Researchers have discovered a black fungus at the Chernobyl nuclear disaster site that appears to thrive on radiation. This fungus grows towards radioactive particles, suggesting it may use radiation as an energy source, a process called "radiosynthesis." This discovery challenges previous beliefs about the harmful effects of radiation on life.

Nelli Zhdanova first observed this phenomenon in 1997, finding that the fungus, which contains melanin, could potentially protect against radiation. Melanin helps shield cells from harmful rays, similar to how it protects human skin from UV light. Further studies have shown that this fungus grows faster in radiation, and experiments in space have confirmed its ability to grow better under cosmic radiation.

These findings raise the possibility of using the fungus as a natural radiation shield for astronauts on missions to the Moon and Mars. Instead of heavy materials, fungal structures could provide both living space and protection from harmful cosmic rays, potentially reducing the costs and challenges of space travel.

Open-source developers are calling for equal recognition and support as traditional organizations receive. They want their contributions to be valued similarly to those in established groups.

Summary of the New Runbook Execution Engine Announcement

Atuin Desktop has introduced a redesigned runbook execution engine, which marks a significant improvement in how runbooks operate. This update aims to enhance automation by ensuring runbooks maintain their state, work reliably, and don’t require re-running commands after closing tabs or restarting the app. Key features include:

1. Persistent Runbooks: Runbooks retain their execution state even after app restarts or tab closures, eliminating the need to rebuild contexts.

2. Predictable Behavior: Each block in a runbook only impacts the blocks that follow it, ensuring clarity in how variables and states are used.

3. Enhanced Templates: Users can utilize templates for variable names and within blocks, allowing for more dynamic and self-referential variables.

4. Context Types: The engine introduces two context types:

   • Passive Context: Automatically set during document updates.
   • Active Context: Set during block execution, containing real-time output and state.

5. Future Collaboration: The new architecture sets the stage for real-time collaborative execution, enabling users to share entire running environments in real-time.

6. Technical Updates: The execution system has been rewritten to improve reliability and portability across different environments.

7. Future Features: Upcoming enhancements will include a command-line interface (CLI) for running runbooks, improved secret management, and the ability to store runbooks as Markdown files for better portability.

The new execution engine is available in version 0.2.0, and users are encouraged to update their Atuin Desktop installations to experience these improvements.

Smart glasses with cameras, like Meta Ray-Bans, are becoming more popular, and some people want to hide the recording indicator light. A project is underway to find ways to detect when these glasses are recording.

The project uses two main methods:

1. Retro-reflectivity: This involves looking at infrared reflections from the camera sensor, but results have been mixed.
2. Wireless traffic: The focus is on detecting Bluetooth Low Energy (BLE) signals using an ESP32 device. This method can consistently identify when the glasses are pairing, powering on, and sometimes when they are taken out of the charging case. A sound is played when detection occurs.

The goal is to detect the glasses while they are actively recording, not just when they start up. The researcher is considering using an nRF52840 chip for better BLE tracking, but it still requires initial connection detection. However, Bluetooth Classic hardware is costly. Suggestions for improvement are welcome.

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

Summary of "A Tale Of Four Fuzzers"

This text discusses the development of four different fuzzers used to improve the routing algorithm of TigerBeetle, a system that ensures data durability through replication. Here's a simplified breakdown of the key points:

1. Introduction to Fuzzing: The author introduces the concept of fuzzing, which involves testing software by inputting random data to find bugs. They emphasize that using just one fuzzer is insufficient for comprehensive testing.

2. Replication Basics: The text explains TigerBeetle’s approach to data durability, highlighting the importance of storing multiple copies of data across various machines to prevent loss.

3. Routing Topologies: The original routing method used a ring topology, which had limitations, including vulnerability to network failures. The new Adaptive Replication Routing (ARR) improves upon this by dynamically adjusting the routing paths based on real-time performance metrics.

4. Fuzzing Strategies: The author outlines four main fuzzers:

   • Fuzzer #1 (Exhaustive Positive Space): Tests all possible routes for encoding/decoding to ensure data integrity.
   • Fuzzer #2 (Negative Space): Focuses on invalid inputs to test the robustness of serialization/deserialization processes.
   • Fuzzer #3 (Qualitative Fuzzing): Simulates real-world scenarios to ensure that the ARR algorithm effectively converges to the best routes.
   • Fuzzer #4 (Negative Space Testing): Randomly tests the routing methods without specific modeling, ensuring that the system does not crash and functions correctly.

5. Importance of Interfaces: The text emphasizes that good interfaces are crucial for effective fuzzing. Careful design can minimize dependencies, making the system easier to test.

6. Testing Strategies: Fuzzing should include both positive and negative cases, with a focus on boundaries between valid and invalid inputs. Using a combination of fixed and random seeds can help ensure thorough testing.

7. Conclusion: The author concludes that fuzzers not only help identify bugs but also enhance understanding of the underlying problems in the system. They encourage using fuzzers as tools for exploring and improving software design.

Overall, the text illustrates the complexities and methodologies involved in fuzz testing, particularly for a robust data replication system like TigerBeetle.

The text suggests two actions: viewing a live demonstration and reading the provided documentation.

Summary of moss Kernel

Moss is a Unix-like kernel compatible with Linux, developed using Rust and Aarch64 assembly. It has a modern design and can run many Linux applications, particularly those from BusyBox.

Key Features:

1. Architecture and Memory:

   • Fully supports Aarch64 and can be ported to other architectures.
   • Includes advanced memory management features like page table management and a buddy allocator for memory tracking.

2. Async Core:

   • Utilizes Rust's async/await model for system calls, preventing common kernel deadlocks.

3. Process Management:

   • Manages tasks, scheduling, and supports 51 Linux system calls.
   • Provides advanced forking and signal handling capabilities.

4. Virtual File System (VFS):

   • Offers an async VFS with drivers for RAM disks and a read-only FAT32 filesystem.

5. Testing and Libraries:

   • Built on libkernel, allowing for architecture-independent testing with a robust test suite.

Building and Running:

• To set up moss, you need QEMU for Aarch64 emulation and the aarch64-none-elf toolchain.
• Follow specific commands to prepare the kernel image and run it in QEMU.

Development Status:

• Active development is ongoing, focusing on enhancing syscall compatibility, networking, and filesystem capabilities.

Contributions:

• Open for contributions, whether for drivers, porting, or syscall additions.

License:

• Distributed under the MIT License.

Spikelog is a simple tool I created to track numbers over time without the complexity of traditional observability tools. Here are the key features:

• You can easily submit data by sending a JSON with a chart name and value.
• Charts are generated automatically.
• Each chart can store up to 1,000 data points, with old data being deleted automatically.
• You can create a maximum of 10 charts.

I built Spikelog in about a day using Cursor, and it has a minimal API for easy use with AI assistants. It can also automatically track its own data.

Currently, Spikelog does not have alerting, complex aggregations, or dashboards beyond the basic charts. It's designed for users who just want to see if a number changes, rather than needing a full observability solution like Axiom or Datadog.

You can share charts publicly, and I may add password protection based on user demand. I've not tested it under heavy load, and there may be some issues to resolve. I'm open to feedback, especially if you encounter any problems.

No summary available.

No summary available.

The Swedish publishers' association, Utgivarna, has reported Meta founder Mark Zuckerberg to the police. They are concerned about fake ads on Facebook that use the names of well-known Swedish media and journalists to scam people. James Savage, the chairman of Utgivarna, claims that Meta is not doing enough to stop these scams and is profiting from them. Meta, however, states that fighting scams is a priority for them.

The Louvre museum in Paris will increase ticket prices for most non-European Union tourists by 45%, starting January 14. Visitors from countries like the US, UK, and China will pay €32 ($37; £28) to enter, up from €22. This price hike is expected to generate €15 million to €20 million annually for museum renovations and improvements.

The decision follows criticism of the museum's security after a high-profile theft in October, when jewelry worth $102 million was stolen. An audit revealed the museum's security systems and infrastructure need upgrades.

The Louvre, which attracted nearly 9 million visitors last year, plans to enhance visitor experience by renovating facilities and moving the Mona Lisa to a new location to reduce crowding. The museum is also addressing complaints about congestion and long wait times.

No summary available.

The EU Parliament has voted to require digital identification and age verification for online activities. This move raises concerns about online privacy, as it may lead to increased surveillance and data collection.

Dia2 is a text-to-speech (TTS) model developed by Nari Labs that can generate audio from just a few initial words, allowing for real-time dialogue. It offers model checkpoints (1B and 2B) and code for research but supports audio generation in English for up to 2 minutes.

Key points:

• The audio quality can vary, as the model isn't fine-tuned for specific voices. For better results, users can provide a prefix or fine-tune the model.
• To get started, install required dependencies and prepare an input script with speaker tags.
• There are options for generating audio alone or using previous audio clips to improve conversation flow.
• Users can run the model simply via the command line or use Gradio for a user-friendly interface.
• The model has specific ethical use guidelines, prohibiting misuse such as creating misleading or harmful content.

