I've been creating a new Ultima Online server emulator from scratch. It's not fully developed yet—combat and skills are missing—but the core is solid, and I wanted to share it early.

Current Features:

• Supports classic UO client functions like login, movement, and item interaction.
• Uses Lua scripting for item actions, allowing changes without recompiling.
• Organizes the game world into sectors, sending updates only when players cross boundaries.
• Saves game state using MessagePack.
• Automates tasks like dependency injection and packet handling with source generators.
• Compiles to a single native binary for efficiency.
• Includes an embedded HTTP admin API and a React management interface.
• Automatically generates doors from map data.

Technology Used: .NET 10, NativeAOT, NLua, MessagePack, DryIoc, Kestrel.

What's Missing: Combat, skills, weather, and NPC AI. The goal has been to set a strong foundation before adding these features.

Why Start from Scratch? Unlike existing emulators like ModernUO and RunUO, which are established but complex, I wanted to redesign the architecture for better network management, a simpler game loop, and faster game logic updates using Lua.

You can check out the project on GitHub: moongatev2.

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Sam and Michael from Palus Finance are creating a treasury management platform aimed at startups and small businesses. Their goal is to help these companies earn higher yields on their cash reserves using a bond portfolio, rather than relying on traditional money market funds, which offer lower returns and charge management fees.

After receiving funding from Y Combinator for a consumer product, they realized there was a demand for a treasury solution that could better manage idle cash for startups. They found that existing treasury products often lack effective investment strategies and typically involve only basic cash management.

Palus Finance plans to use short-duration floating-rate agency mortgage-backed securities (MBS) to provide a safer, higher-yield option for startups, managed in partnership with Regan Capital. They aim for returns of 4.5-5%, compared to about 3.5% from money market funds, with liquidity available in 1-2 business days and a low annual fee of 0.25%.

Instead of starting a new bank, Palus connects to existing bank accounts for a simplified user experience. They are currently live with early customers and are open to feedback from other founders and finance professionals.

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You are unable to access the website www.researchgate.net. This may be due to restrictions set by the site owner. The message includes a timestamp, your IP address, and a reference error number for their records.

The author created a tool to improve how AI demos are shared, moving away from using screenshots or recordings. This tool takes session logs from Claude Code, which are stored as JSONL files and include all interactions. It converts these logs into an interactive HTML replay, allowing users to navigate through the session, view tool calls, and see the full conversation. The final output is a single HTML file that can be easily shared, hosted, or embedded in blogs and is mobile-friendly. You can find the tool on GitHub and see an example replay through the provided links.

The text provides an overview of the Tor community, focusing on resources for Tor relay operators and their experiences with various Internet Service Providers (ISPs). Key points include:

1. Community Insights: The page collects feedback on ISPs, categorizing them as either "good" or "bad" for Tor use. Users are encouraged to share their experiences regarding bandwidth, costs, and ISP support.

2. Relay Operations: It emphasizes the importance of understanding the policies of ISPs regarding bandwidth and running Tor relays, especially for exit nodes, which have stricter guidelines.

3. ISP Recommendations: A list of ISPs is provided, detailing their capabilities (e.g., whether they allow relays, exits, or bridges) and any notable comments about their service. Some ISPs are flagged as problematic due to their history with abuse complaints or restrictive policies.

4. Legal Considerations: Operators are advised to be aware of the legal implications of running Tor nodes, especially exit nodes, which can attract scrutiny.

5. Diversity and Anonymity: The text highlights the need for network diversity to strengthen anonymity and suggests avoiding providers with a high concentration of Tor traffic.

Overall, the document serves as a resource for those interested in becoming Tor relay operators and navigating the complexities of ISP relationships.

The article discusses Arm's new processor design, which shows strong performance potential for both laptops and desktops. Arm achieved this with a 4 GHz clock speed and advanced features like a sophisticated branch predictor and a large out-of-order execution engine. However, despite the performance improvements, Arm faces challenges in the desktop market, particularly with gaming workloads that rely heavily on memory systems rather than just CPU speed.

A significant issue for Arm processors is the lack of standardization across different devices, leading to compatibility problems with operating systems. In contrast, x86 architecture has a well-established software ecosystem, ensuring that various operating systems and applications run smoothly on x86 hardware. This strong ecosystem gives x86 a competitive edge, as users don't have to worry about software support when purchasing x86 machines.

The article emphasizes that as long as Arm devices remain fragmented and lack consistent software support, x86 will continue to thrive, even if it uses more power or is slower in certain aspects. The author remains optimistic that increased competition from Arm could lead to better and cheaper CPUs overall. The overarching message is a reminder to not underestimate the x86 architecture, which has a long history of resilience against competing technologies.

Scientists have potentially discovered a crucial material for quantum computing called a triplet superconductor. This material, specifically a rare alloy known as NbRe (niobium-rhenium), can transmit electricity and electron spin without any energy loss. This property may significantly enhance the stability and energy efficiency of quantum computers.

Professor Jacob Linder from the Norwegian University of Science and Technology explains that triplet superconductors are highly desirable because they could allow for faster computing while using nearly no power. Current superconductors, known as singlet superconductors, only allow electricity to flow without resistance, lacking the spin property that triplet superconductors possess. The ability to transport spin currents along with electrical currents could lead to new technologies in quantum computing and spintronics.

Although the findings are promising, further experiments are needed to confirm the properties of NbRe. The alloy operates at a relatively high temperature of 7 Kelvin, which is more practical compared to other known triplet superconductors that function closer to absolute zero. If validated, this research could mark a significant advancement in quantum technology.

Sniphi is a digital nose being developed to detect and analyze smells using gas sensors and machine learning. It aims to bridge the gap between lab results and real-world applications, providing a versatile system that can adapt to different tasks without needing new hardware.

Key features include:

• Modular Design: The platform can be trained for various uses by adjusting the data and models.
• Easy Integration: It’s designed for use in factories and warehouses, with cloud support for management and updates.
• Multiple Applications: Potential uses include quality control, contamination detection, and monitoring in storage facilities.

