Summary: Local-First Software: Balancing Collaboration and Ownership

Motivation for Local-First Software:

• Online collaboration tools like Google Docs, Trello, and Figma have made teamwork easier, but they often compromise data ownership and long-term accessibility.
• Creative professionals feel a strong emotional connection to their work and want to retain ownership of their digital creations.

Challenges of Cloud Apps:

• Cloud apps store data on remote servers, limiting users' control and ownership. If a service goes down or gets shut down, users lose access to their data.
• Users are dependent on the service provider, which can lead to issues with data accessibility and privacy.

Local-First Software Concept:

• Local-first software prioritizes data stored locally on devices while still enabling collaboration and cloud features.
• This approach provides full ownership of data, allowing users to work offline and sync changes later.

Seven Ideals for Local-First Software:

1. No Spinners: Fast access to data without waiting for server responses.
2. Multi-Device Support: Seamless synchronization across various devices.
3. Offline Capability: Functionality without needing an internet connection.
4. Seamless Collaboration: Real-time teamwork without conflicts.
5. Longevity: Data remains accessible long-term, even if the software provider disappears.
6. Privacy and Security: Data is stored locally, reducing risks of breaches.
7. User Control: Users have the freedom to manage and modify their data without restrictions.

Technological Innovations:

• The use of Conflict-free Replicated Data Types (CRDTs) is proposed as a foundational technology for local-first applications, allowing for real-time collaboration and data merging without the need for central servers.
• Prototypes like Trellis (Kanban board), Pixelpusher (collaborative drawing), and PushPin (mixed media canvas) have been developed to explore these concepts in practice.

Conclusion:

• The local-first approach aims to combine the benefits of cloud apps with the ownership and control of traditional software.
• While progress has been made, further development is needed to enhance user experience and ensure that local-first software can be widely adopted.
• Collaboration among researchers, developers, and entrepreneurs is crucial to realize the potential of local-first technologies.

This summary highlights the key points regarding the need for local-first software that balances collaboration and ownership, along with the challenges posed by current cloud applications.

Europe has launched its first geostationary sounder satellite, the Meteosat Third Generation Sounder 1 (MTG-S1), to improve its ability to respond to extreme weather. Launched on July 1, 2025, MTG-S1 will provide valuable atmospheric data, helping meteorologists deliver more accurate and timely weather warnings, which can protect lives and property.

The satellite will monitor temperature, humidity, and trace gases in the atmosphere, allowing forecasters to detect severe weather conditions before they become critical. It is equipped with advanced technology that offers a continuous view of storm developments, enhancing short-term weather forecasting and long-term climate monitoring.

MTG-S1's successful deployment was celebrated by the European meteorological community, marking a significant achievement in European cooperation. The satellite is part of a broader program that aims to revolutionize weather forecasting and improve air quality monitoring across Europe.

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Nikkei Asia is a publication that provides news and information about Asia. They offer various subscription options, including individual and corporate subscriptions, as well as gift subscriptions. The site also includes a sitemap for easy navigation and sections for announcements, advertising, and support. Additionally, it has legal and privacy information to ensure user rights are protected.

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The paper "Build Systems à la Carte" by Andrey Mokhov, Neil Mitchell, and Simon Peyton Jones discusses how build systems, which are essential tools for software developers, can be better understood and improved.

Key Points:

1. Build Systems Overview: Build systems automate the process of compiling and linking code. They are complex and often overlooked despite being critical for software development.

2. Framework for Understanding: The authors propose a systematic framework that allows for the analysis and comparison of various build systems by identifying their components and how they can be recombined.

3. Key Properties: Build systems differ based on several factors, including:

   • Dependency types (static vs. dynamic)
   • Build environments (local vs. cloud)
   • Task execution (deterministic vs. non-deterministic)

4. Design Choices: Two fundamental design choices in build systems are the order of task execution and whether tasks are rebuilt. These choices lead to a classification system that helps in understanding different build systems.

5. Examples of Build Systems: The paper examines several build systems:

   • Make: Uses static dependencies and file modification times.
   • Excel: Handles dynamic dependencies but sacrifices some efficiency.
   • Shake: Addresses dynamic dependencies while maintaining efficiency.
   • Bazel: A cloud-based system that accelerates builds through shared resources.

6. New Build Systems: By understanding existing systems, the authors suggest that new build systems can be designed with desired properties by combining features from existing ones.

7. Contributions: The paper outlines abstractions for build systems, making it easier to create and analyze them using functional programming principles.

In conclusion, the paper aims to foster a better understanding of build systems, highlighting their importance and potential for improvement through a systematic framework.

On July 4, 2025, the author is rebuilding their homelab and downsizing their storage from a large NAS with 120 TB to a mini NAS with around 6 TB of usable space, due to reduced storage needs after stopping a YouTube channel. They are considering three new mini NAS options: GMKtec G9, Aiffro K100, and Beelink ME mini, all of which have similar Intel chips and 2.5 Gbps networking.

Here’s a brief overview of each:

1. GMKtec G9: Previously reviewed, it has cooling issues with multiple drives but has been redesigned for better airflow. The budget-friendly option but may still have stability problems.

2. Aiffro K100: Smaller and more efficient than the G9, it stays cooler and quieter. However, it lacks built-in eMMC and WiFi, and has limited BIOS customization. It's the most expensive option.

3. Beelink ME mini: Very quiet and features 6 NVMe slots, but with limited bandwidth per slot. It includes built-in eMMC and has a compact design with an internal power supply, which is rare for mini PCs.

Each NAS has pros and cons, and there's no single best choice; it depends on individual needs. The author leans towards the K100, provided they find affordable SSDs to meet their storage requirements.

Gecode is an open-source C++ toolkit designed for creating constraint-based systems and applications. Here are its key features:

• Open: Gecode allows users to easily connect it with other systems and supports programming new constraints and search methods.

• Comprehensive: It includes a wide variety of features such as constraints for integers, Booleans, sets, and floats, and offers advanced search techniques and support for MiniZinc.

• Efficient: Gecode is known for its high performance in both speed and memory use, having won multiple awards at the MiniZinc Challenges from 2008 to 2012.

• Well-documented: It comes with extensive tutorials and reference materials to aid users in learning and using the toolkit.

• Free: Gecode is free software under the MIT license, with all components available for download.

• Portable: It follows the C++ standard and can run on various hardware platforms.

• Parallel: Gecode takes advantage of multi-core processors for efficient parallel processing.

• Thoroughly tested: It has a robust testing suite with over 50,000 test cases, ensuring high reliability and coverage.

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The article discusses SIMD (Single Instruction, Multiple Data) functions and vectorization, focusing on their use in programming for improved performance by processing multiple data elements at once. Key points include:

1. What are SIMD Functions?
   SIMD functions handle multiple data inputs in one function call, enhancing performance. For instance, a standard sine function sin(double angle) can be vectorized to handle an array of angles, sin(double[4] angle).

2. Why Use Vector Functions?
   They allow compilers to optimize loops by choosing between scalar (single value) or vector (multiple values) implementations based on performance needs.

3. Declaring Vector Functions:
   Vector functions can be declared using specific compiler pragmas (like OpenMP) which inform the compiler about their vectorized nature.

4. Function Parameters:
   Different types of parameters can influence how SIMD functions operate, such as:

   • Variable: Each lane can have different values (default).
   • Uniform: All lanes have the same value.
   • Linear: Values increase in a linear fashion.

5. Limitations of SIMD Functions:

   • Limited Compiler Support: Not all compilers support SIMD features, impacting usability.
   • Efficiency Issues: Compilers may generate inefficient implementations, often resorting to repeated scalar functions instead of optimized vector code.
   • Complexity in Implementation: Custom implementations using intrinsic functions require understanding of compiler details and ABI (Application Binary Interface).

6. Best Practices:
   Use attributes like inbranch and notinbranch to inform the compiler about how to optimize function calls, especially when handling conditional logic.

7. Conclusion:
   While SIMD functions can significantly boost performance, their practical application can be complex and compiler-dependent, often requiring careful management to achieve efficient execution.

Overall, leveraging SIMD functions involves navigating various compiler specifications and understanding function declarations to maximize performance effectively.

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A 37-year-old individual is eager to learn computer science, driven by a passion for building and creating. They have some experience in web development, having created a simple blog and a more complex website for a passion project, mainly through self-teaching and using helpful frameworks.

Their career has been varied, including jobs as a waiter, sales person, and teacher of Math, Science, and Computers. Now, they are ready to dive deep into computer science, aiming for mastery over the next decade, although they are not focused on becoming a software developer.

With some savings to support their minimal lifestyle, and encouragement from their wife, they are determined to learn about designing APIs, building databases, and more. Despite concerns about ageism in the tech field, they are enthusiastic about their journey.

They have several project ideas, including apps for their community, educational tools, and an e-commerce platform for wooden toys they design. They plan to keep track of their progress and share updates along the way.

