Mariano and Anton created ISSEN, a foreign language voice tutor app designed to improve speaking skills based on individual interests and goals. They developed the app after struggling to find effective tools for practicing Japanese and French, noting that traditional tutors can be expensive and hard to schedule.

ISSEN uses advanced speech technology, including speech-to-text and text-to-speech, to facilitate realistic conversations. The app avoids gamification, focusing instead on immersive language practice, which they believe is more effective for learning.

The app features a customizable word bank and flashcards to enhance vocabulary and speaking skills, along with tailored curriculums for each user. It is available on web, iOS, and Android, offering a free 20-minute trial and subscription plans ranging from $20 to $29 per month.

They welcome feedback on their technology and user experience.

No summary available.

Summary of AI Dataset Generator

The AI Dataset Generator is a tool that helps you create realistic datasets for demonstrations, learning, and dashboards. Here are the main features and steps to use it:

Key Features:

• Conversational Prompt Builder: Customize your dataset by selecting the business type, schema, row count, etc.
• Real-Time Preview: View a sample of your data directly in the browser.
• Export Options: Download your datasets as CSV files or SQL inserts.
• Metabase Integration: Launch Metabase with one click to explore your data.

Requirements:

• You need Docker (with Docker Compose) and an OpenAI API key.

Setup Instructions:

1. Clone the repository using Git.
2. Create a configuration file (.env.local) and add your OpenAI API key.
3. Install dependencies and run the application.

Using the App:

• Define your dataset using the prompt builder and preview it.
• Download the dataset as CSV or SQL.
• Use Metabase to analyze your data after launching it in Docker.

Cost Structure:

• Previewing data incurs a small fee (~$0.05).
• Downloading datasets as CSV or SQL is free.

How It Works:

• The app generates a data specification using OpenAI, and local data rows are created using the Faker library. Once you preview the data, further downloads do not incur additional costs.

Schema Options:

• Choose between a single table format (One Big Table) or a more complex structure (Star Schema) for advanced analytics.

Extending the App:

• You can add new business types or schema logic by modifying specific files in the codebase.

This tool allows users to easily generate and manipulate datasets for various applications, making data exploration and analysis efficient.

Researchers have created a new tetrahedron shape that can only rest on one specific side, confirming a long-held mathematical conjecture. The tetrahedron, a polyhedron with four triangular faces, has been studied since ancient times, yet its balancing properties remained unresolved until now.

In 1966, mathematicians John Conway and Richard Guy questioned whether a uniform tetrahedron could be designed to balance on just one face. They initially found it impossible but suggested that using uneven weight distribution might work. Gábor Domokos later explored this idea and, in 2023, proved that it's theoretically possible to create such a shape.

Domokos and his team faced challenges in constructing a physical model. After much experimentation, they successfully built a tetrahedron made of lightweight carbon fiber and dense tungsten carbide, which consistently lands on one face, as intended. This project highlights the importance of hands-on experimentation in mathematics and could have practical applications, such as in designing self-righting spacecraft.

The team's findings may lead to new insights in geometry and enhance our understanding of polyhedra, showcasing how seemingly simple shapes can reveal complex mathematical properties.

On June 26, 2025, Black Forest Labs announced the release of FLUX.1 Kontext [dev], an open-weight model for image editing that offers high-quality performance and can run on consumer hardware. This model is now available for free for research and non-commercial use under the FLUX.1 Non-Commercial License.

Key features of FLUX.1 Kontext [dev] include:

• Focus on image editing tasks, enabling detailed local and global edits while preserving character details.
• Extensive evaluation shows it outperforms both open and proprietary models in various benchmarks.
• Optimized for NVIDIA's latest Blackwell architecture, enhancing speed and reducing memory use.

The company also introduced a self-serve licensing portal, simplifying commercial access to their models. Changes to the Non-Commercial License clarify usage definitions and require content filters to prevent misuse.

For more information, users can access model weights, code, and documentation through provided links. Black Forest Labs is also hiring to expand its team.

Summary of MUVERA: Efficient Multi-Vector Retrieval

MUVERA is a new algorithm developed by Google Research that aims to make multi-vector retrieval as fast as single-vector search. The traditional method of retrieving information involves transforming data into single-vector embeddings for efficient similarity comparison. However, multi-vector models, which use multiple embeddings for each data point, provide better accuracy but are computationally expensive.

MUVERA simplifies this process by creating Fixed Dimensional Encodings (FDEs). These FDEs are single vectors that approximate the multi-vector similarity, allowing for the use of faster search methods. The process involves three main steps:

1. FDE Generation: Queries and documents are converted into FDEs that capture essential similarity.
2. MIPS Retrieval: The FDEs are indexed for quick retrieval using maximum inner product search (MIPS).
3. Re-ranking: The initial results are refined using the original multi-vector similarity measure for improved accuracy.

MUVERA's method is efficient and adaptable to various data distributions, making it suitable for real-time applications. The algorithm has shown significant improvements in retrieval speed and accuracy over previous methods, with a remarkable reduction in latency and fewer candidate documents needed for the same recall rate.

Overall, MUVERA enhances the practicality of multi-vector retrieval, which is important for applications like search engines and recommendation systems. An open-source implementation is available on GitHub for further exploration and use.

In Puerto Rico, the town of Adjuntas is collaborating with researchers to create solar microgrids that provide electricity during frequent power outages. This initiative aims to enhance energy reliability on the island. Meanwhile, the federal government has decided to redirect $365 million away from solar projects to focus on fixing the main power grid.

No summary available.

Summary of Learnings from Building AI Agents

Paul Sangle-Ferriere, co-founder of Cubic, shares insights on improving their AI code reviewer, which initially generated too many irrelevant comments during code reviews. Key issues included excessive false positives, loss of developer trust, and unclear reasoning behind feedback.

Key Improvements Made:

1. Explicit Reasoning Logs: The AI now has to explain its reasoning before giving feedback. This helps track its decision-making and reduces arbitrary conclusions.

2. Simplified Toolset: The original complex toolkit was streamlined to essential tools, which improved the AI's ability to identify real issues without confusion.

3. Specialized Micro-Agents: Instead of a single agent with many rules, they created specialized agents focused on specific tasks, enhancing precision and reducing cognitive overload.

Outcomes: These changes led to a 51% reduction in false positives, halved the median comments per pull request, and improved the overall review process, making it smoother and more efficient. Developers felt more confident and engaged in the review process.

Key Lessons:

• Clear reasoning enhances accuracy.
• Simplify the toolkit by removing rarely used tools.
• Use specialized micro-agents for focused tasks.

No summary available.

Here are the key points from the text:

• There is a GitHub repository available at this link.
• The original project explanation can be found at this link.

These links provide access to the project's code and its background information.

To make OpenAI transcriptions faster and cheaper, you can speed up your audio before sending it for transcription. Using tools like ffmpeg, you can double or triple the speed of your audio files, which reduces the time and costs associated with transcription without significantly affecting quality.

Here's a simple workflow:

1. Extract audio from a video using yt-dlp.
2. Speed up the audio using ffmpeg (e.g., to 2x or 3x speed).
3. Send the sped-up audio to OpenAI for transcription.
4. Use an LLM to summarize the transcription.

This method is effective because OpenAI charges based on the duration of the audio. By speeding up the audio, you reduce both the time taken and the costs associated with transcription. For example, speeding up a 40-minute audio can cut costs significantly, with 3x speed potentially saving you about 33% on the input tokens.

In summary, to save time and money on transcriptions, consider using 2x or 3x speed for your audio files. This approach is simple, quick, and surprisingly effective, though speeding it beyond that may lead to less accurate results.

Summary of Willy Tarreau's Performance Comparison of Tree Structures

Willy Tarreau conducted a performance comparison of three types of tree structures: Elastic Binary Trees (ebtree), Compact Elastic Binary Trees (cebtree), and Red-Black Trees (rbtree). The main focus was on how these trees perform with different types of keys and distributions during operations like insertion, lookup, and deletion.

Key Findings:

1. Performance Variation: The performance of each tree type varies based on key types, distribution, and the ratio of lookups to updates.

2. Testing Methodology: A new tool called "ops-time" was created to measure the cost per operation for each tree structure. Tests were run with different keys such as random numbers, strings, real IPv4 addresses, and user-agent strings.

