisements: Misleading links that look genuine but redirect you to products or services.

9. False Hierarchy: Presenting preferred products in a way that makes them more attractive while downplaying others.

10. Redirection or Nagging: Constant pop-ups or prompts that distract you from completing your intended task, like leaving the site.

Being aware of these tactics can help you make smarter choices while shopping online.

No summary available.

No summary available.

Eduard Agavriloae and Matei Josephs, cloud security researchers, conducted a study on Google Cloud Platform (GCP) images to find security secrets, following previous research on Amazon Web Services (AWS) and Azure. Unlike AWS, where they discovered many exposed secrets in public images, they scanned over 8,400 GCP images and found none. This suggests that GCP's strict control over who can publish images contributes to better security.

Their research involved creating disks from public images, extracting files, and searching for common file types associated with secrets. Despite processing a large volume of data (over 100 GB), no sensitive information was detected. The study highlighted that GCP's validation policies likely prevent secret exposure, indicating that their curated approach is effective in enhancing security.

Overall, the findings show that GCP's strict publishing rules resulted in zero secrets found, contrasting with the higher numbers found in AWS and moderate findings in Azure. This research emphasizes the importance of security measures in cloud services and encourages ongoing monitoring of public images across platforms.

No summary available.

No summary available.

Eclipse SUMO (Simulation of Urban Mobility) is an open-source traffic simulation tool that allows users to model complex transportation systems, including vehicles, public transport, and pedestrians. It is highly portable and can run on Windows, Linux, and macOS.

Key features of SUMO include:

• Intermodal Traffic Simulation: Models different types of transport, such as cars, buses, trains, and pedestrians.
• Automated Driving: Integrates automated vehicles into simulations.
• Vehicle Communication: Supports communication technologies for vehicles.
• Traffic Management: Allows interactive traffic management with tools for controlling traffic lights and speed limits.
• Microscopic Simulation: Simulates the movement of individual objects in detail.
• Network Import: Can import road networks from various formats.
• Demand Generation: Creates realistic traffic demand based on data or models.
• Traffic Light Management: Offers tools for modifying traffic light schedules.
• Performance: Supports large networks and a high number of vehicles without limits.
• Portability: Compatible with multiple operating systems and implemented in C++ and Python.
• Open Source: Users can modify the software as it is available under open-source licenses.

For more information and to download SUMO, visit their official website.

No summary available.

No summary available.

The U.S. Senate has introduced a bipartisan bill called "Block BEARD," aimed at blocking foreign piracy websites. This bill is similar to a previous House bill called the Foreign Anti-Digital Piracy Act (FADPA).

Key Points:

• Purpose: Block BEARD would allow copyright holders to request federal courts to label websites as "foreign digital piracy sites" and order U.S. internet service providers (ISPs) to block them.
• Criteria for Blocking: Rightsholders must demonstrate harm from the site, make reasonable efforts to notify the operator, and confirm that the operator is not based in the U.S. The site must also be primarily for piracy.
• Court Process: If a site is designated as a pirate site, the court can decide if blocking is feasible and consider public interest. Blocking orders would last for a year, with options to extend or update for new site addresses.
• Service Provider Inclusion: The bill applies broadly to service providers, including ISPs, search engines, and social media, but excludes those with fewer than 50,000 subscribers and public venues like libraries.
• Support: The bill has received positive feedback from rightsholder organizations, indicating it could be an effective tool against piracy without harming free speech or internet security.
• Next Steps: The bill needs to pass both the Senate and the House, and lawmakers are collaborating to achieve this.

Overall, Block BEARD seeks to enhance legal tools against online piracy while balancing rights and public interests.

Summary: Diagnosing Stuttering in Trackmania Without Source Code

As a programmer, it can be frustrating to deal with software issues without having access to the source code. A recent example of this was my experience with the game Trackmania (2020), which had persistent stuttering problems that affected gameplay. The game would drop from about 130 frames per second to as low as 5, making it difficult to perform well.

I initially tried common fixes suggested by other players, like updating drivers and disabling overlays, but these did not resolve the issue. Determined to find the cause, I used a profiling tool called Superluminal to analyze the game's performance. I discovered that the game was heavily reliant on its main thread, alongside other threads for tasks like video playback.

During my profiling, I noticed that the game was using certain libraries associated with overlays from Steam and Ubisoft, but disabling these overlays didn't help. I also found a separate thread for decoding videos, which raised questions about why the game was using CPU resources for this task during gameplay.

Further investigation led me to a community-driven scripting platform called Open Planet, which can add plugins to Trackmania. After uninstalling Open Planet, the stuttering stopped, suggesting that a plugin was causing the performance issues. When I reinstalled Open Planet, the stutters didn’t return, indicating that the problem was likely linked to a specific plugin that I had previously installed.

Overall, I was able to resolve the stuttering issue through careful analysis and profiling, demonstrating that even without source code access, systematic investigation can lead to solutions.

Summary of Carbon Language: An Experimental Successor to C++

Carbon is a new programming language being developed as a successor to C++. It aims to improve upon C++ while maintaining its strengths, particularly in performance-critical applications. Here are the key points:

• Purpose: Carbon aims to solve issues with C++ stemming from its technical debt while ensuring good performance and compatibility with existing C++ code.

• Features:

  • Performance: Matches C++ in speed while allowing low-level access.
  • Interoperability: Can work alongside existing C++ code, allowing gradual migration.
  • Modern Syntax: Designed to be easy to learn, especially for C++ developers.
  • Safety: Focuses on improving memory safety and reducing bugs.

• Development Status: Carbon is still in the experimental stage. A toolchain is being created that includes a compiler and linker, but it is not ready for production use.

• Learning Curve: C++ developers should find it familiar and easy to transition to Carbon.

• Community: Carbon is open-source and aims to foster a welcoming community for contributors.

• Getting Started: Users can experiment with Carbon through an online toolchain, but it is still in early development with limited functionality.

• Future Goals: The project aims to reach a stable release (0.1) and expand features like generics and memory safety over time.

Contributors interested in the Carbon project can join discussions on Discord and contribute to its development.

GenosDB (GDB) Summary

GenosDB is a lightweight, decentralized graph database designed for modern web applications. It features real-time peer-to-peer synchronization, WebAuthn-based authentication, and role-based access control (RBAC). It uses efficient local storage with OPFS.

Main Features:

• Core Functionality:

  • Efficient storage and real-time sync across devices.
  • CRUD operations for managing data.
  • Supports external modules for added capabilities.

• Project Status:

  • Currently in beta; not recommended for production use yet. Features include basic and advanced queries, distributed storage, and conflict resolution.

• RBAC Features:

  • Allows customizable roles and permissions, biometric authentication, and cryptographic transaction verification.

• Security:

  • Ensures critical operations are digitally signed and permissions are validated in real time.

Installation:

• Can be installed via NPM or directly in the browser using a CDN.

Dependencies:

• Uses libraries like @msgpack for data serialization, pako for compression, and trystero for peer-to-peer synchronization.

Community and Contributions:

• Encourages community involvement through discussions and contributions. For support, users can join GitHub Discussions or Gitter.

Licensing:

• The project is under the MIT License, with third-party dependencies having their own licenses.

Maintenance:

• The project is actively maintained and available for use, though only minified builds are currently provided.

For detailed documentation and examples, visit the project's GitHub Wiki.

Go's data race detector has a limitation that can lead to missed data races in certain situations. Although Go includes this tool to spot unsynchronized access to shared memory, it can overlook issues when specific locking mechanisms are involved.

In a particular example, two threads increment a shared counter. One thread uses a mutex (a type of lock) to control access, while the other thread performs an additional increment without the lock. This can create a race condition, but the data race detector may not always catch it, depending on the timing of thread execution.

The detector relies on "happens-before" relationships to identify whether two operations could occur simultaneously. However, the way locks are modeled can create blind spots. If the threads acquire locks in a certain order, the tool may incorrectly conclude that there is no race, even though a race could potentially occur with different timing.