The N-Back test is a task that measures working memory and is used for cognitive training. In this test, you see a sequence of blue squares in a grid and need to identify if the current square matches the one from a certain number of steps back (N steps).

Originally created by Wayne Kirchner in 1958, the N-Back test is popular in neuroscience research. Studies show that regular practice can improve working memory, attention, and even overall intelligence.

To play the N-Back test, focus on the grid and respond when you see a match by clicking 'Match' or pressing the spacebar. If there’s no match, click 'No Match' or press 'N'. Each square is shown for 3 seconds, followed by a 1-second break.

Benefits of N-Back training include:

• Improved working memory
• Increased fluid intelligence
• Better attention and focus
• Enhanced ability to switch between tasks
• Improved academic performance

Research supports these benefits, with studies showing significant cognitive improvements after consistent training. To perform better, start with easier levels, practice regularly, minimize distractions, and use memory strategies.

Different variations of the N-Back test include 1-Back for beginners, 2-Back as the standard level, and more challenging options like 3-Back and Dual N-Back.

For best results, aim to practice 15-20 minutes daily, and you may notice improvements in 2-3 weeks. Yes, the effectiveness of N-Back training is backed by scientific research.

The article discusses the history of EverQuest, an influential MMORPG that launched in 1999 and shaped the genre. While Ultima Online pioneered online fantasy worlds, it was EverQuest that successfully capitalized on this concept, attracting a massive player base and generating significant revenue.

Key Points:

1. Origins: EverQuest was developed by a team at Sony Interactive Studios America, led by John Smedley. He had a vision of creating a multiplayer online RPG inspired by earlier games like Dungeons & Dragons and Neverwinter Nights.

2. Development Team: Smedley recruited Brad McQuaid and Steve Clover, who had previous experience with shareware games. They created a detailed design document, focusing on making EverQuest fun and accessible.

3. Gameplay Focus: Unlike Ultima Online, which allowed player-versus-player (PvP) combat, EverQuest emphasized player-versus-environment (PvE) gameplay, creating a safer and more welcoming atmosphere for players.

4. Launch and Reception: EverQuest went live on March 16, 1999, and quickly gained popularity, boasting 10,000 subscribers on its first day. By October 1999, it had over 150,000 subscribers, far surpassing Ultima Online.

5. Addiction and Controversy: The game attracted attention for its addictive nature, with players often spending excessive amounts of time in-game. This led to discussions about the potential negative impacts of MMORPGs on real-life relationships and responsibilities.

6. Cultural Impact: EverQuest's success paved the way for future MMORPGs and changed how games were marketed and monetized, leading to a focus on long-term engagement with players.

In summary, EverQuest transformed the MMORPG landscape with its focus on fun, community, and accessible gameplay, while also sparking important conversations about gaming addiction and its effects on players.

The Senate Finance Committee has proposed new legislation that expands the tax benefits for "qualified small business stock" (QSBS) acquired after the law is enacted. Currently, QSBS allows founders and investors in certain C corporations to exclude up to 100% of gains from the sale of their QSBS, with specific conditions.

Key proposed changes include:

1. Tiered Gain Exclusion: The proposal introduces a tiered system where:

   • 50% of gains can be excluded for QSBS held for 3 to 4 years.
   • 75% for QSBS held for 4 to 5 years.
   • 100% for QSBS held for over 5 years.

   This means lower effective tax rates for early exits.

2. Increased Gain Exclusion Cap: The maximum gain exclusion will rise from $10 million to $15 million and will adjust for inflation starting in 2027.

3. Higher Gross Asset Threshold: The limit on corporate gross assets will increase from $50 million to $75 million, also adjusting for inflation in 2027.

The proposed changes would be effective for stock issued after the final legislation is passed. Founders could benefit from earlier exits with reduced tax consequences, and startups might consider delaying financing if they risk exceeding the current asset threshold. Overall, these changes aim to enhance support for startups and emerging companies.

GamingOnLinux is celebrating its 16th birthday today. Over the past couple of years, many similar websites have shut down or changed focus, but GamingOnLinux continues to provide news and information about Linux gaming. The author, Liam Dawe, thanks readers and supporters for their loyalty.

Despite challenges, like being removed from Bing News after a brief downtime, the website's traffic is at an all-time high. Liam emphasizes the importance of following GamingOnLinux directly and sharing articles on social media to help keep the site visible.

The website has no plans to adopt AI-generated content, focusing instead on original writing. There are also upcoming improvements, such as the revival of their PC Info system.

Readers can support GamingOnLinux through Patreon, donations, or by purchasing games through affiliate links. Thank you to everyone for their continued support!

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Summary: How to Disable Google Tag Manager and Protect Your Privacy

Google Tag Manager (GTM) is a tool that helps websites track user behavior, often leading to invasive surveillance. It operates by disguising various tracking scripts, making it easier for websites to collect personal data. Recently, Google has shifted from third-party to first-party tracking, which can seem like a privacy improvement but is actually a way to bypass content-blocking measures.

Key Points:

1. Surveillance Tool: GTM is primarily used for monitoring users rather than general website management. Its close integration with Google Analytics allows for detailed tracking of individual behaviors.

2. Increased Monitoring: Google Analytics has evolved to conduct more invasive tracking, including monitoring mouse movements and clicks, often exploiting psychological vulnerabilities.

3. Blocking GTM: It can be blocked by disabling JavaScript in your browser. This renders GTM ineffective since most of its functions rely on JavaScript. However, many websites now require JavaScript to function properly.

4. Prevention Methods:

   • Block All Cookies: Prevent both first-party and third-party cookies to limit tracking.
   • Disable JavaScript: This can be done globally or selectively using browser extensions like uBlock Origin.
   • Use Text-Only Browsers: Browsers like Lynx can display pages without any tracking capabilities.
   • Disconnect Internet After Loading Pages: This stops data from being sent after the initial load.

5. Challenges: Many websites have designed their pages to break or limit functionality without JavaScript, making it difficult for users who want to maintain privacy.

In conclusion, disabling GTM and protecting online privacy is crucial but challenging. Saying "no" to invasive tracking can result in a poor user experience, but it is essential to resist exploitation.

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The ADXL345 is a low-cost MEMS accelerometer from Analog Devices, popular among hobbyists. However, caution is advised when purchasing, as some units may have defects. One user received faulty ADXL345s with issues like measurement errors and non-functional features, which prompted them to seek help in diagnosing the problem.

Upon examination, unusual markings were found on the chip, suggesting it might be from a defective batch that was re-marked and sold. Inside, the chip consists of two silicon layers: one containing the MEMS accelerometer and the other a readout chip. This design allows for high performance, as the ADXL345 can measure acceleration up to +/- 16 g, unlike its predecessor, the ADXL335.

The MEMS chip operates by measuring capacitance changes caused by a moving proof mass in response to acceleration. Despite the chip appearing correct, it likely failed quality tests during production and was improperly sold. This teardown highlights the intricate design and potential issues with MEMS devices.

NVIDIA is facing significant criticism following the troubled launch of its RTX 50 series graphics cards. Key issues include:

1. Scalper Problems: Bots are purchasing GPUs before consumers can buy them, leading to inflated prices in secondary markets. Retailers are receiving limited stock, fueling speculation that NVIDIA is deliberately creating a sense of scarcity.

2. Defective Hardware: Some GPUs are reportedly being shipped with missing processing units, resulting in reduced performance. NVIDIA acknowledged that a small percentage of cards have these defects but downplayed the impact.

3. Power Connector Issues: The RTX 50 series continues to suffer from problems with melting power connectors, a flaw inherited from previous generations. This design oversight creates safety concerns and potential damage to the hardware.

4. Deceptive Marketing: NVIDIA is accused of manipulating media narratives and pressuring reviewers to focus on specific performance metrics that favor their products, undermining the trustworthiness of reviews.

5. Proprietary Technologies: NVIDIA's exclusive technologies, such as DLSS and G-Sync, create a dependency on their hardware, making it difficult for consumers to switch to competitors like AMD.

6. Generational Performance: Despite the high prices of their latest cards, performance improvements have been minimal, leading to disappointment among consumers, especially regarding ray tracing capabilities.

7. Market Dominance: NVIDIA's overwhelming market share allows them to dictate terms and prices, often to the detriment of consumers, who face rising costs without corresponding improvements in quality or performance.

Overall, the sentiment is that NVIDIA is prioritizing profits from data center sales over consumer needs, leading to frustration among gamers and PC builders.

Heart attacks have become less deadly in the U.S. due to significant medical advancements and public health efforts. A recent article highlights the progress made since the 1960s, when heart attack death rates peaked. For instance, the death rate from coronary heart disease dropped by nearly 90% from 1970 to 2022. Today, over 90% of men over 65 survive a heart attack if hospitalized, compared to just 60% in 1970.

Key factors contributing to this improvement include:

1. Anti-Smoking Campaigns: A major public health effort has successfully reduced smoking rates from 40% in 1970 to 14% in 2019, lowering heart attack risk.