3. Testing Results:

   • Timers: Ebtree showed significantly faster performance compared to rbtree for timer-like keys due to better balance and less rebalancing overhead.
   • 64-Bit Randoms: Ebtree performed best overall, especially when the keys were randomly distributed; cebtree was slower for lookups.
   • Short Strings: Ebtree outperformed rbtree for insertions and lookups unless hashing was used, where rbtree performed better with hashed keys.
   • IPv4 Addresses: Performance varied with tree size; ebtree was faster for smaller sizes, but rbtree excelled as the size increased.
   • User Agents: Cebtree performed poorly on mostly similar long strings, while ebtree was slightly slower than rbtree for both insertions and lookups.

4. General Conclusions:

   • Ebtree is preferable for well-distributed keys and dynamic datasets, while rbtree is better for larger keys and overall performance consistency.
   • Compact trees (cebtree) can be efficient for smaller keys but struggle with deletions and larger key sizes.
   • Hashing keys can improve performance across all tree types, particularly for poorly distributed datasets.

5. Overall Recommendations: For applications where order is not critical, using rbtree with hashed keys is beneficial. For dynamic use cases with frequent insertions and deletions, ebtree is generally the best choice.

This analysis highlights the importance of key distribution and tree type selection based on specific use cases and performance needs.

No summary available.

Summary:

Xor, a graphics programmer, enjoys creating tiny shader programs that fit within 280 characters, a process known as "code golfing." These shaders produce visual effects in real-time for games and animations. He uses a tool called Twigl.app to develop and share his work.

Xor’s motivation for creating these shaders includes curiosity, learning through constraints, the challenge of compact coding, and connecting with a community of artists and developers. He explains that shaders are programs that run on the GPU, processing graphics for each pixel on the screen.

His creative process involves starting with an idea, then focusing on scaling and centering to ensure the visuals look good at different resolutions. He emphasizes the fun and educational aspects of crafting shaders, which also involves techniques to minimize code size.

Xor shares techniques for code golfing, such as reducing variable names, minimizing initializations, and avoiding complex statements like "if." He encourages others to explore shaders, suggesting platforms like GameMaker, Godot, and ShaderToy for learning.

Overall, Xor highlights the joy of experimenting with graphics programming and invites readers to delve into shader creation themselves.

The author recently purchased a Nanoleaf Pegboard Desk Dock, which only supports Windows and macOS. To use it with Linux, they decided to write a Linux device driver, even though they had no prior experience with Linux drivers or USB devices.

After setting up a Windows virtual machine to reverse-engineer the official drivers, the vendor provided helpful documentation about the device's protocol. The author used the lsusb utility to confirm that the device was recognized by the Linux system, but realized that the kernel did not know how to interact with it beyond basic recognition.

To control the device, the author considered two options: writing a kernel driver or a userspace driver using libusb. They chose the latter for simplicity. They also set up udev rules to allow non-root access to the device.

After creating a basic Rust program to communicate with the device, they encountered challenges such as needing to detach the kernel driver to claim the device interface. Once they successfully claimed it, they were able to send commands to change the LED colors.

However, they discovered that the device required polling for interrupts, which meant they needed to read responses from the device after sending commands. They implemented a background task to handle this polling.

Overall, the author learned that writing a simple device driver is achievable, even for beginners, and that a small amount of code can effectively control a USB device. They plan to continue improving their driver and eventually share it with others.

Bereket Engida, a self-taught programmer from Ethiopia, has created an innovative authentication tool called Better Auth. This open-source framework simplifies user authentication for developers and has gained significant attention, raising $5 million in seed funding from notable investors like Y Combinator and Peak XV.

Engida began programming at 18 when he took on a project to build an e-commerce search app. He noticed a recurring problem with existing authentication tools, which he found too limited or expensive. To address this, he developed Better Auth, allowing developers to manage user data directly on their databases, avoiding third-party data storage.

In just six months, Engida built the first version of Better Auth from his home in Ethiopia. Since launching on GitHub, the tool has garnered over 150,000 weekly downloads and a thriving community of developers.

Better Auth appeals to early-stage AI startups needing customizable authentication solutions. While currently free, Engida plans to introduce a paid enterprise version. He aims to build a small team to support the project, but for now, he continues to write most of the code himself. Engida's success is inspiring for other Ethiopian entrepreneurs, showing that global ambitions are possible.

This article explains how to use Llamafile to generate structured outputs in JSON format. Llamafile is a local executable LLM (Language Model) that allows users to run machine learning models on their own computers.

Key Points:

1. Structured Output in Llamafile: Unlike LangChain models, Llamafile does not have a built-in method for structured outputs. Instead, users must use LangChain’s JsonOutputParser and PromptTemplate to achieve this.

2. Setting Up Llamafile: Users can run Llamafile on various systems (like an old MacBook) by downloading a specific file and making it executable. It runs a local server accessible via a web browser.

3. Creating a JSON Response:

   • Define an Answer class to represent the desired JSON output, including fields like answer, confidence level, related topics, and follow-up questions.
   • Use LangChain’s JsonOutputParser with the Answer class.
   • Set up a PromptTemplate to structure how the LLM should respond to a question.

4. Chaining Components: Combine the prompt, the LLM, and the parser to create a chain that processes questions and provides structured answers.

5. Displaying Answers: A function is included to format and display the structured answer clearly.

The article provides code snippets and instructions to guide users in implementing these steps effectively.

Summary:

AccessOwl is looking for a Senior Software Engineer with over 5 years of experience, specializing in Elixir and using AI regularly. The role is fully remote, preferably within ±3 hours of Central European Time (CET).

About AccessOwl:

• AccessOwl simplifies how companies manage their SaaS tools, aiming to replace outdated systems.
• The company was founded by experienced entrepreneurs frustrated with inefficient SaaS access processes.
• It is a profitable startup supported by Y Combinator, focusing on customer-centric solutions.

Responsibilities:

• Improve the AccessOwl platform by developing new features and maintaining the codebase.
• Build integrations with other systems and contribute to cloud infrastructure.
• Take ownership of projects and collaborate with team members to solve customer problems.

Ideal Candidate:

• Must have experience with multiple programming languages (Elixir required) and be comfortable with back-end and some front-end work.
• Should be proactive, eager to learn, and willing to tackle challenges.
• Must communicate well in English and enjoy problem-solving.

Not a Good Fit If:

• You prefer only strategic work or fixed hours.
• You want to limit your work to specific technologies.

What AccessOwl Offers:

• Competitive salary (€70,000 - €90,000) plus stock options.
• Flexible working hours and the ability to choose your work equipment.
• Opportunities for team retreats and challenges in building a global SaaS product.

Why Join Us:

• Be part of a team that is transforming SaaS management with innovative technology.
• Work in an inclusive environment that values diverse opinions and promotes growth.

No summary available.

The author discusses their experience with RSS (Really Simple Syndication) and how they created a personalized RSS reader.

Key Points:

1. What is RSS?

   • RSS is a way for blog authors to notify readers about new posts through a machine-readable feed.
   • It allows users to curate their own list of favorite authors instead of relying on social media for updates.

2. Standards of RSS:

   • The original RSS standard is considered complicated and outdated.
   • Atom is a clearer alternative to RSS, but it also has complexities due to its XML format.
   • JSON Feed is a simpler standard but is currently unmaintained.

3. Author's Experience with Feed Readers:

   • Existing RSS readers did not meet their needs as they were too complex.
   • The author prefers to read articles directly on the authors' websites and only wants notifications for new posts.

4. Creating a Custom RSS Reader:

   • The author built a server-side RSS reader as part of their blog, which displays the latest three posts from each followed blog.
   • This solution does not track read/unread states, making it simple and accessible from any device.

5. Technical Implementation:

   • The blogroll is generated from a simple text file listing blog URLs.
   • The system uses a script to fetch and display the latest posts, which is rebuilt automatically daily using GitHub Actions.

This approach provides a straightforward way to stay updated on favorite blogs without the complexities of traditional RSS readers.

No summary available.