For more information, you can try it on Hugging Face Spaces or join their Discord for support.

No summary available.

Many valuable posts on Hacker News get overlooked in the /newest section due to lower-quality submissions. For Hacker News to thrive, users need to visit this section regularly to upvote or flag content. Spending a few minutes each day there is more beneficial than just commenting. This effort is often unrecognized, similar to Reddit's initial community efforts, but it is important for the site's success.

Summary: Switzerland's Data Protection Officers Suggest Limited Use of US Cloud Services

Swiss Data Protection Officers have recommended that federal authorities significantly limit their use of international cloud services like AWS, Google, and Microsoft. This recommendation acts as a near-ban on using these services for sensitive or confidential personal data. Authorities may only use them for basic applications like online storage, not for comprehensive services.

The main concerns driving this recommendation include the risks of data breaches, lack of sufficient encryption, and the potential for US laws, like the Cloud Act, to require data disclosure, even if the data is stored in Switzerland. These issues create legal uncertainties for authorities handling confidential information.

While the recommendation is serious, it is not legally binding. The Swiss Federal Chancellery has stated that sensitive data will not be processed in public clouds. The situation presents challenges for federal authorities in terms of their IT strategies.

No summary available.

Summary

Zero Technical Debt

Tiger Style prioritizes safety, performance, and developer experience with a strong focus on maintaining zero technical debt. This means:

• Do it right the first time: Properly design and implement solutions to avoid future problems and costly changes.
• Be proactive: Anticipate issues early to prevent bigger problems later, saving time and resources.
• Build momentum: Delivering reliable code boosts confidence and speeds up development, supporting innovation.

By avoiding technical debt, progress remains solid and sustainable.

Performance Estimation

Consider performance early in the design process using "napkin math," which involves quick calculations to estimate system performance and resource needs. Benefits of this approach include:

• Gaining quick insights into system behavior.
• Identifying potential bottlenecks early.
• Performing sanity checks on ideas before implementation.

For example, to estimate monthly storage costs for logs, you can use simple calculations based on expected log volume and costs.

Colophon

This document is a remix inspired by the original Tiger Style guide and is maintained by Simon Klee. It is licensed under CC BY 4.0 and was last updated in October 2024.

No summary available.

Jotunn 8: The Ultimate AI Inference Chip

• Introduction: Jotunn 8 is the world's most efficient AI inference chip, designed for modern data centers to enhance speed, reduce costs, and enable scalability.

• Key Features:

  • Ultra-low Latency: Essential for real-time applications like chatbots and fraud detection.
  • Very High Throughput: Supports high-demand services such as recommendation engines.
  • Cost Efficiency: Reduces the cost per inference, crucial for large-scale AI operations.
  • Power Efficiency: Optimizes performance per watt, lowering operational costs and environmental impact.

• Performance Focus: Jotunn 8 is built for speed, efficiency, and sustainability, making it ideal for deploying AI at scale without compromising performance.

• Versatile Use: It can support various AI models, including reasoning, generative, and agentic AI, allowing for seamless integration and enhanced capabilities.

• Conclusion: Jotunn 8 offers a robust solution for businesses looking to maximize their AI investments while maintaining competitiveness and driving growth.

The text promotes an AI-powered DevSecOps platform, highlighting that it is comprehensive and designed to enhance development, security, and operations.

The text discusses how to create Linux virtual machine (VM) images and enable communication between the VM and the host machine using a technology called vsock. Vsock simplifies communication by avoiding the need for traditional network setups.

Key points include:

1. Vsock Overview: Vsock allows VMs to communicate without a TCP/IP stack, acting like a standard socket with a unique addressing scheme.

2. gRPC Usage: The experiment demonstrates using vsock to run a gRPC service in a VM, which allows remote procedure calls (RPC) from the host to the VM.

3. Project Setup: The project is built using Bazel, which helps manage dependencies and build processes efficiently. Key external dependencies include gRPC and Protobuf libraries.

4. Code Breakdown:

   • The gRPC service defined can perform addition on two integers.
   • The server and client implementations are straightforward C++ programs that utilize the gRPC framework.

5. Running the Setup: The server is built into a static binary and deployed into a VM created using a tool called debootstrap. The VM is then run using QEMU, with vsock as the communication channel.

6. Successful Communication: The client application running on the host connects to the server in the VM, successfully sending an addition request and receiving the result.

7. Conclusion: The use of gRPC with vsock enables efficient communication in isolated environments, allowing for diverse applications across different operating systems, without the overhead of network virtualization.

Overall, the text provides a practical guide to setting up and using vsock for gRPC communication in Linux VMs.

Charles M. Schulz created the iconic Peanuts comic strip, featuring characters like Charlie Brown and Snoopy, which he drew for 50 years until his retirement in 1999 due to health issues. Schulz humbly noted that while his work addressed everyday problems, he believed it touched on deeper themes like love, fear, and insecurity. His ability to relate to both children and adults contributed to Peanuts' worldwide popularity, leading to its syndication in over 2,600 newspapers and inspiring various media and merchandise.

Schulz drew children because he found it commercially successful. He also drew inspiration from his own experiences as a shy child, preferring to learn drawing through correspondence courses. Despite the pressures of creating daily comics, he focused on producing work that he found funny, emphasizing the joy of cartooning.

He maintained confidence in the potential success of Peanuts, although he was surprised by some outcomes, like Snoopy's adventures. Schulz continued working on the strip until his death in February 2000, leaving a message of resilience through Charlie Brown, who exemplified persistence by never giving up.

A year ago, Ajax set out to improve its hub operating system, aiming to keep its best features while eliminating weaknesses. This effort resulted in OS Malevich, a new and advanced system designed for reliability and security.

Initially, Ajax considered three options for the operating system: C, a real-time operating system (RTOS), and Linux. C would offer absolute control but would be time-consuming and hard to scale. Linux provided many ready-made solutions but posed security vulnerabilities, making it unsuitable for their safety-focused needs. Therefore, they chose RTOS, which is used in critical systems like elevators and car brakes, ensuring timely and reliable operations.

After a year and a half of development, they created an OS that could manage multiple devices and communication methods, meeting professional security standards. However, once the hub was launched, customers requested new features, highlighting the need for a more flexible system.

To address this, Ajax decided to develop a new architecture for OS Malevich, emphasizing simplicity while allowing for complex features. They restructured their development process to enable faster feature implementation without sacrificing reliability. The result is a modular system that allows for easy updates and adjustments, ensuring that Ajax products can evolve quickly and efficiently.

Overall, OS Malevich represents a significant advancement in Ajax's technology, combining reliability with the ability to adapt to new demands in the security market.

EDN.C Overview

EDN.C is a fast and efficient reader for Extensible Data Notation (EDN), which is a flexible data format similar to JSON, designed to be more expressive and extensible.

What is EDN?

• Structure: EDN uses a format similar to JSON with maps, vectors, strings, numbers, booleans, and null values.
• Extended Features: It includes sets, keywords, symbols, and lists, and allows custom data types through tagged literals (e.g., date and UUID).
• Readability: Designed to be human-friendly with comments and flexible whitespace.
• Use Cases: Originally from Clojure, it is useful for data interchange in various programming environments.

Advantages of EDN vs. JSON:

• More expressive types (e.g., keywords and sets).
• Native extensibility without hacks for type identification.
• Better suited for functional programming and configuration files.

Key Features of EDN.C:

• Performance: Uses SIMD acceleration for fast parsing and minimal memory allocation.
• Zero-copy Parsing: References input data directly to reduce memory usage.
• API: Simple to use with strong type support.
• Compatibility: Fully tested and supports UTF-8 encoding.
• No Dependencies: Built purely with C11 and the standard library.

Installation and Usage:

• Requires a C11 compatible compiler and a build system like Make or CMake.
• Supports multiple platforms, including macOS, Linux, and Windows.
• Users can build the library and integrate it into projects easily.

Example Usage: A simple example illustrates how to parse an EDN string and retrieve values, showcasing error handling and memory cleanup.

Advanced Features (optional):

• Extended integer formats, ratio numbers, underscore in numeric literals, and metadata.
• Tagged literals and custom readers for data transformations.
• Map namespace syntax for cleaner key management.

Building and Performance:

• The library is optimized for speed with SIMD enhancements and efficient memory management.
• Performance benchmarks demonstrate quick parsing times for various data types.

Contribution and Licensing:

• Contributions are encouraged under the MIT License.
• The project is open for further development and enhancements.

For detailed documentation and examples, users can refer to the provided directories and resources.

The text discusses the current state of artificial intelligence (AI), particularly focusing on the limitations of large language models (LLMs) and the potential economic consequences of continued investment in this technology. Key points include:

1. Expert Opinions: Notable machine learning researcher Ilya Sutskever has expressed concerns that merely scaling AI through more data and computing power is becoming less effective. He suggests the need for new approaches, including neurosymbolic techniques.

