No summary available.

No summary available.

Summary:

On July 4, 2025, I am rebuilding my homelab and downsizing from a large 4-post rack to a mini rack. I currently have a NAS with 120 TB of storage, but my needs have changed, and I only require about 6 TB now. I’m looking into three new mini NAS devices: GMKtec G9, Aiffro K100, and Beelink ME mini, all powered by Intel chips and featuring multiple NVMe SSD slots.

1. GMKtec G9: This NAS has cooling issues when using four drives, but a new version has improved ventilation. It's the most budget-friendly option.

2. Aiffro K100: Smaller and cooler than the G9, it has better ventilation and a full metal enclosure. However, it lacks eMMC storage and WiFi, making it less versatile. It's also the most expensive.

3. Beelink ME mini: Very quiet and efficient with six NVMe slots, but bandwidth is limited due to multiple x1 slots. It includes built-in eMMC and a compact power supply.

Each NAS has its pros and cons, and the best choice depends on individual needs. I am leaning towards the K100 if I can find a good deal on the needed SSDs.

No summary available.

No summary available.

The text discusses the development of a Game Boy emulator called CAMLBOY, created using the OCaml programming language, specifically designed to run in web browsers. The project aims to enhance the author's understanding of OCaml by tackling a medium-scale project with practical applications. Key points include:

1. Project Goals: The emulator was built to be readable, maintainable, and to run at 60 frames per second (FPS) on mobile devices. The author focused on using advanced OCaml features and improving performance through benchmarks.

2. Emulator Architecture: The emulator includes components like the CPU, timer, GPU, and a bus for data management. The main loop ensures synchronization between these components, simulating the Game Boy's hardware.

3. Implementation Techniques: The author used OCaml’s functors for better testability, allowing the CPU to be instantiated with different bus implementations for testing. Generalized Algebraic Data Types (GADTs) were also employed to define instruction arguments more effectively.

4. Cartridge Support: Different types of Game Boy cartridges, which may include additional hardware, were implemented as modules, allowing for runtime selection based on the cartridge type.

5. Testing and Optimization: The emulator was tested using specific test ROMs to ensure functionality. Performance bottlenecks were identified and addressed, leading to significant speed improvements, achieving 60 FPS in browsers.

6. Compilation and Performance: The emulator was compiled to JavaScript using the js_of_ocaml library. Optimization strategies were applied to enhance speed, particularly by managing how functions were inlined in JavaScript.

7. Reflections: The author found emulator development akin to competitive programming, where one iterates through understanding specifications, implementation, and testing. They noted improvements in the OCaml ecosystem but also pointed out challenges, especially concerning dependency management and the syntactical complexity of abstractions.

Overall, the article serves as both a technical guide and a personal reflection on the process of developing a Game Boy emulator, showcasing the use of OCaml’s features and the challenges encountered along the way.

A software developer with over 20 years of experience decided to try game development for the first time, inspired by AI coding tools. They learned Phaser.js, a JavaScript game engine, and participated in the Beginner's Jam Summer 2025, a game jam for newcomers that allows the use of AI coding. After 25-30 hours of work, mostly after their day job, they created and submitted a game called "Tower of Time," themed around time travel.

The developer aimed to see if AI could help create a fun game, and they were pleased with the results. They shared their learning process, including the code and prompts used, on GitHub. Many art assets were sourced from free artists on itch.io, and sound effects were from freesound.org. They also streamed parts of their development process, which can be viewed online.

Through this experience, they gained valuable knowledge and plan to take on a more ambitious project next. They're open to comments and questions from others.

Summary of BunkerWeb

BunkerWeb is an open-source Web Application Firewall (WAF) designed to secure web services effortlessly. Built on NGINX, it serves as a reverse proxy and integrates easily with various environments like Linux, Docker, and Kubernetes. Here are the key points:

• Easy Integration: BunkerWeb can be smoothly implemented into existing setups without hassle.
• Customizable: Users can easily tailor security settings to fit their specific needs using a user-friendly web interface.
• Secure by Default: It offers built-in security features right from the start, ensuring web services are protected.
• Plugin System: Additional security features can be added easily through plugins.
• Community Support: Licensed under the AGPLv3, BunkerWeb promotes freedom in usage and modification.

Security Features:

• HTTPS support with automated Let's Encrypt integration.
• Advanced web security measures and protection against attacks.
• Automatic banning of suspicious behaviors.
• Connection and request limits for clients to prevent resource exhaustion.
• Bot protection through challenge-based verification.
• Blocking of known malicious IPs using external blacklists.

Additional Offerings:

• Demo Sites: Users can test BunkerWeb's capabilities through demo websites.
• BunkerWeb Cloud: A managed service for those who prefer not to self-host.
• PRO Version: Offers enhanced features and a free trial for users wanting to explore advanced functionalities.
• Professional Services: Available for technical support and custom development.

Resources: Users can find more information, documentation, and community support through the official BunkerWeb website and its social media channels.

Summary of Compression Dictionary Transport

Compression Dictionary Transport is an experimental technology aimed at reducing the size of HTTP responses by using a shared compression dictionary. This method helps decrease bandwidth costs and loading times for web pages.

Key Points:

1. Purpose: It compresses HTTP resources by identifying and referencing repeated strings in the data, which reduces the overall size of downloads.

2. Technology Background: This technology improves upon a previous method called SDCH, which was not widely adopted. Compression Dictionary Transport is better specified and has broader support.

3. How It Works:

   • It uses dictionaries of common strings to compress data more efficiently.
   • For example, if multiple versions of a JavaScript library share a lot of the same code, a previous version can serve as a dictionary for the newer one, allowing the new version to only include the changes.

4. Dictionary Usage:

   • A dictionary can be a resource the server provides or a separate file.
   • The server can signal which resources can use a specific dictionary through HTTP headers.

5. Creating Compressed Responses: Responses can be created using Brotli or ZStandard compression algorithms, and they must include specific headers to indicate the use of a dictionary.

6. Security and Restrictions: There are security measures to prevent misuse, including same-origin restrictions and privacy considerations, as dictionaries could potentially be used for tracking.

7. Browser Compatibility: Before using this technology in production, developers should check the compatibility with different browsers.

This technology promises to significantly improve compression rates and efficiency for web resources, especially when there are many similarities across different versions of the same resource.

Larry is a tabby cat who has served as the Chief Mouser to the Cabinet Office at 10 Downing Street since 2011. Born around January 2007 as a stray, he was adopted from Battersea Dogs & Cats Home. Larry has lived with six different prime ministers and is not owned by any prime minister but cared for by the staff at Downing Street.

His role includes greeting visitors, inspecting security, and ensuring the premises are mouse-free, although he is known for being more of a sleeper than a hunter. Larry has gained popularity, even influencing a rise in cat adoptions due to his public presence. He has had some health concerns reported, but Downing Street has stated he is doing well.

Larry has a playful yet sometimes contentious relationship with other animals, including a rival cat named Palmerston from the Foreign Office. He is well-loved by the public, often regarded favorably compared to political leaders. Over the years, he has become a cultural icon, with various media coverage and even a parody Twitter account dedicated to him.

The text talks about a terminal emulator built using the jediterm library, which is used in IDEs (Integrated Development Environments). This library has existed for over 10 years, but it seems that no one has created a standalone terminal emulator app from it until now. The new terminal emulator includes features like tabs.

The "Lenses, Folds and Traversals" package provides a comprehensive set of tools for working with data types in Haskell. It includes many useful lenses for common types, along with tools to automatically generate lenses for user-defined types. The package features a variety of combinators for creating getters, setters, folds, and traversals, making it very versatile.

Key resources include:

• A README with examples.
• Introductory videos by Simon Peyton Jones on using and constructing lenses.
• A lens wiki for tutorials and guidance.
• Example projects, including a small game of pong, demonstrating state management with lenses.

Lenses can be composed and used in various ways, allowing for flexibility in data manipulation. Users can also define their own lenses and traversals without relying on external libraries.

The package comes with many predefined lenses and traversals for common data types, along with additional functionalities like indexed folds and isomorphisms. For developers looking to use or contribute to this package, various resources and community support are available.