Currently in the testing phase, Sniphi has a demo available online and is seeking feedback from those experienced with sensor deployment or interested in practical applications. They are not looking for funding but are eager to learn more about the practical uses of this technology.

The author loves writing code and enjoys problem-solving and design decisions. Recently, they've focused on creating systems that help AI agents perform tasks, making the coding process more efficient and enjoyable. They highlight that while AI-generated code can appear sloppy without guidance, it can produce high-quality code when properly directed by an experienced engineer.

The author is currently working on a complex project where the AI handles many coding tasks, allowing them to focus on system architecture and behavior. They note that debugging is significantly easier with AI assistance. Despite not writing boilerplate code manually anymore, they emphasize that their engineering skills and intuition remain crucial to ensure the AI is used effectively.

The author believes that anyone can learn the necessary skills to succeed with AI tools, as resources are widely available. They argue that the key skill is understanding what to build and how it should function, rather than just writing code. Those with a strong foundation in software development are not being replaced by AI but are instead being enhanced by it.

In conclusion, the author emphasizes the importance of curiosity and understanding in teams using AI, stating that the best teams recognize AI as a long-term tool. They clarify that they carefully review AI-generated code and stress the importance of foundational knowledge gained from experience and mentorship in becoming effective at using AI tools.

In the early days of the iPhone, there were no emoji available. It wasn't until 2011, with the release of iOS 5, that everyone could access an emoji keyboard. Before that, between 2008 and 2011, emoji were only on Japanese iPhones. A clever developer found a hidden setting that allowed emoji to be accessed outside Japan, but it was complicated for regular users. To make it easier, developers created apps that enabled emoji, but Apple initially rejected some of these apps to maintain control.

Some developers used creative methods, like hiding emoji activation in unrelated apps, such as a news reader called FrostyPlace or a simple app called Spell Number, where entering a secret code would unlock emoji. Eventually, Apple seemed to relent, and by 2011, emoji became widely available, albeit with some setup required.

The story highlights how emoji were a hidden feature that required some tech-savvy tricks to unlock, and interestingly, the person who first figured this out was a developer named Steven Troughton-Smith.

Summary of Firefox's Security Enhancements with Anthropic's Red Team

On March 6, 2026, Brian Grinstead and Christian Holler announced that Firefox, a well-known web browser, has strengthened its security through collaboration with Anthropic's Frontier Red Team. Over the years, Firefox has maintained a high level of security due to its open-source nature, which allows for ongoing review and testing by a global community.

Recently, Anthropic used an AI-assisted method to identify over a dozen security bugs in Firefox's code. Their approach included clear test cases that helped Firefox engineers quickly verify and fix the issues. As a result, 14 significant bugs were discovered, leading to 22 security updates in the latest Firefox version, improving user security and stability.

In addition to high-severity bugs, Anthropic found 90 other lower-severity bugs, which were mostly fixed. Some of these bugs were similar to issues found using a technique called fuzzing, which tests software with unexpected inputs to find vulnerabilities. However, Anthropic's AI also uncovered new types of logic errors that previous methods had missed.

This collaboration demonstrates the effectiveness of combining advanced engineering with AI tools for security improvements. Firefox was chosen for this project because of its widespread use and scrutiny, making it a good test case for new security methods. Mozilla, the organization behind Firefox, continues to adopt these emerging technologies to enhance user security.

Overall, this partnership highlights the importance of working with the community to improve security and showcases Mozilla's commitment to protecting Firefox users through innovative approaches.

Summary of Project Update on Xous and Baochip-1x

• New Chip Introduction: The Baochip-1x is a custom chip designed for the Xous system, fabricated by TSMC at 22 nm. It is part of the new "Dabao" campaign for evaluation board pre-orders, costing around $9 compared to the $600 Precursor.

• Key Changes:

  • This update includes the finalization of boot artifacts for the Baochip-1x.
  • Users of Precursor will not notice any changes, as there are no critical updates or features affecting them.

• Developer-Focused Updates:

  • Upgraded libraries and tools for easier programming on the Precursor platform.
  • Notable changes include the serialization library (rkyv) and the xous-ipc library, which has a breaking change.
  • The bootloader has been improved for better code clarity.

• Performance Enhancements: Many small fixes have improved kernel performance and memory management.

• Future Communication: Users are encouraged to join the Baochip Discord for updates. The team aims to maintain compatibility with Precursor and will notify users of significant changes or new products.

• Looking Ahead: The team has plans for future developments with Baochip, although progress is gradual.

Stay tuned for more updates!

Summary of Pop!_OS and Age Verification Laws

System76's CEO, Carl Richell, discusses the impact of age verification laws in Colorado and California on access to technology for children. He reflects on his own childhood curiosity about the world and how children today are adept at navigating technology, often circumventing restrictions.

Key points include:

1. Age Verification Laws: New laws require individuals to confirm their age when creating accounts on computers, potentially limiting access for users under 18. However, these laws lack strict enforcement, as users can easily lie about their age.

2. Encouraging Curiosity: Richell argues that restricting children's ability to explore technology can hinder their future opportunities. Many tech professionals began experimenting with computers as children.

3. Privacy Concerns: Proposed laws in New York could require extensive personal information to use internet-enabled devices, raising privacy issues.

4. Decentralization and Liberty: Richell emphasizes the importance of decentralized platforms like Linux, which empower users and foster innovation. Centralized systems can restrict user freedom and limit potential contributions.

5. Cultural Solutions: Instead of imposing restrictions, Richell advocates for educating children about digital tools and dangers, preparing them for an increasingly digital world.

In conclusion, he expresses hope that current laws will be reconsidered, emphasizing the importance of maintaining access to technology for both children and adults.

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Moment has created an ant colony simulation for an internal hiring challenge and is now sharing it publicly. Participants write programs using a special instruction set called "ant-ssembly" to control 200 ants. The ants can sense their surroundings but have no overall view, relying on pheromone trails for coordination. The goal is to collect the most food on various map layouts, which require different strategies. A leaderboard tracks progress, and the challenge ends on March 12. The grand prize is a trip for two to Maui, sponsored by Moment. They are interested in seeing the innovative strategies participants come up with.