Despite this limitation, Go's data race detector is still considered one of the best tools available for identifying data races in programming. Users should be aware of its boundaries, as a lack of reported races does not guarantee that the code is free of data races.

My name is Solène Rapenne (she/her). I enjoy learning and sharing knowledge. My hobbies include Qubes OS, BSD, OpenBSD, Lisp, command line gaming, security, and internet-related topics. I am a member of the Qubes OS core team and a former OpenBSD developer. I do not use AI on my blog. You can contact me at [email protected] or @[email protected] on Mastodon. I work as a freelance consultant for OpenBSD, FreeBSD, Linux, and Qubes OS, focusing on DevOps, DevSecOps, and technical writing.

The text discusses the Altima NSX, a laptop computer introduced in the early 1990s, focusing on its features, history, and reviews.

Key points include:

1. Background: Altima was a short-lived computer company that contributed to the personal computer market before disappearing. The author aims to highlight such companies in a newsletter.

2. Specifications: The NSX featured a 386SX processor, a VGA display, a 20MB hard drive, and weighed around 9-10 pounds. It included 2MB of RAM (expandable to 8MB), a built-in modem, and a backlit screen.

3. Performance: Reviews noted the NSX was heavier than typical notebooks and had a shorter battery life of about 1.5 hours. While it had a large display, its performance in terms of speed and battery life was considered average.

4. Design: The laptop was praised for its keyboard comfort and design, although it lacked portability due to its weight. It came with an external keyboard port and could connect to external monitors.

5. Pricing: The NSX was priced at $4,999 at launch, which put it above some competitors but was still considered a good value for its features.

6. Legacy: The laptop received mixed reviews but was noted for its rugged design and usefulness for power users. The author encourages readers to share their experiences if they have used an Altima NSX.

Overall, the text reflects nostalgia for early computer technology and the impact of smaller companies in shaping the industry.

Nova is a new web framework for Erlang aimed at making web development easier and faster. It takes advantage of Erlang's strengths in concurrency, reliability, and scalability to offer a lightweight framework for building modern web applications.

Key features include:

• Lightweight and modular: Easy to use with existing Erlang projects.
• Concurrency-focused: Utilizes Erlang's actor model for efficient web apps.
• User-friendly: Simplifies tasks like routing, middleware, and templates.
• Extensible: Allows for plugins and custom integrations.

You can check it out on GitHub or visit the homepage for more information. The developers welcome feedback from the community, especially from Erlang enthusiasts. They are interested in hearing thoughts on using Erlang for web development and any desired features for the framework.

No summary available.

The text discusses Lean, a programming language primarily used by mathematicians to formalize mathematics. Lean allows mathematicians to express mathematical concepts as code, enabling collaboration and sharing of theorems on platforms like GitHub.

The author provides an example of using Lean to prove a simple theorem: that 2 equals 2. They explain the syntax and tactics used in Lean, such as "sorry" (used as a placeholder for an incomplete proof) and "rfl" (which proves equality for the same numbers). The author contrasts correct proofs with incorrect or nonsensical ones, demonstrating how introducing a false axiom (e.g., claiming 2 equals 3) can lead to absurd conclusions like 2 + 2 equaling 6.

The text emphasizes that while Lean is a powerful tool for proving theorems, it is only as reliable as the axioms it’s based on. A real-world example is mentioned—Fermat’s Last Theorem—which took centuries to prove and is currently being formalized in Lean.

Finally, the author encourages readers to explore Lean through various resources, highlighting its enjoyable and thought-provoking nature.

Summary of Ollama's New App (July 30, 2025)

Ollama has released a new app for macOS and Windows that makes it easier to chat with AI models. Key features include:

• Chat with Models: Users can download and interact with different models.
• File Support: You can drag and drop text or PDF files for easier analysis. For large documents, you can increase the context length in settings, but this will need more memory.
• Multimodal Capability: The app allows sending images to compatible models, like Google DeepMind’s Gemma 3.
• Code Processing: Models can help understand code files.

You can download the new app from Ollama's website for macOS and Windows, or get the command-line versions from their GitHub releases page.

Summary: Advice for First-Time Managers

Congratulations on becoming a manager! This role can be challenging as you shift from doing the work yourself to helping others succeed. Here are some key points to keep in mind:

1. Shift Your Focus: Your job is no longer to do the work; it's to support your team. Trust them to deliver results instead of doing everything yourself.

2. Expect Mistakes: You will make mistakes as a manager. It's important to recognize them, learn from them, and be open about your errors. Your team needs a relatable leader, not a perfect one.

3. Communicate Clearly: Be explicit in your expectations and goals. Avoid ambiguity to help your team understand their roles and the significance of their work.

4. Learn from Your Boss: If you have a good manager, learn from them. If your boss is not great, don’t let their bad habits influence your management style. Set your own standard.

5. Take Care of Yourself: Management can be stressful, so prioritize your well-being to avoid burnout. Regular self-care is essential for you and your team.

6. Celebrate Team Successes: Your achievements are now tied to your team's successes. Recognize and empower their contributions instead of seeking personal accolades.

Remember, you won’t get everything right, but with humility and a desire to improve the work environment for your team, you can be an effective leader. You've got this!

Figma has announced that it is starting its roadshow for its planned Initial Public Offering (IPO). This event marks a significant step for the company as it prepares to go public.

No summary available.

The author shares their experience with coming up with ideas in the shower and how this relates to their struggles with management. Initially, while trying to manage a small team, they found themselves distracted by programming, which hindered their management effectiveness and led to mistakes. This experience highlighted the importance of focus in knowledge work, where productivity is tied to how much attention one can give to a task.

The author identifies strategies to improve focus:

1. Care Viscerally: Being emotionally invested in the work helps maintain focus.
2. Monotask: Working on one task at a time can lead to better outcomes, even if it feels less efficient in the short term.
3. Evade Obligations: Limiting commitments to avoid overwhelming distractions allows for better focus on priority tasks.
4. Timebox Minor Tasks: Setting aside specific times to handle minor chores prevents them from distracting from major projects.

In their later management role, the author found that being fully focused on management without distractions allowed for better performance. They noted that while they had challenges, their ability to concentrate improved significantly in this full-time role.

No summary available.

I'm unable to access external links, but if you provide the text or main points from the document, I can help you summarize it!

The provided text appears to be a long string of random characters and symbols, making it difficult to extract meaningful content or summarize. If you have a specific topic or clearer text you would like me to summarize, please provide that, and I would be happy to help!

The author compares orchestra conductors to prompt engineers in AI. Conductors guide musicians to improve their performance, while prompt engineers help AI models complete tasks effectively. Both roles involve communication and making choices based on skill levels: conductors select music appropriate for their ensemble's abilities, and prompt engineers craft prompts that minimize errors from AI.

The author believes current AI models are capable but still make many mistakes, likening them to high school musicians rather than professionals. While AI can handle simple tasks well, it struggles with more complex ones, similar to how a high schooler might falter with advanced music.

The analogy has limits; mistakes made by a musician may only disappoint their parents, but errors made by AI can have serious consequences, such as compromising data or failing to provide proper mental health support. The author expresses hope for future improvements in AI but remains skeptical about its potential impact if current limitations persist.

An Australian ship successfully navigated for six days using a new technology called a quantum dual gravimeter. This device, developed by Q-CTRL, serves as a backup for GPS, especially in situations where GPS signals are unreliable or jammed. It is the first of its kind for maritime use and is part of a broader solution to ensure safe navigation without relying solely on GPS.

More developers are using AI tools to help with coding, but a recent survey shows a growing distrust in these tools due to issues with accuracy. The 2025 Stack Overflow Developer Survey, which included over 49,000 developers, found that while AI usage increased to 84%, only 33% trust its accuracy—down from 43% the previous year. Many developers are frustrated with AI-generated code that is "almost right," requiring more time to fix than if they wrote it from scratch.

The survey highlights that developers are using multiple tools, adding complexity to their workflow. Even though AI tools promise productivity, they can create new technical challenges and security risks. Developers still rely heavily on human resources, like Stack Overflow, for help, with many turning to the platform after encountering issues with AI.