The article discusses the concept of pandemic bonds created by the World Bank, which allow investors to put money into a fund that helps combat pandemics. If a pandemic occurs, investors lose their initial investment, but if not, they receive their money back with interest. This approach aims to secure funds before a crisis hits, instead of waiting for government funding.

The author, Susan Erikson, shares her journey to understand these financial instruments, which are part of a growing market for insurance-linked securities (ILS). These securities emerged in the 1990s as insurers sought to manage risks from disasters more effectively. ILS allow investors to speculate on risks, such as pandemics, and potentially earn high returns if those risks do not materialize.

Key points include:

• Pandemic bonds release funds only after a certain death toll from a pandemic is reached.
• ILS are a small but growing part of the global insurance market, valued at $195 billion.
• Investors are drawn to ILS for the opportunity to earn significant returns by taking on risks associated with disasters.
• The use of parametric triggers in these securities allows for quicker payouts based on predetermined criteria, rather than actual losses.

Overall, the article highlights the intersection of finance and risk management in addressing global health threats.

In a letter to his former student Koichi, Richard Feynman expresses concern about Koichi's feelings of sadness and inadequacy regarding the value of his work. Feynman encourages him to focus on simpler, more manageable problems that he can actually solve, rather than feeling pressured to tackle grand scientific challenges. He emphasizes that worthwhile problems are those where one can make a genuine contribution, no matter how humble they may seem. Feynman shares examples of smaller problems he has worked on and found joy in, reinforcing the idea that no problem is too trivial if it leads to learning and success. He advises Koichi to recognize his worth and contributions, both personally and professionally, and to not let unrealistic ideals define his self-evaluation.

The Claude app now allows developers to easily build, host, and share interactive AI-powered applications. Key features include:

• Creation of Apps: Developers can create apps that interact with Claude using an API, which simplifies sharing and managing costs.
• User Experience: Users log in with their existing Claude account, and their usage counts against their own subscription, meaning developers don't incur extra costs.
• Community Projects: Early users are creating various applications like AI games, personalized learning tools, data analysis apps, writing assistants, and complex workflows.
• Easy Development: Developers can quickly start building by describing their app idea, and Claude will generate the necessary code. Claude can also help debug and refine the code based on feedback.
• Instant Sharing: Once complete, apps can be shared through a simple link without complicated deployment processes.

Current limitations include no external API calls, no persistent storage, and it only supports text-based completion. This feature is in beta for all plan users.

No summary available.

The United States has had one of the largest prison populations in the world for over 40 years, reaching a peak of over 1.6 million inmates in 2009. However, this number is now declining significantly. By the end of 2023, the prison population fell to about 1.2 million and is projected to drop to around 600,000 in the next decade, a decrease of about 60%.

This shift is linked to the history of crime and incarceration in the U.S. Most people in prison began their criminal activities in their youth, and the high incarceration rates from the late 20th century were largely driven by a crime wave and harsh anti-crime policies. After the crime rate peaked in 1991, the prison population continued to grow due to the cycle of re-incarceration. Now, as crime rates have stabilized, the prison population is finally starting to decline.

Howdy is a tool that allows you to use facial recognition for logging into Linux systems, similar to Windows Hello™. It works through the central authentication system (PAM), meaning you can use it for logging in, unlocking your screen, and other password-required actions.

Installation

Howdy is available for several Linux distributions, including Debian/Ubuntu, Arch Linux, Fedora, and openSUSE. Here are installation instructions for common distros:

• Ubuntu/Linux Mint:
  Run these commands in the terminal:

  sudo add-apt-repository ppa:boltgolt/howdy
  sudo apt update
  sudo apt install howdy
  

• Debian:
  Download the .deb file and install it using gdebi.

• Arch Linux:
  Install from the AUR and follow additional configuration steps from the ArchWiki.

• Fedora:
  Use the COPR repository with:

  sudo dnf copr enable principis/howdy
  sudo dnf --refresh install howdy
  

  If there are issues with Python2, switch to the beta repository.

• openSUSE:
  Check the openSUSE wiki for installation details.

Building from Source

To build Howdy from source, you need some dependencies like Python, pip, and others. Use the following command to install them on Debian/Ubuntu:

sudo apt-get update && sudo apt-get install -y \
python3 python3-pip python3-setuptools python3-wheel \
cmake make build-essential \
libpam0g-dev libinih-dev libevdev-dev python3-opencv \
python3-dev libopencv-dev

Setup

After installing, run sudo howdy add to teach Howdy your face. You can test it by running sudo -i and showing your face. Configuration options can be accessed with sudo howdy config.

Commands

You can manage face models with commands like:

• add: Add a new face model
• clear: Remove all models
• list: Show saved models
• test: Check camera and recognition

Contributing

You can help by starring the repository, reporting issues, or contributing code. If you want to package Howdy for another distro, open an issue.

Troubleshooting

If you encounter Python errors, they will show in the console. Check /var/log/auth.log for authentication issues. Refer to the wiki for common problems.

Security Note

Howdy is not as secure as a password and can potentially be fooled. It should not be your only method of authentication, so use it with caution and keep it in a secure location.

The QEMU project has established a new policy regarding the use of AI code generators. Here are the key points:

1. Policy Overview: The QEMU project will not accept contributions that are known or suspected to include content generated by AI tools, such as ChatGPT, Copilot, and similar technologies.

2. Legal Concerns: There is currently no clear legal framework regarding the licensing of code produced by AI generators, which raises risks for software projects. Contributors must certify their submissions comply with the Developer's Certificate of Origin (DCO), but the copyright status of AI-generated content is often unclear.

3. Strict Approach: The policy is designed to be strict initially to avoid legal complications, with the possibility of revision as the legal landscape evolves. Contributors can request exceptions on a case-by-case basis, but they must clearly demonstrate the licensing and copyright status of the AI tool's output.

4. Non-AI Uses: The policy does not apply to the use of AI for research or analysis purposes, as long as the outputs are not included in contributions.

5. Future Adaptation: This policy may change as AI tools develop and the legal situation becomes clearer.

In summary, QEMU is prioritizing legal safety by declining AI-generated contributions while remaining open to future changes in policy.

No summary available.

The Offline Club is a community focused on helping people take a break from screens and enjoy offline activities. They have received an excellent rating of 4.7 out of 5 based on 251 reviews. The club offers various events and retreats, such as phone-free dinners, café hangouts, and digital detox retreats in beautiful locations like Amsterdam, London, and Paris. Members join to connect meaningfully with others, enjoy hobbies, and relax without digital distractions. The club also encourages people to start local chapters in their cities to expand the community. Overall, it's about creating a more connected and relaxed experience away from the digital world.

The article by Michael Lai, edited by Scott Summers, discusses the art of folding origami using flower petals, a technique he refers to as "hanakami," which combines the Japanese words for "flower" (hana) and "paper" (kami).

Key points include:

1. Choosing the Right Petals: Lai emphasizes the importance of selecting flower petals that are flat, thin, and pliable, as these qualities make them easier to fold. He suggests using petals that have fallen and dried naturally for better results.

2. Preparation Process: The process involves drying and pressing the petals to remove excess moisture while retaining some pliability. This ensures the petals can hold creases without becoming brittle.

3. Cutting Petals: After drying, petals should be cut into squares for folding. Lai advises maximizing the size of the squares and being mindful of vein lines in the petals to facilitate easier folding.

4. Testing and Folding: Before folding, it's important to test the petal's flexibility. Lai suggests practicing with regular origami paper to get comfortable with the folds before using the petals.

5. Preserving Models: Once a model is completed, it can be preserved in resin to extend its lifespan, although natural deterioration is expected over time.

6. Final Thoughts: Lai highlights the unique experience of working with natural materials, suggesting that this practice can deepen appreciation for art and its connection to mental well-being.

Overall, the article encourages readers to explore this creative technique while being mindful of the delicate nature of flower petals.

GitHub is a platform where developers can share and collaborate on code. The provided link leads to the "gemini-cli" project by Google. This project likely involves tools or features related to "Gemini," which may refer to a specific technology or service by Google. You can visit the link for more information and to explore the project further.

No summary available.

No summary available.

No summary available.

PNG is making a comeback! A new PNG specification has just been released, revitalizing the format after more than 20 years of stagnation. Major institutions like the U.S. Library of Congress and the National Archives of Canada recommend PNG, making it important to keep it updated and competitive.