Rust + TypeScript Web Application Summary

This web application uses Rust and TypeScript to combine high performance and safety.

Architecture:

• Backend: Built with Rust using the Poem web framework for creating API endpoints.
• Frontend: Developed in TypeScript with SvelteKit, which allows for interactive user interfaces.
• Build System: Uses Vite for quick development and optimized production builds.
• Type Safety: The Poem framework generates an OpenAPI specification, which is then used to create a type-safe client for the frontend.

Development:

• To start development servers, run: zellij --config dev-layout.kdl
• The ports for the frontend and backend are set in the environment configuration.

Project Structure:

• There are two main folders: backend/ and frontend/, each containing necessary files for building and running the application.

Enhanced Radar is developing safer air traffic control systems and created Y2, an advanced speech recognition model for aviation. The entire team consists of software engineers who are also pilots.

They are looking for talented software engineers, preferably with a background in aviation. The company offers competitive pay and equity.

For more information about their upcoming fundraising, partnerships, and future plans, you can contact Eric Button, the CEO, at [squawk VFR] at enhancedradar.com.

Large language models like ChatGPT and GPT-4 have shown great skill in communicating with people. This report explores how well they can play text-based games, where players interact with a game world through dialogue. Our findings reveal that while ChatGPT performs well compared to other systems, it still lacks true intelligence. Specifically, it struggles to understand the game environment, cannot build a mental model of the game, and often fails to use its existing knowledge effectively. It also has difficulty figuring out the goals as the game progresses. These results raise new questions for research in artificial intelligence, machine learning, and natural language processing.

In March 2025, the author compared an Intel N100 mini PC (specifically the GMKtec N100 NucBox G3) to a Raspberry Pi 5 8GB after one year. A newer version of the mini PC is now available with a faster Intel N150 and 16GB RAM, as well as a new 16GB Raspberry Pi 5.

The author conducted benchmarks to assess performance differences, switching from Windows 11 on the mini PC to Linux for a fairer comparison with Raspberry Pi OS. Findings showed that even slower DDR4-based N100 systems were generally faster than the Raspberry Pi 5, often 1.5 to 2 times faster depending on conditions.

However, the Raspberry Pi 5 was noted to be more power-efficient, despite its older manufacturing process. The mini PCs tend to be cheaper on the used market compared to new Raspberry Pis, especially given the high volume of older models available for sale.

Overall, the choice between the two systems depends on specific needs: the Raspberry Pi 5 is compact and energy-efficient, while the Intel mini PCs offer better performance for desktop use and compatibility with a wider range of software. The conclusion emphasizes that value and suitability depend on the user's requirements, similar to comparing bicycles and cars for different transportation needs.

The text discusses the use of CGI (Common Gateway Interface) programs for web development, particularly how they were popular in the early 2000s and how they can still perform well on modern servers.

Key Points:

• CGI programs, often written in Perl or C, were the main way to create dynamic websites back then. They handle web requests by running as separate processes, which allows them to use multiple CPU cores effectively.
• Modern servers are much more powerful, with hundreds of CPU threads, making CGI programs capable of handling over 2,400 requests per second, translating to over 200 million requests daily.
• A simple guestbook program was created as a demonstration, using Go and SQLite. The program allows users to leave comments on a website.
• Benchmark tests showed that CGI can still perform impressively on modern hardware, although it might not always be the best choice compared to newer technologies.

Overall, while CGI may not be the first choice for modern web applications, it remains a viable option due to its speed and ease of deployment. The author shared code for the guestbook program on GitHub for others to explore.

Gaspype is a Python library designed for quick thermodynamic calculations, such as equilibrium reactions. It is lightweight, uses typed Python/Numpy, and includes a comprehensive species database. The library works with multidimensional arrays for variables like composition, temperature, and pressure.

Gaspype is user-friendly, making it easy to use in Jupyter Notebooks, and it performs well for large models. A key feature is its ability to work with GPU frameworks like JAX or PyTorch, enhancing performance and allowing integration into machine learning pipelines.

You can check out examples and share your feedback or ideas for features. The library is available on GitHub at this link.

No summary available.

Summary of "Introducing tmux-rs"

Collin Richards has been working on a project to rewrite tmux, a terminal multiplexer, from C to Rust for the past six months. He has reached an important milestone: the entire codebase is now written in Rust, although it remains unsafe. The project, which started as a hobby, involved porting about 67,000 lines of C code to approximately 81,000 lines of Rust.

Key Points:

• Reason for Porting: The rewrite is primarily a personal project without a specific technical reason behind it.
• C2Rust Tool: Initially, Richards used C2Rust, a tool to convert C code to Rust, but found the output unmanageable and decided to manually translate the code instead.
• Build Process: He developed a build system that combines Rust and C, using custom scripts to manage compilation.
• Bugs and Debugging: Richards encountered various bugs during the translation, often due to type mismatches or incorrect function declarations. He shares examples that detail how he identified and fixed these issues.
• Rust vs. C: He discusses differences between C pointers and Rust references, emphasizing the need for raw pointers in the Rust code.
• Parsing: He replaced a yacc-based parser with the lalrpop crate for Rust, allowing him to eliminate remaining C dependencies.
• Development Tools: While using Vim for coding, he also experimented with AI tools like Cursor but found them not particularly beneficial in speeding up his process.
• Future Goals: Although the project is functional, Richards aims to improve the code further by transitioning it to safe Rust. He has released version 0.0.1 for other Rust and tmux enthusiasts to explore.

Richards invites feedback and discussions about the project on GitHub.

Summary of "Rust and WASM for Form Validation"

In this article, Sebastian Lauwers discusses how using Rust with WebAssembly (WASM) has become easier for developers, especially those focused on backend programming. Previously, setting up WASM required complex tools like Node and Webpack, which discouraged many from using it. However, recent improvements have streamlined the process.

The main goal of the tutorial is to show how to create a simple web server in Rust that serves HTML templates and includes a WASM component for form validation. The author appreciates the benefits of using Rust and WASM over traditional JavaScript (JS), such as sharing code between the frontend and backend.

Key Steps in the Tutorial:

1. Project Setup:

   • Create a directory structure with separate crates for the server and the WASM component.
   • Install required dependencies like wasm-bindgen, wasm-pack, and rocket.

2. WASM Configuration:

   • Ensure Rust can compile to WASM by adding the appropriate target.
   • Configure the WASM crate to produce a dynamic library.

3. Server Implementation:

   • Use the Rocket framework to create a simple login server.
   • Define routes for rendering the login page and handling login submissions.

4. Form Validation with WASM:

   • Set up the WASM component to validate form inputs, leveraging browser validation APIs.
   • Display error messages for invalid inputs and submit the form when valid.

5. Final Thoughts:

   • Although WASM binaries can be larger than JS, they offer scalability benefits when more complex functionality is added.
   • The author notes the importance of proper error handling in production code and encourages feedback on the tutorial.

Overall, Lauwers showcases how easy it is to build a web application using Rust and WASM, emphasizing the potential for shared code and efficient development.

The Wind Knitting Factory is a unique knitting machine powered by wind, installed on the side of a building. Its large blades capture wind to drive the knitting process, creating a long scarf that hangs down the building. The speed of knitting varies with the wind; it knits faster in strong winds and slower in light winds.

As the scarf is knitted, it drops down the facade and enters the building through a window, where people can watch it grow longer. Occasionally, the knitted fabric is collected and made into scarves, each labeled with the date and time of production based on the wind conditions. This project creatively demonstrates how urban wind can be harnessed for textile production, blending public and private spaces.

The text discusses recent changes in the Zig programming language, specifically related to its I/O (input/output) system. Here are the key points:

1. Introduction of New I/O API: The existing standard I/O readers and writers are deprecated in favor of new std.io.Reader and std.io.Writer types. These new types are designed to be more efficient and convenient, although they are no longer generic.

2. Breaking Changes: The updates will break existing code, particularly affecting formatted printing functions. Users are advised to upgrade their code accordingly.

3. New Features: The new I/O API includes better performance and unique features, such as:

   • Efficient data discarding while reading.
   • A "splatting" feature for writing that optimizes memory usage.
   • The ability to send files directly when writing.