To improve AI integration, organizations are advised to invest in better debugging processes, maintain a pipeline of human expertise, adopt AI tools gradually, and focus on proper training for developers. The key to successful AI adoption lies in enhancing collaboration between AI tools and human developers, ensuring that AI contributes positively to productivity rather than becoming a source of technical debt.

Qwen3-Coder Collection Summary

• The collection contains 5 items.
• It was updated approximately 3 hours ago.
• The current status is rated 45.

Lucidic AI is a tool created by Abhinav, Andy, and Jeremy to help observe and debug AI agents. It allows users to easily track AI performance and issues with just one line of code. Key features include:

1. Easy Setup: Users can start by adding a simple command in their code and logging into the dashboard.
2. Debugging Tools: It provides visualizations of agent runs, trends, and failure modes, making it easier to identify problems.
3. Time Traveling: Users can modify the agent's state and re-simulate runs to see how changes affect outcomes.
4. Trajectory Clustering: This feature groups similar runs to reveal behavioral patterns and failure trends across multiple simulations.
5. Custom Evaluations: Users can create their own evaluation criteria (called "rubrics") to assess agent performance against specific requirements.

The tool can be accessed for free with limited features, and users can get started by visiting their dashboard. Feedback is welcomed, and they encourage users to reach out for support.

Summary:

Andrej Karpathy introduced the term "vibe coding," which refers to using AI to code without fully understanding the code itself. This concept relates closely to "legacy code," which is difficult to comprehend and maintain, leading to technical debt. Although vibe coding can be quick and fun for small, temporary projects (like prototypes), it can create significant problems if the code needs to be maintained later, especially for those without programming knowledge.

The text warns against non-programmers attempting large projects without understanding coding, comparing it to giving a credit card to a child. While AI tools like Townie can assist in vibe coding, it's crucial to use them wisely, especially for serious projects that require ongoing maintenance. The author emphasizes the importance of understanding the code and suggests that sometimes starting fresh with well-written code is better than trying to fix incomprehensible legacy code.

In conclusion, while AI is changing programming, fundamental coding skills remain essential for building complex software.

Google is testing a new technology in the U.S. that uses machine learning to estimate users' ages and adjust content accordingly. The company will analyze information from users' Google accounts, like their search history and YouTube viewing habits, to determine their age. If a user is identified as under 18, they will receive an email explaining the changes to their Google experience.

For users under 18, Google plans to:

• Disable timelines in Maps.
• Stop personalized ads and restrict certain ad categories.
• Prevent access to adult-themed apps on the Play Store.
• Activate features on YouTube for digital wellbeing, like reminders to take breaks and notifications to go to bed.

Users who believe they were wrongly identified as underage can appeal the decision by providing a government ID or a selfie.

This initiative follows similar measures implemented on YouTube and is part of Google's broader strategy to enhance age verification and ensure that younger users are protected online. Other platforms, such as Instagram and Roblox, are also using AI for age estimation, and lawmakers are working on regulations to protect minors online.

The author expresses frustration about how code is generated and integrated into projects, emphasizing they care more about the quality of the final code rather than the method used to create it. They point out that some code generated by large language models (LLMs) often does not adhere to established project conventions, making it clear that it wasn't written by a human developer.

The author believes that while speed in development is valued, it should not compromise the quality and maintainability of the software. They draw a parallel to a barista rushing to serve coffee, highlighting that people prefer quality over speed, even if it means waiting longer.

Ultimately, the author urges developers to prioritize quality, consistency, and the long-term impact of their work when using LLMs. They advocate for clearer prompts and better guidelines when generating code, and emphasize the importance of adhering to existing coding principles to ensure maintainable software.

Experts warn that air turbulence is becoming more severe due to the worsening climate crisis. Recently, a Delta Air Lines flight from Salt Lake City to Amsterdam had to make an emergency landing in Minneapolis after experiencing significant turbulence, injuring at least 25 passengers. Medical personnel were on hand when the plane landed, and those injured were taken to local hospitals.

One passenger described the turbulence as the worst he had ever experienced, noting that it caused objects, like a wine cart, to fly through the air. Experts predict that severe turbulence incidents could double or triple in frequency over the next few decades because of climate change. Since 2009, there have been 207 severe injuries reported in the U.S. related to turbulence.

The article discusses the decline of America as a leading scientific power, comparing it to the fall of the Soviet Union's scientific achievements. Roald Sagdeev, who began his scientific career in the Soviet Union during its peak, reflects on how corruption and ideological pressures undermined scientific progress there. He recalls the glory days of Soviet space achievements, but also highlights how political ideologies, particularly under Stalin, distorted scientific truth and limited innovation. The piece suggests that similar threats may be affecting America's current scientific landscape.

NASA's James Webb Space Telescope (JWST) has discovered numerous mysterious "little red dots" in the early universe, which could represent a new type of celestial object. These dots, observed within the universe's first billion years, are thought to be massive balls of hot gas powered by black holes, rather than traditional stars.

Astronomers, including Jenny Greene and Anna de Graaff, believe these "black hole stars" might be key to understanding galaxy evolution and the growth of supermassive black holes. Initially thought to be mature galaxies, these dots are too compact to be explained by conventional models, leading scientists to consider that their brightness comes from a surrounding gas shell heated by a black hole.

Research shows that the light emitted by these dots matches characteristics of gas around active black holes, suggesting they are dense gas cocoons. The discovery of these objects indicates a potential new phase of black hole growth and could reshape our understanding of galaxy formation.

While the little red dots are difficult to study due to their distance, recent findings of similar objects closer to Earth may provide more insights. If confirmed as black hole stars, this discovery would mark a significant breakthrough in astronomy.

The text discusses the concept of "Everything Machines," a term coined by journalist Karen Hao to describe modern AI systems. These systems are often portrayed as capable of solving any problem, but the author argues that they disconnect from the realities of what AI can truly do.

The author reflects on the idea of "friction," which, in technology, is often seen as something to eliminate for smoother user experiences. However, friction can also represent meaningful connections and social interactions. A frictionless experience can lead to individualism and isolation, as it caters solely to personal needs without acknowledging others.

AI systems, designed for frictionlessness, foster a sense of being unbothered by others and can contribute to feelings of loneliness. As people increasingly turn to chatbots for companionship, the promise of AI becomes one of avoiding real human interaction. Ultimately, the author warns that this "Utopia" of AI could lead to a dystopia where individuals are never truly touched or impacted by the world around them.

The U.S. government is investigating Brazil's popular digital payment platform, Pix, due to concerns that it may be unfairly restricting American companies like Apple Pay and Google Pay. Pix, which is free to use and managed by Brazil’s central bank, has rapidly gained users — about 160 million Brazilians now use it, compared to only a small percentage using American alternatives.

The investigation reflects growing geopolitical tensions, as the U.S. seeks to counter Brazil’s ties with China and gain access to consumer data. Experts suggest that the U.S. aims to enhance competition for American companies and encourage Brazil to align more closely with the West.

Since its launch in 2020, Pix has transformed payment habits in Brazil, surpassing traditional payment methods like credit and debit cards. This investigation has sparked resentment among Pix users, who view it as a challenge to their national pride and a threat to their publicly managed payment system.

No summary available.

Summary: Data Privacy Concerns with Matrix for EU Organizations

Matrix, a decentralized communication platform, poses significant risks for EU organizations regarding data privacy and compliance with laws like GDPR. Key points include:

1. Jurisdiction Issues: Matrix's main client, Element, is based in the UK, which is no longer governed by EU laws due to Brexit. UK surveillance laws, such as the Investigatory Powers Act, can compromise data security and privacy.

2. Encryption Limitations: Although Matrix uses end-to-end encryption (E2EE), its protocols (Olm for one-on-one chats and Megolm for groups) do not fully protect metadata, such as who is communicating and when. This metadata can be exposed during transmission, violating EU privacy standards.