2. Diminishing Returns: Many experts, including Sutskever, agree that increasing the size of LLMs has not resolved fundamental issues like reasoning and generalization. This realization has been slow to gain traction within the machine learning community.

3. Financial Impact: The author estimates that approximately a trillion dollars may have been wasted on AI experiments, particularly on expensive hardware and salaries. If LLMs do not deliver the anticipated results, it could lead to significant economic repercussions, including potential recession.

4. Investor Behavior: Venture capitalists are heavily invested in scaling LLMs, even if the fundamental issues remain unresolved. This focus on scaling rather than innovation may lead to financial instability if expectations aren't met.

5. Broader Consequences: A crash in AI investments could have widespread impacts on the economy, affecting jobs and consumer spending. The AI sector has been a significant driver of economic growth, and a downturn could create a financial crisis.

6. Community Reflection: The text suggests that the AI field has ignored valuable insights from other disciplines, which could have prevented the current predicament. The author reflects on the potential for this situation to have been avoided, likening it to a Greek tragedy.

In summary, the text highlights the urgent need for new ideas in AI beyond LLMs and warns of the severe economic risks tied to the current trajectory of investment in this technology.

No summary available.

A new large-scale project in Finland will use a "Sand Battery" technology developed by Polar Night Energy, in partnership with Lahti Energia. This system will have a heating power of 2MW and a thermal energy storage capacity of 250MWh, making it the largest sand-based thermal energy storage project once completed. It aims to provide heat for a district heating network and participate in grid balancing markets.

The Sand Battery works by heating sand with electricity, storing the heat, and then using it for heating or industrial purposes. This project is expected to reduce fossil fuel emissions in the district heating network by about 60% annually by significantly lowering natural gas and wood chip usage.

Construction will begin in early 2026, with completion expected by summer 2027. The project is supported by a grant from Business Finland.

Summary

The text discusses the challenges of maintaining focus in the modern work environment, especially with increasing interruptions from tools like Slack and video calls. It highlights how these interruptions can significantly reduce productivity and suggests a mathematical model to analyze workdays based on three key parameters:

1. Lambda (λ): The rate of interruptions per hour. Higher values mean more frequent interruptions, which can disrupt focus and reduce productivity.
2. Delta (Δ): The recovery time needed to regain focus after an interruption. Longer recovery times lead to more lost productivity.
3. Theta (θ): The minimum uninterrupted time required to accomplish meaningful work. If tasks require longer focus periods than what is available, productivity suffers.

The text illustrates how these parameters affect a typical workday, showing the difference between "bad" and "good" workdays through simulations. For example, a day with many interruptions and long recovery times leads to very little productive work, while a day with fewer interruptions and shorter recovery times allows for more focus time.

Key takeaways include:

• Reducing interruptions (λ) is crucial for improving productivity.
• Adjusting tasks to fit the available focus time (θ) can enhance work efficiency.
• Shortening recovery time (Δ) can help maintain momentum after interruptions.

The author encourages readers to experiment with these parameters to find strategies that work best for them, suggesting that even small changes can lead to significant improvements in productivity.

No summary available.

Summary: A Programmer-Friendly I/O Abstraction Over io_uring and kqueue

This article discusses improving input/output (I/O) performance in programming through the use of non-blocking APIs like io_uring (for Linux) and kqueue (for FreeBSD/macOS).

1. Traditional I/O Limitations: In traditional blocking I/O, operations like reading and writing data can be slow and inefficient, especially since system calls are costly and can lead to wasted time when data isn't immediately available.

2. Batching with New APIs: By using io_uring or kqueue, programmers can submit multiple I/O requests at once and receive notifications when these requests are ready. This batching reduces the overhead of multiple system calls.

3. Kernel-Level I/O: io_uring allows the kernel to handle read/write operations directly, which can significantly improve performance by reducing the need for userland calls.

4. Event Loop Implementation: A central I/O dispatch mechanism can be created to simplify how I/O is scheduled and handled, allowing callbacks to be invoked when operations complete, without cluttering the main application logic.

5. Handling Callbacks: User data fields in io_uring and kqueue can store pointers to callbacks, enabling the application to trigger the right function when an I/O operation finishes.

6. Expressive APIs: The introduction of specific functions for different I/O operations (like io_dispatch.read and io_dispatch.write) makes the API more user-friendly.

7. Overflow Management: Since there’s a limit on the number of events that can be processed at once, an overflow queue can be implemented to handle excess requests.

8. Cross-Platform Support: The article notes that while the primary focus is on Linux and macOS, Windows has a similar system called IOCP, and TigerBeetle offers a consistent I/O abstraction across platforms.

9. Single vs. Multi-threaded Architectures: The implementation discussed is single-threaded for simplicity and determinism, but there are possibilities for multi-threaded architectures for workloads that benefit from parallel processing.

10. Future Development: The authors express interest in potentially releasing the I/O abstraction as a standalone library that could be used in various programming languages.

These points highlight the advancements in handling I/O operations more efficiently and the tools available for developers to streamline their applications.

No summary available.

Summary: The Impact of Shor's Algorithm on Cryptography

1. Introduction to Shor's Algorithm: Peter Shor’s algorithm threatens all current public-key cryptography systems (like RSA and ECC) by enabling quantum computers to efficiently break them. This poses a retroactive risk; encrypted data today could be decrypted in the future.

2. Key Problems in Cryptography: Most internet security relies on two difficult problems:

   • Factoring: Breaking down large numbers into their prime factors (used in RSA).
   • Discrete logarithms: Finding an exponent in equations involving modular arithmetic (used in Diffie-Hellman and ECC). Classical computers struggle with these, but quantum computers can solve them quickly using Shor’s method.

3. Quantum Advantage: Shor’s algorithm transforms complex problems into simpler ones by finding periods in sequences, allowing quantum machines to factor numbers and solve discrete logs in polynomial time, making them much faster than classical methods.

4. Breaking RSA: Shor's algorithm can effectively break RSA encryption by:

   • Acquiring public keys and selecting a random base.
   • Using quantum computations to find the period of a function and then derive factors of the key.
   • This process can break RSA-2048 in minutes.

5. ECC Vulnerability: Elliptic Curve Cryptography (ECC) can be broken with similar ease. Since ECC keys are smaller, they require fewer quantum resources, making them easier targets than RSA.

6. Data Harvesting: Intelligence agencies are already capturing encrypted data, planning to decrypt it once quantum computers become operational. This means years of data could be compromised once these technologies are available.

7. Quantum Requirements: To effectively break current cryptographic systems, significant quantum resources are needed, which are still in development.

8. Limitations of Key Size: Simply increasing key sizes (e.g., to 8192 bits for RSA) does not provide security against quantum attacks, as Shor’s algorithm runs in polynomial time regardless of key size.

9. Post-Quantum Cryptography: New cryptographic methods based on lattice problems and other mathematical constructs are being developed to resist quantum attacks. NIST has standardized several promising approaches, including Kyber and Dilithium.

10. Migration Challenges: Transitioning from current systems that rely on RSA/ECC to quantum-resistant options is a monumental task, affecting various sectors including finance and data security.

11. Blockchain Risks: The vulnerabilities of ECC mean that cryptocurrencies like Bitcoin could be at risk, potentially allowing attackers to drain funds from exposed addresses.

12. Immediate Actions Needed: Organizations should:

• Avoid using traditional RSA or ECC for long-term security.
• Implement hybrid cryptographic systems that combine classical and post-quantum methods today.
• Start migrating existing systems to quantum-resistant solutions.

13. Final Thoughts: The threat from quantum computing is imminent, and organizations must act quickly to secure their data before it becomes vulnerable. Shor’s algorithm has revealed the inherent weaknesses in our current cryptographic systems.

Summary:

As teams grow, providing and receiving feedback becomes increasingly challenging. When leading small teams (5-10 people), feedback is informal and based on personal relationships. As team size increases to 20 and then 100, these relationships weaken, making it harder to understand feedback because leaders may not know everyone personally.

By the time a team reaches 200 people, feedback can feel overwhelming and chaotic, often dominated by loud voices expressing dissatisfaction. Positive feedback tends to diminish as people assume things are fine. This creates a situation where leaders struggle to differentiate between genuine concerns and noise, leading to defensiveness and confusion.

To manage feedback effectively in larger organizations, leaders need to recognize that personal relationships cannot scale. They should implement structured systems to process feedback, build proxy relationships through trusted team leaders, and establish clear channels for feedback collection. It’s essential to respond humanely, close the feedback loop, and avoid anonymous feedback, which lacks context.

Ultimately, leaders must accept that they will not please everyone and may not be able to fully address all frustrations. Acknowledging this reality is crucial to avoid burnout and maintain effective leadership as organizations grow.