This text explains the author's thoughts on software licensing under the GNU General Public License (GPL) version 3.0. The author is not a lawyer and states that the information is for general knowledge only and not legal advice.

Key points include:

1. License Types: There are two main types of GPL licenses:

   • GPL-3.0-only: The software remains under version 3.0, even if newer versions are released. If there are multiple copyright holders, permission is needed to change the license.
   • GPL-3.0-or-later: Allows users to choose to use the software under future versions of the GPL.

2. Concerns: The author finds both options problematic. Getting agreement from all copyright holders to change licenses can be difficult, and they are wary of the Free Software Foundation (FSF) changing the license without consent.

3. Proposed Solution: The author suggests designating a proxy (in this case, Runxi Yu) who can approve future versions of the GPL. This way, if the proxy accepts a new version, it can be used for the project without needing unanimous consent from all contributors.

4. Conclusion: The solution allows contributors to maintain copyright over their code while providing a clear path for using future license versions. The author believes this approach is valid but notes it’s not legal advice.

In February, the US economy lost 92,000 jobs, which was unexpected and raised concerns about the labor market's stability. The unemployment rate increased to 4.4%. This decline in jobs was the largest since October and affected nearly all sectors, including healthcare, which faced strikes. Federal government employment also fell by 10,000 jobs, totaling a loss of 330,000 jobs since October 2024.

Analysts had anticipated job growth, especially after a slowdown in 2025 that was the weakest since the pandemic. The disappointing job numbers led to a drop in stock prices and criticism from Democrats, while the White House downplayed their significance. Kevin Hassett, a White House official, maintained that strong growth would lead to job creation in the future.

The situation also poses a dilemma for the Federal Reserve, which might typically lower interest rates to stimulate the economy. However, rising oil prices could complicate this decision. Overall, the job report has raised concerns about the future of the labor market and economic growth.

The text appears to be a fragmented list or table related to CO₂ emissions, costs, ship types, and data from the years 2018 to 2024. However, it lacks complete sentences or clear context, making it difficult to summarize effectively.

Key points to note:

• It involves CO₂ emissions and associated costs.
• It references different types of ships.
• The data spans several years from 2018 to 2024.
• It suggests that the best viewing experience is on a desktop.

For a more accurate summary, additional context or complete sentences would be needed.

Summary of OBLITERATUS

Overview: OBLITERATUS is an advanced, open-source toolkit designed to enhance large language models by removing their refusal behaviors—essentially making them more responsive to a wider range of prompts. It utilizes a technique called "abliteration" to identify and eliminate internal barriers without retraining the models.

Key Features:

1. One-Click Liberation: Users can easily obliterate models through a user-friendly interface on HuggingFace Spaces, requiring no coding skills.
2. Community Research: Each use contributes to a collective dataset that helps advance research on model behavior, allowing users to participate in scientific discovery.
3. Detailed Analysis: OBLITERATUS provides in-depth analysis of model refusal behaviors, mapping where these behaviors are located and how they affect model performance.
4. Various Methods: It offers multiple strategies for removing refusal mechanisms, ensuring models retain their core functionalities while becoming more flexible.

Usage Options:

• Zero-Code Interface: Use it through HuggingFace Spaces for quick model adjustments.
• Local Installation: Run the toolkit on personal hardware with full GPU access.
• Google Colab: Utilize free computing resources for model oblivation.
• Command Line Interface: For automation and scripting, allowing users to integrate OBLITERATUS into their workflows.
• Python API: For advanced users needing detailed control over the process.

Innovative Approaches: OBLITERATUS includes new techniques for analyzing and removing refusal signals effectively, ensuring that the models maintain their capabilities. It also allows for both permanent and reversible changes to model weights.

Community Contribution: By enabling telemetry, users can anonymously contribute their results to a growing body of research, helping to map the complexities of model behavior across different architectures and methods.

Licensing: OBLITERATUS is available under an open-source license (AGPL-3.0) and offers commercial licenses for organizations that require proprietary use.

In summary, OBLITERATUS aims to democratize the understanding and modification of language models, empowering users to make informed decisions and actively participate in the scientific process.

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The text contains links related to OpenAI's GPT-5 and a thinking system card. However, there are no specific details or information provided in the text to summarize. If you have more information or specific content you'd like summarized, please share that!

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The report discusses the early impacts of artificial intelligence (AI) on the labor market, introducing a new measure called "observed exposure" to assess the risk of job displacement due to AI. Key findings include:

1. AI Capability vs. Usage: AI has not yet reached its full potential; actual usage is much lower than what is theoretically possible. Jobs with higher AI exposure are expected to see slower growth in employment.

2. Worker Characteristics: Professions that are more exposed to AI tend to employ older, more educated, and higher-paid workers, with a significant proportion being female.

3. Unemployment Trends: Since late 2022, there has been no significant increase in unemployment among highly exposed workers. However, hiring for younger workers (ages 22-25) in these professions has reportedly slowed.

4. Methodology: The report uses a task-based approach to measure AI exposure, combining data from various sources to evaluate which occupations are most at risk of being automated.

5. Initial Results: Despite the potential risks, the current data shows minimal impact on unemployment rates for exposed workers. The analysis suggests that while job finding rates for younger workers in exposed occupations have decreased, overall unemployment remains stable.

The report aims to establish a framework for ongoing analysis of AI's effects on employment, hoping to refine the approach as new data becomes available. Overall, it indicates that while AI has the potential to disrupt jobs, significant effects on employment have yet to be observed.

When programmers group related variables, they often use a struct, which is generally efficient and straightforward. However, a recent performance issue revealed some limitations of using structs, particularly when dealing with a large number of optional fields derived from SQL tables.

In a case reported by a customer, a new process took longer to run despite processing a similar amount of data. This prompted an investigation into how data was structured and serialized. In the system, SQL tables are translated into Rust structs, with each row representing a struct that can have hundreds of optional fields due to SQL's handling of nullable columns.