2. Statins: These cholesterol-lowering drugs have been widely adopted since the 1980s and save nearly 2 million lives globally each year.

3. Emergency Response: The introduction of CPR training and portable defibrillators has increased survival rates during cardiac events.

4. Medical Innovations: Advances like coronary care units and minimally invasive procedures have improved treatment outcomes for heart attacks.

Despite these successes, heart disease still causes about 700,000 deaths annually in the U.S. Many factors, including rising obesity and diabetes rates, continue to pose risks. New treatments like GLP-1 inhibitors show promise in further reducing heart disease rates. Additionally, more Americans could benefit from advanced screening tests for heart disease, as only a small percentage currently receive them.

Overall, while we have made remarkable strides in reducing heart attack fatalities, there is still work to do in preventing heart disease before it occurs.

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Summary:

"Baba is You" is a puzzle game where players manipulate rules to solve puzzles, making it a challenging reasoning benchmark. Unlike traditional benchmarks, this game has existing solutions online, but many player-created levels do not, which keeps the challenge alive.

The project aims to create a demo version called "Baba is Eval," inspired by other game environments. Key goals include reading the game state, allowing the model to control the game more quickly than a human, and automating menu navigation.

To get the game state, the developers discovered the game's Lua scripts and functions that allow them to access and serialize level data. They set up a server to display this information in a grid format.

For control, instead of simulating key presses, they found a way to execute commands directly from the code, improving speed. However, navigating levels and selecting them proved to be complicated due to sparse code.

They used the Claude Desktop app as the demo client, which struggled with complex tasks in the game, highlighting the challenges of reasoning models in this context. Future improvements may involve switching to more advanced models or changing how game states are represented to enhance efficiency. Overall, the project is ongoing, and the developers welcome contributions and ideas from others.

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A software developer with over 20 years of experience, who had never created games before, recently decided to try making one using 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 to game development that allows AI assistance. After about 25-30 hours of work outside their full-time job, they completed and submitted a game called "Tower of Time," themed around time travel.

The developer aimed to see if AI could help create an enjoyable game and found that it did. They documented their process, sharing both the code and the prompts used on GitHub. Most of the art assets were sourced from free artists on itch.io, and sound effects came from freesound.org. They also streamed parts of their development process on Twitch.

Having learned a lot from this experience, the developer plans to apply their newfound knowledge to future projects and welcomes any comments or questions. You can play their game here.

The Wind Knitting Factory is a unique knitting machine powered by wind, installed on the side of a building. It features large blades that capture wind to operate. As the wind blows, the machine knits a long scarf that hangs down the building. The speed of knitting varies with the wind strength—faster winds produce more knitting.

The knitted material drops from the top of the building and is transported inside through a window, where people can watch it grow longer. Occasionally, the scarves are collected, and each one is labeled with the date and time it was made, showcasing how urban wind can be used for production. This project blends public and private space, illustrating the creative possibilities of harnessing wind energy.

The text discusses a unique feature and bug in early versions of Commodore BASIC, particularly focusing on how the interpreter handles whitespace and tokenization.

Key points include:

1. Tokenization in BASIC: When you type a line of code, BASIC converts keywords into tokens (integer values) to save memory and speed up execution. For example, the keyword "LET" is represented by a specific token value.

2. Whitespace Handling: BASIC ignores whitespace between keywords and identifiers. This can lead to confusion, as in the example where "LE THEN" is misinterpreted as "LET HEN" due to missing spaces.

3. Memory Efficiency: By using tokens for keywords, BASIC programs take up less memory, which was crucial in early computing when memory was limited.

4. Line Structure: BASIC programs are stored in memory as linked lists, where each line is connected to the next. This affects how quickly the interpreter can access different lines of code.

5. Comparisons with Other BASIC Versions: Other versions, like AppleSoft BASIC, handle whitespace differently, sometimes leading to loss of information (like skipping over spaces entirely).

6. Numbers and Identifiers: BASIC allows users to include spaces in numbers and variable names for ease of typing, but this can slow down execution as the interpreter has to parse these spaces.

Overall, the text illustrates the quirks and design choices of early BASIC interpreters, particularly in relation to whitespace and tokenization, and how these choices affected programming on systems like the Commodore PET.

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Summary of the ITTAGE Indirect Branch Predictor

The ITTAGE indirect branch predictor is a performance tool used in modern CPUs, particularly effective in predicting indirect jumps in bytecode interpreters. Recent developments in CPU technology have improved the accuracy of these predictions, even in traditional interpreter loops.

1. Branch Prediction Basics: Modern CPUs use complex algorithms to predict the behavior of branches in code, aiming to improve performance by anticipating which path a program will take based on historical data.

2. TAGE and ITTAGE Predictors: The ITTAGE predictor is a variant of the TAGE predictor. While TAGE focuses on conditional branches, ITTAGE predicts the destination of indirect jumps. Both use historical data to make predictions and adaptively select the best prediction strategy based on past performance.

3. Key Features:

   • They store multiple tables with different history lengths to improve prediction accuracy.
   • They adaptively choose the most suitable table for each branch, learning from previous errors to refine predictions.
   • They use tagging to distinguish between different branches stored in the same table to reduce collision errors.

4. Implementation: ITTAGE retains confidence counters that measure the reliability of predictions. When a prediction is wrong, it updates the predicted target address only if the confidence is low, ensuring that only reliable data influences future predictions.

5. Applications and Future Ideas: The ITTAGE predictor could inform other software tools, like coverage-guided fuzzers, by helping them explore program states more effectively. This raises potential applications in machine learning and reinforcement learning, where prediction errors could guide exploration in learning algorithms.

Overall, ITTAGE enhances the understanding of branch behavior in interpreters, which can lead to better performance in software execution and more effective exploration strategies in programming tools.

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Soham Parekh is trending on Twitter because many startups are claiming they have hired him recently or in the past. People are questioning why these startups aren't better at screening candidates to avoid hiring someone who might be scamming or holding multiple jobs at once.

The author shares their experience transitioning from a developer to a CTO, noting a shift from coding to managing people and projects. Over time, their coding time has decreased significantly, leading to a focus on product and systems rather than technical details. While this role allows for greater influence, it also brings less satisfaction, particularly in terms of dopamine rewards that come from solving coding problems.

As AI tools become more prevalent in coding, everyone is now managing these AI agents. This can boost productivity and make tasks easier, but it raises concerns about job satisfaction and motivation. The author questions whether the ease of using AI will provide the same sense of accomplishment that comes from overcoming challenging problems.

They argue that while solving user problems is essential, the day-to-day work of developers still involves writing and fixing code. The reliance on AI may shift the nature of the industry, potentially affecting job satisfaction, especially for those who thrive on intense problem-solving.

As users become better at managing AI, their traditional coding skills may decline, making it challenging to handle complex issues when they arise. The author warns that while managing AI can be rewarding, it might also lead to feelings of disconnect from the core aspects of software development.

In summary, the text reflects on the evolving role of developers in an AI-driven world and the implications for job satisfaction and skill maintenance.

Summary: Impact of PCIe 5.0 Bandwidth on GPU Content Creation Performance

In July 2025, the release of new NVIDIA and AMD GPUs supporting PCIe 5.0 raises questions about how this increased bandwidth affects GPU performance in content creation tasks. PCIe (Peripheral Component Interconnect Express) is a standard for connecting devices like GPUs to motherboards, and each version offers higher data transfer rates. For example, PCIe 5.0 can achieve a maximum throughput of 64 GB/s with a 16-lane configuration, doubling what PCIe 4.0 can provide.

The availability of PCIe lanes varies by motherboard. Many consumer boards have limited slots, often leading to GPUs operating with less than maximum bandwidth, which could impact performance. The article specifically examines how different PCIe configurations (like x16, x8, and x4) influence performance across various applications such as video editing (DaVinci Resolve, After Effects), game development (Unreal Engine), and rendering (Blender, Octane).

Key findings include:

• Video Editing: DaVinci Resolve shows significant performance drops with lower PCIe bandwidths. Using x16 or x8 configurations offers similar performance, but x4 and below can reduce speeds by 25% or more.
• After Effects: Shows less sensitivity to PCIe bandwidth changes, with minor performance variations across different configurations.
• Game Development: Unreal Engine performance is mostly stable until bandwidth drops to x4, where a slight performance decrease occurs.
• Rendering: Both Blender and Octane show negligible impact from different PCIe configurations, indicating that bandwidth is less critical for rendering tasks since scenes primarily load into GPU memory.
• AI Tasks: Performance in AI-related tasks shows minimal differences across bandwidths, though some scenarios involving multiple GPUs may still be affected.

Overall, while modern motherboards typically allow for PCIe 5.0 x8 configurations without significant losses in performance for most tasks, using lower bandwidths like x4 can result in noticeable slowdowns, particularly in video editing applications. Therefore, users should carefully consider their specific use cases when configuring systems for content creation.