3. Federation Risks: Matrix allows open communication between servers, which can lead to unauthorized servers causing spam and data leaks. This open model increases the risk of violating GDPR by inadvertently sharing personal data with non-EU entities.

4. Commercial Solutions with Drawbacks: Element offers a Secure Border Gateway to address federation risks, but it is a closed-source solution that users cannot audit, raising concerns about compliance and trust.

5. Governance Concerns: The Matrix Foundation is losing its independence as Element gains more control over its operations, creating potential conflicts with privacy governance.

6. Safer Alternative - Wire: For EU organizations seeking secure communication, Wire is recommended. Based in Switzerland, it offers stronger data protection, better compliance with EU laws, and advanced security features without the risks associated with Matrix.

In conclusion, Matrix may not be a safe option for organizations needing to comply with stringent EU data privacy laws, highlighting the importance of choosing platforms that ensure true privacy and security.

Summary: Fixing Ctrl+C in Rust Terminal Apps

When you use Ctrl+C in terminal applications that manage child processes, it can lead to a messy terminal and processes that don’t shut down properly. This guide explains how to fix these issues, using the Moose CLI as an example.

Key Problems:

1. Terminal Corruption: After pressing Ctrl+C, the terminal may behave incorrectly, like hiding the cursor or mixing outputs.
2. Hanging Processes: Child processes might not receive the right signals to terminate, leading to them running in the background.
3. Race Conditions: Conflicts can occur between cleanup tasks and child process outputs.

Solutions:

1. Process Output Management:

   • Isolate output from child processes to avoid conflicts.
   • Use logging systems instead of directing outputs to the terminal.
   • Ensure all output is processed before cleanup.

2. Terminal State Management:

   • Always clean up the terminal when the application exits.
   • Use libraries like crossterm for consistent terminal handling.

3. Graceful Process Termination:

   • Attempt to shut down processes gently before forcefully terminating them.
   • Maintain a list of all spawned processes for tracking.

4. Thread-Safe Management:

   • Coordinate spinners and other interactive elements to avoid display issues.
   • Use atomic operations for smooth communication between threads.

Testing Strategies:

• Test how the application handles signals.
• Check for race conditions and ensure terminal states are correct.

Common Mistakes to Avoid:

• Don’t send child process output directly to the terminal.
• Always consider input handling and ensure that threads are properly managed.

Conclusion: To create effective terminal applications, focus on managing child processes well. This includes isolating outputs, cleaning up the terminal state, and ensuring smooth process shutdowns. Following these practices will enhance user experience and prevent terminal issues.

Meta is significantly increasing its investment in AI infrastructure, planning to spend between $66 billion and $72 billion in 2025, which is about $30 billion more than the previous year. This investment will help build data centers and servers to support their AI initiatives. Meta expects similar increases in spending for 2026 as it aims to enhance its AI capabilities.

The company is developing major AI clusters, including Prometheus in Ohio and Hyperion in Louisiana, which will be among the largest AI superclusters. These projects will require substantial energy, potentially impacting local communities, as seen in Georgia where some residents have experienced water shortages due to Meta's activities.

Meta is also focusing on attracting AI talent, expecting this to be a key driver of growth. Despite a significant loss in its Reality Labs division, the company's overall revenue was strong, reaching $47.5 billion in the second quarter, boosted by AI tools that enhance advertising.

Overall, Meta is committed to building a leading AI infrastructure to improve its products and services.

Summary of "Emacs: The macOS Bug"

The author has been experimenting with various programming languages and took time to debug a long-standing issue with Emacs on macOS, which has been slow and memory-intensive. They found that Emacs' performance drops drastically over time, often requiring a restart.

Key Points:

1. Performance Issues: Emacs on macOS consistently increases in RAM usage, slows down, and sometimes freezes, unlike its performance on Linux or Windows.

2. Underlying Cause: The issue stems from how Emacs interacts with the macOS event handling system. Frequent memory allocation and deallocation occur when handling user events, leading to inefficient memory usage.

3. Complexity of Code: The code handling these operations is complex, shaped by years of changes to the macOS API and not being Emacs' primary platform. This has made troubleshooting difficult.

4. Resource Management: Faster Macs exacerbate the problem, as they handle events quickly, leading to more rapid and unnecessary memory allocations that the system starts to cache, causing further slowdowns.

5. Proposed Solutions: Fixing the issue is challenging due to the code's complexity. However, discussions are ongoing about improving the event queue and threading in Emacs. The author suggests moving some code to Swift, which could enhance memory management and threading safety.

6. Future Vision: There's hope that improvements could lead to a more efficient Emacs on macOS, potentially paving the way for better cross-platform support.

Overall, Emacs on macOS is compared to a high-performance car that struggles due to design limitations, and while there are ideas for improvement, significant changes are needed.

The author describes themselves as a "side project collector," having started several projects that they never finished. They've attempted a software service for freelancers, an AI tool, and a unique social network, but lost interest in each. Their collection of domain names represents many unfinished ideas. Despite not completing these projects, the author feels they've gained valuable knowledge and enjoyment from the process. They remain hopeful that one day, they might successfully launch a project. They invite others with similar experiences to share their own successes and failures.

No summary available.

Apache Flink 2.1.0 has been released, marking a major step in its development as a unified platform for real-time data processing and AI. This version includes contributions from 116 global contributors, implements 16 improvement proposals, and fixes over 220 issues, focusing on integrating AI with data processing.

Key Features:

1. Real-Time AI Enhancements:

   • AI Model Management: Users can now manage AI models using Flink SQL and the Table API.
   • Real-Time Predictions: The ML_PREDICT function allows for real-time AI model usage within SQL queries.

2. Improved Data Processing:

   • Process Table Functions (PTFs): These functions enable more complex data transformations and event processing.
   • New VARIANT Data Type: This type efficiently handles semi-structured data like JSON, making data analysis more flexible.

3. Optimized Streaming Joins:

   • DeltaJoin and MultiJoin: New strategies reduce resource usage and improve performance in streaming jobs.

4. Additional Features:

   • Support for custom batching in asynchronous sinks, improved metrics for monitoring, and new SQL connectors for better state management.

5. Python Support:

   • PyFlink now supports Python 3.12 while dropping support for Python 3.8.

Overall, Flink 2.1.0 enhances its capabilities in real-time data processing and AI integration, providing tools for enterprises to make intelligent decisions based on real-time analytics. Users are advised to review the upgrade notes for any necessary adjustments.

The text discusses the benefits of using shorter trains in urban metro systems. Here are the key points:

1. Cost Savings: The biggest expense in metro systems is often the stations, which can be made smaller for shorter trains, leading to significant cost reductions (about 15-20% depending on the type).

2. Faster Construction: Smaller stations are quicker to build, which can reduce project timelines by 30-40%, allowing for faster implementation of transit systems.

3. Increased Frequency: Shorter trains allow for more frequent service, which improves the overall experience for passengers since waiting times are reduced.

4. Flexibility and Experience: Smaller train systems can be built incrementally, providing valuable experience for future projects, especially in places like the US that lack recent infrastructure development.

5. Capacity Management: With automated trains, running more frequent short trains is feasible and can meet passenger demand without the need for longer trains, which can be more costly to operate.

6. Examples of Success: Successful implementations of this concept include Vancouver’s Skytrain, London’s DLR, and the Copenhagen Metro, which were built efficiently at lower costs.

7. Potential for Jersey City: The text suggests Jersey City could benefit from developing a small, efficient metro system to enhance its growth and connectivity to New York City.

8. Caution Against Poor Implementation: The author warns against creating “small trains” without a proper plan, as this could lead to unnecessarily large and expensive infrastructure, negating the benefits of smaller systems.

Overall, the author advocates for adopting shorter trains as a smart strategy for improving urban transit systems.

Emiel Kollof reported that a certain project or software doesn't work properly yet and won't build successfully. He tested it on the latest version available and confirmed the issue as of July 30, 2025.