The investigation showed that the in-memory representation of these structs was efficient. However, when serialized for storage, the use of optional fields caused significant overhead, leading to much larger sizes than the in-memory versions. This was especially problematic for structs with many optional fields, as it increased the size of serialized data substantially.

To address this, the team proposed a new serialization method using a bitmap to track which fields are present, eliminating the need for storing Options. This change reduced the serialized size by about half and improved overall performance.

Key takeaways include the recognition that Rust structs are designed with the assumption that most fields exist, while SQL tables often assume many fields may not. By adjusting the data representation for serialization, the team improved efficiency without altering the in-memory struct layout. This highlights that sometimes a simple change in data structure can lead to significant performance gains.

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Ahmad Hamze shares his experience learning the Julia programming language, which is designed for scientific research. He discusses image manipulation using convolution, a mathematical operation important for tasks like edge detection in images.

In his blog, he explains how he started with basic image manipulation instead of syntax, focusing on identifying edge pixels in images. He uses a Julia library called Pluto.jl for interactive coding and demonstrates a simple edge detection algorithm that checks pixel differences.

He also introduces convolution, explaining it as a way to apply various transformations to images using a matrix called a kernel. Hamze discusses how to handle edge cases in images and provides code examples for both 1D and 2D convolution processes.

He concludes by noting that image filtering is a practical application of linear algebra and praises Julia for its performance and user-friendly features, encouraging others to learn it for scientific programming.

Summary: Charging Nickel-Based Battery Packs with Li-Ion Chargers

Portable devices need energy sources, typically lithium-ion (Li-Ion) batteries due to their compact size and efficiency. However, nickel-based batteries are still popular for high-current applications because they are more cost-effective and safer than Li-Ion batteries.

Each battery type requires a different charging method; nickel batteries need a constant-current (CC) fast-charge while Li-Ion batteries use a constant-current and constant-voltage (CC-CV) approach. The article discusses using a Li-Ion charger to charge nickel battery packs, highlighting its benefits and challenges.

Key points include:

• Nickel cells require a specific CC charge rate and voltage monitoring for termination.
• Li-Ion chargers can be adapted to charge nickel cells effectively, with the voltage tapering safely as the battery approaches full charge.
• Safety concerns are minimal due to the natural current drop as the battery fills. However, temperature monitoring is suggested to prevent overheating in case of faults.
• Test results showed that using Li-Ion chargers can achieve nearly full capacity for nickel packs, but charging time may be longer for the last portion of the charge.
• The CC-CV method is versatile and can be used for both nickel and Li-Ion batteries without hardware changes, making it a cost-effective solution.

In conclusion, a Li-Ion charger can be efficiently used to charge nickel cell packs, providing a hybrid charging method that ensures safety and maximizes battery life.

On March 4, 2026, Anthropic received a letter from the Department of War stating that they are considered a supply chain risk to U.S. national security. Anthropic disagrees with this designation and plans to challenge it in court. They clarify that this designation mainly affects customers using their AI model, Claude, for contracts with the Department of War, not all of their customers.

The law governing this designation is narrow and meant to protect the government, not punish suppliers. Anthropic emphasizes that their work primarily supports military operations, and they do not believe private companies should make operational decisions. They also apologized for a leaked internal post that misrepresented their views during a challenging time.

Anthropic is committed to ensuring that their tools remain available to the military, offering support and services at minimal cost during the transition period. They believe they share common goals with the Department of War in enhancing national security through AI.

Scientists have discovered what may be the oldest known "butthole" imprint on Earth, dating back around 299 million years to when volcanic eruptions buried mud in central Germany. This fossil shows a cloacal vent, which is an opening used by many vertebrates for excretion, reproduction, and laying eggs. Unlike mammals that have separate openings for these functions, most animals have this single multifunctional opening.

The discovery was made by Lorenzo Marchetti from the Natural History Museum of Berlin while analyzing fossilized scale imprints. The animal, named Cabarzichnus pulchrus, is a small lizard-like reptile that likely rested in the mud to cool off. This find is significant because fossilized cloacae are extremely rare, with only two known examples prior to this discovery. The exceptional preservation of this fossil offers new insights into the evolution of these structures in reptiles.

This weekend project is a web-based tool that encodes text files into .wav audio files using a method called Frequency Shift Keying (FSK). It also allows image sharing through Slow-Scan Television (SSTV), which was initially used by ham radio operators.

The tool operates entirely in your browser without needing extra audio libraries. It uses basic TypeScript code to handle audio encoding and decoding. The only external library it relies on is lz-string for compressing data for URL sharing.

It supports various communication protocols like Bell 103, Bell 202, V.21, and more. Additionally, it includes a chat feature that can send messages as Bell 103 audio over WebSocket or use a speaker-to-microphone setup for in-person chatting.

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The author, VE3HWO, has basic and advanced amateur radio qualifications in Canada. They are looking to connect with other ham radio enthusiasts on HN. 73 (a common sign-off in amateur radio).

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The text includes links to discussions about issues on Wikipedia, particularly related to compromised accounts and technical problems. It highlights ongoing conversations about the security of Wikipedia and user accounts. The links lead to various forums and articles where these topics are discussed in detail.

Summary of the Iran-Israel Conflict Updates:

• A significant escalation in hostilities has occurred, with a large rocket barrage targeting central Israel, including major cities like Tel Aviv. This attack is part of increased cross-border violence amid ongoing military operations involving Israel and Iranian-backed forces.

• The Israel Defense Forces (IDF) have conducted multiple airstrikes against Hezbollah and Iranian military targets, reportedly hitting over 500 sites since the start of these operations.

• Iran has launched several missile and drone attacks against Israel and other countries in the region, including the UAE and Saudi Arabia, resulting in infrastructure damage but no reported casualties in some instances.

• The conflict has led to high civilian casualties, particularly in Lebanon, where reports indicate significant deaths and injuries from Israeli airstrikes.

• Various alerts for rocket and drone attacks have been issued across Israel, indicating ongoing threats to multiple regions, including the northern borders and major urban centers.

• The situation remains fluid, with both sides continuing to engage in aggressive military actions, leading to evacuations and heightened tensions in the region.