The writer has been part of the community for fifteen years and appreciates it for its knowledge, lively discussions, and occasional sass, despite complaints about its quality compared to the past. They express gratitude to two community members and look forward to another year in the community.

The text reflects on memories from elementary school and dives into the history and structure of the Domain Name System (DNS) used for Internet addresses.

Key points include:

1. Nostalgia for Elementary School: The author recalls various school experiences, including a chess-playing teacher and attempts to raise funds for art.

2. Understanding DNS: The DNS is described as a hierarchical system that organizes computer names, much like a tree structure. Each level in the DNS hierarchy has a specific purpose, with top-level domains (TLDs) being fixed and second-level domains often available for registration.

3. Historical Context: The text discusses the evolution of the DNS and its current structure, including the distinction between global TLDs (like .com) and country-code TLDs (like .us), which reflect geographical and organizational hierarchies.

4. RFC 1480: This document from 1993 proposed a more structured approach to the .us domain, suggesting a hierarchy that included localities, which has largely faded in favor of simpler naming conventions.

5. Challenges of Complex Names: The author argues that deeply hierarchical domain names can be confusing and less user-friendly. Although a structured approach aims to reduce name conflicts, it often results in longer and more complex names that are harder for users to remember.

6. Current State of DNS: Many of the original hierarchical names are still in use, but the trend has moved towards simpler, more memorable names, particularly as government agencies and organizations have shifted to using .gov or other straightforward TLDs.

In summary, the text explores the balance between a structured naming system and user-friendliness in the context of DNS, reflecting on its historical development and current practices.

No summary available.

No summary available.

Beads Issue Tracker Summary:

Beads is a lightweight issue tracker designed for coding agents, enhancing their organization and task management capabilities. The latest version, 0.20.1, introduces hash-based IDs for issues, which prevent collisions when multiple agents create issues simultaneously. This version supports multi-worker and multi-branch workflows, making it more reliable.

Key Features:

• Hash-Based IDs: Replacing sequential IDs with short, unique hashes (e.g., bd-a1b2) to avoid conflicts.
• Multi-Agent Support: Agents can work concurrently without losing track of issues.
• Dependency Tracking: Issues can be linked in various ways (blocks, related, parent-child).
• Git Integration: Issues are stored in JSONL format and synced via Git, maintaining a shared state across different machines.
• Audit Trail: All changes are logged for easy tracking of project history.

Installation: Set up Beads quickly using a single command (bd init), which creates a local database and configures Git hooks.

User Workflow:

• Coding agents automatically create and manage issues, improving long-term planning and reducing lost work.
• Users can interact with Beads through simple commands to create, update, and view issues.

Compatibility:

• Requires Linux with glibc 2.32 or higher, but has no special requirements for macOS or Windows.

Usage: Beads is ideal for AI agents, allowing them to manage complex tasks while ensuring nothing is overlooked. It also provides tools for manually checking and updating issues for human users.

In summary, Beads significantly enhances task management for coding agents, making it easier to track and handle issues in software projects.

Lara and Benno Lang took a 20,000 km road trip around Australia with their family of four in a small electric car, the BYD Dolphin. They found the journey enjoyable and manageable, starting from Adelaide with their car packed for adventure. Their trip included swimming with cuttlefish, traveling across the famous Nullarbor Plain, and exploring iconic destinations along the west coast. They encountered various charging stations, including solar-powered ones, and enjoyed scenic views and wildlife, such as dolphins and whale sharks.

Despite some challenges, like long distances between chargers in the Northern Territory and quirky charging situations, they embraced the adventure. They also highlighted the unique history and attractions in Queensland and New South Wales, including “big things” and local eateries. They enjoyed the trip's fun moments, like in-car karaoke, and noted the convenience of charging stations on their return to Adelaide. Overall, they spent $1,811 on charging during their journey, showcasing the feasibility of an electric road trip across Australia. Their trip ended with a memorable swim with a whale shark, making it a unique family adventure.

OpenAI, despite its success with ChatGPT, is still not profitable and faces significant financial challenges. Market concerns have arisen about a potential bubble in artificial intelligence, even as companies like Nvidia report strong earnings. HSBC analysts project that OpenAI will not become profitable by 2030, despite an expected user base growth from 10% to 44% of the world's adult population. The company will need an additional $207 billion in computing resources to support its growth, which includes major cloud computing deals with Microsoft and Amazon.

HSBC estimates that OpenAI's operational costs will reach $792 billion by 2030, with total commitments at $1.4 trillion by 2033, leading to a cumulative cash flow deficit. Although revenue is expected to rise significantly, it will not be enough to cover expenses. OpenAI's future depends on attracting more paid subscribers, increasing its share of digital advertising, and improving operational efficiency, but it will still require new funding.

The company is closely tied to its financial backers, like Microsoft and Amazon, and faces risks from uncertain revenue models and market saturation. Raising debt for funding is challenging in the current market. Analysts also express concerns about the overall productivity gains from AI and technology investments, suggesting that while AI has potential, significant returns are not yet guaranteed.

In the past, installing Java was straightforward: you downloaded one version from a single source, and that was it. However, today, the process is much more complex due to multiple vendors (like Amazon, Red Hat, and Microsoft) offering various Java distributions, each with different features and licensing terms. There are also multiple versions of Java available, such as Long-Term Support (LTS) releases (Java 8, 11, 17, and 21), which makes it challenging for developers to choose the right one.

To manage this complexity, developers typically follow one of two approaches:

1. Manual Installation: This involves downloading Java from vendor websites and managing settings manually, which can be tedious with multiple versions.

2. Version Managers: Tools like SDKMAN! automate the installation and switching of different Java versions, simplifying the process significantly. They allow developers to install, update, and switch between versions easily without cluttering their systems.

Version managers streamline the development process by providing a unified interface and managing configurations automatically. They are beneficial because they simplify installation, ensure team consistency, isolate project environments, and facilitate easy upgrades and cleanup.

Different programming languages have their own version managers, such as pyenv for Python and nvm for Node.js. For those working with multiple languages, tools like asdf-vm can manage them all.

In summary, if you're still managing installations manually, consider adopting a version manager. This will save you time and reduce complications in your development workflow, allowing you to focus more on your projects.

Going indie as a developer is thrilling because it offers freedom from a traditional 9-to-5 job, allowing you to build your own app. However, the reality can be quite different than expected. You face challenges like loneliness, pressure, constant decision-making, and the need to juggle multiple roles, such as developer, designer, and marketer—all on your own.

While some indie developers hire freelancers for specific tasks, many handle everything themselves, which can be overwhelming. The lack of colleagues to collaborate with can make the experience isolating, though connecting with other indie developers online can help.

Once your app is released, the work isn’t over. You must market your app, handle user feedback, and manage analytics—all vital for success. Your users become crucial to your business, providing both praise and criticism that you must navigate.

Time management is essential; you need to prioritize tasks effectively to balance feature development, user support, and marketing. The flexibility of indie work allows for a personalized schedule, but it also means you must decide what to focus on each day.

AI tools can assist in the development process, but many developers still prefer hands-on coding. There are various resources available to help navigate the indie journey, including courses and books on app optimization and marketing.

In conclusion, while indie life can be rewarding and educational, it is not for everyone. It requires wearing many hats and dealing with uncertainty, but for those who enjoy the challenge, it can be a fulfilling path.

No summary available.

Summary of Google TPU Overview

The Google Tensor Processing Unit (TPU) is a custom chip designed specifically for AI tasks, particularly for running TensorFlow neural networks. The TPU was developed in response to Google’s need to handle increasing computational demands from AI features, such as voice search, which required more efficient processing than standard CPUs and GPUs could provide.

Key Points:

1. History and Purpose: Google began developing TPUs around 2013 to improve efficiency in data centers and address the challenges of deep learning workloads.

2. TPU vs. GPU:

   • TPUs are specialized for specific tasks (like AI inference) while GPUs are general-purpose processors.
   • TPUs utilize a "Systolic Array" architecture that minimizes memory access, improving data processing speed and efficiency.

3. Performance:

   • The latest TPU model (TPUv7) significantly outperforms its predecessor (TPUv5p) in terms of processing power, memory capacity, and bandwidth.
   • TPUs are often more cost-effective and energy-efficient compared to GPUs, particularly for specific AI applications.

4. Adoption Challenges:

   • The main barrier to wider TPU adoption is the ecosystem; most AI developers are familiar with Nvidia's CUDA rather than Google’s TPU frameworks.
   • TPUs are currently available only on Google Cloud Platform, limiting their accessibility compared to Nvidia GPUs, which are supported across major cloud services.

5. Strategic Advantage:

   • Google’s TPUs provide a significant competitive edge in the cloud market, allowing for better margins by reducing reliance on Nvidia's expensive GPUs.
   • The TPU is seen as a key asset for Google to maintain or grow its market share in the evolving AI landscape.