Hyprnote is an open-source, privacy-focused AI note-taking app created by Yujong, John, Duck, and Sung. It operates entirely on your device, meaning no data is sent to the cloud or external servers. This app was developed after hearing that some people were uncomfortable with using certain note-taking tools due to data privacy concerns, leading them to revert to manual note-taking.

Hyprnote can transcribe and summarize meetings locally by capturing audio from your microphone and system. It uses local AI models, including Whisper and HyprLLM, to generate summaries. The team acknowledges that improving the summarization abilities of their model is a work in progress.

The app also supports custom endpoints for users to integrate their company's internal models and offers an optional self-hosted server component for team collaboration. They aim to enhance the app's functionality, similar to VSCode, by allowing extensions and customizable workflows.

The creators believe that privacy-first applications powered by local AI models will drive the next generation of AI tools. They welcome feedback on their project.

GDAL (Geospatial Data Abstraction Library) is an open-source library used for translating and processing raster and vector geospatial data formats. It is maintained by the Open Source Geospatial Foundation and offers a unified data model for various formats along with command line tools for data manipulation.

Key features include:

• Support for Multiple Formats: GDAL supports a wide range of raster and vector formats, making it versatile for geospatial data handling.
• Utilities: It includes command line utilities for data translation and processing tasks.
• Documentation: Comprehensive documentation is available online and as downloadable PDFs for offline access.
• Community and Development: GDAL has an active community, and users can contribute or seek help through mailing lists and forums.
• APIs: It provides APIs in several programming languages, including C, C++, Python, and Java.

GDAL is licensed under an MIT-style open-source license, ensuring it is free to use and modify.

The text discusses a significant security vulnerability found in Base44, a platform for "vibe coding," which allows users to create applications using natural language prompts instead of traditional coding. This vulnerability enabled unauthorized access to private applications, posing risks to sensitive corporate data.

Key points include:

1. Vibe Coding Revolution: Platforms like Base44 allow non-technical users to build applications easily, leading to widespread adoption in various enterprises.

2. Identified Vulnerability: Wiz Research discovered a flaw in Base44 that allowed anyone to register for private applications using only a publicly visible app ID. This flaw bypassed all authentication measures, including Single Sign-On.

3. Immediate Response: Upon discovering the vulnerability, Wiz responsibly reported it to Base44 and Wix, who quickly confirmed and fixed the issue within 24 hours, finding no evidence of exploitation.

4. Shared Risk Model: The vulnerability highlights the risks of relying on shared infrastructure in vibe coding platforms, where a single flaw can jeopardize many applications.

5. Impact Assessment: The flaw could have allowed attackers to access sensitive data across various enterprise applications, although no actual breaches were reported.

6. Security Recommendations: Organizations using Base44 are advised to review their application settings and monitor for unusual activity, even though the vulnerability has been resolved.

7. Call for Better Security: The incident emphasizes the need for robust security measures in AI development platforms to protect user data and maintain trust.

Overall, the document serves as a reminder of the importance of security in rapidly evolving tech landscapes, urging developers and users to prioritize security alongside innovation.

A recent expedition to the deep ocean has revealed surprising communities of life at depths exceeding 9 kilometers (5.6 miles) in the northwest Pacific Ocean. A research team led by Chinese scientists used a submersible, Fendouzhe, to explore these extreme environments, capturing images of various creatures, including tube worms and clams. This mission documented life at depths previously thought to be less populated, with scientists noting the abundance of animals they observed as "amazing."

The expedition covered over 2,500 kilometers and found thriving ecosystems fueled by chemicals like hydrogen sulfide and methane that seep from the ocean floor, rather than sunlight. Observations included species never seen before, prompting further research into how these creatures survive and convert chemicals into energy under immense pressure.

The findings challenge previous beliefs about the scarcity of life at such depths, suggesting that ecosystems driven by methane may be more common than expected. Scientists expressed excitement about the discoveries, emphasizing the potential for future exploration and understanding of deep-sea life.

Summary of "Tracking Source Locations"

Futhark is a programming language designed for speed, but sometimes programmers create slow programs and need to understand why. Profilers help by showing how long different parts of a program take to run. Although Futhark initially had limited profiling capabilities, a recent update improved its profiling tool, making it easier to understand where time is spent in the code.

Previously, Futhark's profiling output was difficult to interpret because it used compiler-generated names that programmers couldn’t recognize. To address this, the author introduced the concept of "provenance," which connects the generated code back to the original source code. This was challenging because the Futhark compiler optimizes and rewrites code, making it hard to track where it originated from.

The solution involved enhancing how the compiler attaches information to code statements, allowing it to maintain a record of where each part of the code comes from. This change means that when profiling data is generated, it includes detailed source information, helping programmers identify slow sections of their code more effectively.

Going forward, the author plans to improve how profiling information is presented, making it easier to read and use. Ideas include creating visual heat maps of code performance and refining how the profiler links slow GPU operations back to specific parts of the source code. The ultimate goal is to provide clearer insights and suggestions for optimizing Futhark programs, enhancing the user experience significantly.

Researchers have used advanced imaging to study the tattoos on a 2,500-year-old Siberian "ice mummy," revealing intricate designs of animals like leopards, a stag, a rooster, and a mythical griffin. This woman, from the nomadic Pazyryk culture, was about 50 years old when she died. The tattoos, which are highly detailed and sophisticated, reflect the artistry of ancient warrior societies.

Archaeologists collaborated with a modern tattooist to understand the tattooing techniques used. They discovered that the quality of tattoos varied between her arms, suggesting different artists or errors during the process. The tattoos were likely applied using stenciling techniques, with tools made from animal materials.

The findings highlight the skill involved in ancient tattooing and provide insights into the cultural significance of these markings during life, although they appeared to hold little meaning in the afterlife. The research was published in the journal Antiquity.

Microsoft has released the sixth preview of .NET 10, introducing various enhancements for application development, including better JSON handling, updates for Blazor WebAssembly, ASP.NET Core, .NET MAUI, and improvements to .NET tools.

Key features of .NET 10 Preview 6 include:

• Improved JIT Code Generation: The Just-In-Time (JIT) compiler can now optimize struct arguments better, enhancing performance through techniques like loop inversion.
• One-Shot Tool Execution: Developers can run .NET tools without needing to install them, which is useful for continuous integration and temporary uses.
• JSON Property Handling: A new option allows developers to disallow duplicate JSON properties, addressing potential security issues.
• Cross-Platform Tool Support: Tools can now be packaged with multiple RuntimeIdentifiers, simplifying distribution across different platforms.
• New CLI Schema Option: A new command option outputs a JSON representation of command trees for better integration and scripting.
• Native Executable Support: File-based apps can now be published as native executables easily.
• Blazor Enhancements: Introduces a component for preloading assets and improved form validation features.
• WPF and Windows Forms Updates: Improvements include a better Fluent theme and enhanced dark mode support.

This preview follows previous versions and aims to further enhance developer experience and application performance. The full release of .NET 10 is expected in November. Developers can download the preview from the official .NET website.

Summary of Cryptography & Security Newsletter #127

Encrypted Client Hello (ECH) Approved for Publication

• ECH has been approved by the TLS working group and will be published as an RFC, aiming to enhance privacy in TLS communications.
• TLS 1.3, released in 2018, modernized encryption but left certain features, like the server identity, in plaintext. ECH addresses this gap.

How ECH Works

• ECH uses special encryption keys stored in DNS records to protect server identity during the TLS handshake, which is necessary for setting up encryption.
• These keys can also provide connection parameters like ALPN and IP address hints.

Privacy Concerns

• ECH is supported by major browsers and Cloudflare, but its use raises privacy issues, especially in countries like Russia and China that may block or monitor encrypted traffic.
• While ECH can obscure the websites users visit, it also makes users noticeable to authorities, which can be risky.

Additional News Highlights

• New security features and updates, including a first IP address certificate from Let's Encrypt and updates on various cryptographic protocols and vulnerabilities.
• Ongoing discussions about age verification measures in the UK and the EU's plans for potential decryption backdoors by 2030.