Key updates in the new PNG spec include:

1. HDR Support: PNG now supports High Dynamic Range (HDR) with a more efficient use of data.
2. Animation Support: Animated PNGs (APNGs) are officially recognized, aligning with widespread support in programs like Firefox.
3. Exif Data: The spec now supports Exif data, which holds additional information like copyright and GPS details.
4. Clarifications: Various errors and ambiguities from the previous spec have been corrected.

The last PNG update was over 20 years ago, and technological advancements have driven this revival. Notable companies like Adobe, Apple, and Google are involved in the new developments, with further updates already in progress.

Many popular applications, such as Chrome, Safari, and Photoshop, already support the new PNG spec. Future improvements, including better compression and encoding techniques, are on the way.

Overall, the PNG Working Group has worked hard to bring this format back to life, and their efforts deserve recognition.

No summary available.

Summary of Iroh

Iroh is a tool that helps you connect to devices using their public keys, ensuring the fastest connection possible. It employs techniques like hole-punching to create direct connections and can use public relay servers if needed. Iroh is built on the QUIC protocol, which offers secure and efficient data transmission.

Key features include:

• Protocols: Instead of creating your own from scratch, you can use existing protocols like:
  • iroh-blobs: For transferring large files.
  • iroh-gossip: For creating scalable communication networks.
  • iroh-docs: For managing key-value data.
  • iroh-willow: An upcoming protocol implementation.

Getting Started:

• Iroh is primarily used with Rust. You can install it and create connections easily using provided code examples.
• For other programming languages, you can use the iroh-ffi for bindings.

Repository Structure:

• The project includes several components like the core library, relay server, and DNS server for discovering nodes.

Licensing:

• The project is licensed under both the Apache License 2.0 and the MIT License.

You can find more information, examples, and the project's source code through the provided links.

On June 23, 2025, Hannah Forsyth reflects on a moment she witnessed at a Post Office involving a child proudly announcing her achievement of earning five stickers for her music performance. This sparked her thoughts on the nature of value, comparing stickers to the hoarding of money in George Eliot's novel Silas Marner.

In the story, Silas, a skilled weaver, becomes obsessed with accumulating gold coins after losing his community and purpose. His wealth, rather than providing satisfaction, turns into a mere object of desire, illustrating how money can lose its intended purpose and become a fetish. Forsyth draws parallels between Silas's experience and modern-day attitudes towards wealth, highlighting how some individuals feel entitled to money and status without earning it.

She discusses how social status can lead to a sense of deservingness, contrasting Silas's hard work with characters like Dunstan, who squander their wealth yet believe they deserve more. Ultimately, Silas finds redemption not in gold but in the love and companionship of a child who enters his life, symbolizing a move from material wealth to true human value.

Forsyth concludes by expressing a personal connection to Silas's longing for worth and a hopeful reflection on the transformative power of love over material possessions.

A recent study found that people with depression often struggle with decision-making due to a phenomenon called "sticky thinking," which refers to getting stuck on negative thoughts. Researchers Hang Yang and Marieke van Vugt from the University of Groningen studied 124 participants to see how rumination affects decision-making. They discovered that those who ruminated more had a harder time making decisions and made more mistakes in tasks.

Participants who experienced sticky thinking took longer to respond correctly during tasks and showed increased brain activity associated with being unfocused. The findings suggest that sticky thinking contributes to decision-making difficulties in people prone to depression. However, a limitation of the study is that most participants with high sticky thinking were women, which may affect the results. Further research is needed to explore this gender difference.

The article "Interstellar Flight: Perspectives and Patience" by Paul Gilster reflects on the relationship between music, technology, and the possibility of interstellar travel. Inspired by John Coltrane's album Sun Ship, Gilster connects the themes of speed and exploration in both music and space missions.

He discusses the Parker Solar Probe, which recently approached the Sun, and highlights the impressive speeds of various spacecraft. For instance, the fastest human-made object, the Parker Solar Probe, reached speeds of 191.2 kilometers per second, but even at that speed, it would take over 6,600 years to reach Proxima Centauri, our closest star.

Gilster emphasizes the long timelines required for interstellar travel, noting that current technology requires imagining new solutions, like using beamed energy for propulsion. He also reflects on the historical context of human achievements in technology, comparing the effort behind the Voyager missions to ancient monumental projects like the Great Pyramid.

Overall, the piece conveys a sense of wonder about the future of space exploration and the need for a long-term perspective as humanity dreams of interstellar travel.

No summary available.

The blog post discusses RaptorCast, a solution for improving the communication process in Proof of Stake blockchains, where a leader proposes blocks of transactions. The main challenges are:

1. Performance: Quickly sharing block proposals with all validators.
2. Security: Ensuring that validators can verify the block's origin and its integrity.
3. Robustness: Allowing honest validators to reconstruct proposals despite packet loss or malicious actions.

To tackle these, RaptorCast focuses on three design areas:

• Data Transmission Protocol: The choice is between TCP, which is reliable but slower, and UDP, which is faster but less reliable. RaptorCast opts for UDP and plans to manage packet loss through additional encoding.

• Encoding System: Since UDP may lose packets, an effective encoding scheme is necessary. RaptorCast uses R10, which can handle missing data effectively, and incorporates measures to ensure data integrity.

• Broadcast Strategy: RaptorCast chooses a structured broadcast approach, where specific validators re-broadcast data to designated peers, making it more efficient than random forwarding methods.

Additionally, the design includes security features like Merkle proofs to authenticate data chunks without requiring a signature for each one, enhancing efficiency while maintaining integrity. Overall, RaptorCast aims to improve the speed and reliability of transaction block propagation in blockchain networks.

No summary available.

No summary available.

No summary available.

The article discusses the new features in C++26, particularly focusing on a method to convert JSON data directly into C++ objects at compile time. The key points include:

1. C++26 Reflection: The latest version of C++ has finalized several reflection features that allow for more dynamic programming capabilities.

2. JSON to C++ Objects: A practical example shows how to take a JSON file and convert it into a structured C++ object. For instance, a JSON file containing:

   {
       "outer": "text",
       "inner": { "field": "yes", "number": 2996 }
   }
   

   can be translated into a C++ struct that reflects this structure.

3. Code Implementation: The process involves defining a method that reads JSON data and generates the corresponding C++ type and values using reflection techniques. The article walks through creating a simplified version of this process, starting with single key/value pairs and then extending it to handle multiple pairs.

4. Handling Different JSON Types: The implementation can differentiate between JSON numbers, strings, and objects, allowing for a flexible and recursive parsing approach.

5. User-Friendly Interface: The article concludes with a way to easily incorporate JSON files into C++ code using new syntax, making it simple to embed JSON data directly and access it as structured C++ objects.

Overall, the author highlights the innovative capability of C++26 to seamlessly integrate JSON data handling into C++ programming, much like features seen in other programming languages.

No summary available.

No summary available.

No summary available.

Summary: CUDA Ray Tracing 2x Faster Than RTX: My CUDA Ray Tracing Journey

This article shares the author's experience creating a CUDA-based ray tracer that performs better than a popular Vulkan/RTX implementation, achieving speedups of over 2x on the same hardware. The author aimed to enhance performance through continuous profiling and optimization, not just replicating existing methods.

Key points include:

• The author compared their CUDA ray tracer to RayTracingInVulkan, noting significant performance improvements.
• Initially claiming a 3.6x speedup, the comparison adjusted to 2x after including missing performance factors.
• The author used procedural sphere tracing, which is simpler than traditional triangle tracing, leading to different performance outcomes on GPUs.
• Insights from Tanguy Fautré indicated that procedural ray tracing might not utilize RTX cores effectively, as they excel with triangles.
• The article discusses how CUDA allows for deeper optimization and understanding of GPU performance, emphasizing the need for low-level programming knowledge.

Overall, the article aims to inspire others in GPU programming and optimization, showcasing the potential of CUDA through hands-on experience.

Blender 5.0 is set to introduce High Dynamic Range (HDR) support for Linux users, but only when using the Wayland display server and the Vulkan graphics API. This HDR feature is still experimental, meaning it's not fully tested and may have limitations.