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Summary of Compression Dictionary Transport

Compression Dictionary Transport is a new experimental technology designed to reduce the size of HTTP responses by using a shared "compression dictionary." This method helps decrease the amount of data transferred over the network, which can lower costs and speed up page loading.

Key Points:

• HTTP Compression: Uses algorithms to identify and eliminate redundancy in the data being sent. For example, if a string is repeated, only one copy is sent, and references are made to it instead.

• Improved Method: Compression Dictionary Transport builds on a previous method called SDCH, which was not widely adopted. It allows custom dictionaries to be used for better efficiency.

• How It Works:

  • A dictionary can be any file containing common strings or previous versions of resources.
  • When a new version of a resource (like a JavaScript library) is released, it can use the previous version as a dictionary to avoid sending identical data again.

• Example: If a library updates from version 1 to version 2, the new version can use the old version's dictionary to compress the data, only sending the differences.

• Dictionary Formats: There is no specific format for dictionaries; they are regular files. They can be defined using HTTP headers (e.g., Use-As-Dictionary) to indicate which resources can utilize a specific dictionary.

• Creating Compressed Responses: Compressed files can be created using algorithms like Brotli or ZStandard, and can either be generated dynamically or built in advance.

• Security Considerations: There are restrictions to prevent security issues:

  • Dictionaries must be from the same origin as the resource using them.
  • They could potentially be used for tracking, so browsers may limit their use under certain privacy settings.

Conclusion:

Compression Dictionary Transport offers a promising way to significantly reduce data size for web applications, improving loading speeds and decreasing bandwidth usage while ensuring security and privacy.

Summary: Open Source FPGA Maker Board for Networking

Private Island Networks Inc. is offering sponsorship for university projects in the 2025/2026 academic year that involve their Private Island® open source networking stack. This initiative focuses on network security, privacy, and machine learning and is ideal for senior projects, master's theses, and advanced high school cybersecurity clubs.

Students interested in sponsorship must have a professor's support and can apply via a form or email. The Betsy™ maker board uses an Altera Cyclone 10 LP FPGA for various networking functions, such as packet processing and security, and supports Ethernet connectivity.

The project encourages innovative ideas for applications, including neural networks for detecting intrusions, cloud-based machine learning, and secure communication channels. There's also an emphasis on creating visualizations of network data and testing for vulnerabilities.

The Betsy Maker Board prototype is currently available in limited quantities, with a production model expected in early 2026. Documentation and project resources are being actively developed and shared online.

For project consideration, interested individuals should fill out the sponsorship form.

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Ben from K-Scale Labs is developing open-source humanoid robots. The company aims to make these robots more affordable and accessible, targeting indie hackers and developers. Currently, their humanoid robot, K-Bot, is priced at $8,999, significantly lower than existing options that cost over $50,000.

K-Scale Labs started by creating a basic robot using 3D printing and parts from online marketplaces. Their goal is to transition from hobby-grade to consumer-grade robots without increasing costs or relying heavily on Chinese suppliers, especially due to tariffs.

To navigate challenges in manufacturing and supply chains, they are open-sourcing their hardware and software, making it easier for suppliers to work with them. They believe there's significant interest among developers for hacking on humanoid robots, which could be a better market than traditional business robotics.

Currently, many potential buyers want fully autonomous robots for household tasks, which is challenging to create. To address this, K-Scale Labs offers a "Full Autonomy" option, allowing customers to receive free upgrades until the robot can operate autonomously.

Overall, the company values feedback from the community to improve their products and embrace the collaborative nature of open-source development.

The author created MCP-123 to simplify the process of using MCP examples, which were often too complicated or required specific tools. With MCP-123, you can use a tools.py file and run server.run_server(...), allowing the client to automatically find and use functions with OpenAI. The author hopes this tool is helpful to users.

Summary of JSONPath for Querying JSON Data

Introduction to JSONPath
JSON (JavaScript Object Notation) is widely used, especially in APIs and logs, but working with complex, nested structures can be challenging. JSONPath is a query language designed to help you easily extract data from JSON, similar to how XPath works for XML.

What is JSONPath?
JSONPath allows you to query JSON data without needing to write complex loops. It supports:

• Root and recursive navigation
• Filters using conditions
• Wildcards, unions, and slicing
• Built-in functions like length(), count(), and search()

Basic Syntax and Operators
Key JSONPath syntax includes:

• Root selector: $ for the root
• Child access: $.store, $['name']
• Wildcard: * to select all children
• Recursive descent: .. to get all descendants
• Filter expressions: ?() to apply conditions
• Function usage: e.g., count(@)

Common Use Cases
Here are some practical examples of JSONPath queries:

1. Fetch all book titles: $.store.book[*].title
2. Filter books by price: $.store.book[?(@.price > 10)].title
3. Get the bicycle price: $.store.bicycle.price
4. Get all prices: $.store..price
5. Get the last book: $..book[-1]
6. Get the first two books: $..book[:2]
7. Filter books with an ISBN: $..book[?(@.isbn)]

Advanced Features
JSONPath allows for more complex queries, such as:

• Length-based filtering: length(@.authors) >= 5
• Regex matching: match(@.sku, '^[A-Z]{3}\\d{4}$')
• Counting nodes: count(@['category','title','price','isbn']) == 4

Using JSONPath in Different Languages
JSONPath is available in various programming languages, including Java, Python, C#, and more. The syntax is consistent across languages, making it easy to learn and use.

Interactive Tools
For a hands-on experience, tools like PostPilot.dev allow you to test JSONPath queries in a user-friendly interface, helping you explore JSON data easily.

Conclusion
By learning JSONPath, you can efficiently query and analyze JSON data. Its clear syntax and powerful features make it an essential tool for developers working with JSON. Happy querying!

The "Lens, Folds and Traversals" package is a Haskell library that provides many useful tools for working with data types. It includes pre-defined lenses for common types and offers functions to create lenses and isomorphisms for custom data types.

Key features of the package include:

• A set of combinators for building getters, folds, isomorphisms, traversals, setters, and lenses.
• The ability to use any type of lens as another type in the hierarchy (e.g., a Traversal can also be used as a Fold).
• Instructions on how to create your own lenses without needing additional dependencies.
• Example applications, such as a simple game of Pong, to illustrate how to manage state using lenses.

The library is well-documented with a README, tutorial videos, and a wiki for further guidance. It aims to simplify the management of data structures in Haskell.

The package is maintained by Edward A. Kmett and is available under the BSD-2-Clause license. It supports various Haskell versions and has a wide range of dependencies.

Summary of GREMLLM

GREMLLM is an upgraded utility class designed to enhance coding functionality. It allows for dynamic object behavior, enabling methods and properties to be created on-the-fly using language model reasoning.

Key Features:

• Dynamic Behavior: Objects can change methods and properties during runtime.
• Wet Mode: Methods return living objects, allowing for infinite chaining of actions.
• Verbose Mode: Displays the code generated for debugging and understanding.
• Multi-Model Support: Works with various models including OpenAI, Claude, and local models.
• Inheritance & Smart Error Handling: Child objects inherit settings, and errors are handled gracefully.

Installation:

You can install GREMLLM using pip:

pip install gremllm

Usage Example:

To create a counter:

from gremllm import Gremllm

counter = Gremllm('counter')
counter.value = 5
counter.increment()
print(counter.value)  # Outputs 6

Configuration:

Set up your preferred model using the llm library:

• For OpenAI: llm keys set openai
• For Claude: pip install llm-claude-3 and then llm keys set claude
• For local models: pip install llm-ollama

You can specify the model when creating a GREMLLM object.

Example Scenarios:

• Basic Counter: Increment and manipulate a counter.
• Shopping Cart: Manage items and calculate totals.
• Wet Mode: Allows for continuous interaction with living objects.
• Verbose Mode: Helps in debugging by showing generated code.

Conclusion:

GREMLLM offers an innovative way to interact with code, making it more dynamic and user-friendly.

No summary available.

Large language models (LLMs) like ChatGPT and GPT-4 are good at communicating with people. This report explores how well they can play text-based games, where players interact with the game through dialogue. The findings show that ChatGPT performs well compared to other systems but still lacks true intelligence. It struggles to understand the game world, cannot build a mental model from playing or reading instructions, and often fails to grasp the goals of each step in the game. These results raise new questions for research in artificial intelligence, machine learning, and natural language processing.

The article discusses the rumored interest of Sun Microsystems in Commodore's Amiga 3000, particularly its UNIX version (A3000UX), during the early 1990s. It reflects on how the Amiga, despite its innovative features, failed largely due to management issues at Commodore.

Key Points:

1. Background: The Amiga 3000 was launched in 1990 and was a powerful model for its time. Commodore later released a UNIX version, the A3000UX, in 1991.

2. Rumors of a Deal: There are stories that Sun Microsystems considered licensing the A3000UX for their low-end machines. However, these claims are based on unverified accounts from former Commodore engineers, Dave Haynie and Bryce Nesbitt, who provide differing details about the alleged negotiations.