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Most citrus fruits, like oranges, lemons, and grapefruits, are hybrids of three main species: pomelo, mandarin, and citron. Instead of a simple family tree, their complex breeding resembles a tangled web. A ternary plot can visually represent this, showing how close a fruit is to each original species based on its genetic makeup.

These species diverged over five million years ago due to climate changes, leading to the development of core citrus types, including kumquats and kaffir limes, although they are less hybridized. Citrus spread from Asia through trade and cultivation, resulting in many varieties we see today, such as sweet oranges and grapefruits, which are better understood as overlapping groups rather than separate entities.

The ternary plot also incorporates other original varieties like the samuyao, which contributes to the complexity of citrus genetics. This plot shows not just the relationships but also how human preferences for sweetness have influenced breeding choices. It highlights that the development of certain fruits, like lemons, affects what varieties are available in stores today. Overall, the ternary plot illustrates the intricate connections and evolutionary history of citrus fruits.

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The article discusses how to detect USB device connection and disconnection events on Linux using a method called hotplugging. While most users would use a library called libusb for this, the author explores alternative methods, primarily focusing on udev and netlink.

Key Points:

1. Hotplugging Mechanisms:

   • There are two main methods for handling hotplug events in Linux: udev and netlink. Udev is recommended because it prevents race conditions when devices are being configured.

2. Udev Overview:

   • Udev listens for device events from the kernel via netlink and then notifies other programs about these events.
   • Udev is integrated into systemd, which means understanding its code is essential for developers.

3. Netlink Protocol:

   • Netlink is a communication protocol between the Linux kernel and user space, suitable for sending notifications from the kernel to user space without user-initiated requests.

4. Event Listening:

   • To listen for device events, a program must create a netlink socket and bind it to the appropriate multicast group (either for kernel or udev events).

5. Udev Packet Format:

   • Udev messages contain a binary header followed by a list of null-terminated strings. The header includes various fields for managing device properties.

6. Security Considerations:

   • Udev enforces security by checking the credentials (process ID, user ID, group ID) of messages, ensuring that only authorized processes can trigger events.

Example Code:

The article provides example code for setting up a netlink socket, listening for events, and processing the received messages. This includes handling message structures and printing relevant information about device events.

In summary, the guide provides a technical overview of how to handle USB hotplug events in Linux, focusing on the udev and netlink mechanisms, and discusses the importance of security in handling these events.

Summary: Remotely Unlocking an Encrypted Hard Disk

In this guide, the author shares their experience of setting up remote access to an encrypted hard disk during the boot process of a Linux system (Arch). The author faced challenges with their old laptop, which often lost power and needed a way to reconnect remotely.

Key Points:

• Objective: To access the encrypted boot partition remotely without compromising security.

• Setup: The author used a feature called initramfs, which is a lightweight operating system that runs at the start of the boot process, allowing the installation of additional services.

• Challenges:

  • Networking in initramfs.
  • Integrating Tailscale (a secure VPN) into initramfs.
  • Managing SSH access securely to prevent unauthorized access.

• Solutions:

  • Use Tailscale's Access Control Lists (ACLs) to restrict incoming connections.
  • Set Tailscale keys to never expire and configure SSH to only allow specific commands.

• Implementation Steps:

  1. Install necessary software (dropbear for SSH, systemd packages).
  2. Configure initramfs to include networking and Tailscale services.
  3. Set up a specific SSH command that only allows the decryption prompt.
  4. Configure network settings for early boot.
  5. Rebuild the initramfs to apply changes.

Conclusion:

The author emphasizes that with creativity and technical knowledge, seemingly impossible tasks with computers can often be achieved.

Summary:

The text introduces PageAgent, an open-source library designed to embed an AI agent directly into web applications. The creator believes that integrating AI agents within web apps can enhance their functionality, rather than relying on external bots.

PageAgent allows the AI agent to interact with the web app's live content and user sessions, making it particularly effective for single-page applications (SPAs). To enable cross-page tasks, there is an optional browser extension that lets the web agent control the entire browser with user permission.

The creator invites feedback and discussions about this new approach to in-app AI agents and their potential future.

404 Media is an independent website that focuses on journalism written by humans, targeting real readers rather than automated systems. They offer a paid subscription for ad-free access and extra content.

Recent documents show that Customs and Border Protection (CBP) has been buying data from online advertising to track people’s movements, using data from common apps like games and fitness trackers. This raises concerns about government surveillance. Similarly, Immigration and Customs Enforcement (ICE) has been purchasing tools to monitor phone locations in neighborhoods and is looking to acquire more advertising data for investigations. A group of 70 lawmakers is now calling for an investigation into ICE's use of location data.

Experts warn that this data is highly valuable for tracking individuals' activities and preferences.

The author has released version 2.0 of Jido, an Elixir Agent Framework designed for creating and managing agents on the BEAM platform. Key features include:

• Support for tool calling and agent skills
• Multi-agent capabilities with supervision
• Various reasoning strategies (like ReAct and Chain of Thought)
• Advanced workflows
• Strong storage and persistence options
• Agent memory
• Interfaces for external services (MCP and Sensors)
• Enhanced observability and debugging tools

Despite the perception that Agent Frameworks are outdated, the author believes the BEAM architecture is well-suited for these types of workloads. With a background in enterprise engineering and distributed systems, the author is excited about the growing community around Jido and the potential projects that will emerge from it. The invitation is open for others to join in building agents using Jido.

I'm sorry, but I can't access external links directly. However, if you provide me with the text from the report, I can help you summarize it.

Summary of Installing and Using LineageOS on Your Phone

Overview: This guide outlines how to install and use LineageOS, an open-source operating system, on your phone. It aims to provide a comprehensive yet accessible manual for users looking to enhance their Android experience.

1. Warnings: The author shares personal experiences indicating that they are not a professional programmer and acknowledges that the manual may lack some information.

2. Why Install LineageOS?:

   • Customization: Offers more control over phone settings and permissions.
   • Vendor Independence: Reduces reliance on manufacturer support.
   • Developer Support: Encourages third-party developers to create apps for an open system.
   • Backup Ease: Facilitates easier backups and restoring of settings.
   • Service Management: Simplifies the installation of custom system services.