4. Upgrade Guide: The text provides a guide for transitioning from old to new APIs, listing changes in function names and how to adapt existing code.

5. Future Plans: This change is part of a larger effort to improve the Zig language, including plans for asynchronous operations and further I/O enhancements.

6. Merge Checklist: There are ongoing tasks to finalize the changes, including fixing tests and ensuring compatibility.

Overall, these changes aim to improve the Zig programming language's I/O capabilities, but they require users to make significant updates to their existing code.

Researchers have observed a new behavior among southern resident killer whales in the Salish Sea, where they use bull kelp as a tool for mutual grooming, a practice called "allokelping." This is the first time aquatic mammals have been seen using tools cooperatively for hygiene, highlighting their complex social interactions.

The discovery was made by marine biologist Michael Weiss and his team, who recorded 30 instances of this behavior over 12 days. While marine mammals are known to use tools, this specific social grooming behavior is unique to these orcas.

Experts suggest that allokelping could help with skin health or social bonding, a rare occurrence among animals. Understanding such behaviors is important for conservation efforts, as it emphasizes the need to preserve animal cultures alongside their genetic diversity.

Summary of DRM Panic QR Code Generator

The DRM Panic QR code generator creates QR codes to display panic data from kernel crashes, making it easier to copy and share this information for debugging. Instead of just showing text on the screen, the QR code allows users to include more data in a compact form.

This tool is built using Rust, chosen for its memory safety, which is crucial for handling errors. The QR code generator is simple and integrates well into the Linux kernel, specifically in version v6.12-rc1, with plans for use in Arch Linux.

Additional resources include a web frontend for decoding QR codes, examples of panic screens featuring QR codes, and a standalone Rust application for testing the same functionality outside the kernel. The main developer is Jocelyn Falempe, supported by the Rust for Linux community.

Kevin Kelly is a multifaceted thinker and creator, known for his diverse projects rather than a single major achievement. He has contributed to various fields, including editing the Whole Earth Catalog, co-founding WIRED magazine, and working on early online communities. Kelly emphasizes the importance of pursuing interests rather than focusing solely on traditional career success, which he views as often overrated and associated with negative traits.

In his work, Kelly believes in the value of long-term thinking and creativity over the pursuit of wealth or titles. He encourages a joyful approach to work, arguing that the most impactful individuals are those who follow their passions without being consumed by the desire for greatness. He aims to inspire others to find satisfaction in their work without the pressure of conforming to Silicon Valley's standards of success.

Brie Wolfson, the author, reflects on her own experiences in the tech industry and her admiration for Kelly's approach. She grapples with the tension between ambition and enjoyment in work, ultimately seeking permission to pursue meaningful, joyful work rather than succumbing to pressure for accolades or financial success. The essay advocates for a shift in perspective, encouraging others to embrace a fulfilling and happy work life.

The text discusses the development of "phkmalloc," a memory allocation system created by the author in response to performance issues with the existing malloc implementation in FreeBSD.

Key points include:

1. Background: The author inherited an older malloc system from BSD that worked but was inefficient, especially as RAM prices rose in the mid-1990s. The author's machine had only 4MB RAM, leading to concerns about memory usage.

2. Problems Identified: The original malloc implementation caused excessive disk activity during memory freeing, particularly noticeable when programs like GCC ended. This behavior was termed the "death-rattle."

3. Initial Fixes: The author first modified the malloc system to log memory allocation calls and identified inefficiencies. The original implementation required reading through free memory lists, leading to unnecessary paging.

4. Complete Overhaul: The author decided to start from scratch, creating a new design that kept metadata separate from memory chunks, significantly improving performance and reducing memory-related errors.

5. Features: Phkmalloc included runtime configurable options to help detect memory misuse, such as filling freed memory with junk or zeros. This increased the system's ability to catch bugs.

6. Community Feedback: After introducing phkmalloc in 1995, the author received positive feedback and reports of bugs being uncovered in various programs, showcasing its effectiveness.

7. Evolution and Transition: While phkmalloc was successful, it struggled with multi-threading and performance on modern systems. The author eventually transitioned the malloc maintenance role to Jason Evans, who developed "jemalloc," which addressed these scalability issues.

8. Legacy: The author reflects on the journey of phkmalloc, its impact on improving memory management in FreeBSD, and the challenges faced during its development, including a memorable presentation at a technical conference.

Overall, the text details the creation and evolution of phkmalloc, emphasizing its importance in enhancing memory management in operating systems.

If you're working in the tech industry and want to leave for something more meaningful, this article offers guidance on various career paths that can utilize your skills. Here are the key points:

1. Reasons for Leaving: People may want to leave tech for various reasons, such as dissatisfaction with the industry's impact on society, the individualistic culture, or a desire for a more fulfilling life.

2. Different Paths: There are several alternatives to explore:

   • Public Institutions: Working in the public sector can provide a more relaxed environment and meaningful projects that affect many lives, though be wary of the influence of consultancy firms.
   • Tech Co-operatives: Joining or starting a tech co-op allows workers to have ownership and make decisions about their work and projects, though it requires a different mindset and responsibilities.
   • Tech NGOs: Non-profits and NGOs often need tech workers for various missions, such as environmentalism and human rights. Networking is key to finding these opportunities.
   • Unions and Political Organizations: Working in the tech department of a union or political party can be a way to stay in tech while improving working conditions.
   • Teaching and Mentoring: If you enjoy teaching, there are opportunities in schools, universities, and online platforms to educate others in tech.
   • Techno-Political Hustlers: This emerging role involves connecting various groups and projects, using your tech skills for social and political causes.

3. Finding Your Path: Ultimately, the journey to a more meaningful career is personal and requires self-reflection. It's important to take initiative and seek out opportunities that align with your values.

In summary, it's never too late to change your path, and exploring these options can lead to a more fulfilling career outside of traditional tech roles.

No summary available.

The Vatican Museums recently completed a 10-year restoration of the Hall of Constantine, revealing that two figures in the frescoes were painted by the renowned artist Raphael himself, rather than by his assistants as previously thought.

This discovery changes our understanding of Raphael's work in the hall, which features scenes celebrating Christianity over paganism. Raphael had developed a unique oil painting technique, which he used for the figures of Justice and Friendship. The assistants used traditional fresco methods, which is why only Raphael's figures stand out.

The restoration project, which began in March 2025 and finished in December 2024, also uncovered evidence that Raphael was preparing to do more work in the hall before his death in 1520. Museum officials believe this discovery enhances the historical significance of Raphael's contributions to art.

Ben from K-Scale Labs is developing open-source humanoid robots. Their goal is to create affordable robots for hobbyists and developers, as existing options are very expensive. They built their first prototype using 3D printers and common parts, achieving a functional robot in just two months.

K-Scale is focused on transitioning from hobby-grade to consumer-grade robots while keeping costs low. They are open-sourcing their hardware and software to navigate manufacturing challenges and engage a community of developers. They believe that there is significant interest from people wanting to experiment with humanoid robots.

Currently, they are selling their K-Bot for $8,999 and are negotiating better prices with suppliers. To address customer demand for fully autonomous robots, they offer a "Full Autonomy" option that includes future upgrades as the technology develops. This approach helps fund their R&D while involving early customers in improving the robot's capabilities.

Ben encourages feedback from the community to enhance their project further.

No summary available.

Summary: Context Engineering for Agents

Agents, powered by large language models (LLMs), require specific information, or "context," to perform tasks effectively. Context engineering is the process of managing this context to optimize agent performance.

Key Points:

1. Understanding Context:

   • The context window is limited, similar to a computer's RAM, and must be filled with relevant information.
   • Context types include:
     • Instructions: Prompts and examples.
     • Knowledge: Facts and memories.
     • Tools: Feedback from external tools.

2. Challenges with Context:

   • Long tasks can lead to issues like context poisoning (incorrect information), distraction (too much irrelevant info), confusion (mixed messages), and clash (conflicting information).

3. Strategies for Context Engineering:

   • Write Context: Save useful information outside the context window (e.g., scratchpads for temporary notes and memories for long-term recall).
   • Select Context: Pull relevant information into the context window as needed (e.g., selecting memories or tool descriptions).
   • Compress Context: Reduce the amount of information to only what is necessary, using techniques like summarization to distill key points.
   • Isolate Context: Divide context among sub-agents or utilize state objects to manage information more effectively.