This newsletter aims to keep readers informed about developments in cryptography and security, enjoyed by over 50,000 subscribers.

Summary of Data Representation Formats: XML, JSON, and CBOR

In the world of computing, exchanging data is crucial for various applications, and there has been an evolution of data formats to address different needs. This overview focuses on three key formats: XML, JSON, and CBOR.

1. XML (Extensible Markup Language):

   • Origins: Developed from SGML (Standard Generalized Markup Language) in the 1990s by the W3C to create a structured way to share data on the web.
   • Features: Uses a tag-based structure that allows for complex documents and supports validation through schemas. It is human-readable but can be verbose, which can lead to inefficiencies.
   • Adoption: Widely used in web services and document formats, XML played a crucial role in structured data exchange, especially in enterprise settings.

2. JSON (JavaScript Object Notation):

   • Emergence: Created by Douglas Crockford in the early 2000s as a lightweight alternative to XML, particularly for web APIs and data interchange between servers and browsers.
   • Design: Based on JavaScript object syntax, JSON is simpler and more compact than XML, focusing on key-value pairs and arrays. This simplicity makes it easier to parse and reduces bandwidth usage.
   • Popularity: JSON rapidly gained traction and became the standard for RESTful APIs due to its efficiency and ease of use across various programming languages.

3. CBOR (Concise Binary Object Representation):

   • Development: Designed for constrained environments like the Internet of Things (IoT), CBOR is a binary format that combines the data model of JSON with the efficiency of binary encoding.
   • Advantages: Offers smaller message sizes and faster parsing compared to text-based formats, making it ideal for devices with limited resources.
   • Standardization: Established by the IETF, CBOR maintains compatibility with JSON while adding features for binary data and extensibility.

Conclusion: The evolution from XML to JSON and then to CBOR reflects a trend toward optimizing data formats for specific use cases. While XML is robust for complex documents, JSON simplifies data interchange, and CBOR enhances efficiency for constrained environments. Each format has its strengths, leading to a landscape where multiple formats coexist based on application needs.

Crush Overview

Crush is a coding tool designed to enhance your coding experience in the terminal, integrating various tools and workflows with your preferred large language models (LLMs).

Key Features:

• Multi-Model Support: Choose from many LLMs or add your own using OpenAI or Anthropic APIs.
• Flexible Switching: Change LLMs during a session while keeping context.
• Session Management: Handle multiple projects and contexts simultaneously.
• LSP Enhanced: Uses Language Server Protocols for added context.
• Extensibility: Add new capabilities via Model Context Protocols (MCPs).
• Cross-Platform Compatibility: Works on macOS, Linux, Windows, and more.

Installation Options:

• Install via package managers such as Homebrew, NPM, or Nix.
• Available in Debian and RPM formats, or can be installed using Go.

Getting Started:

• Set up an API key from your preferred provider (like OpenAI or Anthropic) to start using Crush.
• Configuration is simple, with options to customize settings stored in JSON format.

Customization:

• Add LSPs and MCPs for enhanced functionality.
• Whitelist tools for permission-free usage.
• Support for custom API configurations.

Logging:

• Crush logs activities for easy tracking, with commands available for viewing recent logs.

Community and Support:

• Engage with the community on platforms like Twitter, Discord, and Slack for support and feedback.

License: Crush is open-source and follows the FSL-1.1-MIT license.

The author shares their journey into embedded software development and PCB design after university. They initially found the transition from software to hardware design enjoyable, despite assuming it would be difficult. The main challenge they faced was organizational, particularly in managing components for their projects.

As they designed circuits, they discovered that sharing components between different designs led to confusion about their inventory. This made it hard to know what parts were available and what was needed for new builds. Unlike software development, where dependencies can be easily managed, keeping track of physical components proved complicated.

To solve this, the author developed a program to organize their electrical components using a grid system based on the open-source Gridfinity storage system. They designed bins for each component and created a labeling system to keep everything organized. The software allows them to manage a Bill of Materials (BOM), showing the location of all components needed for their circuit designs.

Although the software is functional, the author plans to add features like BOM export for bulk purchases and improved search capabilities. They enjoyed building the software and previously created a command-line version for testing purposes. Future plans include sharing a blog post about the software's development and architecture.

No summary available.

The text mentions an interactive map that has been contributed by the US. However, there are no further details provided about the content or purpose of the map.

Christian, co-founder of Frigade, introduces an AI agent designed to enhance user experience with web-based products. This agent learns to navigate applications, guides users directly, generates documentation, and performs tasks on their behalf, similar to a more advanced and helpful version of Clippy from MS Office.

Frigade AI stands out from typical AI customer support tools, which often act as simple chatbots providing vague help. Instead, Frigade guides users in real time based on their specific context, allowing the agent to take actions like inviting colleagues or retrieving billing info.

Recent advancements in AI technology have made this possible, as models can now understand software interfaces better than before.

To use Frigade, you simply invite the agent to your product, let it explore your application, optionally attach resources, and install a small JavaScript snippet. This setup is quick, enabling users to ask questions and receive immediate assistance. Feedback can further improve the agent's performance, and developers can integrate their code for more functionality.

Christian invites feedback from the Hacker News community on this approach and whether they are developing their own AI agents or looking for existing solutions.

No summary available.

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AgentGuard is a tool designed to help AI developers avoid excessive API charges, which can happen when an AI agent enters an infinite loop. It monitors API usage in real-time and automatically stops the process when a budget limit is reached, preventing costly mistakes.

To use AgentGuard, you simply add two lines of code to your existing AI project. For example, setting a budget limit of $50 is easy, and it tracks costs automatically. When your usage hits the limit, it stops the execution and informs you of what happened.

The creator developed this tool because many developers often report unexpected high charges from OpenAI. While some existing tools can measure costs after they occur, AgentGuard prevents overspending in real-time.

Currently, it is compatible only with OpenAI and Anthropic APIs, and the cost estimates are based on their documented pricing.

To install AgentGuard, you can use the command: npm i agent-guard. For more information, visit the GitHub page.

Winston, Edward, and James have developed Meka Agent, an open-source framework that allows vision-based language models to perform tasks on a computer like a human. Initially, they created agents for quality assurance testing but found existing browsing frameworks lacking. They built a browsing agent that achieved a score of 72.7% on WebArena, surpassing OpenAI's ChatGPT agent, which scored 65.4%.

Meka offers several key features:

• True vision-based control: It can see the screen and interact with elements directly.
• Full computer access: Unlike browser-only tools, Meka can manage system-level tasks.
• Extensible: Users can easily integrate their own language models and systems.
• High performance: It boasts a strong performance score.

Their goal is to help developers automate tasks on any computer simply by directing the agent. They invite feedback and encourage users to try Meka via their GitHub repository and hosted platform.

The text details the online availability of the magazine "Fantasy & Science Fiction" from June 1953. Here are the key points:

• The magazine is part of the Internet Archive and can be read online using a JavaScript-enabled browser.
• It consists of 130 pages and offers various viewing options, like one-page and two-page views.
• Users can share the magazine on social media or embed it on other sites.
• It has a publication date of June 1953 and is available in English.
• The item is part of several collections, including fantasy, science fiction, and pulp magazines.
• There are multiple download options for different formats, including PDF, EPUB, and DAISY for users with print disabilities.
• The magazine was uploaded by "The Pulp Librarian" on May 1, 2017, and has received over 1,800 views.

Overall, the text provides information on how to access and share a historical publication.

No summary available.

Ezra Klein and Derek Thompson’s book, Abundance, argues that the American government has become inefficient at building infrastructure due to excessive regulations and bureaucratic processes. This issue is highlighted by a specific example: a proposed EV charging station in Seattle, which was supposed to take three months to complete but has been delayed for three years without any construction progress.

The project faced numerous bureaucratic hurdles, such as vendor changes and redesigns, rather than issues like funding or community opposition. Klein and Thompson suggest that the government has shifted from a focus on outcomes to one focused on processes, making even small projects complicated. They advocate for a more effective governance approach that prioritizes execution over caution.