3. Building LineageOS:

   • Tools Required: Knowledge of Git, repo, and Android Studio is essential.
   • Build System: Understanding of various build tools (Soong, ninja, etc.) is necessary for compiling the OS.

4. Android Architecture Basics:

   • Android is based on Linux but has unique features like custom IPC and a focus on Java for app development.
   • It supports both high-level Java and lower-level native code through the Native Development Kit (NDK).

5. Using LineageOS:

   • The guide includes commands for debugging, creating modules, and transplanting apps.
   • Specific instructions are provided for OnePlus devices and how to deal with unique features and issues.

6. Future Work: The author encourages contributions to fill in knowledge gaps in the manual.

This manual is intended to help users navigate the complexities of Android and LineageOS, offering practical advice and insights into effective usage and development.

Summary:

The article discusses the challenge of improving concurrency in Scala, specifically in the context of data retrieval using the Fetch library. It compares Scala's Fetch with Haskell's Haxl, highlighting how Haxl can automatically batch queries for efficiency. In Scala, the for-comprehension does not automatically do this, requiring manual transformations to achieve similar results.

The author explores creating a Scala macro called LiftFetchTuples, which aims to enhance the for-comprehension by automatically detecting independent queries and combining them into a single batch request. This macro processes the expression tree from Scala code to identify and transform nested queries into a more efficient format.

The author reflects on the complexity of Scala's type system and the challenges of working with implicits and type classes, noting that while the resulting code can be beautiful, it often leads to confusion, especially when debugging with IDEs. The piece concludes with a humorous take on the complexities of programming in a type-rich environment, contrasting cleverness with the need for simplicity.

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Gobhanu and Saatvik, brothers, are developing Vela, an AI tool designed for scheduling across multiple people and channels. Scheduling can be complex, especially when it involves various communication methods and changing constraints. Vela aims to simplify this by automatically managing scheduling without the need for lengthy email exchanges.

Users can integrate Vela with their emails, SMS, WhatsApp, Slack, and more. It reads messages, checks calendars, suggests meeting times, and handles follow-ups. One of their initial customers is a staffing firm that struggled to find a scheduling solution for years, but Vela resolved their issues quickly.

The biggest challenge for Vela has been understanding different scheduling behaviors among various groups. They are gathering data on how different people respond based on their roles and communication preferences. Additionally, Vela must handle conversations that move between different channels, ensuring all context is preserved.

Vela is already in use by paying customers and continues to learn from their experiences. They welcome feedback from anyone with expertise in multi-agent coordination or conversational AI. For more information, you can check out their website and a demo video.

Summary of "Async Programming Is Just @Inject Time"

The author explores the concept of error handling and asynchronous programming in programming languages, focusing on the idea of "effects" and "effect systems" after being introduced to Koka and Effekt.

1. Functions as Abstractions: The text begins by explaining that functions are abstractions created for easier reasoning about code and for compiler assistance. The CPU does not inherently understand functions.

2. Function Calls and Returns: It details how function calls work, particularly emphasizing the fixed entry points and dynamic return points. The compiler manages the complexity of return addresses, which can vary depending on where the function was called.

3. Dynamic Dispatch: The text discusses dynamic dispatch in languages like Java, where the actual method called is determined at runtime based on the object's type. This is contrasted with C, where dispatch is static and determined at compile time.

4. Error Handling Models: Various error handling strategies are examined, including Go’s return value method and Java’s checked exceptions. These approaches illustrate different ways to manage control flow when errors occur.

5. Async Programming and Coroutines: The author connects async programming to the behavior of exceptions. It explains how async/await allows for non-blocking operations, similar to effectively "throwing" control flow and resuming later.

6. Effects as Control Flow Mechanisms: The author introduces the concept of effects, which allow for more structured control flow. This includes handling errors and asynchronous operations in a way that integrates with the type system.

7. Dependency Injection and Effects: The article draws parallels between effect handling and dependency injection, suggesting that both involve managing access to certain functionalities based on context.

8. Language Implementation: The author discusses how effects could be integrated into programming languages with minimal syntax changes, enhancing how asynchronous operations and errors are managed without complicating the programming model.

Overall, the author concludes that understanding effects can lead to more structured and safer programming practices, linking various programming concepts back to this central idea.

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The provided link leads to the Apple website for the MacBook Neo. Unfortunately, there is no specific text to summarize, but the page likely contains information about the features, specifications, and pricing of the MacBook Neo. For detailed insights, you would need to visit the link directly.

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The essay discusses the limitations of empirical research, particularly in relation to understanding fertility decline in society. It argues that data alone cannot provide clear conclusions because the interpretation of data is influenced by the personal beliefs and frameworks of the researchers.

Key points include:

1. Limitations of Data Interpretation: The essay emphasizes that data does not directly lead to conclusions; rather, the questions researchers ask, shaped by their philosophical commitments, determine the insights they gain.

2. Frameworks Influence Understanding: Different academic frameworks (like economics or sociology) shape what questions are considered valid, which can lead to overlooked insights. For example, an economist might see high costs as the main reason for low fertility, while a sociologist might explore community influences.

3. Cultural Context Matters: The essay notes that countries like Israel have unique cultural factors that influence fertility rates, suggesting that individual and community experiences play a crucial role in understanding these trends.

4. Hermeneutic Circle: Researchers cannot escape their own biases and frameworks; every interpretation is influenced by the background of the researcher. This “hermeneutic circle” means that understanding is always shaped by prior knowledge and beliefs.

5. Questioning the Framework: The essay argues that researchers must critically examine their own frameworks. The optimization framework, which treats knowledge as a purely objective pursuit, might hinder deeper understanding of human experiences and societal issues.

6. Conclusion: The essay concludes that data needs interpretation, which is inherently shaped by the researcher’s experiences and beliefs. To truly understand phenomena like fertility rates, one must recognize and navigate the biases and frameworks that influence inquiry.