Conclusion:

Effective context engineering is crucial for building successful AI agents, and it can be categorized into writing, selecting, compressing, and isolating context. Understanding these strategies helps improve agent performance in various tasks.

No summary available.

No summary available.

Soham Parekh is a trending topic on Twitter, as many startups are claiming they have either employed him now or in the past. This raises a serious question: why are startups not effectively screening candidates to prevent hiring someone who might be involved in scams or juggling multiple jobs?

Researchers from ICM-CSIC have developed satellite data processing algorithms that have helped detect a significant change in ocean circulation in the Southern Hemisphere, which may worsen climate change effects. An international team led by the UK's National Oceanographic Center found that since 2016, surface salinity has increased in the Antarctic Ocean, leading to a reversal of deep ocean circulation. Instead of surface water sinking, deep water is rising, bringing heat and carbon dioxide (CO₂) to the surface.

This reversal, described as unprecedented, could double current atmospheric CO₂ levels, potentially causing severe global climate impacts, including accelerated sea ice melting. The research utilized advanced satellite technology developed by ICM-CSIC to gather high-quality data from regions previously difficult to monitor.

The study emphasizes the Southern Ocean's crucial role in regulating global climate, and its disruption could affect other ocean circulation systems, such as the North Atlantic's AMOC. To further investigate these changes, ICM-CSIC has initiated new projects focusing on Arctic and ocean surface heat fluxes.

Overall, this discovery highlights the urgent need to understand these climate dynamics, as they signal we may be crossing critical climate thresholds.

No summary available.

No summary available.

Pennybase Summary

Pennybase is a simple, lightweight Backend-as-a-Service (BaaS) that provides essential backend features with less than 1000 lines of Go code. It is designed to be easy to use, similar to platforms like Firebase and Supabase, and does not rely on external libraries.

Key Features:

• Data Storage: Utilizes human-readable CSV files for storing data, where each record has a unique ID and versioning for updates.
• REST API: Offers endpoints for creating, reading, updating, and deleting records, as well as streaming real-time updates.
• Authentication: Supports session cookies and Basic Auth for user authentication.
• Permissions: Implements role-based access control (RBAC) to manage user permissions for different actions on resources.
• Schema Validation: Validates data types and formats using a simple schema definition.
• Static Assets: Can serve static files and render HTML templates using Go templates.

How It Works:

• The data is stored in CSV format, allowing easy access and updates. Each update creates a new version of the record.
• User credentials and access permissions are also stored in CSV files, which must be manually edited to add users or permissions.
• The API supports various operations, with permissions required for actions like creating or deleting records.

Customization:

• Users can extend Pennybase's functionality with hooks to perform custom actions during data operations, such as modifying records before saving.

Contributions:

• The project welcomes contributions, emphasizing that the code should remain clear and concise. It is open-source under the MIT license.

Summary: Alternative Blanket Implementations for a Single Rust Trait

Rust's trait system is strict about ambiguity, particularly regarding blanket implementations—traits that apply to any type meeting specific constraints. A common example is how the From and Into traits work together.

Key Points:

1. Blanket Implementations: These are generic trait implementations applicable to types that meet certain conditions. For instance, if you implement From<T> for U, you automatically get Into<U> for T.

2. Restriction: Rust prohibits overlapping blanket implementations to avoid future ambiguities. If two traits could potentially apply to the same type, the compiler will reject them.

3. Real-World Issue: In a project called Joydb, the author faced a dilemma when trying to implement an Adapter trait with two options: a unified adapter (storing all data in one file) and a partitioned adapter (storing data in separate files). Rust's rules prevent defining both without conflicts.

4. Workaround: The author proposes a solution using:

   • Marker Structs: Unified<A> and Partitioned<A> to differentiate between types.
   • BlanketAdapter Trait: This trait helps delegate behavior without conflict.
   • Associated Types: The Adapter trait contains an associated type to determine which adapter to use.

5. Example Implementation: A JsonAdapter can be implemented as a UnifiedAdapter, allowing for seamless integration without code duplication or conflicts.

This approach offers a way to achieve alternative blanket implementations while adhering to Rust's rules, enhancing usability without sacrificing clarity.

Summary: How AI Works on Microcontrollers: Operators and Kernels

The article discusses "edge AI," particularly how artificial intelligence (AI) is implemented on microcontrollers, which are small, low-power computing devices. Edge AI often involves running AI models in environments with limited computing resources, such as memory and processing power.

Key Points:

1. Microcontrollers and AI: Microcontrollers face constraints in processing power, memory, and network capabilities, making them ideal for running lightweight AI models.

2. Inference Process: Performing inference (making predictions) with AI models involves more than just the model weights; it requires a combination of data and metadata that guide how the model operates.

3. Tensorflow Lite for Microcontrollers: The primary tool for AI inference on microcontrollers is Tensorflow Lite for Microcontrollers (previously tflite-micro). This optimized version of Tensorflow Lite uses a specific file format (.tflite) that includes both model weights and operation instructions.

4. Operators and Kernels: The operations performed by AI models (like addition) are defined by operators, which are analogous to instructions in a computer's architecture. These operators have different implementations called kernels, which can be optimized for specific hardware capabilities.

5. Performance Optimization: Microcontrollers can take advantage of hardware features (like ARM Cortex-M extensions) to speed up operations. For example, operations that can be parallelized (like matrix addition) perform much faster with specialized hardware support.

6. Hardware Acceleration: Libraries like CMSIS-NN provide optimized kernel implementations that utilize the specific capabilities of the hardware, enhancing performance without needing to change the underlying AI model.

7. Advanced Microcontrollers: Some microcontrollers, like the Alif Ensemble E3, have dedicated neural processing units (NPUs) that can execute AI tasks more efficiently. These NPUs can run models optimized with specialized tools like the Vela compiler.

The article concludes by highlighting the range of optimization techniques available, from simple software implementations to advanced hardware acceleration, and hints at future discussions about how AI model files are structured and processed.

Hibiki is a new model designed for real-time speech translation. It uses a multistream language model to handle both the source and target speech at the same time, producing text and audio outputs together. Unlike traditional translation, which waits for the speaker to finish, Hibiki translates speech as it is spoken, adjusting to provide accurate translations word by word.

The model employs a weakly-supervised method to find the best timing for translations, using data from a text translation system to create aligned training data. After training, Hibiki can translate speech simultaneously while maintaining high quality, speaker accuracy, and naturalness. It is also easy to use, making it suitable for batch translations and real-time applications on devices. Examples, models, and code for using Hibiki are available.

Summary:

The author discusses how the GitHub Copilot's Agent Mode and Model Context Protocol (MCP) have improved their coding efficiency. Key enhancements include:

1. Customization: Users can tailor AI responses in Visual Studio Code (VS Code) by setting custom instructions, prompts, and chat modes for different development phases.

2. VS Code Settings: Adjustments to settings allow the AI to function more autonomously, improving workflow without constant user input.

3. MCP Tools: The MCP enables access to various external tools for tasks like web searching, browser automation, and database operations, enhancing the development process.

4. Workflow Phases:

   • Research: Conducting thorough research using custom chat modes and tools to gather information.
   • Planning: Generating structured implementation plans without writing code, focusing on analysis and strategy.
   • Implementation: Using prepared prompt files to execute plans, ensuring context is maintained throughout.
   • Course Correction: Adjusting the AI's direction as needed based on its progress and findings.
   • Validation: Testing implementations, particularly for UI elements, using automated tools.

5. Benefits: This process leads to more consistent coding practices, increased efficiency, higher quality outputs, and better testability. The author emphasizes that this approach allows them to focus more on design rather than implementation details.

Overall, the combination of Agent Mode and MCP offers a more sophisticated way to work with AI, making it a valuable partner in the development process.

Summary: Where is my von Braun wheel?

The article discusses the history and potential future of artificial gravity space stations, particularly the concept of the von Braun wheel, which was envisioned in the 1960s. NASA had designs for rotating space stations that could provide artificial gravity, but these were sidelined by the Apollo program, which focused on lunar missions instead.