To use HDR in Blender 5.0 on Linux, users need a compatible HDR display, the Wayland desktop environment, and must enable Vulkan instead of OpenGL. The feature has been tested on a few setups, showing promising results in early tests.

For more information and to provide feedback, users can refer to the Blender DevTalk thread.

The working paper titled "Third Places and Neighborhood Entrepreneurship: Evidence from Starbucks Cafés" by Jinkyong Choi, Jorge Guzman, and Mario L. Small explores how cafés, referred to as "third places," impact local entrepreneurship. The authors studied the effects of introducing Starbucks cafés in U.S. neighborhoods that previously had no coffee shops. They found that neighborhoods with Starbucks saw an increase in startups by 9.1% to 18%, equivalent to about 2.9 to 5.7 new firms per year over seven years. The partnership between Starbucks and Magic Johnson in underprivileged areas showed even greater positive effects. The research suggests that these increases in entrepreneurship are linked to enhanced networking opportunities provided by the cafés.

No summary available.

The article titled "LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigation" discusses the challenges faced when using large language models (LLMs) for generating code. Although LLMs have improved efficiency in code generation, they often produce incorrect or nonsensical ("hallucinated") outputs, particularly when handling complex projects.

Key points include:

1. Study Focus: The research examines hallucinations in LLM-generated code within more complex contexts, beyond simple function generation.
2. Methodology: The authors categorized hallucinations by analyzing code generation results from six popular LLMs.
3. Findings: They identified four main factors contributing to these hallucinations.
4. Mitigation Strategy: The paper proposes a method based on Retrieval-Augmented Generation (RAG) to effectively reduce hallucinations across various models.

The study aims to enhance the reliability of LLMs in code generation, making them more useful for practical development tasks.

The blog post discusses a debugging session that uncovered issues with Bash, getcwd(), and OverlayFS after a customer reported a problem with OpenSSH's scp command. The main error indicated that Bash couldn't access the current directory, leading to a deeper investigation.

Key findings include:

1. Initial Problem: The error message originated from Bash, not scp, which failed to determine the current working directory.

2. Investigating getcwd(): The team traced the issue to Bash's own implementation of getcwd(), which was used instead of the one provided by glibc. This was unexpected because it was believed that Bash would use glibc's version.

3. Cross-Compilation Issues: The problem stemmed from a misconfigured cross-compilation environment that incorrectly flagged the getcwd() function as broken. This led Bash to use its fallback implementation.

4. OverlayFS Behavior: OverlayFS altered how inode numbers were handled, causing inconsistencies that broke assumptions made by Bash's fallback getcwd() function. Specifically, the inode numbers returned by OverlayFS's readdir() could differ from those returned by stat(), leading to failures in getting the current directory.

5. Error Handling Mistake: Bash’s implementation of readdir() had a long-standing oversight where it did not reset the error number (errno) before calling readdir(). This meant that it sometimes returned misleading error messages.

In conclusion, the investigation revealed that a combination of cross-compilation configuration errors, OverlayFS behavior, and flaws in Bash's error handling led to the issue. A simple build tweak resolved the problem, but it highlighted important lessons about system portability and legacy code.

No summary available.

Many iPhone users struggle with quickly filling storage. They often don't have a Mac, don't want to pay for iCloud, and find setting up a home NAS difficult. Manually organizing photos can be tedious and overwhelming.

To solve this problem, I created an app called BackiGo. It allows users to back up Live Photos directly from their iPhone to an external hard drive without needing a Mac.

Key features of BackiGo include:

• Backup of Live Photos, preserving their motion
• Ability to restore Live Photos back to the iPhone
• Easy backup of new photos
• Option to browse and view saved Live Photos directly from the external drive
• A free trial for backing up up to 500 photos and videos before purchasing.

Since Google Glass was introduced in 2012, there has been a lot of excitement about augmented reality (AR) technology improving productivity in various industries. However, there has been little actual use of these technologies in real-world applications. Many expected that features like hands-free access to information, video calls, and sharing views would be beneficial across sectors. Some pilot projects, like the Hololens in US defense and healthcare in Serbia, are being explored. The text asks for examples of AR use, personal experiences, and opinions on challenges such as usefulness, display quality, and cost that may be limiting wider adoption.

Anthropic, an AI company, recently won a significant legal decision regarding the use of copyrighted books for training its models. A judge ruled that while Anthropic's scanned versions of books fall under "fair use," the company is still facing issues due to its earlier use of over seven million pirated copies of books. This ruling means that the pirated ebooks will be taken to trial, as the judge agreed with authors that Anthropic should have paid for these copies.

The case dates back to Anthropic's early days when co-founder Ben Mann downloaded large amounts of pirated books from various online sources. Although the company later shifted to legally acquiring print books for its research, the judge emphasized that training AI on unlicensed data could still be considered fair use, as it transforms the original works.

The judge, William Alsup, noted that it is common for people to read and use texts without needing to pay for every instance, which supports the argument for fair use in this context.

The Ainu language, once nearly extinct after Japan's colonization efforts, is experiencing a revival thanks to modern technology, including artificial intelligence. The language is critically endangered, with only a few native speakers remaining, primarily due to past government policies that suppressed its use.

In 2019, Japan legally recognized the Ainu as Indigenous people, which has sparked efforts to preserve their culture and language. Maya Sekine, a young Ainu woman, shares her family's Ainu stories and has created a YouTube channel to promote the language. Despite her efforts, Ainu is not taught in schools, which limits its transmission to future generations.

Researchers, including Tatsuya Kawahara from Kyoto University, are utilizing AI to analyze old recordings of the Ainu language, aiming to enhance its accessibility and learning. They have created AI systems capable of recognizing and generating Ainu speech, but concerns remain about the accuracy and authenticity of this technology. Community members are cautious about potential mispronunciations and the risk of cultural appropriation.

While there is hope for Ainu revitalization, challenges such as historical injustices and the need for community involvement in language preservation efforts remain. The Ainu community continues to adapt, creating new terms and embracing their cultural identity. Overall, there is optimism that with the combined efforts of technology and community engagement, the Ainu language can thrive again.

This article explains how to create a simple web tool that combines Text-to-Speech (TTS) and sentence-level highlighting using JavaScript. Here's a simplified summary of the key points:

1. What is TTS?
   TTS in the browser allows text to be read aloud using the SpeechSynthesis API in JavaScript. You can control playback (play, pause, stop) and choose different voices.

2. Core Components:

   • speechSynthesis: Controls speech playback.
   • SpeechSynthesisUtterance: Represents the text to be spoken.

3. Building the Tool:
   The project involves creating a mini tool using HTML, CSS, and JavaScript that:

   • Reads sentences one at a time.
   • Highlights the current sentence being read.
   • Includes buttons for Play, Pause, Resume, and Stop.

4. HTML Structure:
   The tool's HTML includes a toolbar for controls, a text block with sentences, and a progress display.

5. CSS Styling:
   Basic styles are applied to make the interface user-friendly and visually appealing.

6. JavaScript Logic:
   The JavaScript handles:

   • Populating voice options.
   • Speaking sentences and updating the UI.
   • Highlighting the active sentence as it's read.

7. Functionality Overview:
   When a sentence is spoken, it gets highlighted, and the next sentence is automatically read when the current one finishes.

8. Conclusion:
   The article teaches how to implement TTS and dynamic highlighting, and suggests ways to expand the project, such as saving progress or loading external content.

This project helps enhance accessibility and creates an engaging reading experience on web pages.

No summary available.

Summary:

The DeepSpeech project, which was an open-source Speech-To-Text engine, has been discontinued. It was based on research from Baidu and used Google's TensorFlow for implementation.

• You can find installation and usage documentation at deepspeech.readthedocs.io.
• The latest release, including pre-trained models, is available on GitHub.
• For contribution guidelines, refer to CONTRIBUTING.rst.
• For support, check SUPPORT.rst.

Summary: Reading NFC Passport Chips in Linux

The article discusses how to read the NFC chip data in passports using Linux, specifically through a tool called pypassport. The author explains that the NFC chip contains sensitive information, including biometrics, which is protected by a password found in the Machine Readable Zone (MRZ) of the passport.

Key Points:

1. NFC Chip and Password: The NFC chip in a passport is secured with a password printed in the MRZ. This password is necessary for reading the chip's data.