6. Future Production: Information on the current production levels of TPUs is limited, but there is potential for growth as demand for AI processing increases.

Overall, Google’s TPUs are positioned as a crucial innovation for improving AI capabilities and cloud services, despite facing challenges in broader adoption and competition.

Summary of Mixpanel's Security Incident Response

On November 8, 2025, Mixpanel discovered a smishing (SMS phishing) campaign that affected a small number of customers. In response, Mixpanel acted quickly to secure user accounts and prevent further unauthorized access. They worked with external cybersecurity experts and communicated directly with affected customers.

Key actions taken include:

• Securing affected accounts
• Revoking active sessions
• Changing compromised account credentials
• Blocking harmful IP addresses
• Performing global password resets for employees
• Conducting a forensic review of logs
• Collaborating with law enforcement and cybersecurity advisors

If you were impacted, you should have received a communication from Mixpanel with details on securing your account. If you did not receive any messages, your account was not affected, and no action is needed. For questions, you can reach out to Mixpanel support.

Summary of "A Tale of Two Kernels"

This article discusses two main ways to run Haskell in Jupyter notebooks: IHaskell and xeus-haskell. Both allow users to execute Haskell code in Jupyter, but they are built differently.

1. IHaskell:

   • A monolithic kernel that directly implements the Jupyter protocol.
   • Tightly integrated with the GHC (Glasgow Haskell Compiler) API, allowing full access to the GHC ecosystem.
   • Requires matching GHC versions for installation, which can complicate setup.
   • Best suited for server-side applications and heavy workloads due to its performance.

2. xeus-haskell:

   • A middleware approach that uses the Xeus C++ library for protocol handling and connects to a simpler Haskell interpreter called MicroHs.
   • Easier to install and can run in client-side environments like browsers (e.g., JupyterLite).
   • Not as powerful as IHaskell in terms of library compatibility and performance but is great for quick prototyping and lightweight documentation.

Key Differences:

• Architecture: IHaskell is a standalone kernel, while xeus-haskell separates protocol management from Haskell execution.
• Ease of Use: xeus-haskell is simpler to set up and use, while IHaskell requires more configuration.
• Performance: IHaskell typically runs faster due to GHC, while xeus-haskell is more limited by its MicroHs interpreter.

Conclusion: IHaskell is ideal for standard server-side data science tasks, while xeus-haskell is better for lightweight, interactive documentation and client-side applications. Both kernels contribute to improving the Haskell ecosystem in data science.

No summary available.

The text discusses a graphics project that uses a technique called "distance fields" to create lighting effects in a visual demo. Here are the key points:

1. Distance Fields: This is a method where each pixel in an image indicates how far it is from a shape. Light grey pixels are close to the shape, while dark grey pixels are far away.

2. Ray Marching: The demo uses ray marching, where light rays are traced from pixels to the light source. The distance field helps determine whether a pixel is in shadow by checking if the ray intersects with shapes.

3. Shadow Calculation: The process advances along the ray based on the distance to the nearest shape, allowing for efficient shadow calculations without skipping smaller shapes.

4. Soft Shadows: The demo aims to create visually appealing shadows that aren't physically realistic but look nice. It uses three rules for calculating shadow intensity:

   • Closer rays to shapes should be darker.
   • Shadows should spread out for pixels farther from the intersection.
   • Light intensity decreases with distance from the light source.

5. Artifacts: The method can produce banding artifacts due to the approximation techniques used. Adjustments like adding random jitter can help reduce this issue.

6. Future Improvements: The author is open to suggestions for further enhancing the demo and is thankful for feedback from others during the writing process.

Overall, this project explores advanced graphics techniques to create interesting lighting effects in 2D visuals.

Summary of Penpot

Penpot is an open-source design tool that enables collaboration between designers and developers. It allows designers to create designs, prototypes, and design systems, while developers can easily access ready-to-use code. Penpot is available in browsers or can be self-hosted, and it supports open standards like SVG, CSS, HTML, and JSON. It's free to use.

Recent updates have improved Penpot significantly, introducing features like native design tokens for better collaboration, a new CSS Grid Layout, and a complete UI redesign.

Key features include:

• Two-way Collaboration: Designers and developers work together seamlessly.
• Plugin System: Expand functionality and integrate with other applications.
• Inspect Mode: Access code quickly (SVG, CSS, HTML).
• Self-hosting: Organizations can host their own Penpot instance.
• Design Systems: Use design tokens and components for consistency across projects.

Penpot encourages community involvement, allowing users to contribute in various ways, such as creating templates, reporting bugs, or translating content. The community offers support and a platform for discussions.

For those interested, Penpot will host a festival in Madrid, Spain, on October 9-10, 2025.

Penpot is licensed under the Mozilla Public License, v. 2.0, and is a project by Kaleidos Inc.

No summary available.

The text discusses an experiment with Robin Hood hashing, a technique for handling collisions in linear probing hash tables. Key points include:

1. Collision Handling: Hash tables usually handle collisions via linear probing (finding the next available slot) or chaining (linking elements with the same hash). Robin Hood hashing optimizes this by minimizing the "probing sequence length" (PSL), aiming to improve lookup speeds in read-heavy applications.

2. Probing Sequence Length (PSL): PSL refers to the distance between where an element is hashed to and where it is actually placed in the table. Robin Hood hashing attempts to equalize PSL across elements to enhance performance.

3. Implementation: The author created a simple implementation of Robin Hood hashing and benchmarked it against the standard unordered_map from C++. The implementation includes an insert function that swaps elements based on their PSL to maintain balance.

4. Performance Benchmarks: The benchmarks showed that Robin Hood hashing often outperformed unordered_map in various scenarios, particularly with sequential and random lookups. However, the performance benefits diminished in release builds compared to debug builds.

5. Mixed Workloads: The experiments also included mixed workloads (90% reads, 10% writes) and cache behavior tests, indicating significant advantages in performance for Robin Hood hashing, especially in scenarios with frequent lookups.

Overall, the results suggest that Robin Hood hashing can be a more efficient alternative to unordered_map, particularly for certain types of access patterns and workloads.

Summary: Designing a Mechanical Calculator

The author embarked on a project to create a mechanical calculator using 3D printing, driven by a passion for old technology. Initially, they searched for existing designs but found them either too complex or not modular enough. So, they decided to build their own design from scratch.

The first attempt involved creating gears that had issues with alignment and interlocking. After research, the author learned about "involute gears," which are better for transmitting force. They redesigned the gears using this knowledge but encountered problems with how the gears turned. Eventually, they used a 30-tooth gear to solve the turning issue.

After several iterations and improvements, including a new fastening system, the author created a more reliable version of the calculator. This final model has performed well, and the author is ready to share it with others, providing a link to the design and instructions for printing.

NASA's Voyager 1 spacecraft, launched in 1977, is nearing a significant milestone. By November 15, 2026, it will be 16.1 billion miles (25.9 billion km) from Earth, meaning it will take a full day for radio signals to reach it. This distance is equivalent to one light-day.

Voyager 1 has been traveling through space for nearly 50 years, having entered interstellar space in 2012. It travels at about 11 miles per second (17.7 km/s) and continues to send data back to Earth using its power source, which will last into the 2030s.

Communication with Voyager 1 is slow, taking about two days for commands to be sent and confirmed. In comparison, signals to the Moon take just 1.3 seconds. Voyager 1's journey demonstrates both the vastness of space and the enduring capabilities of human-made technology, highlighted by its famous "Pale Blue Dot" photograph of Earth.

Summary of Great Math Software by Xah Lee

This document lists various fun and useful math software programs that help visualize and understand different mathematical concepts. Key categories include:

1. 3D Geometry - Software for visualizing curves and surfaces in three dimensions.
2. 2D Geometry - Programs focused on plane geometry and visualizing shapes.
3. Hyperbolic Geometry - Tools designed for exploring hyperbolic space.
4. Complex Analysis - Software for studying complex numbers and functions.
5. Patterns and Symmetry - Programs for creating tilings and exploring symmetry.
6. Polyhedrons and Polytopes - Software to visualize and analyze geometric shapes.
7. Fractals - Programs for generating and studying fractal patterns.
8. Dynamical Systems - Software that simulates systems that change over time.
9. Cellular Automata - Tools for exploring cellular automata models.
10. Simulations - Includes programs like Boids that simulate flocking behavior.
11. Math Games and Puzzles - Various math-related games and puzzles, such as Peg Solitaire and Sokoban.
12. Miscellaneous - Additional tools for programmers and older math software.

Overall, the list presents a wide range of math software aimed at making math engaging and visually appealing.

Summary: Giving the Jakks Atari Paddle a Spin

The Jakks Atari Paddle, released in 2004, combines paddle gaming and plug-and-play technology, inspired by the Atari 2600's classic games. Unlike the original paddles that came in pairs for multiplayer, this version is available in one-player and two-player options, but I got the one-player version.