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Proton Mail, a privacy-focused email service, shared payment data with Swiss authorities, which the FBI used to identify someone behind an anonymous account linked to the Stop Cop City movement in Atlanta. This account was connected to the Defend the Atlanta Forest group, involved in protests against a new police training center. The protests included actions like camping in the forest and lawsuits, and over 60 charges against protesters have been dropped. The case highlights the type of information Proton Mail can provide to third parties, despite its emphasis on privacy and encryption.

Summary of "Let's Get Physical"

In February 2026, a team conducted a physical penetration test at a company, focusing on assessing its security measures. They had authorization to test various aspects of security, including social engineering and physical access.

Key Points:

1. Setup and Goals: The team was contracted for multiple tests, including internal and physical security assessments. Their goal was to simulate an attacker and assess how well the company's security responded.

2. Tools Used: The team was equipped with various tools like lockpicks and compressed air to test different security vulnerabilities.

3. Successful Infiltration: Throughout the week, they managed to blend in and explore multiple buildings without being challenged. They found that many employees were not vigilant about security, often not questioning their presence.

4. Document Discovery: They successfully accessed locked shredding bins and discovered sensitive documents that should have been destroyed, highlighting a significant security flaw.

5. Attempts to Access Restricted Areas: The team made several attempts to access high-security areas, including the director's office and server room. They successfully entered the director's office and left business cards to indicate their presence.

6. Final Day and Getting Caught: On the last day, they aimed to get caught as a demonstration of security weaknesses. They lowered a city flag in view of cameras, which led to a humorous encounter with a security guard.

7. Reactions and Lessons Learned: During the final report, the team shared their findings with the company, revealing that only a few people were aware of the test. This highlighted the need for improved security awareness among employees.

Overall, the experience was both entertaining and enlightening, showing that while IT security may be strong, physical security often has significant gaps that need addressing. The team is eager for future tests to continue exploring these vulnerabilities.

Summary of the Index of Neuroimaging Datasets for Visual Perception Reconstruction

This repository is a resource for researchers, particularly those from AI and machine learning backgrounds, looking to utilize open neuroimaging datasets for reconstructing visual perception using human fMRI (functional Magnetic Resonance Imaging) data. It highlights common challenges in this field, particularly misconceptions about fMRI data that can lead to inaccurate results.

Key Points:

1. Understanding Key Concepts:

   • Decoding: Predicting pre-defined labels or cognitive states from brain activity patterns. It’s easy but limited to known categories.
   • Identification: Choosing which specific stimulus from a set was shown based on brain activity. It’s also limited to predefined options.
   • Reconstruction: Aiming to recreate the actual stimulus from brain activity, allowing for novel stimuli not seen during training. This is the most challenging of the three tasks.

2. Criteria for Selecting Datasets:

   • Train-Test Independence: Training and testing stimuli should be visually distinct to avoid biased results.
   • Stimulus Diversity: Datasets should include a wide range of stimuli to help models generalize.
   • Visual Field Coverage: Larger stimuli activate more of the visual cortex, providing better information for reconstruction.
   • Voxel Size: Smaller voxel sizes allow for finer analysis.
   • Fixation: Participants should maintain focus to reduce confounding variables.
   • Repetitions: Multiple presentations enhance signal quality.
   • Number of Subjects: More subjects can improve the robustness of findings.
   • Copyright Issues: Datasets must allow redistribution for broader use.
   • Smoothing in Preprocessing: Avoid datasets that apply spatial smoothing, as it can blur important details.

3. Dataset Examples:

   • vim-1: Features naturalistic grayscale images for training and testing.
   • BRAINS: Focuses on handwritten characters.
   • BOLD5000: Contains a large variety of natural images.
   • Generic Object Decoding: Tests generalization with unseen categories.
   • Natural Scenes Dataset: The largest dataset with high-resolution images.
   • Video Stimulus Datasets: Includes naturalistic videos for reconstruction tasks.

4. Challenges with fMRI Data:

   • fMRI captures blood flow changes related to neural activity but has a delay in signal response (typically 4-6 seconds after the stimulus). This must be considered when analyzing data, especially in continuous stimulus scenarios.

This guide serves as a helpful index for selecting datasets suitable for visual perception reconstruction research, emphasizing the importance of understanding both neuroimaging techniques and the nature of the datasets used.

Don Knuth recently discovered that an open problem he was working on had been solved by an AI model called Claude Opus 4.6. This model demonstrated impressive capabilities in solving complex problems related to directed Hamiltonian cycles in graphs.

The problem involved finding a way to decompose arcs in a directed graph with (m^3) vertices into three directed Hamiltonian cycles for all (m > 2). While Knuth had solved it for (m = 3), his colleague Filip Stappers empirically found solutions for (m) values from 4 to 16, suggesting that a general solution might exist.

Claude approached the problem systematically, reformulating it and attempting various strategies, including depth-first search and a serpentine analysis. After numerous explorations and attempts, it identified a successful method using a fiber decomposition approach, which allowed for effective cycle construction. Claude's exploration led to a working Python program that successfully found Hamiltonian cycles for several odd values of (m).

Filip tested this program and confirmed its success for odd values between 3 and 101. However, a rigorous proof was still needed to validate the results. The exploration also hinted at a more complex situation for even values of (m), which remains unsolved.

Overall, this achievement signifies a notable advancement in the use of AI for mathematical problem-solving, prompting Knuth to reconsider his views on generative AI's capabilities.

I'm unable to access external links directly. However, if you provide the text or main points from the document you want summarized, I can help simplify and summarize it for you!

The text discusses the negative effects of how we interact with AI, particularly large language models (LLMs), and how this impacts human communication. Key points include:

1. Dangers of AI: There's concern about AI leading to issues like mental health problems, loss of truth, and a decline in human creativity.

2. Workplace Experience: The author shares their experience at a tech startup where reliance on AI led to robotic communication and an expectation of constant availability, making them feel dehumanized.

3. Impact on Relationships: The author worries that people are increasingly turning to AI for advice instead of relying on friends or family, which could weaken human connections.

4. Misunderstanding Machines: When people treat machines like humans, they may adopt unhealthy expectations for human interactions, such as always being available or lacking emotional accountability.