2. Recreating the MRZ: If part of the MRZ is missing (like in a cancelled passport), you can recreate it using the passport number, date of birth, and expiry date, along with specific checksum calculations.

3. Reading Cancelled Passports: Even if a passport is cancelled (physically altered), the NFC chip can still be read, as the chip remains intact.

4. Brute-Forcing the Password: While theoretically possible, brute-forcing the MRZ password is impractical due to the vast number of combinations. However, if you know certain details (like the passport number and date of birth), it may be easier.

5. Installation: The author provides installation instructions for the pypassport library and example Python code to read the passport data.

6. Data Extraction: The passport data is organized into various "Data Groups". Key information includes personal details and biometric data, such as a photo.

7. Limitations: The method won’t detect fraudulent passports or verify if a passport has been revoked.

In conclusion, while the process of reading NFC chips in passports can be technically complex, it is feasible and can reveal a lot of information. However, the author suggests that for most purposes, manually reading the passport is just as effective.

Google has informed Android users that its AI service, Gemini, will soon have access to important apps like Phone, Messages, and WhatsApp, regardless of whether users have opted in or out. This change, effective July 7, raises privacy concerns as it means Gemini could access sensitive information without explicit consent from users.

The email from Google suggests that users can turn off these features in the app settings, but it lacks clear instructions on how to do so or what disabling the features entails. Currently, when Gemini is active, it can store and even share some user data for up to 72 hours.

Many people are worried about the implications of AI needing access to personal information to function effectively. As AI becomes more integrated into our daily lives, the need for transparent data collection practices and privacy protections is more crucial than ever. Users express that while they appreciate AI conveniences, protecting their privacy, especially regarding personal messages, remains a top priority.

In May 2025, Cloudflare successfully blocked the largest recorded DDoS attack, which reached 7.3 terabits per second (Tbps). This attack was 12% larger than the previous record and targeted a Cloudflare customer, a hosting provider, using their Magic Transit service for protection.

Key details include:

• The attack delivered 37.4 terabytes of data in just 45 seconds, equivalent to streaming thousands of HD movies or downloading millions of songs in a minute.
• The attack used a variety of methods, mainly UDP floods, but also included reflection attacks involving older protocols like QOTD and NTP.
• It originated from over 122,000 IP addresses across 161 countries, with significant traffic from Brazil and Vietnam.

Cloudflare's advanced DDoS protection systems detected and mitigated the attack autonomously without human intervention. The global network's ability to route attack traffic to the nearest data center allowed for efficient mitigation, demonstrating the strength of their DDoS defenses. Overall, this incident highlights the increasing threat of DDoS attacks on internet infrastructure and the importance of robust protective measures.

Summary of How to Write Compelling Software Release Announcements

1. Focus on User Experience: Release announcements should highlight how the new software improves the user experience, not just list new features.

2. Describe Benefits: Instead of merely stating what has changed, explain how these changes benefit the user. For example, instead of saying a "repeat" button was added, explain that users can now easily create recurring events.

3. Differentiate Between Announcements and Release Notes: Release announcements should be engaging and user-focused, while release notes can be more technical and exhaustive.

4. Highlight Key Changes: Include only the most impactful updates that enhance the user experience. Avoid technical jargon or details that don't matter to users.

5. Celebrate Improvements: Emphasize improvements rather than just fixing issues. For example, say "new file creation is now 100x faster" instead of mentioning a bug fix.

6. Introduce Your Product: Provide a brief overview of your product to help new users understand its purpose without overwhelming existing users.

7. Avoid Vague Language: Don't use phrases like "various improvements and bug fixes." Be specific about enhancements.

8. Use Effective Visuals: Include clear screenshots that highlight new features, making sure they are easy to understand without extensive text.

9. Keep Demos Short: Use short animated demos (under 15 seconds) to showcase features without wasting users' time.

10. Plan Ahead: Consider the announcement during development to ensure that it highlights changes that truly benefit users.

In summary, craft release announcements that are engaging, user-centered, and focused on meaningful improvements to capture and maintain user interest.

No summary available.

Summary: Writing Toy Software Is A Joy

The article emphasizes the benefits of creating "toy programs," which are simple software projects that can help developers learn and enjoy coding. It cites Richard Feynman's quote, “What I cannot create, I do not understand,” to highlight the importance of hands-on experience in understanding software.

Key Points:

• Learning Through Creation: Building your own software, even simple versions, deepens your understanding more than passive learning from books.
• Counteracting AI and Commodification: With AI and the industrialization of software development, there's a need to reconnect with the joy of programming.
• Simplicity and Efficiency: Toy programs often follow the 80:20 rule, focusing on minimal code for maximum functionality. This approach encourages creativity and problem-solving without over-engineering.
• Practical Knowledge: Working on toy projects often leads to valuable insights and skills that can be applied in professional settings.

The article lists several toy program ideas with estimated difficulty and time required, such as:

• Regex Engine: Learn regular expressions (Difficulty 4/10, Time 5 days).
• OS Kernel: Create a simple operating system kernel (Difficulty 7/10, Time 2 months).
• Game Emulators: Build emulators for classic games (Difficulty 6/10, Time 3 weeks).
• Physics Engine: Implement a basic physics engine (Difficulty 5/10, Time 1 week).

Finally, the author advises against using AI models for these projects, as the learning comes from exploring unknowns, which enhances the joy and satisfaction of coding.

Young people are currently facing a tough job market, with recent college graduates experiencing high unemployment rates similar to those seen during recessions. This "new grad gap" indicates that young workers are struggling more than the overall job market suggests. Several factors contribute to this issue, including economic slowdowns due to interest rate hikes and the increasing influence of artificial intelligence (AI).

AI is changing how companies hire, with tools like ChatGPT able to perform tasks typically done by entry-level workers. Many companies are starting to replace young employees with AI, leading to concerns about job availability. For instance, predictions suggest that AI could eliminate half of entry-level jobs in the next five years.

Moreover, the job application process itself is being transformed. Technology allows students to apply to hundreds or even thousands of jobs quickly, overwhelming hiring departments. AI is now heavily involved in recruitment, with companies using it for screening and interviewing candidates, sometimes even replacing human interactions with chatbots.

This shift not only complicates the hiring process but also raises questions about the value of traditional qualifications, like college degrees, as AI makes it easier to cheat in academic settings. Overall, AI is fundamentally altering the transition from college to the workforce, making it a challenging time for young people seeking employment.

You can enter your phone number and receive a call within 30 seconds for a brief AI-powered screening interview lasting 2-3 minutes.

Currently, the service handles basic screening questions and produces simple reports. They are looking to expand by adding features like technical screening libraries, integrations with applicant tracking systems (ATS), custom questions for specific roles or companies, and support for multiple languages.

They are seeking feedback from recruiters and startup founders who are involved in hiring. They ask you to try the call first and then share your thoughts on its naturalness, comfort level, potential for use in hiring, and any areas for improvement. To see the full recruiter dashboard, you can leave your email for a demo.

This is an early version (MVP) to test the idea, and they are curious about opinions on whether this approach is the future of recruiting or just unnecessary automation.

Summary of "Temporal Resources: Managing Time When Time Doesn't Exist"

The text discusses the paradox of time management in the context of modern physics, particularly quantum mechanics. It begins by humorously imagining explaining lateness to a boss using the idea that time may not truly exist. The article highlights humanity's long history with time management, from ancient calendars to Isaac Newton's concept of absolute time, which dominated for centuries.

However, Albert Einstein's theories revealed that time is relative, and further developments in quantum mechanics, particularly the Wheeler-DeWitt equation, suggest that time may not exist at the fundamental level of reality. Recent research indicates that time emerges from quantum entanglements, meaning it is created through interactions rather than being an inherent quality of the universe.

The text proposes practical strategies for managing time in light of these insights, such as embracing flexible scheduling, focusing on engagement to enhance temporal experience, and recognizing that deadlines may vary for different individuals. It concludes by emphasizing that our conscious participation in tasks contributes to the creation of time itself, making procrastination not just inefficient, but a missed opportunity to engage in the universe's processes.

Overall, the article encourages a new understanding of time management as a collective, conscious effort rather than merely a resource to be optimized.