3. Discrepancies: Haynie claims Sun was interested in the hardware, while Nesbitt suggests they wanted the software. Both accounts, while potentially true, show inconsistencies and raise doubts about their reliability.

4. Market Context: At the time, Sun was focusing on their SPARC architecture and had already launched competing machines. The Amiga 3000UX was relatively priced competitively but lacked the performance needed to attract UNIX customers who were moving towards newer technologies.

5. Software Issues: Commodore's UNIX offering was the first SVR4 port for Motorola's 68k CPUs, which might have intrigued Sun. However, the feasibility of porting efforts and the existing competition from Sun's own software made this less likely.

6. Conclusion: The article suggests that while there were discussions between Sun and Commodore, the timeline and circumstances make a formal deal highly improbable. The failure of Amiga UNIX can be attributed more to Commodore's management failures than to any missed opportunity with Sun.

In summary, the narrative around the potential Sun-Commodore deal remains speculative, with various factors complicating the situation. The Amiga 3000UX was an interesting product but ultimately couldn't compete effectively in the market.

The text discusses the mixed perceptions of large language models (LLMs) in the tech community. Some people view them as miraculous tools, while others find them ineffective. The author highlights that many criticisms stem from a lack of understanding of how LLMs work and the specific contexts in which they are used.

Key points include:

1. There is a significant gap between those who find LLMs helpful and those who believe they are useless.
2. Many discussions lack clarity on critical factors, such as the types of projects, the expertise of users, and the additional work involved in using LLMs.
3. LLMs are non-deterministic, meaning their effectiveness can vary greatly, making it hard to compare experiences across different users and scenarios.
4. The hype surrounding LLMs often overshadows critical thinking, leading people to accept exaggerated claims without questioning them.
5. The author, who has experience using various AI tools, finds that they work only about half the time, emphasizing that while they can seem magical, they are not infallible.

Overall, the text calls for a more nuanced understanding of LLMs, moving beyond hype and wishful thinking.

No summary available.

Larry is a British domestic tabby cat who has held the title of Chief Mouser to the Cabinet Office at 10 Downing Street since February 2011. He was born around January 2007, originally as a stray, and was adopted from Battersea Dogs & Cats Home. Larry is cared for by Downing Street staff and is not owned by the prime minister.

Throughout his time at Downing Street, Larry has lived through the premierships of six prime ministers, including David Cameron and Rishi Sunak. His duties include greeting guests and inspecting security, but he is known more for his casual approach, often seen napping rather than hunting mice. Although he has caught a few mice, he has earned nicknames like "Lazy Larry" due to his laid-back demeanor.

Larry has a notable public image, even having a higher approval rating than some political leaders. He has been involved in playful interactions with other pets, including a rivalry with Palmerston, another cat from the Foreign Office.

In recent times, there were concerns about his health, but official statements have assured the public that he is doing well. Larry has become a beloved figure, often featured in media and public events, and is recognized for his charm and character at the heart of British politics.

If you're in a tech job and want to switch careers for more meaningful work, this guide offers several options. Your reasons for leaving may vary, such as dissatisfaction with the tech industry, a desire for a more positive impact, or simply personal reflection on your life choices.

Here are some potential paths to consider:

1. Public Sector Work: Transitioning to a job in public institutions can be a smooth move. These roles often involve creating software that serves the public and addresses important issues, although be wary of consultancy firms that may compromise quality.

2. Tech Co-operatives: Joining or starting a tech co-op allows workers to own and manage their projects. This option provides more freedom but also comes with additional responsibilities. Co-ops usually focus on consultancy, which is easier to start.

3. Tech NGOs: There are many non-profits and NGOs that need tech skills to tackle issues like human rights, the environment, and education. These organizations often struggle to find technical talent, so there are many opportunities available.

4. Unions and Political Parties: If you want to improve conditions in tech, consider working for a union or political party. They need tech infrastructure and often develop their own software.

5. Teaching and Mentoring: If you enjoy helping others learn, consider teaching programming or design, either in schools, universities, or online platforms.

6. Techno-Political Hustler: This emerging role involves connecting various projects and organizations, using your tech skills for social or political causes. It requires a broad understanding of multiple fields and networking skills.

Finding a fulfilling career path is a personal journey, and it's important to explore options that align with your values and skills. It's never too late to make a change and pursue a more meaningful career.

In the past year, James has worked on building an AI coding agent named Codebuff. He reflects on the journey, starting from a hackathon prototype to competing in the market. Here are the key points:

1. Initial Successes: The team focused on creating a command line interface (CLI) tool, which helped streamline their efforts. They also innovated with features like reading multiple files for context and creating knowledge files to improve learning.

2. Challenges Faced: Despite early optimism, the product struggled with reliability, leading to lower user retention and growth. Issues with file editing and task failures hindered progress.

3. Lessons Learned: James identified areas for improvement, such as implementing regular evaluations to track performance, focusing on core features, involving the whole team in product development, and holding monthly retrospectives for strategic discussions.

4. Future Plans: Recently, Codebuff launched a new multi-agent framework, which has received positive feedback. James is optimistic about the future, predicting significant advancements in coding agents, such as "live learning" and autonomous quality assurance.

5. Opportunities: The author invites readers to join the team as they continue to develop their coding agent and explore new possibilities.

Overall, James remains excited about the potential of AI coding agents and is committed to improving Codebuff's capabilities.

Large Language Models (LLMs) are improving rapidly and could soon complete complex tasks much faster than humans. By 2030, they might be able to finish in hours what currently takes a human a month. This exponential growth in AI capabilities suggests that LLMs will significantly enhance their efficiency in the near future.

Summary of BunkerWeb

BunkerWeb is an open-source Web Application Firewall (WAF) designed to secure web services easily and effectively. Here are the key points:

• Integration: BunkerWeb works well with existing systems like Linux, Docker, Kubernetes, and more, making it easy to implement.

• Customization: Users can easily configure and tailor BunkerWeb’s security features to fit their needs, with a user-friendly web interface available for those not comfortable with command-line tools.

• Security Features: BunkerWeb offers built-in security measures, including:

  • Automated HTTPS support using Let's Encrypt.
  • Advanced web security with HTTP headers and ModSecurity for attack protection.
  • Automatic blocking of suspicious activities based on HTTP status codes.
  • Connection and request limits to prevent misuse.
  • Bot protection through challenges (like captchas).
  • Blocking of known bad IPs using external blacklists.

• Cloud Option: For those who prefer not to self-host, BunkerWeb Cloud offers a managed service with all features, monitoring, and support.

• PRO Version: There is a PRO version available for a free trial, offering enhanced features. Users can upgrade easily from the open-source version.

• Professional Services: The BunkerWeb team provides technical support and consulting services.

• Community: Resources, documentation, and community support are available through various online platforms.

For more hands-on experience, demos and a read-only UI demo are accessible online.

No summary available.

Summary of "Introducing tmux-rs" by Collin Richards

On July 3, 2025, Collin Richards announced the completion of a personal project: porting the terminal multiplexer tmux from C to Rust. The new codebase now consists of about 81,000 lines of Rust code, compared to around 67,000 lines in C. This endeavor was primarily a hobby without a specific goal other than experimentation.

Key Steps in the Process:

1. Using C2Rust: Richards initially employed C2Rust, a tool to convert C code to Rust. However, the output was hard to maintain, leading him to manually translate the code instead.

2. Development Process: He used a combination of tools, including Vim for editing and a custom build script to manage the compilation process. The transition involved translating one function at a time to ensure accuracy.

3. Handling Bugs: Richards encountered various bugs during the translation. For example, issues arose from mismatches in type declarations and implicit function declarations in C, which caused segmentation faults.

4. C Patterns in Rust: He encountered challenges translating certain C programming patterns into Rust, such as raw pointers and the use of goto. He adapted these patterns to fit Rust's model, often needing to create custom implementations for data structures.

5. Parser Reimplementation: The original tmux parser, built with yacc, was successfully reimplemented using the lalrpop crate in Rust.

Conclusion:

While Richards has completed the port to Rust, he acknowledges that the resulting code still has many bugs and is not yet as robust as he desires. He plans to continue improving the code, with a goal of transitioning to safe Rust in the future. The project is available on GitHub for others interested in Rust and tmux.

In March 2025, a review comparing an Intel N100 mini PC (GMKtec N100 NucBox G3) to a Raspberry Pi 5 was shared. A year later, a new version of the mini PC with an Intel N150 processor and 16GB RAM was released, along with a new 16GB Raspberry Pi 5. The reviewer conducted benchmarks while installing Linux on the mini PC, addressing criticisms of previous comparisons that used Windows on the PC and Raspberry Pi OS on the Pi.