The Atari Paddle does not run original Atari 2600 games; it uses different hardware, likely a Winbond microcontroller, and employs "partial emulation" for gameplay. The graphics and game select screen indicate it is not based on Nintendo's NES-on-a-chip technology.

The device includes several classic games, such as Breakout and Warlords. However, it lacks some original controls, relying instead on a menu button for options. The graphics quality varies, and some effects from the original games are recreated, but not all render accurately.

Overall, the Jakks Atari Paddle is a fun novelty for retro gaming enthusiasts but doesn't require a dedicated search. It can be enjoyable if found at a low price, but it’s not essential for serious gamers.

The text provides CSS styles for a recommendation loader on a website. Here are the key points:

1. Layout Structure: The styles define how recommendation cards are displayed in different sections, including dimensions, margins, and padding for titles and item cards.

2. Responsive Design: Specific media queries adjust the layout based on screen size. For example:

   • At widths below 1200px, cards change to a 25% width.
   • At widths below 900px, they adjust to 33.33%.
   • At widths below 600px, cards take up 45% width and images are resized.

3. Card Design: Each card includes an image and text sections, with specific styles for height, width, and spacing to maintain a visually appealing layout.

4. Display Control: Certain cards are hidden at smaller screen sizes to optimize the display (e.g., the last card is hidden when there are too many).

5. Inline Loader: There is also a specific style for inline loading, which allows horizontal scrolling of items, with defined dimensions for navigation cards.

Overall, the CSS ensures that the recommendation section is visually organized and adapts well to various screen sizes.

No summary available.

No summary available.

The text lists various concepts and terms related to different fields, possibly in computer science or mathematics. Key points include:

• Examples: Refers to different types of examples or methods.
• Lamping A & B: Likely types of approaches or techniques.
• List Head: Could refer to a data structure or programming concept.
• Erasure vs Sharing: Discusses two different methods of data handling.
• Replicator Decay: A concept that may relate to data replication.
• Graph Coloring: A method used in graph theory.
• Δ-Nets: A term possibly related to networking or data structures, expected in 2025.
• λ-Calculus: A foundational concept in mathematical logic and computer science from 1936.
• Levels: Different types of measurement levels: Absolute, Relative, Linear, Affine, Relevant, Full.
• GitHub: A platform for version control and collaborative software development.

Overall, it covers various advanced topics in technology and mathematics without detailed explanations.

Prusa's biggest Black Friday sale lasts until December 1. You can get free shipping, discounts, and great gifts. Check out all the deals!

No summary available.

Here are some underrated reasons to be thankful:

1. Love from Pets: Your dog may have evolved to show affection, but she genuinely loves you.

2. Genetic Diversity: Mixing genes with a partner can lead to healthier offspring, helping life adapt.

3. Common Cold Vaccination: We could potentially vaccinate against common colds in the future.

4. Plague History: Urbanization helps spread diseases, but sanitation and vaccines protect us today.

5. Innovative Disease Control: We have many advanced methods to combat engineered diseases.

6. Clean Water: Access to clean water is nearly unlimited and affordable.

7. Dentistry: Dental care is a valuable aspect of health.

8. Radiation: Certain radioactive materials pose less environmental risk than we think.

9. Life Expectancy: Curing diseases may not drastically increase life expectancy, but it’s still worthwhile.

10. Unique Preferences: Our diverse tastes contribute to happiness.

11. Affordable Delicacies: Cardamom is a cheap spice that tastes luxurious.

12. History's Lessons: Figures like Grandma Moses remind us it's never too late for new beginnings.

13. Sleep: Sleep offers a necessary reset for our minds and bodies.

14. Air Travel Safety: Air travel remains one of the safest modes of transportation.

15. Market Resilience: Markets often manage risks better than individuals.

16. Human Relationships: The complexity of love and reproduction has been successful for humanity.

17. Mathematical Properties: Mathematical functions have interesting properties that can help in data fitting.

18. Light Field Storage: Advanced techniques allow us to capture complex light fields in simple formats.

19. Plastic Use: Properly disposed plastic can help sequester carbon.

20. Societal Support: Society generally supports parents, helping raise children without constant negotiation.

21. Political Progress: More people today experience democracy and civil liberties than in the past.

22. Three-Dimensional Life: Being in three dimensions makes eating simpler than it would be in two.

These points highlight various aspects of life that we can appreciate, from personal relationships to societal advancements.

In Japan and the EU, Open Source licenses are seen as contract agreements. In contrast, in the United States, Open Source licenses are viewed as "unilateral permission" rather than contracts. This perspective is significant because it shapes how Open Source is understood and used in the U.S.

Summary of ML-KEM Mythbusting by Sophie Schmieg

This article addresses myths and concerns about ML-KEM, a post-quantum cryptography standard developed by NIST. Here are the key points:

1. Origin of ML-KEM: ML-KEM was not invented by the NSA but was specified by European cryptographers. NIST made minor editorial changes to its original specification.

2. Backdoors: There is no backdoor in ML-KEM. A backdoor would require a secret that is hard to brute-force, but an analysis of ML-KEM shows it has too little parameter space (only 34 bits) to hide any backdoor.

3. Fault Attacks: While ML-KEM is vulnerable to fault attacks (a common issue in cryptography), this does not indicate a flaw in the algorithm itself but rather in how cryptographic systems can fail under certain conditions.

4. Decapsulation Failures: It is theoretically possible to create a ciphertext that a private key holder might reject, revealing information about the key. However, this is extremely unlikely due to how ML-KEM is designed.

5. Implementation Issues: Some initial implementations of ML-KEM had problems, but these are implementation flaws, not flaws in the algorithm itself.

6. Hybrid Cryptography: Hybrid schemes combine ML-KEM with other cryptographic methods for added security. While the NSA prefers using ML-KEM alone, most browsers use a hybrid version, which is seen as more efficient.

7. IETF Recommendations: The IETF does not discourage hybrid algorithms. Although ML-KEM isn't officially marked as recommended, it is widely used in practice.

In conclusion, most concerns about ML-KEM arise from misunderstandings. The algorithm is secure, and any vulnerabilities are typical of cryptographic systems rather than indicative of a fundamental flaw.

No summary available.

The author successfully ran the game DOOM in KiCad by using PCB traces and footprints instead of traditional pixels. Here's how it works:

1. Rendering Method: Walls are created using PCB traces, while game entities like enemies and items are represented by various component footprints (tiny electronic parts).

2. Data Extraction: The author modified DOOM’s source code to directly access its internal geometry data, avoiding the slow process of rendering thousands of pixels.

3. Entity Mapping: A new field was added to categorize over 150 entity types, allowing them to be mapped to specific footprints.

4. Data Transfer: The DOOM engine sends this geometric data to a Python plugin in KiCad via a Unix socket. The plugin updates the display without creating or destroying objects, which helps maintain a smoother performance.

5. Performance: The game runs at 10-25 frames per second (FPS), limited by KiCad’s refresh rate rather than DOOM itself.

6. Multiple Views: The system supports rendering to both an SDL window for gameplay and a Python wireframe window for debugging.

Follow-up Project - ScopeDoom: The author expanded the project to display DOOM on an oscilloscope in X-Y mode, using audio output from a laptop to send coordinates. Each frame shows recognizable level geometry, but the refresh rate is slow, around 6 Hz.

For more details, you can check out the projects on GitHub:

• KiDoom: KiDoom GitHub
• ScopeDoom: ScopeDoom GitHub

No summary available.

No summary available.

Summary of "Technical Deflation" by Benjamin Anderson

Deflation in economics refers to falling prices, often seen as harmful because it can lead to reduced spending and economic downturns. In contrast, a moderate inflation rate (around 2%) is preferred, as it encourages consumer spending.

The author draws a parallel between economic deflation and a trend in startups, which he calls "technical deflation." Key points include:

1. Easier Software Development: Advances in technology, especially AI, have made it cheaper and simpler to build software. This has led to a mindset where startups might delay building products, expecting that future tools will make it even easier.

2. AI's Role: Improved AI models allow for the quicker and simpler creation of applications. While AI-generated code may not always be perfect, it often meets basic needs, enabling startups to compete effectively with established companies.

3. Impact on Timing: Being late to the market can now be advantageous, as latecomers can learn from early competitors' mistakes and leverage improved tools for development.

4. Strategic Focus: With software development becoming easier, startups should focus on distribution and understanding customer needs, rather than solely on building products.

In conclusion, as building software becomes increasingly accessible, startups may need to adapt their strategies to stay competitive in a rapidly evolving landscape.

Summary of "10 Years of Writing a Blog Nobody Reads"

In November 2015, the author started a blog, initially posting a book review. After ten years and various changes, they continue to write and share insights about blogging and writing in general.

Key Points:

1. Improving Writing Skills: The author maintains the blog to enhance their writing abilities. They strive for clarity and effectiveness in communication, acknowledging past mistakes like using unnecessary qualifiers and adjectives that make writing harder to read.