The text discusses the new features in Python that simplify running one-off scripts.

Key Points:

1. Introduction of uv: uv is a fast Python package and project manager written in Rust, which allows users to run Python scripts without setting up a specific environment or dependencies beforehand.

2. Tool uvx: Similar to npx in JavaScript, uvx helps execute Python tools by creating a temporary virtual environment and installing necessary dependencies automatically.

3. PEP 723: This is a new Python Enhancement Proposal that allows embedding metadata in single-file scripts. This metadata helps tools and IDEs understand the script's requirements, such as Python version and dependencies.

4. Example Usage: The text provides examples of using uv and PEP 723 metadata to run Python scripts, including fetching PEP information and extracting YouTube transcripts.

5. Executable Scripts: By adding a specific shebang line to a script, users can easily run it directly from the command line, making the process seamless.

6. Personal Experience: The author shares their positive experience with uv, stating it makes Python more appealing for one-off scripts compared to other languages like Go.

In summary, uv and PEP 723 enhance the Python experience by simplifying script execution and dependency management, making it easier for developers to use Python for quick tasks.

No summary available.

Summary: Understanding Time in Programming

Time management in programming can be complex, often causing confusion among developers. This guide outlines key concepts for handling time effectively.

1. Absolute Time vs. Civil Time:

   • Absolute Time: Refers to specific moments in time, measured from a reference point called an "epoch." For example, Unix time counts seconds from January 1, 1970.
   • Civil Time: A human-friendly way to express time using calendars, like the Gregorian calendar. It includes dates and times formatted for easy reading, but can be ambiguous (like when adding months).

2. Modern Timekeeping:

   • UTC (Coordinated Universal Time) is a global standard that accurately defines a second. It is synchronized with atomic clocks and can include adjustments like leap seconds to account for Earth's rotation variations.
   • Leap seconds can cause complications in precise timekeeping, especially in programming.

3. Timezones:

   • Timezones allow local times to reflect the Sun's position while being based on UTC. Each timezone has a specific UTC offset, which can change (e.g., due to daylight saving time).
   • Understanding how timezones work is crucial, as they can have varying rules and be subject to changes by local governments.

4. Handling Time in Code:

   • When programming, avoid assumptions about time validity across timezones. Use libraries that can manage timezones and handle historical changes in rules.
   • Consider using the IANA Timezone Database to accurately track timezone rules and changes.

5. Practical Applications:

   • When saving event times, consider whether the time should remain constant (like for a solar eclipse) or if it should adapt to changes in timezone rules (like for a scheduled event).
   • Always clarify user intentions regarding time inputs, especially for features that involve durations or scheduling.

Understanding these principles helps prevent bugs and ensures accurate time management in software applications.

Summary of Restmail

Restmail is a command-line tool that allows you to send emails using Gmail and Outlook's REST APIs. It's useful for email automation, notifications, and sharing patches with git.

Key Points:

• Installation: You can install Restmail using the Go programming language with the command:

  go install github.com/tonymet/restmail@latest
  

• Setup: You need to set up your email provider (Gmail or Outlook) once. This involves creating an OAuth2 client ID and secret:

  [email protected]
  CLIENT_ID=xxxxxx
  CLIENT_SECRET=yyyy
  restmail -configClient -provider gmail -clientId "${CLIENT_ID}" -clientSecret "${CLIENT_SECRET}" -f "${FROM}"
  

• Authorization: After provider setup, complete the OAuth flow in a web browser. This only needs to be done once or if the tokens expire:

  [email protected]
  restmail -setup -provider gmail -sender "${FROM}"
  

• Sending Emails: You can send messages using a simple command. Example:

  echo "subject: test subject\n\ntest message" | go run . -f "${FROM}" -provider gmail "${TO}" cc:"${CC}"
  

• Git Integration: You can configure Git to send emails using Restmail by adding the following to your Git configuration:

  [sendemail]
          smtpServer = /home/USERNAME/go/bin/restmail
          smtpServerOption = [email protected]
          smtpServerOption = -provider
          smtpServerOption = gmail
  

Restmail requires minimal access permissions, not needing to read or delete emails.

My 7-year-old daughter Kate loves Minecraft, and we used different AI tools to create a 1-minute animation from just one photo of her. You can read more about how we did it on my website or watch the video on YouTube.

Summary of "The Unbearable Anger of Broken Audio"

The Linux audio stack often receives negative feedback, and it's understandable since many daily computer tasks involve audio. When audio issues arise, users tend to express their frustration to the PipeWire and PulseAudio communities, which maintain the audio software.

The history of Linux audio has many layers, which can contribute to user frustration. Unlike large organizations that have dedicated support teams, the free and open-source software (F/OSS) community often relies on maintainers to handle complaints directly.

Dealing with negative feedback requires maintainers to develop thick skin and stay calm. While some user interactions can be toxic, recent feedback in the PipeWire community has been mostly positive.

The author encourages readers to vent their frustrations privately rather than directing anger at maintainers, fostering a healthier community for everyone involved.

The text discusses switching from using pip to uv in Dockerized Flask and Django applications, resulting in a significant speed improvement. Here are the key points:

1. Speed Improvement: The switch to uv resulted in about a 10x increase in speed for various projects.

2. Dependency Management:

   • Instead of using requirements.txt, you can create a pyproject.toml file to define your project dependencies.
   • uv automatically generates a lock file with proper dependency management, improving upon pip's method.

3. Dockerfile Changes:

   • Ensure environment variables are set before installing dependencies.
   • Install uv and its binaries correctly within the Dockerfile.
   • Use uv commands instead of pip commands for managing dependencies.

4. Using uv:

   • uv supports commands to add, update, or remove dependencies easily.
   • Commands like uv add, uv remove, and uv outdated help manage your dependencies without installing them as packages unless needed.

5. Scripts for Dependency Management:

   • The text provides example shell scripts for syncing and checking lock files, which ensure dependencies are up-to-date.

6. Demo Video: A video is mentioned that demonstrates the changes and commands discussed in the post.

Overall, the transition to uv simplifies dependency management in Dockerized apps while providing better performance.

IBM's Granite Vision is the leading small model for understanding documents. This model excels in its ability to process and interpret document content effectively.

The author struggled with distractions from social media and found regular site blockers ineffective. To break the habit, they created a tool called "Scream to Unlock." This extension requires users to say something embarrassing out loud to access social media, with louder screams granting more time. So far, it has helped the author stay focused. The tool is open source, ensuring transparency, and it doesn’t collect or track any user data, processing audio locally in the browser.

Links:

• Scream to Unlock Extension
• GitHub Repository

No summary available.

On June 23, 2025, FICO announced it will start including buy-now-pay-later (BNPL) loans in credit scores for the first time. This change is significant because over 90 million Americans are expected to use BNPL this year. Critics argue that current credit scores do not fully reflect a person's ability to repay loans.

FICO will introduce two new credit scores, FICO Score 10 BNPL and FICO Score 10 T BNPL, which will consider BNPL data. This aims to give lenders a clearer picture of consumers' repayment habits and improve the lending process.

A study by FICO and BNPL provider Affirm found that most consumers with several BNPL loans would see their credit scores improve or stay the same. However, some critics are concerned that BNPL could lead to "phantom debt" and affect credit scores negatively, as nearly 25% of BNPL users were reported to have paid late in 2024.

Affirm has started reporting its interest-free purchases to the credit agency Experian, but these won't immediately impact traditional credit scores. The Financial Technology Association supports FICO's move, believing responsible BNPL users should see positive credit outcomes.

This article discusses mixed DPI (dots per inch) configurations in the X Window System (X11) and clarifies misconceptions about its support.

Key Points:

1. X Window System Overview: X11 is a protocol for managing graphical user interfaces, allowing programs to communicate with the display server about what to show on the screen.

2. DPI Explained: DPI measures the resolution of displays. Different monitors can have different DPI, leading to visual inconsistencies in user interfaces if not properly managed.

3. Mixed DPI Configurations: This occurs when multiple monitors with different DPI are used together. For example, a high-density laptop screen paired with a standard external monitor can cause display issues.

4. Support for Mixed DPI: X11 has historically supported mixed DPI setups, especially with the introduction of the RANDR extension, which provides necessary information about each display's resolution and physical size.