Key findings include:

• Performance varies widely among Intel N100 systems due to different RAM and cooling options. Generally, even slower DDR4 configurations outperformed the Raspberry Pi 5 by 1.5-2 times in benchmarks, but power efficiency was lower.
• Used Tiny PCs are generally cheaper than new Raspberry Pi 5s, with many available from business leases.
• When comparing new models with similar specs, the Raspberry Pi 5 is more compact and slightly more power-efficient, but Intel systems are better for desktop use and software compatibility.
• The cost of running these devices is not significantly different for most users, making value comparisons complex.

Overall, the review emphasizes that both devices have their strengths and weaknesses, and the choice depends on user needs.

Summary: Rust and WASM for Form Validation

Sebastian Lauwers discusses how using Rust with WebAssembly (WASM) has become easier for backend developers who may not be familiar with frontend technologies like React. Initially, using WASM required complicated tools like Node and Webpack, but recent improvements have streamlined the process.

In this tutorial, Lauwers shows how to create a simple web application using Rust that includes a server to render HTML and a WASM component for form validation. He emphasizes the appeal of sharing code across the frontend and backend, particularly for data structures.

Key components of the tutorial include setting up the project structure, configuring the WASM target, and implementing a simple login form. The server uses the Rocket framework to handle requests, while the WASM part validates form data and interacts with the DOM.

Lauwers provides code snippets for setting up the server, creating HTML templates, and adding form validation in WASM. He highlights the benefits of using Rust and WASM together, noting that while WASM binaries can be larger than equivalent JavaScript, they can be more efficient at scale.

Overall, the tutorial demonstrates how to build a web application that leverages both Rust on the backend and WASM on the frontend, making it an effective choice for developers looking to utilize both technologies.

Summary:

The DRM Panic QR Code Generator creates QR codes to display kernel panic data, making it easier for users to report bugs. Instead of dealing with difficult-to-copy panic traces on screens, users can scan the QR code to include the information in bug reports, which aids developers in fixing issues. QR codes can hold more data than text displayed on a monitor.

The project is written in Rust for better memory safety and easier integration into the Linux kernel, and it was added in version v6.12-rc1. Arch Linux will soon enable this feature.

Additional resources include a web frontend to decode the QR codes, sample panic screens, and a standalone Rust application to test the code. The main author is Jocelyn Falempe, supported by the Rust for Linux community.

OpenDrop Digital Microfluidics Overview

OpenDrop is an open-source project that focuses on digital microfluidics, combining hardware and software for fluid manipulation.

Product Offerings:

1. OpenDrop V4 Digital Microfluidics Platform - Prices range from €975.00 to €1,595.00.
2. OpenDrop V4 Cartridge - Available from €79.00 to €375.00.
3. OpenDrop V4 Cartridge with Heated Pads - Priced at €129.00.
4. Digital Liquid (5ml) - Costs between €19.00 and €49.00.
5. Open Cartridge Kit - Available for €53.00.
6. Digital Liquid with Magnetic Beads (200ul) - Priced at €27.00.
7. OpenDrop V4 Basic Bundle - Costs €1,205.00.
8. OpenDrop V4 Full Bundle - Priced at €2,575.00.
9. OpenDrop V4 Glass Bundle - Costs €1,611.00.

The products can be sorted by popularity, latest additions, or price.

No summary available.

Summary:

Agents, which use large language models (LLMs), require context to perform tasks effectively. "Context engineering" is the process of providing the right information at the right time for the agent to succeed. Key types of context include instructions, knowledge, and feedback from tools.

As agents become better at handling tasks, the amount of context they use can become overwhelming, leading to issues like confusion or errors. Therefore, effective context management is crucial for their performance.

There are four main strategies for context engineering:

1. Write Context: This involves saving information outside the agent's immediate context to help it complete tasks. Techniques include using scratchpads for note-taking and creating long-term memories from past interactions.

2. Select Context: Agents need to pull relevant information into their working context. This can be done by selecting useful memories or using tool descriptions effectively.

3. Compress Context: To manage large amounts of information, agents can summarize interactions or trim unnecessary details to retain only what's essential for the task.

4. Isolate Context: This strategy involves dividing tasks among sub-agents or using separate environments to keep context organized and manageable.

Overall, these strategies are key to developing effective AI agents today.

No summary available.

No summary available.

I created tinykv because I wanted a simple way to store data for my Rust projects, but other options were either too complicated or not maintained. Tinykv is designed to be easy to use, using JSON and serde, and it has an optional time-to-live feature. It's great for command-line tools, game saves, and configuration storage. I would love to get feedback from the Hacker News community!

The text discusses the history and significance of the ARPANET, the precursor to the modern internet. Here are the key points summarized simply:

1. Initial Impressions: When people first learn about ARPANET, they often see maps showing how it connected computers across the U.S. in the late 1960s and early 70s. These maps can give the impression that ARPANET’s main achievement was connecting distant computers.

2. Misconceptions: Many assume that before ARPANET, computers were completely disconnected. However, even before ARPANET, remote computer access was possible through existing teletype devices.

3. Key Events: The ARPANET was publicly demonstrated at the 1972 International Conference on Computing Communication (ICCC) in Washington, D.C., showcasing its capabilities to about 800 attendees, including researchers and professionals from various fields.

4. Demonstration Features: Attendees could use terminals to access ARPANET and try out various software applications, including games and programming tools. Importantly, the demonstration highlighted not just human-computer interaction but also the ability of computers to communicate with each other.

5. Real Innovation: The true breakthrough of ARPANET was its ability to connect different computer systems, allowing them to communicate despite their technical differences. This was achieved through the development of protocols that facilitated interoperability among diverse machines.

6. Historical Context: Prior to ARPANET, there were social networks based on time-sharing systems, where users could connect and collaborate. Recognizing these earlier networks helps us understand the evolution of digital communication.

7. Network Working Group: A group of young researchers, known as the Network Working Group, was crucial in establishing the protocols necessary for ARPANET's success. Their collaborative approach to standardization, exemplified by the Request for Comments (RFC) series, laid the foundation for future internet standards.

8. Legacy: The ARPANET's significance lies not just in connecting computers but in solving the complex challenge of enabling different systems to work together. This achievement was critical for the development of the internet we use today.

In summary, ARPANET was innovative because it allowed diverse computer systems to communicate effectively, marking a significant step forward in networking technology.

A recent post discussed the challenges of using numpy with arrays that have more than two dimensions. One issue is that Python loops are slow, making them less efficient for these tasks. In the programming language J, you can solve multiple equations efficiently using a concept called rank. An example code in J shows how to solve a system of equations for ten random vectors.

The author suggests that a similar approach could be created in numpy, proposing a new function, numpy.linalg.solve(a, b, rank=(1, inf)), to handle this type of problem more effectively.

The jediterm library, created for integrated development environments (IDEs), can also function as a standalone terminal emulator that supports tabs. Although this library has existed for over a decade, it seems no one has used it to create a terminal emulator application until now.

The text describes significant updates to the Zig programming language's input/output (I/O) system, focusing on the deprecation of existing standard I/O readers and writers in favor of new, non-generic versions. Key points include:

1. New I/O API: The new std.io.Reader and std.io.Writer are introduced, which are designed to optimize performance while simplifying the interface. They allow for better handling of buffers and improve formatted printing.

2. Breaking Changes: The update includes many breaking changes, particularly affecting formatted printing functions. Users will need to adapt their code to the new API.

3. Upgrade Guide: A guide is provided for transitioning to the new system, including renaming deprecated functions and methods.

4. New Features: The new API introduces features like efficient data discarding, a method for handling I/O without direct memory copying, and the ability to send files directly between file descriptors.

5. Future Plans: This change is part of a larger effort to improve Zig's I/O capabilities, with additional changes planned for future updates.

Overall, the changes aim to enhance Zig's performance and usability in handling I/O operations, although they require users to update their existing code.

The author’s company is heavily focused on prompt engineering, with the CEO and CTO promoting it as the preferred method for coding. They suggest replacing manual coding, like fixing test failures, with AI-generated solutions. The author, a senior engineer with about five years of experience, is considering leaving the company because they are concerned about:

1. Their technical growth being hindered by this workflow.
2. The quality of future work being compromised by relying on AI-generated code.

They are open to advice on their situation and general opinions about this trend.

Summary of phkmalloc:

Jason Evans recently honored phkmalloc as he retired jemalloc, prompting a reflection on its development. Initially, FreeBSD used Chris Kingsley's malloc implementation, which became problematic as RAM prices rose in the mid-90s, leading to inefficient memory use, especially on systems with limited RAM.

The main issue was that memory freeing caused excessive disk activity, termed the "death-rattle." This behavior stemmed from how the original malloc managed memory, especially in a virtual memory environment. To address this, the author created a modified malloc that logged memory allocation calls and identified performance issues.

The solution involved rethinking memory management. Rather than modifying free memory chunks directly, phkmalloc utilized a separate structure for tracking free memory, improving performance significantly.

The new approach made phkmalloc stricter, detecting memory misuse and issuing warnings, which helped identify bugs in programs. Over time, it gained popularity for its efficiency and error-checking capabilities, becoming a go-to choice for many projects.