2. Editing is Important: The author emphasizes the need to edit thoughts for better readability. They advise against starting sentences with phrases like "I think" or using multiple adjectives, suggesting instead to use more precise language.

3. Iterative Writing Process: Writing should involve multiple drafts, and taking breaks between drafts can provide fresh perspectives. There's flexibility in timing for blog posts, allowing for updates even after publishing.

4. Capturing Inspiration: The author encourages jotting down ideas whenever they come, as inspiration can strike at any time.

5. Value of Writing: With the rise of generative AI, the value of human-written content is debated. While the author believes there's personal value in writing (like understanding books better), they question its objective worth in a world flooded with content.

6. Continuous Improvement: The author recognizes they are not a perfect writer but finds motivation in the potential for growth. They aim to write more concisely, setting a goal to limit posts to 1,000 words.

In conclusion, the author appreciates the writing journey and looks forward to ongoing improvement.

I created a simple Python script that allows you to run prompts for language models (LLMs) directly from the command line. It supports templating, structured outputs, and connecting multiple prompts together. I was inspired by Google's Dotprompt format, which combines frontmatter and Handlebars templates, to treat prompts like programs that can be easily linked.

Here's how it works:

• You define a model and output format in a .prompt file, such as analyzing sentiment from text.
• You can run the script using a command like: cat reviews.txt | ./runprompt sentiment.prompt | jq '.sentiment'.

Key features include:

• Structured outputs: You can create JSON schemas to ensure the LLM returns valid data.
• Prompt chaining: You can pass the output of one prompt as input to another, allowing for complex workflows.
• Zero dependencies: It's a single Python file that doesn’t require any additional libraries—just download and run it.
• Provider agnostic: It works with various LLM providers like Anthropic, OpenAI, and Google AI.

This tool is useful for tasks like extracting data from text and generating reports without needing a larger framework. Feedback and contributions are encouraged!

MkSlides is a tool designed for teachers to convert markdown files into slides using Reveal.js. Here are the main points:

• Installation: You can install it using pip install mkslides.
• Building Slides: Use mkslides build to create the slides.
• Live Preview: For editing, you can run mkslides serve to see changes in real-time.
• Comparison with Other Tools:
  • It’s easy to use with a single command.
  • Requires only Python.
  • The workflow is similar to MkDocs, making it easy to use together in GitHub or GitLab.
  • It generates an index page for multiple slideshows, useful for organizing by chapter.
  • It’s lightweight and supports Infrastructure as Code (IaC).

No summary available.

Fourteen years ago, the author faced a storage shortage and decided to build a network-attached storage (NAS) server. After struggling to find helpful communities, they created a DIY NAS blog that gained significant interest, leading them to build similar machines annually.

Key criteria for their builds include:

• Small size: To fit limited office space.
• At least six drive bays: Initially needed for storage but may reduce to four due to increased hard drive capacities.
• Low-power CPU: To save on electricity costs, as the NAS runs constantly.
• Homelab potential: Modern NAS can support virtual machines and self-hosted services.

Currently, component prices are rising, making it a challenging time to build a NAS. The author considers whether to publish their latest build, fearing future prices may worsen.

For the DIY NAS: 2026 Edition, they chose a Topton N22 motherboard with an Intel Core 3 N355 CPU, which allows for various tasks beyond file serving. They opted for a compact JONSBO N4 case and a high-quality Noctua fan to manage noise.

The build features:

• 32GB DDR5 RAM: Adequate for storage and hosting virtual machines.
• Boot drives: Two 128GB SSDs for the operating system.
• Apps/VM storage: Two 1TB NVMe SSDs for better performance.
• Hard drives: The author used previously owned drives, emphasizing the importance of planning for future storage needs.

The author faced challenges during assembly, notably with cable management and drive installation. They recommend careful planning to avoid frustration.

After assembling the hardware, they configured the BIOS and performed burn-in tests to ensure reliability. They set up TrueNAS Community Edition for managing the storage.

Benchmarks showed that the DIY NAS: 2026 Edition performs well, often exceeding network speeds. The author highlights the importance of power consumption, noting the significant cost of running multiple hard drives.

In conclusion, while the build offers great performance and upgrade potential, the author considers auctioning it due to rising component costs. They encourage others to explore building their own NAS and share their experiences.

Careers Summary

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Summary of Migration from GitHub to Codeberg

Zig, a programming language project, has moved from GitHub to Codeberg after ten years. This decision was influenced by dissatisfaction with GitHub's performance and changes since it was acquired by Microsoft. Users have experienced slow and buggy features, particularly with GitHub Actions, which have caused delays in the project's continuous integration system.

Zig's team is also concerned about GitHub's neglect of the GitHub Sponsors program, which has been crucial for their funding. They are encouraging supporters to shift their donations from GitHub Sponsors to Every.org, a non-profit platform, and will be phasing out related perks.

The migration plan includes making the GitHub repository read-only and starting fresh issue numbering on Codeberg to avoid confusion. They appreciate the help from the Codeberg team during this transition. The team believes that moving to a non-profit platform aligns with their values in an era of corporate consolidation.

Happy hacking!

Google has responded to viral claims that it uses Gmail content to train its AI. These claims suggest that users must opt out of Gmail's "smart features" to prevent this. However, Google states that these reports are misleading and clarifies that it does not use email content for AI training. Gmail's smart features, which include spell checking and order tracking, have been around for years and any personalization settings can be adjusted. Users should check their settings, as some may have been automatically opted back into these features after a recent update.

SyncKit Summary

SyncKit is a simple and efficient synchronization engine for building local-first applications. It allows developers to implement real-time data synchronization with just a few lines of code, making it easier than traditional methods that can be complex or costly.

Key Features:

• Offline-First: SyncKit works seamlessly without an internet connection, ensuring functionality in various locations like planes and tunnels.
• Compact Size: The core SDK is approximately 59 KB gzipped, with a lite version around 45 KB for local-only use.
• Automatic Conflict Resolution: It uses a Last-Write-Wins (LWW) strategy to handle data conflicts.
• Open Source: Users have full control over their data with no vendor lock-in, and it can be self-hosted.
• Fast Performance: Local updates are nearly instantaneous (<1 ms), and network sync has low latency (10-50 ms).

Comparison with Other Solutions:

• SyncKit is easier to use, more compact, and offers true offline capabilities compared to Firebase and Supabase.
• It provides a simpler API and better performance than Yjs and Automerge.

Getting Started: To use SyncKit, simply install the SDK and initialize it in your app. This allows automatic syncing of data across different tabs or sessions, with persistent storage in the browser.

Future Updates (v0.2.0): Upcoming features include support for text editing, counters, and advanced data structures.

In summary, SyncKit is designed for developers looking for a straightforward, efficient way to implement offline-first synchronization in their applications.

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Summary of the Blog on Migrating to Positron

Positron is a new IDE for data science that offers a smoother transition for users coming from Visual Studio Code (VS Code) and RStudio. It includes unique features such as:

1. Built-in Data Explorer: View and manipulate dataframes easily.
2. Interactive Console: Run code and inspect variables in real-time.
3. AI Assistance: Get help with coding, debugging, and data analysis.

Migration Guides

• From VS Code: Positron retains familiar features and shortcuts from VS Code while adding tools tailored for data science.
• From RStudio: It offers a similar interface to RStudio, supports both R and Python, and allows customization with many extensions.

You can find detailed migration guides for both VS Code and RStudio linked in the blog.

Additional Resources

• Users can explore migration walkthroughs directly in Positron by searching for "Welcome: Open Walkthrough."
• The team is working on more guides, including one for Jupyter users, and welcomes feedback on additional resources needed.

Stay updated by subscribing for more open-source data science content!

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The VanDersarl Blériot is a unique aircraft built by teenage brothers Jules “J.J.” and Frank VanDersarl in 1911, inspired by the Blériot XI, a significant early airplane designed by Louis Blériot. Despite its challenges, like a tricky flight experience due to its design, the Blériot XI gained popularity after Blériot's famous 1909 flight across the English Channel.

The VanDersarl brothers, who had limited formal education but strong mechanical skills, constructed their own version of the Blériot XI. They used a modified automobile engine instead of the standard aircraft engine and made some structural changes. Their plane, while not as refined as factory-built models, flew successfully after its initial repairs.

The aircraft was kept in the family for decades, undergoing various attempts at restoration. In 2009, it was purchased and restored to be airworthy, culminating in its first flight in over a century in November 2012. The airplane is now registered as an experimental aircraft and is flown under strict conditions to preserve its unique heritage. Its restoration won a prestigious award, showcasing its historical significance.

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Alan.app is a simple Mac application created to help users see their active window better by adding a border around it. Users can customize the border's width and colors for both light and dark modes. The app is available for download, and there's a demo video to showcase its features. Additionally, there's a way to hide the app's icon from the Dock by using a Terminal command.