Key points include:

1. Historical Context: In the early 1960s, NASA was exploring large rotating space stations to address the health issues faced by astronauts in zero gravity. Werner von Braun believed these stations were essential for long-term space habitation.

2. Engineering Challenges: Building large rotating stations poses significant engineering problems, such as ensuring they can fit into slender rockets and managing the effects of rotation on astronauts.

3. Shift in Focus: The Apollo program shifted NASA's focus away from ambitious space station designs to direct lunar missions. This change halted the development of large rotating space stations and led to smaller, less effective structures like the International Space Station (ISS).

4. Modern Interest: Today, private companies are revisiting the idea of artificial gravity stations. One such company, Vast, aims to create a rotating station by 2035, though its design has limitations regarding comfort and gravity distribution.

5. Future Prospects: There is potential for developing artificial gravity stations as part of future missions to Mars and beyond. However, current priorities in space exploration focus more on uncrewed manufacturing in space rather than immediate needs for artificial gravity.

6. Call to Action: The author advocates for renewed efforts to build rotating space stations, emphasizing the need for innovative engineering and regulatory changes to enable their development.

Overall, the article argues that revisiting the concept of artificial gravity is crucial for the future of human space exploration.

The text reflects on how computers and the internet have shifted from being fun, creative spaces to platforms dominated by commercial interests and generative technologies.

1. Decline of Fun: The author laments the loss of enjoyment in using computers, which has been influenced by the rise of payment systems like PayPal and the failure of Bitcoin to become a practical currency for everyday transactions. Instead of empowering creators, these systems have led to frustration and control over how money is spent.

2. Centralization of the Web: The web has become dominated by a few large platforms, reducing the diversity of content and creativity. This centralization pushes creators to prioritize engagement and ad revenue over authentic expression, leading to a culture of low-quality "content" instead of meaningful work.

3. Critique of AI and LLMs: The author expresses disappointment with advancements in AI, particularly language models that generate text without substance. These technologies often produce misleading or incorrect information, leading to more confusion rather than aiding creativity or productivity.

4. Cultural Impact: The proliferation of generative AI raises concerns about the future of creative work and critical thinking, suggesting a trend toward mediocrity where people rely on machines rather than developing their own skills.

5. Call to Action: Ultimately, the author advocates for valuing creativity and individual effort. They encourage people to embrace the process of making things themselves, rather than relying on AI-generated outputs, arguing that true fulfillment comes from creating meaningful work.

Summary: Batteries vs. No-Batteries in Software

The text discusses a new way to categorize software into two types: "battery-included" and "no-batteries."

• Battery-Included Software: This type works right away and comes with all necessary components, making it easier for developers to start building. Examples include Express, which offers more features than Flask but can make troubleshooting harder due to its abstraction.

• No-Batteries Software: This requires developers to add their own components and can lead to tedious setup. While it allows for more control, it may result in bloated systems as developers try to compensate for missing features.

• Balance is Key: A good framework should allow users to remove unnecessary parts while still functioning well. The author shares a positive experience using Flask for a quick school project, appreciating its out-of-the-box usability.

In conclusion, both types of software have their advantages and drawbacks, and the best choice depends on the specific needs of the project.

The text appears to be a chaotic mixture of random characters, emojis, and phrases without a clear or coherent message. It includes greetings like "Hello" and "Hi," along with some nonsensical words and symbols. Overall, it lacks a structured narrative or key points to summarize in a meaningful way.

No summary available.

The text discusses the role of caching in software development. Traditionally, caching is seen as a way to speed up data access by storing frequently used data in faster locations, like memory, instead of retrieving it from slower sources like databases. However, the author argues that caching should be viewed as a simplification tool rather than just an optimization for performance.

The author questions the reliance on generic caching algorithms (like LRU and LFU) and suggests that developers should have a more nuanced understanding of their data needs. They believe that effective caching can create a cleaner separation of concerns in software design.

While acknowledging that data access patterns can be unpredictable, the author emphasizes the importance of caching as an effective abstraction that can simplify data management. They conclude that rather than getting lost in the complexities of caching algorithms, the focus should be on ensuring fast access to the required data.

The fullstack architecture described combines three technologies—Eta, HTMX, and Lit—to create a web application that offers the advantages of both fast Multi-Page Applications (MPAs) and interactive Single-Page Applications (SPAs) without their drawbacks.

Key Points:

1. Combining Technologies:

   • Eta is used for server-side templating, ensuring fast initial page loads by sending pre-rendered HTML to the browser.
   • HTMX handles dynamic interactions, allowing users to interact with the application without full page reloads, using simple HTML attributes instead of complex JavaScript.
   • Lit is used for specific interactive components (like pagination) that require client-side logic, creating reusable "islands of interactivity."

2. Performance Focus:

   • The architecture minimizes the amount of JavaScript sent to the client, resulting in faster loading times and a better user experience, particularly on mobile devices.
   • The initial JavaScript bundle size is significantly smaller compared to traditional SPAs.

3. User Experience Enhancements:

   • The View Transitions API is used to create smooth animations during content updates, making the application feel fast and responsive.
   • Users can choose to disable transitions for certain interactions to avoid distractions.

4. How It Works Together:

   • Eta renders the initial page, including Lit components.
   • HTMX manages server requests for dynamic content without heavy JavaScript.
   • Lit components handle their own UI state while remaining integrated with HTMX for server interactions.

Overall, this architecture provides a balanced approach to web development, achieving speed, interactivity, and maintainability without the complexity of monolithic frameworks.

The World Economic Forum (WEF) has released a paper highlighting the need for age assurance in video games, noting that nearly 80% of children aged 5 to 18 play games. The paper emphasizes the importance of creating safer gaming environments due to the risks of grooming, bullying, and exploitation that children face while gaming, often without supervision.

The WEF praises two models for age assurance: Microsoft's Xbox Gaming Safety Toolkit and k-ID's platform. The Xbox Toolkit helps parents navigate their children's online gaming experiences by providing age-specific advice and scenarios. It was developed collaboratively with educators and organizations in several countries to ensure it is user-friendly and trustworthy.

K-ID addresses age assurance by using privacy-focused techniques to tailor gaming experiences based on age and local laws. This approach is seen as innovative and affordable, allowing smaller developers to comply with child safety regulations without extensive changes to their games.

The paper calls for a proactive approach to safety in game design, clearer regulations, improved digital literacy for both youth and parents, and recognizing children as active participants deserving of protection. It suggests that engagement with young users is essential for effective safety measures in the gaming industry.

Canonical is excited about promoting Ubuntu for RISC-V devices, including tablets, single-board computers, and embedded systems. However, with the upcoming Ubuntu 25.10 release, they are changing the requirements for RISC-V hardware.

Key points include:

• Ubuntu 25.10 will require a new RISC-V profile (RVA23) instead of the previous RVA20. This change affects compatibility, as most current RISC-V devices do not support the RVA23 profile.
• The RVA23 profile includes mandatory extensions like Vector and Hypervisor, which enhance performance for tasks such as AI, machine learning, and cryptography.
• As a result, many existing RISC-V devices will not be able to run Ubuntu 25.10. However, Ubuntu 24.04 LTS, which supports older hardware, will remain available until 2029.
• Although the change in requirements might not significantly impact the niche RISC-V market now, it positions Ubuntu to become the leading operating system as RISC-V hardware improves and becomes more affordable in the future.
• Currently, there are very few RISC-V devices that support the new RVA23 profile, but this is expected to change by the time Ubuntu 26.04 LTS is released.

The July issue of Toronto Life provides an inside look at Doug Ford's strong political ambitions. It also includes extensive coverage of important current events in the city.

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The text provides a link to a GitHub repository called "longfellow-zk" created by Google. The repository likely contains code or resources related to a specific project or technology, but no further details are provided in the text. For more information, you can visit the link.

Summary:

Postcard, a personal website and newsletter platform created by Philip I. Thomas in 2022, is now open source. He started it to stay connected with friends after deleting social media. Many people have used Postcard since its launch, and while it generates modest revenue, Thomas values its importance as a reliable tool.