The failure to build simple infrastructure, like the eight EV charging spaces, reflects larger issues in the government's capacity to deliver essential services. Delays in projects impact public adoption of electric vehicles, housing availability, and overall economic growth. Klein and Thompson emphasize the need for streamlined approval processes and efficient government action to rebuild trust in public institutions and tackle significant challenges.

The empty lot in Morgan Junction serves as a symbol of these systemic inefficiencies, highlighting the urgent need for reform in how government executes infrastructure projects.

The article discusses a custom Python dictionary class called TrackingDict that helps track which keys have been accessed. This is useful when working with large data sets, like when retrieving information from a database, to ensure all retrieved data is used in reports.

Key Features:

• Initialization: Inherits from the standard dictionary and initializes a set to keep track of accessed keys.
• Key Accessing: Overrides the __getitem__ method to add accessed keys to the tracking set.
• Accessed and Never Accessed Keys: Provides properties to retrieve accessed keys and those that were never accessed.

Example:

When a TrackingDict instance is created with user information and certain keys are accessed, the class can report:

• Accessed keys: {'name'}
• Never accessed keys: {'email', 'age'}

This can be helpful for unit testing to ensure all data is checked. An updated version includes type hints for better clarity in code.

Additional Notes:

• There are discussions in the comments about improving functionality, such as handling the .get() method and tracking unused keys over time.

A recent article discusses how negative capacitance can enhance gallium nitride (GaN) devices, improving their performance without the typical drawbacks. This advancement helps overcome limitations in transistors, making them more efficient. The author, Katherine Bourzac, emphasizes the potential benefits of using ferroelectric materials in semiconductor technology.

TUXEDO Computers has announced the InfinityBook Pro 15 Gen10 laptop, designed for Linux users and powered by AMD's Ryzen AI 300 series processors, featuring Zen 5 cores and integrated Radeon graphics. This laptop has a 15.3-inch screen with a resolution of 2560 x 1600 and a brightness of 500 nits. It supports up to 128GB of RAM and has a long-lasting 99 Wh battery.

The laptop will be available in several configurations, ranging from the Ryzen AI 7 350 to the Ryzen AI 9 HX 370. However, the software support for the Ryzen AI features is currently limited. The starting price is 1090 EUR for the base model, which is higher compared to other laptops with similar features that have been available since July 2024.

The InfinityBook Pro 15 Gen10 will officially launch in August 2025. More details can be found on TUXEDO Computers' website.

Optician Sans Summary

Optician Sans is a free font inspired by traditional eye charts used by opticians worldwide. It is designed to improve readability and is based on the visual principles of the LogMAR chart, which estimates visual acuity.

Key points include:

• Background: The font builds on the historical Snellen chart (developed in 1862) and the Sloan chart (introduced in 1959), ensuring effective letter selection for legibility.
• Purpose: It aims to help patients see commercial information clearly, reflecting the designer's commitment to their profession.
• Design Features: Includes custom alternate glyphs for a cohesive appearance and is fully functional for display use.
• Licensing: Released under the SIL Open Font License, it is open source and available on GitHub.
• Creators: Developed by ANTI Hamar and typographer Fábio Duarte Martins.

For more details or to use the font, images, and other resources, you can contact them via email or access their Dropbox folder.

Many people are now self-hosting services and creating home labs with mini racks. One challenge I've faced is quickly checking the health status of these services and controlling my Raspberry Pi remotely. This led me to think about creating a user-friendly graphical interface (GUI) that can be added to Raspberry Pi nodes in various setups.

I previously designed this GUI for an open-source project called Ubo pod and decided to make it a standalone module. The GUI allows users to manage their Raspberry Pi, monitor system resources, and check application status. I'm also designing a new printed circuit board (PCB) and enclosure for this module to fit server racks.

I’m sharing my redesign journey and would appreciate early feedback, especially regarding hardware needs. The software for the GUI is already fully developed and can be tested online. You can find the PCB designs and more information through the provided links.

Summary of Samsung Galaxy Z Fold 7 Review

The Samsung Galaxy Z Fold 7 is a significant upgrade over its predecessor, offering a thinner and lighter design while addressing previous issues with foldable phones. Priced at $1,999, it boasts a 200 MP camera, improved displays, and powerful multitasking capabilities.

Key Features:

• Design: It has a sleek profile, measuring just 8.9 mm thick when folded and weighing 215 g, making it comparable to regular smartphones.
• Display: The cover screen is 6.5 inches with a 120 Hz refresh rate, while the inner display is an 8-inch flexible OLED, also 120 Hz.
• Camera: The camera system features a 200 MP main sensor, a 12 MP ultrawide, and a 10 MP telephoto lens, providing substantial improvements in image quality.
• Performance: It runs on the Snapdragon 8 Elite chip with options for 12GB or 16GB of RAM, ensuring high-speed performance for gaming and multitasking.
• Battery: The 4,400 mAh battery lasts about a day, but charging speeds are slower, maxing out at 25W.

Pros:

• Slim and lightweight design.
• Excellent camera and display quality.
• Strong multitasking capabilities and robust software support.

Cons:

• High price point.
• Average battery life and charging speed.
• Some software features and apps can feel redundant.

Overall, the Galaxy Z Fold 7 feels like a practical option for those seeking a foldable phone, though its steep price may deter some buyers.

Wind farm developers in northern Europe are facing a new concern as the number of offshore wind farms increases. Larger and more numerous turbines can reduce the wind available to neighboring farms, leading to less power generation. This situation is similar to a neighbor blocking your view after you've built a new house. As the seabed becomes more crowded with turbines, the issue of wind "theft" from existing farms is becoming more significant.

The blog series "Writing an OS in Rust" by Philipp Oppermann guides readers through creating a small operating system using the Rust programming language. Each post serves as a tutorial, providing necessary code and linking to a GitHub repository for further exploration. Key topics include:

1. Freestanding Rust Binary: Initial setup to run Rust code without a standard library.
2. Minimal Rust Kernel: Building a basic 64-bit kernel that can display text.
3. VGA Text Mode: Implementing a safe interface for displaying text on screen.
4. Testing: Techniques for unit and integration testing within the kernel.
5. CPU Exceptions: Setting up a system to handle CPU exceptions.
6. Double Faults: Preventing system resets by managing double faults.
7. Hardware Interrupts: Configuring interrupts for hardware events like timers and keyboard input.
8. Memory Management: Introducing paging and implementing memory allocation techniques.
9. Multitasking: Exploring cooperative multitasking and Rust's async/await feature.

Users can subscribe for updates and access older editions of the blog, but the current version focuses on the latest practices and libraries. Support for the blog is encouraged through sponsorship on GitHub. The content is also available in multiple languages.

Summary: "The Hype is the Product" by Michał Woźniak

Large tech companies are increasingly prioritizing their stock prices over their customers' needs. They focus more on pleasing stockholders than on providing quality products or services. This shift has led to a monopoly business model, where companies create barriers that make it difficult for users to switch to competitors, resulting in exploitation of customers.

The lack of interoperability between major services, like Google Workspace and Microsoft 365, exemplifies this issue. Users often feel trapped, as migrating to another service is too challenging. This situation allows companies to prioritize hype over actual product quality. For example, they may hype "AI" to make their stock appealing, even if the technology isn’t as beneficial as promoted.

Despite many users being unhappy with these services, they remain stuck due to the high switching costs. Companies capitalize on this by generating hype to boost their stock prices, often at the expense of product usefulness and user satisfaction. As one tech trend fades, another, like "quantum computing," is ready to take its place in the hype cycle. Ultimately, the hype itself becomes the product.

No summary available.

Summary: Cracking the Code of Pistachio Genetics

Researchers at the University of California, Davis, have created a detailed DNA map of the pistachio, which is crucial for improving the nut's nutritional value and sustainability. California produces almost all of the U.S. pistachios, making this research economically significant.