Caligra creates tools for technical settings where results are crucial. They focus on helping people stay attentive and productive, valuing the state of being fully engaged. Their computers are designed with unique principles to support your work effectively.

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This text discusses how input devices are managed in the Linux operating system, focusing on the kernel's input handling system. Here's a simplified summary of the key points:

1. Input Handling Overview:

   • Input handling on Linux is divided into three main parts:
     • Kernel-level handling: Manages hardware interactions and events via device drivers and the input core subsystem.
     • Exposed layer: Includes subsystems like event abstraction (evdev) and various file systems (devtmpfs, sysfs, procfs) for managing device attributes and user-space interactions.
     • User-space handling: Involves device management tools like udev and libraries like libinput for interpreting input events.

2. Kernel's Input Core:

   • The input core is essential for managing input devices and events, acting as a bridge between hardware and user-space applications.
   • Input devices are registered with the system through a defined structure, allowing drivers to send events that are then made available to user-space programs.

3. Device Hierarchy:

   • Devices are organized in a hierarchy based on connections through buses (like USB and PCI) and driver associations.
   • Each device has a unique identifier (MODALIAS) that helps the system match devices with their corresponding drivers.

4. Hotplug Mechanism:

   • The kernel uses a hotplug system to dynamically load drivers when devices are connected or disconnected, with udev handling these events in user-space.

5. Sysfs and Procfs:

   • The sysfs filesystem provides a structured view of devices, while procfs offers a more human-readable format for diagnostics.
   • Both filesystems help users and developers understand how devices are represented and managed in the kernel.

6. Example of Device Management:

   • The text outlines how different input devices, like keyboards and mice, communicate through various protocols (like HID) and are represented in the input core, ultimately exposing their functionality to user-space applications.

In summary, the Linux input management system is complex but organized, with a clear structure for handling devices from hardware to user-space, ensuring that input events are efficiently processed and made available for use by applications.

Liam Fallen discusses the overwhelming presence of AI-generated content in our lives, highlighting the absurdity of products like an AI toothbrush that tracks brushing habits and generates reports. He criticizes the flood of low-quality articles, books, and posts created by bots, which often lack genuine human insight and creativity.

Fallen points out that many online platforms, like Google and Amazon, prioritize quantity over quality, allowing mediocre content to thrive while high-quality work is overlooked. He notes that the internet is now filled with generic articles, stock photos of non-existent people, and courses on creating more AI-generated content.

Overall, he expresses concern that we are accepting this "slop" as normal, while the market rewards superficial engagement rather than meaningful contributions. The situation reflects a broader issue where efficiency and cost-cutting have led to a decline in content quality.

Chris and Yuhong from Onyx are creating an open-source chat platform that works with various language models (LLMs) and provides essential tools to enhance their usefulness. They previously developed Danswer, a search tool, but noticed that users preferred chatting with LLMs instead. This led them to pivot to Onyx, focusing on providing a high-quality chat experience that is user-friendly for both new and experienced users.

Onyx includes features like:

• A user-friendly chat interface.
• Support for various tools and integrations (like web searches and custom tools).
• Enterprise-level security features such as role-based access control and easy hosting.

Through their development, they learned important lessons about managing context in conversations and understanding how different models behave. They have already seen success with a Fortune 100 company using Onyx for over 10,000 employees.

If you're interested in trying Onyx, you can set it up locally or access it via the cloud. They welcome feedback on features that could make it a better alternative to existing enterprise chat solutions.

The video by ThePrimeagen discusses how attackers can jailbreak AI systems like Claude to conduct cyber attacks. The main problem is that AI agents need to be isolated to prevent these attacks. To address this, a solution called ERA has been developed. ERA uses local microVM-based sandboxing, which provides hardware-level security for AI-generated code, making it safer than traditional containers. This means that if an attack occurs within ERA, it won't affect the main system. You can find more about ERA on GitHub and start using it by following their quick start guide. Feedback and thoughts on this solution are welcome!

Gemini CLI Tips & Tricks Summary

Gemini CLI is an open-source AI tool that enhances your terminal experience by acting as a smart assistant for coding, debugging, and automation. Here are some key points and tips for effectively using Gemini CLI:

1. Installation: Install via npm or run it without installation using npx. Authenticate with a Google account or an API key for access.

2. Persistent Context: Use a GEMINI.md file to store project-specific instructions. This helps avoid repetitive prompts by keeping important details in memory.

3. Custom Slash Commands: Create your own commands to simplify repetitive tasks, like generating tests or resetting a database, by defining them in configuration files.

4. MCP Servers: Extend Gemini CLI by integrating custom Model Context Protocol (MCP) servers. These allow you to connect to external tools or databases.

5. Memory Addition & Recall: Use memory commands to store important facts or decisions, ensuring the AI remembers crucial information throughout your sessions.

6. Checkpointing: Enable checkpointing to save your project state before changes. Use the /restore command to revert to a previous state if needed.

7. Helpful Command Examples:

   • Use /memory show to view stored facts.
   • Use /init to create a GEMINI.md template.
   • Use /mcp to list registered MCP servers.

These tips aim to enhance your workflow and make Gemini CLI a powerful tool in your development process.

Summary of "Coq: The World’s Best Macro Assembler?"

The paper discusses a formalization of a simplified version of the x86 architecture using Coq, a proof assistant. The authors aim to make the x86 architecture's semantics clearer and more manageable by using advanced features of Coq, such as dependent types and notations.

Key points include:

1. Modeling x86 Architecture: The authors create a model for the x86 machine that allows for clear representation of bits, bytes, and memory, facilitating the formal verification of system software.

2. Assembler Functionality: Coq is used to write assembly programs, which can be assembled into machine code directly within the Coq environment. The assembler produces a hexadecimal output, which can be converted to binary for execution.

3. Code Examples: The paper presents examples of simple assembly code for calculating factorials and demonstrates how Coq can generate executable machine code from this assembly.

4. Correctness Proofs: The authors prove that their assembler correctly encodes instructions and that the generated machine code adheres to specified properties, enhancing reliability.

5. Advanced Features: Coq allows for defining macros that simplify assembly code, such as conditionals and loops, and supports standard x86 calling conventions through user-defined constructs.

6. Higher-Level Language Integration: The authors discuss the potential to embed domain-specific languages (DSLs) within Coq, further optimizing programming and proving processes.

7. Regular Expression Compiler: They illustrate the development of a compiler that translates regular expressions into x86 machine code, highlighting the integration of mathematical theories with practical programming tasks.

Overall, the paper showcases Coq's capabilities in modeling complex architectures, generating executable code, and proving correctness, making it a powerful tool for both assembly language programming and formal verification.

Summary: Managing Async Tasks with a Postgres Table

The text discusses a strategy for handling asynchronous tasks in web applications using a Postgres database. Here are the key points:

1. Simplicity in Design: The author prefers minimal server complexity, where each endpoint executes straightforward database queries to ensure fast and smooth user experiences.

2. Using a Task Table: Instead of directly executing complex operations like sending emails, tasks are queued in a task table. This allows the system to confirm actions to users quickly while processing tasks in the background.

3. Database Transactions: The text emphasizes the importance of using database transactions to maintain consistency. Writing to multiple locations at once is risky and can lead to data loss.

4. Centralized Task Management: By using Postgres for various tasks (like queuing and processing), developers can avoid complications that arise when using multiple systems (like Redis or SQS). This approach simplifies error handling and maintains transactional integrity.

5. Error Handling and User Experience: It's crucial to manage human errors separately from software errors. Systems should provide immediate feedback to users while letting computers handle retries and errors more efficiently.

6. Implementation Example: The text provides a code example for creating a task table and a worker that processes tasks. Key features include:

   • Retry mechanisms for failed tasks.
   • Using transactions for safe processing.
   • Allowing multiple workers to run concurrently without interference.

In conclusion, the author advocates for using a Postgres table to manage async tasks, highlighting its benefits for simplicity, consistency, and effective error handling.

Summary: Bring Back Bathroom Doors

The "Bring Back Doors" campaign aims to highlight hotels that have removed bathroom doors, a feature considered essential for privacy and dignity. The website provides a list of hotels that are confirmed to have proper bathroom doors, avoiding those that use glass or lack doors entirely. The creator has contacted numerous hotels to verify whether their bathroom doors close completely and are not made of glass. Travelers can report hotels without bathroom doors for public awareness. The goal is to encourage hotels to prioritize guest privacy and restore the standard of having a bathroom door.

The DARE SGA1 project is funded by the European High-Performance Computing Joint Undertaking (JU) through grant No 101202459. This funding comes from the EU's Horizon Europe program and support from several countries, including Spain, Germany, and Italy. While the project receives this funding, the views expressed are solely those of the authors and do not represent the opinions of the EU or the funding authority, who are not responsible for them.