He has decided to release the source code to allow others to customize and use it. Postcard is built in Ruby on Rails and is designed to be easy to run. The open-source version includes a "Solo" mode for single-site hosting, making it simpler for users. It also retains a "Multiuser" mode for the hosted service.

The project comes with easy deployment instructions, including a Dockerfile for setup. You can find the code and contribute at github.com/contraptionco/postcard.

Recent advancements in artificial intelligence (AI), especially with large language models (LLMs) like OpenAI-o1 and DeepSeek-R1, have shown impressive skills in areas like logical reasoning and coding. This has led to increased interest in using AI to enhance the innovation process in scientific research. However, there is currently no comprehensive survey on AI for Research (AI4Research), which limits our understanding and progress in this area.

To fill this gap, we present a thorough survey that offers a unified view on AI4Research. Our main contributions include:

1. Taxonomy: We introduce a systematic way to classify five key tasks in AI4Research.
2. Research Gaps: We identify important gaps in research and suggest future directions, emphasizing the need for better automated experiments and considering their societal impact.
3. Resources: We provide a collection of valuable resources, including applications, data sets, and tools related to AI4Research.

Our goal is to help the research community access these resources easily and inspire new innovations in the field.

Summary of Wasm-agents: AI Agents Running in Your Browser

Wasm-agents are a new way to run AI agents directly in your web browser without needing additional tools or frameworks. This approach simplifies the process of using open-source agents by allowing them to be packaged as standalone HTML files that can be opened and executed easily.

Key Points:

• No Extra Dependencies: Users can run agents without installing extra software. The agents are packaged in HTML files that include both the user interface and the code.
• WebAssembly (Wasm): This technology allows programming languages like Python to run quickly in web browsers. Pyodide enables Python code and libraries to be executed in this environment.
• Easy Setup: Users can simply paste their OpenAI API key into a configuration file to get started. Local models can also be used if they are properly set up.
• Demos Available: Several demo agents are provided, including:
  • A simple conversational agent.
  • A multi-agent system that routes requests.
  • An advanced agent with practical tools for tasks like web content retrieval.
• Limitations: The project is still experimental and has limitations, such as dependency on the OpenAI framework, issues with CORS (Cross-Origin Resource Sharing), and the requirement for local models to be installed.
• Encouragement to Experiment: Users are encouraged to explore the demos, modify the code, and test different models to see what works best for them.

Overall, Wasm-agents aim to make AI experimentation more accessible and user-friendly, promoting the idea of running tools locally and safeguarding personal data. Feedback and collaboration from users are welcomed as the project develops.

Summary of AI Evals FAQ

This document outlines key concepts and answers frequently asked questions about AI evaluations (evals) for engineers and product managers. The authors, Hamel Husain and Shreya Shankar, share insights based on their experience teaching over 700 professionals in this area.

1. What are LLM Evals? - LLM evals refer to evaluations specific to product applications of language models, distinct from foundational model benchmarks.

2. Is RAG dead? - Retrieval-Augmented Generation (RAG) is not dead. It remains crucial for providing context to improve model outputs. Developers should focus on effective retrieval strategies rather than abandon RAG altogether.

3. Using the Same Model for Tasks and Evaluation - It is generally acceptable to use the same model for both tasks and evaluation, especially for binary classification tasks, but avoid using it for subjective quality assessments.

4. Model Selection Time - Spend more time on error analysis to identify issues before switching models. This approach is more effective for improving LLM applications.

5. Custom Annotation Tools vs. Off-the-Shelf - Building custom annotation tools is highly recommended as they enhance workflow efficiency and adapt to specific needs better than generic tools.

6. Binary Evaluations vs. Likert Scales - Binary evaluations are favored for their clarity and consistency, while Likert scales can introduce subjectivity and confusion.

7. Debugging Multi-Turn Conversations - Start by checking if the entire conversation meets user goals and simplify failures to isolate issues.

8. Automated Evaluators - Focus on building evaluators for persistent issues rather than every failure mode, prioritizing simpler checks over complex evaluators.

9. Annotation Team Size - For small to medium projects, a single expert is often sufficient to guide quality standards, while larger teams may require multiple annotators.

10. Gaps in Eval Tooling - Expect to fill gaps in areas like error analysis, AI-powered assistance, and custom evaluators since most existing tools don’t cover these comprehensively.

11. Generating Synthetic Data - Use structured approaches to create diverse and targeted synthetic data for testing.

12. Evaluation for Diverse Queries - Use error analysis to guide evaluation strategies based on observed failure patterns rather than predetermined categories.

13. Chunk Size in Document Processing - Adjust chunk sizes based on the task type: larger chunks for fixed-output tasks and smaller chunks for expansive-output tasks.

14. Evaluating RAG Systems - Separate evaluations for retrieval (using traditional metrics) and generation quality (using error analysis and human labels).

15. Custom Interfaces for Reviewing Outputs - Build interfaces that streamline the review process, keeping user experience and efficiency in mind.

16. Budget for Evaluations - Consider evaluation as part of the development process. Invest in error analysis and only build automated checks that add significant value.

17. Importance of Error Analysis - This process helps identify unique failure modes and informs the metrics developed for evaluation.

18. Guardrails vs. Evaluators - Guardrails prevent immediate failures in real-time, while evaluators assess overall quality and performance after the fact.

19. Minimum Viable Evaluation Setup - Start with basic error analysis and manual reviews before investing in complex infrastructure.

20. Evaluating Agentic Workflows - Assess tasks in two phases: overall success and step-level diagnostics to identify specific failure points.

21. Vendor Selection for Eval Tools - Choose vendors based on support rather than features, as they are often similar in capabilities.

22. CI/CD vs. Production Evaluations - CI uses small, curated datasets for frequent testing, while production monitoring assesses live data, often requiring more complex evaluations.

The authors conclude by announcing their final AI Evals course cohort and providing a discount code for interested readers.

Summary: An Algorithm for a Better Bookshelf

Researchers have developed a new algorithm to improve the way books are organized on shelves, which has implications for managing large data sets in computer science. Libraries often leave empty spaces on shelves to accommodate new books, a concept that applies to various data management scenarios. The challenge, known as the "list labeling problem," involves efficiently placing new entries while minimizing the movement of existing ones.

For many years, the best algorithms could handle costs of adding new entries at a rate of log2n (a logarithmic scale). Recently, a new algorithm has been introduced that reduces this cost to logn × (log(logn))^2, a significant improvement. This algorithm combines two strategies: maintaining "history independence" (which prevents adversaries from predicting where new entries will go) and being adaptable to adversarial strategies.

This advancement could enhance performance in real-world applications, such as social networks, where sudden influxes of data occur. Researchers believe this work may inspire further studies and possibly lead to even more efficient algorithms, potentially revolutionizing how sorted data is managed in computer science.

No summary available.

The Elixir conference is being organized by Underjord, a consultancy specializing in Elixir and Nerves, and it will take place from September 10-12, 2025, in Varberg, Sweden. The idea for the conference emerged from previous events like Gig City Elixir and NervesConf. The organizer, influenced by Priya Parker's book "The Art of Gathering," aims to create a unique gathering for the Elixir community.

The conference will feature a single track of talks, encouraging engaging and creative presentations rather than simple project updates. The organizer has secured a venue, sponsors, and a lineup of speakers through connections made over years of involvement in the Elixir community. Tools like Sessionize and Tito have been chosen for managing speakers and ticketing.

Marketing efforts have included active promotion on social media, and the use of Discord is planned for event communication. The goal is to bring together local and international Elixir developers, fostering community connections. The organizer is excited yet anxious about the event's success and emphasizes the importance of collaboration and support from their partner and advisors throughout the planning process.

Figma, a design tool, has disclosed in its IPO filing that it spends $300,000 daily on Amazon Web Services (AWS) for cloud computing. The company entered a new agreement with AWS on May 31, 2025, committing to at least $545 million in services over five years. Figma relies heavily on AWS for its operations, meaning any outages or changes to AWS's terms could negatively impact its business. High cloud costs are common as companies grow, leading some, like 37signals, to reduce their reliance on cloud services to save money.

Neural networks are everywhere, used in language models, speech recognition, and robotics. They are built from simple components and learning about them involves understanding how to program and work with these models, a process known as differentiable programming.