However, with the rise of multi-threading and cheaper RAM, the need for phkmalloc diminished. Jason Evans later developed jemalloc, which addressed these new challenges. The author happily passed the maintenance of malloc in FreeBSD to Evans, marking the end of an era for phkmalloc.

Gaspype is a Python library designed for quick thermodynamic calculations, including equilibrium reactions. It's lightweight and uses typed Python/Numpy, featuring a large database of species. The library works with multidimensional arrays for various inputs like composition, temperature, and pressure. It has a user-friendly syntax, making it easy to use in Jupyter Notebooks, while also being efficient enough for large models. Gaspype aims to be compatible with GPU frameworks like JAX and PyTorch for better performance and integration in machine learning workflows. Users are encouraged to check out examples and share feedback or ideas. You can find the repository here.

The author argues that caching should be viewed as a simplification tool for software rather than just a way to speed it up. Traditionally, caching is seen as a method to avoid slower data retrieval from databases or storage by accessing data from faster memory. However, the author believes that this perspective is limited.

They propose that caching can serve as an abstraction, allowing developers to focus on using data efficiently without needing to micromanage how data is stored and accessed. The author questions the reliance on generic caching algorithms, suggesting that developers should have more control over data management based on their specific needs.

While acknowledging the benefits of caching, the author also notes potential issues, such as problems with operating system page caches. They emphasize that understanding caching algorithms is still important, as real-world data access is unpredictable, and heuristics are necessary. Overall, the message is that caching is a powerful abstraction that can simplify software design while improving data access.

On June 24, the European Commission introduced a Roadmap to help law enforcement in the EU access data effectively and lawfully. This initiative is part of ProtectEU, the EU's Internal Security Strategy. With many crimes leaving digital traces, law enforcement now relies heavily on electronic evidence, making it essential to update legal tools while protecting fundamental rights.

The Roadmap highlights six key areas:

1. Data Retention: By 2025, the Commission will assess the current data retention rules and improve cooperation between law enforcement and service providers.

2. Lawful Interception: By 2027, the Commission aims to enhance cross-border cooperation for data interception, including strengthening the European Investigation Order and improving information sharing among security agencies.

3. Digital Forensics: Starting in 2026, the Commission will work with Europol to analyze needs in digital forensics and develop forensic tools, making Europol a center of expertise in this field.

4. Decryption: In 2026, the Commission will present a plan to help law enforcement access encrypted data while ensuring cybersecurity and rights protection, with new decryption technologies expected by 2030.

5. Standardization: The Commission will collaborate with various stakeholders to create a standardized approach for internal security focused on digital forensics and lawful data access.

6. AI Solutions: By 2028, the Commission will encourage the use of AI tools to help law enforcement process large amounts of digital evidence more effectively.

Next, the Commission will discuss this Roadmap with Member States at the July Justice and Home Affairs Council meeting.

Summary: Logging Shell Commands in BusyBox

A new feature has been added to BusyBox that allows users to log shell commands to a remote server. Unlike Bash, which has a PROMPT_COMMAND feature for logging, BusyBox's shell (ash) does not have this capability. This is because BusyBox is designed to be lightweight and lacks some advanced features found in full shells.

The new logging feature is useful for network devices that run BusyBox, such as routers and firewalls, where command auditing is essential. Users can set three environment variables to configure the logging:

• LOG_RHOST: IP address of the remote logging server
• LOG_RPORT: TCP port for the logging server
• SESSIONID_: a unique identifier for the session

When these variables are set, the shell will send each command entered to the specified server, including the session ID for tracking.

To implement this feature, the code uses BusyBox's internal API instead of standard C library functions, ensuring compatibility. A patch has been created for BusyBox that adds this functionality, allowing for lightweight, optional command logging without interfering with users who do not need it.

In conclusion, this update enhances BusyBox for environments where command logging is critical, aligning it more closely with the needs of sysadmins managing network devices.

Canonical is optimistic about promoting Ubuntu for RISC-V devices, including tablets and single-board computers. However, with the upcoming Ubuntu 25.10 release, the support for RISC-V hardware is changing significantly.

The new release will upgrade the RISC-V application profile from RVA20 to RVA23. This change means that most current RISC-V devices will not be able to run Ubuntu 25.10 because they lack the necessary features defined in the RVA23 profile. RVA23 requires mandatory extensions for vector processing and hypervisors, which enhance performance for tasks like AI, machine learning, and cryptography.

While existing RISC-V hardware can still run earlier versions of Ubuntu (up to 24.04 LTS, which is supported until 2029), they won't be able to upgrade to 25.10 and later. This shift is not expected to have a large immediate impact because RISC-V usage is still relatively small. However, focusing on devices with more advanced RISC-V capabilities could strengthen Ubuntu's position as the leading operating system for this architecture in the future.

Currently, there are very few RISC-V devices that meet the new RVA23 standards, but this is expected to change in the next year, aligning with the anticipated release of Ubuntu 26.04 LTS.

DeepSeek, a Chinese AI startup, recently launched its new model, DeepSeek R1-0528, which is open-source and has gained popularity for its cost-effective training and strong reasoning abilities. The German company TNG Technology Consulting has adapted this model into their own version, DeepSeek-TNG R1T2 Chimera, which boasts improved efficiency and speed.

R1T2 is about 200% faster than R1-0528 and 20% faster than the previous model, R1. It generates shorter responses while maintaining high reasoning performance, using only about 40% of the output tokens compared to R1-0528. This reduction results in lower computational costs and faster response times.

TNG's model uses a technique called Assembly-of-Experts (AoE), which merges components from multiple pre-trained models to enhance efficiency without losing reasoning quality. While R1T2 is suitable for general reasoning tasks, it may not be ideal for tasks requiring function calling.

Available under an MIT License on Hugging Face, R1T2 allows for customization and is designed for enterprises looking to reduce costs and improve performance. However, companies in the EU should ensure compliance with the upcoming EU AI regulations.

Overall, R1T2 offers significant benefits for enterprises, including lower infrastructure costs and high-quality reasoning without excessive verbosity.

No summary available.

A recent study has confirmed that adult brains can indeed generate new neurons, a process known as neurogenesis. For years, scientists debated whether this occurred in humans, despite evidence in other animals. Researchers at the Karolinska Institute in Sweden used advanced techniques to study brain samples from both children and adults, uncovering neural precursor cells and immature neurons.

They found that these newly formed neurons exist in the hippocampus, a brain area important for memory. Out of 19 adult brains studied, all but one contained immature neurons, and precursor cells were present in most of them. Interestingly, two adults had significantly more of these cells, potentially linked to epilepsy in one case.

The findings suggest that neurogenesis may also occur in other parts of the adult brain. Understanding this process is vital, as disrupted neurogenesis has been associated with conditions like Alzheimer’s disease and depression. This research opens new avenues for exploring how new neurons contribute to brain function and could enhance our understanding of various neurological disorders.

No summary available.

Summary of Fullstack Architecture: Eta, HTMX, and Lit

In modern web development, developers often face a choice between complex Single-Page Applications (SPAs) and simpler Multi-Page Applications (MPAs). SPAs provide rich interactivity but can be slow due to large JavaScript files, while MPAs are faster but can feel less dynamic.

To combine the benefits of both, we use a fullstack architecture with three technologies:

1. Eta - A lightweight templating engine for fast server-side rendering, which minimizes the amount of JavaScript sent to the client, ensuring quick page loads.
2. HTMX - Enhances interactivity in our server-rendered HTML without excessive JavaScript. It allows users to perform actions like submitting forms or filtering lists dynamically, reducing the need for full-page reloads.
3. Lit - Used for creating reusable Web Components that handle specific client-side logic when necessary, providing targeted interactivity while keeping the overall application lightweight.

This architecture results in faster load times, lower JavaScript bundle sizes, and a more responsive user experience. It integrates server-side rendering with dynamic client-side behavior, all while maintaining simplicity and performance. The application can provide smooth transitions between content updates, enhancing the overall user experience.

In summary, this approach allows us to build web applications that are fast, interactive, and easy to maintain, avoiding the pitfalls of relying solely on heavy frameworks.

Summary of "Flounder Mode" by Brie Wolfson

Kevin Kelly is a unique figure known for his diverse contributions rather than a single, defining achievement. He has worked in various creative projects, including being an editor for the Whole Earth Catalog, co-founding WIRED magazine, and writing extensively on topics like art and technology. He emphasizes a "Hollywood style" of working—engaging in multiple projects driven by his interests rather than seeking corporate success or recognition.

Kelly believes in pursuing long-term thinking, as seen in his project to build a clock that will last 10,000 years. He values curiosity and passion over traditional metrics of success like money or fame. He encourages a career path that may seem "illegible" but is filled with interesting experiences.

Brie Wolfson, the author, reflects on her own career journey and how Kelly's approach challenges the conventional notion that success is tied to climbing the corporate ladder. She grapples with feelings of inadequacy compared to colleagues who chase promotions and titles, but ultimately finds inspiration in Kelly's joyful, exploratory way of working. She aspires to embrace a balance of ambition and happiness, advocating for a work culture that values enjoyment and fulfillment alongside achievement.