This new genetic map is much more precise than previous versions, allowing plant breeders to develop better pistachio varieties, especially as climate change poses challenges like warmer winters that affect crop yields. The study also outlines four key stages of pistachio growth, helping farmers manage their crops more effectively and sustainably.

Additionally, the research identifies genetic factors that influence the nuts' nutritional content, paving the way for breeding healthier pistachios in the future. This work is funded by various agricultural organizations and aims to enhance both the quality and sustainability of pistachio production.

This blog post outlines how to configure Apache APISIX for load balancing AI/ML API traffic between different versions. Here are the main points:

1. Overview of AI/ML API: The API is a comprehensive endpoint compatible with OpenAI and used by over 150,000 developers, providing access to various AI models.

2. What is Apache APISIX?: It is a high-performance API gateway that offers extensive traffic management features and can be adapted as an AI gateway through plugins.

3. Purpose of the Guide: The guide details how to:

   • Install Apache APISIX using Docker.
   • Secure the Admin API.
   • Set up routes for different API versions.
   • Implement traffic splitting between these versions.
   • Test and monitor the setup.

4. Installation Steps:

   • Download and run a quickstart script to set up APISIX with etcd.
   • Verify that APISIX is running properly.

5. Security Setup:

   • Enable authentication for the Admin API using a generated admin key.
   • Whitelist IPs to restrict access.

6. Route Definition: Create routes for version 1 and version 2 of the API to ensure they work individually before traffic splitting.

7. Traffic Splitting: Use the traffic-split plugin to distribute traffic evenly (50/50) between the two versions. This can be adjusted to different ratios for testing purposes.

8. Verification and Testing:

   • Test the new endpoint to ensure it is functioning as expected.
   • Conduct load testing to validate the distribution of requests between the two API versions.

9. Best Practices: Recommendations include implementing rate limiting, authentication, circuit breakers, observability tools, and using Infrastructure as Code for better management.

This guide provides a comprehensive approach to setting up and managing AI/ML API traffic using Apache APISIX, ensuring security and performance.

No summary available.

Traccar Overview

Traccar is an open-source GPS tracking system that provides a Java-based back-end service. It supports over 200 GPS protocols and more than 2000 GPS device models. Traccar works with major SQL databases and offers a user-friendly REST API.

Components:

• Web App: Traccar web application for tracking.
• Mobile Apps:
  • Traccar Manager for Android and iOS.
  • Traccar Client for Android and iOS for tracking mobile devices.

Features:

• Real-time GPS tracking
• Monitoring of driver behavior
• Detailed and summary reports
• Geofencing capabilities
• Alarms and notifications
• Account and device management
• Support for email and SMS

Team Contacts:

• Anton Tananaev: [email protected]
• Andrey Kunitsyn: [email protected]

License: Traccar is licensed under the Apache License, Version 2.0. This means you can use it freely, but there are no warranties provided. For more details, visit the Apache website.

Summary:

Hackers attempted to steal money from a bank by planting a Raspberry Pi device with a 4G modem in its network. This allowed them to bypass security measures and access the bank's internal systems. The hackers, known as UNC2891, used advanced methods to hide their malware, including disguising it as legitimate software to evade detection.

Their goal was to compromise the bank's ATM systems by manipulating a security device that protects sensitive data. The attack was discovered before the hackers could successfully exploit the ATM network. Researchers noted the unusual tactic of physically installing the Raspberry Pi in the bank's infrastructure, which was a new method for such cyberattacks.

Lovable, a Swedish startup that creates AI-powered website and app builders, has quickly grown from a unicorn (valued at over $1 billion) to a centaur (generating over $100 million in annual recurring revenue) in less than a week. Launched just eight months ago, it now has over 2.3 million active users and 180,000 paying subscribers, all with a small team of 45 employees.

The company recently faced a revenue drop of $1.5 million by shifting users to a more affordable plan, but it is now introducing a new Business tier to attract more enterprise customers. This tier includes features like self-serve options, Single Sign-On, and private projects, which could help businesses use Lovable’s tools more effectively.

Lovable has already secured large clients such as Klarna and HubSpot and has seen significant project creation, with over 10 million projects developed on its platform. The growing demand for AI tools is helping more companies reach the $100 million ARR milestone in Europe.

A recent study found that a large AI training data set called DataComp CommonPool includes millions of images containing personally identifiable information (PII), such as passports, credit cards, and birth certificates. The researchers audited only a small portion of the data and estimate that there could be hundreds of millions of such images in the entire set. They discovered thousands of validated identity documents and sensitive details from résumés, including personal information and contact details.

CommonPool, which has 12.8 billion samples, is one of the largest publicly available data sets used for training image generation models. Although the creators intended it for academic research, its licensing allows commercial use, raising privacy concerns. The study highlights the risk that web-scraped data often contains PII, despite attempts to filter out sensitive information.

Researchers point out that privacy protections are inadequate because algorithms missed many identifiable faces and did not effectively filter known PII. They emphasize that even if individuals request the removal of their data, it may not eliminate risks because trained models retain the original information. The findings call for a reevaluation of web scraping practices and highlight potential violations of privacy laws, which often do not protect researchers or consider the complexity of what is deemed "publicly available."

Overall, the study warns that many images and documents that people believed were private are being used in AI systems without their consent, raising significant ethical and legal concerns.

Summary: Writing Memory Efficient C Structs

Tom Scheers discusses how to create memory-efficient structures (structs) in C, using a "Monster" struct as an example.

1. Understanding Struct Size: A typical Monster struct contains various fields (like health, damage, and position), totaling 89 bytes based on calculations. However, the actual size is 96 bytes due to padding added by the compiler for alignment purposes.

2. Reducing Padding: By rearranging the fields from largest to smallest type, the size can be reduced from 96 bytes to 92 bytes.

3. Derived State: Removing redundant fields can also save space. For instance, the is_alive field can be calculated from the health field, further reducing the struct size to 88 bytes.

4. Using Smaller Types: Utilizing smaller data types (like uint16_t instead of int) can significantly cut down the size of the struct, bringing it down to 84 bytes.

5. Bitfields for Booleans: Booleans can be represented more efficiently using bitfields, which allows multiple boolean values to fit into a single byte, reducing the size to 80 bytes.

6. Enums for Identifiers: Instead of using strings for identifiers (like monster names), using enums can greatly reduce memory usage. This can shrink the struct size to just 20 bytes.

7. Trade-offs: While optimizing structs is beneficial, it’s important to balance memory efficiency with code readability. Some methods can introduce risks, like integer overflow.

Overall, carefully structuring and optimizing data can lead to significant memory savings in programs, especially in performance-sensitive applications.

Every week, the author reflects on lessons learned and plans for personal growth. This week, they discuss the significance of rivalry in sports, inspired by recent competitions like Wimbledon and the Tour de France.

The author shares personal experiences from two major rivalries: the Michigan-Ohio State college football rivalry and their long-standing competition with Peyton Manning. They emphasize that rivalry drives athletes to push beyond their limits and focus intensely on their performance.

Rivalries are more than just matchups; they create a heightened sense of urgency and motivation. The author believes that viewing rivals as enemies, rather than friends, can enhance one's competitive edge. This mindset, while potentially leading to temporary hurt feelings, can foster greatness.

The author expresses gratitude for rivals like Manning, who challenge them to excel and achieve their potential. Ultimately, embracing rivalry can lead to significant personal and professional growth.

Oxide has successfully raised $100 million in a Series B funding round, significantly increasing their total capital raised to $189 million. This funding will help Oxide realize its vision of becoming a major player in the cloud computing market, specifically focusing on on-premises solutions.

When the company started in 2019, many investors were skeptical about the market potential. However, with the support of investors who understood the importance of co-designing hardware and software, Oxide began building its products. They developed key technologies including their own hardware designs, operating systems, and integrated services, leading to the successful launch of their first system two years ago.

Since then, customer interest has grown, with quicker sales cycles and positive feedback. The new investment from USIT aligns with Oxide's goals and will help them scale operations and meet customer demands. Oxide is excited about this new phase and is committed to delivering innovative computing solutions.