This guide is designed for beginners, like Alice, who want to explore this field. It covers the basics of optimizing functions using automatic differentiation and introduces key designs for processing sequences, graphs, text, and audio. The focus is on making complex ideas easy to understand, including techniques like convolutional, attentional, and recurrent blocks. By the end, readers will have the knowledge to grasp advanced models, such as large language models and multimodal systems, using programming tools like PyTorch and JAX.

A user created a website called Sinkedin, inspired by a joke about having a platform for sharing failures, like job rejections and interview mistakes. The site allows people to post their stories anonymously. The design is simple, and contributions to improve it are welcome. It’s currently running on free services, so there may be delays if it gets busy. They are looking to test the idea quickly before investing more money. The user is open to questions.

Website: Sinkedin
GitHub: Sinkedin GitHub

No summary available.

The text discusses an experiment focused on improving documentation for AI agents by integrating agent instructions directly into existing engineering documents instead of maintaining separate documents.

Key Points:

1. Initial Concerns: The author expressed concerns about the design of agent documentation, fearing duplication and inconsistency between separate documents for agents and existing engineering documentation.

2. Proposed Solution: The author suggested embedding agent instructions within internal engineering documents, which they tested with promising results.

3. Experiment Results: The author conducted an experiment by embedding AI instructions in the guidelines for code examples on a website. They successfully instructed an AI (Gemini CLI) to convert a specific code example into a buildable and testable format, confirming that the AI followed the instructions closely.

4. Caveats: The experiment was informal and highlighted the need for a more controlled approach to separate the effects of colocated instructions from existing agent documentation.

5. Documentation Updates: The author thoroughly documented their process, including creating a new test file, updating build targets, and verifying the success of the integration. They also confirmed that the documentation build remained functional after the changes.

Overall, the experiment showed promise for integrating agent instructions into existing documents to streamline processes and maintain consistency.

Before the pandemic, the author and their partner enjoyed swimming in the sea. One day, a Labrador named Arthur swam past them, seemingly heading far out to sea. The author expressed concern to another swimmer, who casually mentioned hoping Arthur wouldn’t meet a seal because he wanted to watch a football match later.

Months later, the author witnessed Arthur playing with a seal in the water, which seemed like a friendly game. When the pandemic started, the author adopted a puppy named Lenny, who also loved the water. They took Lenny to a local park where other dog owners gathered. Observing how different breeds interacted, it was clear that even dogs behaved according to their instincts.

While at a café, a stranger suggested Labradors thrive with regular sea visits due to their history of helping fishermen. Encouraged, the author began taking Lenny swimming. However, swimming with Lenny was chaotic, as he would try to guide the author back to shore like a sheepdog. Eventually, after some struggle, the author would swim at their own pace, and Lenny would wait at the shore, looking concerned.

The author reflects on the constant push and pull in their relationship with Lenny, noting that sometimes it feels right to let the dog take the lead while swimming.

Summary: Enhancing SHA256 Calculation on FPGA

Recently, an article detailed the development of a SHA-256 hash calculator on an FPGA, capable of computing a hash for a string (up to 25 bytes) in 68 clock cycles. This design utilized FPGA parallelism but was limited to producing one hash at a time, underutilizing its capacity.

To improve performance, the author introduced multiple hash calculators to compute several hashes simultaneously. Key changes included storing the pre-computed K matrix at a higher level, allowing all hash cores access to it, and initializing W matrix values in parallel. This led to a new module called sha256_core_pif.

A manager module, SHA256_manager, was also added to coordinate inputs to the hash cores. The application developed is a password cracker that tests various strings against a given SHA-256 hash until it finds a match.

The project runs on a Litefury board connected to a Raspberry Pi 5, using 12 sha256_core_pif modules at a clock speed of 62.5 MHz, meeting timing requirements while not fully utilizing the FPGA.

A Python driver was created to manage the FPGA, allowing it to open a communication channel and read/write to registers. A testing script was also provided to verify the functionality by comparing calculated hashes.

The project showcases the potential of FPGAs in accelerating cryptographic computations and is expected to gain more importance in cybersecurity.

For more details, the project files are available on GitHub, and the author invites inquiries from those interested in integrating FPGAs into cryptography projects.

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Create a quick Hacker News (HN) profile to see how little information is needed to personalize your feed. By rating 30 posts, you can get a permanent, customized homepage to revisit. The goal is to test how personal context influences the performance of large language models (LLMs) while reading HN. We are looking into what types of data and how much effort is needed from users to achieve good results. This tool is fun to use, and we decided to share it for feedback and to connect with others working on similar projects.

I'm sorry, but I cannot access external links or specific documents. However, if you provide me with the main points or sections of the research paper, I can help summarize that information for you!

No summary available.

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The Ford Pinto, produced from 1970 to 1980, was notorious for safety issues, particularly its tendency to catch fire in rear-end collisions due to a poorly designed gas tank. Critics claim that Ford was aware of these dangers before the car's release but chose not to make safety modifications. Instead, they conducted a cost-benefit analysis and found it cheaper to settle potential lawsuits than to recall the cars for safety improvements.

The leaked "Pinto Memo" revealed that modifying the Pinto would cost Ford $121 million, while paying off victims of accidents would only cost about $50 million. As a result, the Pinto was launched without safety changes, leading to many accidents and deaths. Investigations showed that nearly 9,000 people died in related incidents, and the National Highway Traffic Safety Administration (NHTSA) began looking into the car shortly after its release.

Public backlash eventually forced Ford to issue a recall for dealer-installed safety kits, which were inadequate to address the serious design flaws. Critics highlighted the Pinto's lack of proper rear bumpers and door reinforcements, contributing to its dangerous reputation. The public even dubbed it "the barbecue that seats four" due to its fiery accidents.

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Summary:

Arista tested different types of cables to see which had the lowest latency when transmitting data. They found that direct-attach copper cables (Twinax) are faster than both single-mode and multi-mode fiber cables.

Key Points:

• The test was done using the Arista 7130 MetaWatch application with 10G Ethernet, connecting two machines.
• They sent 1,000,000 ping packets to measure how long it took for data to travel through the cables.
• Results showed that direct-attach copper cables had an average latency of about 4.60 ns per meter, while fiber cables had a latency of around 5 ns per meter.
• Copper cables perform better over short distances (up to 10 meters), while fiber cables can reach longer distances (up to 10 km).
• Overall, for applications where low latency is critical, direct-attach copper cables are the better choice compared to fiber cables.

No summary available.

I launched NumPad v1 a few years ago as a simple calculator app. Now, I've completely redesigned it into a Progressive Web App (PWA) that allows users to work with multiple documents. It saves documents using IndexedDB and offers a syncing service for paying customers. The syncing is powered by a tool called Automerge, which should make it easier to share documents in the future.

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A former FBI agent, Myron Fuller, visits a Louisiana prison to confront Larry Thompson, a hitman linked to a murder that has haunted him for decades. Fuller, who had a distinguished FBI career, is seeking closure regarding the unsolved murder of Maria Marshall, which he believes he could have prevented. Thompson is serving an 80-year sentence for attempted murder and other crimes, and during their meeting, they discuss their shared past and the consequences of their choices.

The visit takes place in a casual setting, with both men, now in their late 70s, having led difficult lives marked by crime and regret. Fuller, originally from a poor background, found success in the FBI but left Louisiana feeling defeated. He has since tried to move on, but memories of his past linger. This meeting is Fuller's attempt to understand the events that unfolded and to find peace with his past.

Samsung smartphones can endure significantly more charge cycles compared to devices from Google and Apple, according to new data from the European Union's energy label program. This program rates smartphones on various factors, including battery durability.

Key points from the findings include:

• Samsung Devices: Many Samsung phones, such as the Galaxy S24 and S25 series, can handle up to 2,000 charge cycles.
• Other Brands: In comparison, Google’s Pixel phones are rated for 1,000 cycles, while Apple devices also typically rate around 1,000 cycles.
• Other Brands: Other manufacturers like Motorola, OnePlus, and Sony have varying cycle ratings, mostly falling between 800 to 1,400 cycles.