Wolfson concludes that pursuing interests can lead to a fulfilling career without the need for pain or extreme sacrifice, emphasizing the importance of finding joy in work.

Summary:

Kristian Köhntopp argues that chat applications like Revolt should avoid being federated and end-to-end (E2E) encrypted. He believes these features complicate the system without benefiting most users, who simply want a straightforward chat experience.

1. Federation Issues: Federated systems can lead to inconsistent features, security vulnerabilities, and message delays, resulting in a chaotic user experience with missing or out-of-order messages and spam.

2. Chat Administration: A non-federated approach allows for better moderation and user management, providing a single, clear chat history and easier spam detection.

3. Identity Management: Users should be able to connect to multiple servers but have a unified interface for chat. Federated identity systems can help facilitate this without complicating chat operations.

4. Encryption Choices: Köhntopp suggests using transport encryption (like TLS) instead of E2E encryption, as it simplifies user experience by allowing access to full chat histories and better moderation capabilities.

Conclusion: For developing a Discord alternative, avoid federation and E2E encryption. Focus on a single server model that enhances functionality and user experience while minimizing complexity and potential issues.

The EU Commission has announced plans to allow law enforcement to access encrypted data by 2030 as part of a new security strategy called ProtectEU. This initiative aims to address challenges in obtaining digital evidence for criminal investigations, particularly targeting encryption technologies like VPNs and encrypted messaging apps.

Key aspects of the plan include:

1. Data Retention: The EU will assess extending data retention requirements for service providers.
2. Lawful Interception: Efforts will be made to improve cross-border cooperation for data access.
3. Digital Forensics: Authorities will develop methods to analyze and preserve digital evidence.
4. Decryption: A roadmap for encryption technologies will be created, potentially enabling decryption solutions by 2030.
5. Standardization: The EU will work with various stakeholders to standardize approaches to security.
6. AI Solutions: The plan includes promoting AI tools for processing large amounts of data by 2028.

Privacy experts have raised concerns that these measures could weaken encryption, creating vulnerabilities that could be exploited. Critics argue that strong encryption is essential for cybersecurity and that breaking it could lead to greater risks. The EU aims to balance law enforcement needs with privacy rights, but many are skeptical of the potential implications for personal security and privacy.

The author recently built a powerful new server for their home lab using recycled parts, including an Intel i7 third generation processor. During the setup, they accidentally swapped in a desktop drive instead of the intended server drives. The desktop drive, while larger, is formatted as BTRFS, which the author cannot reformat to ZFS at the moment. They want to retrieve some old music from the server drive but are focused on accessing project data on the BTRFS drive for their YouTube channel.

The author prefers using FreeBSD instead of Linux for their servers, but the BTRFS drive poses compatibility issues since FreeBSD does not natively support it. While both Linux and FreeBSD are open-source Unix-like systems, they have diverged over the years, leading to challenges in file system compatibility.

Fortunately, the author discovered a solution using the Linux Kernel as a Library (LKL), which allows BTRFS to run on FreeBSD as a userspace file system. They outlined the steps to set it up, including installing necessary packages, loading kernel modules, and modifying configuration files to ensure proper access and functionality.

In summary, the author is navigating the complexities of file system compatibility between Linux and FreeBSD to access data on a BTRFS drive, utilizing LKL as a workaround.

An Italian court has sentenced executives from a chemical plant to prison terms of up to 17 years for polluting water with harmful "forever chemicals" (PFAS). The Miteni plant, which operated from 1968 until its closure in 2018, contaminated drinking water and soil over a large area in northern Italy. Eleven executives, including those from Mitsubishi and International Chemical Investors, were convicted, while four others were acquitted. The court's total sentence exceeded 141 years, far surpassing the prosecutors' request. Additionally, the convicted individuals and companies must pay over 6.5 million euros in damages to the Veneto region and 58 million euros to the Italian environment ministry. This case, which involved hundreds of civil plaintiffs, has been described as historic by environmental groups.

The text provides a link to a GitHub repository called "longfellow-zk," which is managed by Google. The repository likely contains code or resources related to the project. For more details, you can visit the link.

Summary of the New Cursor Pro Plan Changes

On July 4, 2025, Cursor acknowledged confusion regarding recent pricing changes for its Pro plan and apologized for the lack of clear communication. Here are the key points:

1. New Pro Plan Features:

   • Unlimited usage of certain models in Auto mode.
   • $20 of usage for frontier models each month, with the option to buy more.
   • Clarification that "unlimited usage" only applies to Auto mode, not all models.

2. Reason for Changes:

   • The pricing was adjusted from a request-based system to a monthly credit system to better reflect the varying costs of different types of requests, especially for complex tasks.

3. Refunds for Unexpected Charges:

   • Cursor will refund any unexpected charges incurred from June 16 to July 4. Users can contact support for assistance.

4. Improvements Going Forward:

   • Cursor plans to improve communication about pricing changes, enhance documentation, and provide better visibility of usage limits on the dashboard.

Overall, Cursor is committed to rebuilding trust and ensuring clearer communication in the future.

No summary available.

The article discusses the trend of "prompt engineering," which is now referred to as "context engineering" or "context prompting." It argues that this practice is ineffective and akin to pseudoscience, similar to homeopathy. Prompt engineering attempts to manipulate AI models without understanding their inner workings, such as their training data and model parameters.

Many claims made by those in the field lack solid evidence. For instance, while certain prompting techniques may work for specific cases, they often do not yield better results for broader queries. The article emphasizes that the effectiveness of these prompts can be very limited and requires significant effort to create.

Overall, it suggests that the methods being promoted are more about belief and hope than actual engineering.

A recent study has found that air pollution and other environmental factors may play a significant role in causing lung cancer in people who have never smoked. Traditionally, lung cancer was viewed as primarily affecting smokers, but cases among never-smokers are increasing, especially among women of Asian descent.

Researchers from UC San Diego and the National Cancer Institute analyzed lung tumors from 871 never-smokers across various regions and identified specific DNA mutation patterns linked to air pollution. They found that those living in more polluted areas had more mutations in their lung tumors, particularly mutations associated with cancer development.

Interestingly, the study did not find a strong link between secondhand smoke and genetic mutations in lung cancer for never-smokers, suggesting its effects may be weaker than those of air pollution. Additionally, the study identified a carcinogen from certain traditional Chinese herbal medicines that might also contribute to lung cancer risk.

The researchers plan to expand their study to investigate other potential cancer risks, including marijuana and e-cigarette use, and to gather more detailed pollution data. This research highlights the need for further exploration into environmental factors affecting lung cancer in never-smokers.

Satellite data processing algorithms developed by ICM-CSIC have helped detect a significant change in the Southern Hemisphere's ocean circulation, which may worsen climate change effects.

For the first time, scientists observed a reversal in the Southern Ocean's circulation, where surface waters are now being replaced by deep water masses that bring heat and carbon dioxide (CO₂) to the surface. This change, noted since 2016, is alarming as it can potentially double the current atmospheric CO₂ levels, contributing to the accelerated melting of sea ice and other serious climate impacts.

The breakthrough was made possible through advanced satellite observations, which overcame challenges of monitoring this remote and dynamic region. The research highlights the crucial role of the Southern Ocean in regulating the planet's climate. Due to these findings, ICM-CSIC is launching new projects to further study and monitor climate change effects.

In summary, the discovery indicates a troubling shift in ocean circulation that could have far-reaching consequences for global climate systems.

Summary:

ICEBlock is a new iPhone app that allows users to anonymously report sightings of U.S. Immigration and Customs Enforcement (ICE) agents. The app gained popularity quickly, particularly in Los Angeles, after criticism from U.S. Attorney General Pam Bondi. As a result, it became one of the top free apps in the U.S. App Store, with around 20,000 users. ICEBlock helps users share real-time information about ICE's presence within a 5-mile radius and sends alerts when ICE is nearby. Importantly, the app does not collect or store any user data.

Recent developments in artificial intelligence (AI), especially in large language models (LLMs) like OpenAI-o1 and DeepSeek-R1, have shown impressive abilities in areas such as logical reasoning and coding. Many studies are now looking at how AI can help with the innovation process in scientific research, aiming to create systems that can independently conduct research across various scientific fields. However, there hasn't been a comprehensive review of AI's role in research (AI4Research), which limits our understanding and progress in this area.

To fill this gap, we present a detailed survey of AI4Research, with the following key contributions:

1. Systematic Taxonomy: We create a classification system for five main tasks in AI4Research.
2. New Frontiers: We identify important research gaps and suggest future directions, especially in improving automated experiments and considering their societal impact.
3. Applications and Resources: We provide a collection of resources, including applications, datasets, and tools.

Our goal is to help the research community access these resources quickly and inspire new innovations in AI4Research.