5. Toolkit Limitations: While X11 supports mixed DPI, many applications and toolkits (like GTK+) do not fully utilize this capability, leading to poor rendering.

6. Solutions: Developers are encouraged to ensure their applications properly handle mixed DPI. Users can also adjust settings or use workarounds to improve their experience.

7. Updates: There are ongoing efforts to enhance mixed DPI support in toolkits like GTK+, with some progress being made.

In summary, while X11 can handle mixed DPI configurations, the effectiveness largely depends on the applications and toolkits used. Users and developers should advocate for better support to enhance usability across different displays.

Thimerosal is a preservative that contains ethylmercury and was commonly used in vaccines since the 1930s to prevent contamination. However, due to concerns about mercury's toxicity, it has been mostly removed from childhood vaccines. Research has shown that thimerosal does not cause neurodevelopmental disorders and is quickly eliminated from the body, much faster than other forms of mercury like methylmercury, which is more harmful.

In the late 1990s, the U.S. government began to phase out thimerosal from vaccines as a precaution, even though there was no direct evidence of harm. By 2001, it was removed from all childhood vaccines, except some flu vaccines in multidose vials, which still use it to prevent contamination.

Since then, numerous studies have confirmed that thimerosal does not increase the risk of developmental issues or health problems, including autism. The decision to remove thimerosal was seen as a precautionary measure to maintain public trust in vaccines, even though it may have fueled some fears without evidence of harm. Today, most flu vaccines and childhood vaccines in the U.S. are thimerosal-free.

Summary of the Simple Editor Guide

This text describes a simple text editor inspired by the old MS-DOS Editor but designed with a modern look, making it user-friendly for those who may not be familiar with terminal commands.

Installation:

• You can download the editor from the Releases page or install it on Windows using the command: winget install Microsoft.Edit.

Building the Editor:

1. Install Rust and the nightly toolchain using: rustup install nightly.
2. Alternatively, set the environment variable RUSTC_BOOTSTRAP=1.
3. Clone the repository and run cargo build --config .cargo/release.toml --release for a release build.

For Package Maintainers:

• The main executable name is "edit," with "msedit" as an alternative. To avoid conflicts, consider naming packages as "msedit" or similar, but not "ms-edit".
• The editor may depend on the ICU library for its Search and Replace feature. Ensure the correct library name is set at build time if it differs from the defaults (like icuuc.dll for Windows).

Environment Variable Notes:

• Several environment variables are available to customize the build, especially for ICU library configurations.
• Use cargo test -- --ignored to test your settings.

This guide helps users install and build the editor while providing important notes for maintainers regarding naming and library dependencies.

No summary available.

Summary: Swimming with an AI Coach

Sutha Kamal is starting a long-distance swimming journey this summer with a unique twist: his coach is an AI, specifically OpenAI's o3-pro model. After nearly five years away from serious swimming, Sutha is using AI to create a personalized training plan to improve his swimming technique and endurance.

He has provided the AI with details about his fitness level, goals, and constraints, including the fact that he can swim three times a week for about 45 minutes. To enhance the AI's coaching ability, he uploaded a classic swimming technique book, "Total Immersion" by Terry Laughlin.

The AI coach is designed to adapt and respond to Sutha's progress, adjusting the training plan based on his feedback. It prioritizes efficient swimming techniques over brute strength, focusing on balance, streamlining, and gentle endurance building. Sutha finds the AI's ability to analyze data and provide personalized tips motivating and accountable.

Throughout the summer, Sutha will document his training experience, exploring whether this AI-driven approach can help him swim better. He invites readers to follow his journey, promising updates on his progress and the challenges he faces.

This note explains what we think is the first functioning model of a monostable tetrahedron.

No summary available.

Key Points:

• There are guides available for programmers specific to different operating systems: Windows, macOS, and Ubuntu.
• These guides help programmers navigate challenges and improve their skills.
• Source-code editors and Integrated Development Environments (IDEs) are important tools for coding.

Overall, these resources support programmers in their work across various platforms.

Summary of "Donate Less" by Steven Deobald:

The author emphasizes that donating $10 a month for a year ($120 total) is more beneficial for non-profits than giving a one-time donation of $200. Regular monthly donations provide better financial stability for organizations, as they can plan expenses more effectively. Small, manageable donations are easier for donors to maintain over time, which helps the organization consistently receive support. The author encourages GNOME users and supporters to consider supporting the organization in a way that is comfortable for them, whether that's $10, $15, or $25 a month. Ultimately, the goal is to ensure the continuation of GNOME's valuable contributions to the world.

A recent investigation revealed that over 184,000 Ray dashboards are publicly accessible without any login or security measures. This vulnerability allows anyone to run code, steal sensitive information, or take control of AI systems. The author explains the risks involved and offers suggestions for teams to secure their dashboards. The issue reflects a larger problem in the deployment of AI infrastructure, rather than just being a simple misconfiguration. Feedback and similar findings from others are welcomed.

No summary available.

This project is a smart terrarium for growing plants, featuring:

• High-power LED lights
• A built-in water tank and mister
• Airflow fans
• Sensors for temperature and humidity
• Wi-Fi for remote control and monitoring

It's an open-source project, with:

• Electronics designed using KiCad
• 3D models created in CadQuery
• Software developed in Rust

The project started during COVID with a basic prototype using a Raspberry Pi. After redesigning it over several months, the creator has improved the design and learned a lot about electronics and 3D modeling.

For more information, you can check out the demo video and other resources on the website: Oasis Terrarium.

Summary of Edward Burra’s Art and Life

Edward Burra was an English painter known for his unique engagement with various subcultures throughout the 20th century. He experienced significant moments in art and culture, attending Josephine Baker's debut in Paris and the Harlem Renaissance in New York. Despite facing lifelong health issues, Burra created distinctive art, often using watercolors for their ease of use.

His work is characterized by a blend of vibrant experiences from places like Paris, Marseille, and Harlem, where he depicted lively scenes filled with diverse characters. Burra's style evolved with the onset of the Spanish Civil War, leading to larger works that conveyed a sense of violence and despair, reflecting his disgust at conflict and destruction.

In his later years, Burra painted rural scenes, incorporating themes of modernity's impact on nature. His artistic approach was personal and often cryptic, suggesting deep emotions without explicitly stating them. A new exhibition at Tate Britain showcases his multifaceted career, highlighting his significance in 20th-century British art. The exhibition runs until October 19, 2025.

The Translator and Language Detector APIs provide tools for translating text. Here are the main points:

• Experimental Technology: This technology is still in testing, so check compatibility with your browser before using it.

• Key Features:

  • Input Quota: The amount of translation allowed per browser session.
  • Source Language: The original language of the text to be translated.
  • Target Language: The language into which the text will be translated.

• Methods:

  • availability(): Checks if the translation model is available.
  • create(): Creates a new Translator instance.
  • destroy(): Deletes the Translator instance.
  • measureInputUsage(): Checks how much input quota a translation will use.
  • translate(): Translates a given text.
  • translateStreaming(): Streams the translation in real-time.

• Examples:

  • To create a Translator instance and generate a translation, you can follow the provided coding examples.

Overall, these APIs help developers integrate translation features into their applications efficiently.

Canal Boat Simulator Summary

The author shares the story behind creating a canal boat-themed game after a casual comment made during a relaxing evening. Initially inspired by a show about canal boating, the author jokingly imagined a gritty game, which led to a serious endeavor to develop it.

Despite lacking experience in 3D modeling, the author decided to use the Godot game engine, alongside a developer friend, to bring the game to life. Over the course of about two months, they faced various challenges, including making the game mobile-friendly, which required a lot of technical adjustments.

The game is a short prototype that takes only three minutes to complete, but the author reflects that each minute of gameplay involved a month of development. They emphasize the importance of making the game fun and engaging, noting that game development differs from other programming due to its focus on enjoyment.

The author appreciates the tools and knowledge gained throughout the process, thanks to resources like ChatGPT and YouTube tutorials. They conclude by humorously acknowledging that their prototype differs from the relaxing game concept originally imagined by the friend who inspired it.

Overall, the author encourages readers to explore the game and shares insights on game design, development challenges, and the creative process.