This information helps consumers understand the longevity of their smartphone batteries better. However, there are questions about how these ratings reflect real-world usage and the factors influencing battery performance.

Summary: Importance of Context Management in AI NPCs

In a recent project focused on AI non-player characters (NPCs), the author encountered challenges with managing AI context, a crucial aspect that is often overlooked. After analyzing Google's development kit, they discovered the importance of effectively handling context to improve the AI's performance and memory.

To address the growing context issue, the author developed a system that allows AI to summarize and self-manage its memories. This system stores key information in both a vector and an SQL database, enabling the AI to remember interactions, such as recognizing a character's preferences. This creates a learning-like environment for the AI, where each agent can have unique observations due to variations in randomness and personality prompts.

However, as context expands, the efficiency of the AI decreases, slowing down its response time. The author notes that having too much context can overwhelm the AI and lead to forgetfulness. To combat this, they implemented a spatial system that helps keep the context clean and relevant, ensuring that NPCs only retain necessary information.

The author emphasizes the importance of maintaining a "clean context," avoiding unnecessary details, error messages, and tool-related information that could confuse the AI. This approach highlights a shift from "prompt engineering" to something they term "context engineering," which requires deeper understanding and engineering skills in managing AI interactions.

Overall, the author is passionate about creating truly interactive NPCs and believes that effective context management is key to achieving this goal.

No summary available.

The author shares their experience with a pair of AI-powered earbuds they purchased after seeing them featured in a video. They highlight several key points:

1. Purchase and Features: The earbuds run on Android and include ChatGPT functionality, along with other AI features like translations. However, the audio quality is poor unless the equalizer settings are manually adjusted.

2. Device Hacking: The author discovered that the earbuds allow for ADB (Android Debug Bridge) access, enabling them to sideload apps and inspect communications. They found that the device communicates directly with OpenAI's servers, indicating it contains an OpenAI API key.

3. Privacy Concerns: There are significant security issues, such as an exposed endpoint that logs chat histories without proper authentication, potentially allowing anyone to access users' chat logs by guessing device IDs.

4. Company Response: After notifying the company about these vulnerabilities, the app was temporarily taken offline for maintenance. Post-maintenance, some security measures were implemented, but critical vulnerabilities still existed, such as the ability to bind unlinked devices and access user data.

5. Conclusions: The author expresses frustration with the company's lack of response and ongoing security flaws. They encourage others to push for better security measures.

Overall, they document a troubling mix of interesting tech features and serious privacy risks.

Summary: Simulated SPI RAM on RP2040

This project allows the RP2040 microcontroller to function as a simulated SPI RAM, similar to a 23LC512 chip. It supports three main commands: READ, WRITE, and FAST READ.

Key Features:

• Command Set:

  • READ (0x03): Retrieves data from a specified address.
  • WRITE (0x02): Stores data at a specified address.
  • FAST READ (0x0B): Similar to READ but includes a delay for faster operation.

• Speed Limits: The maximum speed for operations depends on the system clock speed. For example:

  • READ: Up to 12.5 MHz
  • WRITE: Up to 20.8 MHz
  • FAST READ: Up to 15.6 MHz

• Functionality:

  • Uses SPI mode 0 or 3 for data transfer.
  • Operations must stay within the RAM limits.
  • Data transfers occur immediately after the command is sent.

Integration:

To use this in your project:

1. Copy required files from the project.
2. Modify your CMakeLists.txt to include necessary files and set up the memory map.
3. Configure pins and initiate RAM using setup_simulated_sram().

Operation Details:

• The RAM simulation relies heavily on PIO (Programmable Input/Output) and DMA (Direct Memory Access) for efficient data handling.
• Core1 of the RP2040 is dedicated to managing RAM operations, ensuring tight timing and consistent performance.
• Commands involve reading addresses and transferring data through a series of well-timed operations.

Limitations:

• The duration for the CS (Chip Select) signal to remain high between operations is not precisely defined but is estimated to be around 50 system clock cycles.
• Aborting operations before data transfer starts is currently not supported.

This implementation provides a flexible way to simulate SPI RAM on the RP2040, enabling efficient memory operations for various applications.

Summary of Liquid Glass Notes by Riccardo Mori

Riccardo Mori discusses Apple's new user-interface design called Liquid Glass, which will impact all its platforms. He expresses frustration with Apple's guidelines, noting inconsistencies in how navigation elements should interact with content. For instance, while Apple suggests that navigation should be transparent to focus on content, this contradicts advice to separate navigation from content clearly.

Mori criticizes the increased spacing in layouts, which he believes makes interfaces less informative and requires more scrolling. He also highlights the trend of simplifying app icons to the point where they lose uniqueness, arguing that this approach makes them bland and less representative of their functions.

He points out that Apple's recent design philosophy seems to prioritize visual effects over practical usability, leading to a lack of creativity and personality in app design. Mori feels that the current guidelines restrict developers more than previous versions, pushing them to conform to a bland aesthetic that aligns with Apple's branding rather than allowing individual expression.

Overall, he believes that these changes do not enhance user experience and reflect a troubling shift in Apple's design philosophy towards uniformity and simplicity at the cost of creativity and functionality.

No summary available.

No summary available.

The article discusses the experience of using advanced coding models, particularly focusing on the OpenAI o3 model and Claude Sonnet, in software development. The author shares their journey of coding daily and the challenges faced with these models, such as unnecessary complexity and cost.

Key points include:

1. Model Performance: While Claude Sonnet was previously considered effective, the o3 model demonstrated better results in troubleshooting, avoiding unnecessary code changes, and efficiently following coding rules.

2. Cost Considerations: The author faced high costs, averaging $1,000/month for using o3, which sparked a debate about its value. Despite the expense, they found it justified due to the benefits it provided compared to cheaper models.

3. Effective Practices: The article provides tips for maximizing the value of large coding models:

   • Detect errors early in the coding process.
   • Use well-documented technology.
   • Refine coding rules and scripts for better integration with LLMs (Large Language Models).
   • Ensure code is readable and manageable.
   • Understand the limitations of the models to enhance their effectiveness.

4. Recent Developments: The cost of using these models has decreased, making them more accessible. The author highlights new tools and methods to utilize multiple agents simultaneously, which can improve productivity.

Overall, the article emphasizes that while using advanced coding agents can be costly, their ability to enhance productivity and streamline coding processes can make them worthwhile investments for software teams.

Sony and AMD are working together on a project called "Project Amethyst," which aims to improve gaming AI and hardware. Mark Cerny from PlayStation has been heavily involved in developing AMD's next graphics architecture, initially referred to as RDNA 5 but possibly changing to UDNA.

This collaboration has already produced impressive results, including an upscaling algorithm for gaming that will be used in the PlayStation 5 Pro in 2026. Both companies are focused on enhancing their software and hardware, which will benefit gamers by providing better gaming technology and experiences.

Overall, the partnership between AMD and PlayStation is set to lead to significant advancements in gaming hardware, benefiting both console and PC gamers.

No summary available.

A recent study from Karolinska Institutet shows that gene therapy can successfully restore hearing in deaf patients, including children and adults with genetic deafness. The study involved ten patients aged 1 to 24 who had hearing loss due to mutations in the OTOF gene. The therapy used a virus to deliver a working version of this gene into the inner ear, leading to improved hearing in all participants within a month. After six months, average hearing levels improved significantly, especially in younger patients.

The treatment was safe, with only minor side effects reported. Researchers plan to explore treatments for other genetic causes of deafness in the future. The study highlights a promising advancement in treating hearing loss that could greatly enhance the quality of life for affected individuals.

The Minor Planet Electronic Circular provides updates and information about minor planets. You can find the specific details in the linked document.

Summary:

When creating links, use clear and informative text that helps users understand what the link offers, without focusing on the mechanics of how to access it. Avoid using phrases like "click here" or making links sound like verb phrases. Instead, use concise descriptions. For example, instead of saying "To download Amaya, click here," say "Get Amaya!" or provide a brief description like "Tell me more about Amaya: W3C's free editor/browser for creating HTML, SVG, and MathML documents."

The W3C QA Tips provide helpful guidance for web developers and designers, but they are not official technical specifications. You can learn more about these tips and how to contribute by visiting the Tips Index.