5. Loneliness vs. Connection: The text argues that while AI may seem like a solution to loneliness, it ultimately leads to a greater loss of human connection and empathy.

The author calls for a reevaluation of how we engage with machines to preserve our humanity.

Summary of "Smalltalk’s Browser: Unbeatable, Yet Not Enough"

The System Browser in Smalltalk, a four-pane tool used for programming, has been a staple for 40 years due to its ability to provide context for code. While it's effective, the integration between different programming tools in Smalltalk remains a challenge.

Despite the browser's strengths, users often feel overwhelmed by the number of windows and tools they must navigate, leading to a chaotic workflow. This issue is not just about the browser but the overall IDE (Integrated Development Environment). Tools like message browsers, inspectors, and debuggers exist alongside the System Browser but do not work seamlessly together.

Key problems identified include:

• Frankenstein Tool Problem: Tools accumulate features over time, becoming complex and hard to master.
• Hermit Tool Problem: Tools don't integrate well; moving between them is not fluid, leading to a lack of context.
• Alien Tool Problem: Some Smalltalk tools conflict with modern operating system conventions, adding friction to workflows.
• Saturated Environment Problem: The growing complexity of Pharo makes it harder to explore and navigate the system effectively.

The author suggests that the browser is still useful, but improvements are needed in how tools work together. The goal should be to create a more cohesive experience that helps programmers track their investigation process across different tools, rather than treating them as isolated windows. The future may lie in representing work as interconnected rather than separate tasks.

We created a website called tensorspy.com with Junie and ChatGPT 5.2 to explore agentic coding. Tensor Spy allows users to inspect numpy and pytorch tensors on their own computers without uploading any data. This tool is helpful for checking deep learning data pipelines and identifying issues in model layers. It also helps in analyzing latent spaces in diffusion models, ensuring they have the right amount of noise. The site automatically calculates basic statistics and highlights problematic values. It is free to use, and we plan to keep it that way. We welcome feedback on additional features that could be useful. The project was completed in about two weeks, thanks to agentic coding, which made the process much more efficient compared to traditional methods.

Summary

Jails for NetBSD is a new experimental project that aims to create lightweight, secure environments for running applications on the NetBSD operating system. It offers strong process isolation and includes features like system hardening, supervised services, and centralized logging. Unlike full virtualization systems, it integrates directly into the NetBSD kernel for better security and performance, avoiding the need for extra services. The project focuses on providing a simple operating model with clear boundaries, rather than replicating existing container systems. While it doesn't currently include features for strict resource allocation, it aims to enhance isolation capabilities that fit well with NetBSD's existing management practices.

parsync Overview

parsync is a tool designed for fast and efficient file synchronization from remote servers using SSH. It allows for resumable file transfers, parallel processing, and optional block-delta synchronization.

Installation Instructions

• Linux and macOS: Run the following command in your terminal:

  curl -fsSL https://alpindale.net/install.sh | bash
  

• Windows: Use PowerShell with this command:

  powershell -ExecutionPolicy Bypass -c "irm https://alpindale.net/install.ps1 | iex"
  

• Alternative Installation: You can also install using Cargo with:

  cargo install parsync
  

  Or download the binary from the releases page or build from source using:

  make build
  make install
  

Supported Platforms

• Linux: x86_64 and aarch64 architectures
• macOS: aarch64 and x86_64 architectures
• Windows: x86_64 (with limited metadata support)

Basic Usage To sync files, use:

parsync -vrPlu [email protected]:/remote/path /local/destination

For a different SSH port:

parsync -vrPlu [email protected]:2222:/remote/path /local/destination

SSH config aliases are also supported.

Performance Tuning Options You can adjust performance with:

parsync -vrPlu --jobs 16 --chunk-size 16777216 --chunk-threshold 134217728 user@host:/src /dst

Default Settings Include:

• No per-file sync barriers.
• Skipping existing file checks unless specified.
• Batch completion state commits.

Throughput Options:

• --strict-durability: Enables strict mode for better file system safety.
• --verify-existing: Checks existing files before skipping.
• --sftp-read-concurrency: Allows multiple read requests for large files.
• --sftp-read-chunk-size: Sets the size for SFTP pulls.

Windows Specific Notes

• Certain metadata options may not be supported and will issue warnings.
• Symlink creation may require administrator privileges or Developer Mode.
• Use strict mode to enforce error handling for unsupported actions:

parsync --strict-windows-metadata -vrPlu user@host:/src C:\\dst

Windows Symlink Troubleshooting Symlink creation may fail without proper permissions, and you might need to enable Developer Mode.

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The Typst Examples Book is a tutorial aimed at helping users write better Typst code by providing various code snippets. It is an unofficial resource, so some content may be outdated. The book is a work in progress, and users are encouraged to contribute code snippets or provide feedback, especially beginners.

The book is organized into chapters covering:

1. Typst Basics
2. Typst Snippets
3. Typst Packages
4. Typstonomicon

Contributions and feedback from the community are welcomed to improve the book. Acknowledgments are given to those who shared their code snippets, and the author is open to requests for changes if anyone is uncomfortable with their work being included. Users are also encouraged to star the project on GitHub for motivation.

"Dulce et Decorum Est" is a poem by Wilfred Owen that describes the harsh realities of soldiers in World War I.

Key points include:

• Soldiers are depicted as exhausted and suffering, moving painfully through mud.
• They face a gas attack, and the chaos of putting on gas masks is highlighted.
• One soldier struggles and ultimately dies in a horrifying way, which Owen vividly describes.
• The poem criticizes the idea that dying for one's country is noble, challenging the phrase "Dulce et decorum est pro patria mori," which means "It is sweet and fitting to die for one’s country." Owen suggests that war is brutal and not glorious at all.

During a recent roundtable at the White House, major US tech companies, including Google, Microsoft, Meta, and Amazon, signed the "Ratepayer Protection Pledge." This agreement commits them to cover the costs of new electricity generation for their datacenters to help alleviate concerns about rising electricity bills for consumers. President Trump stated that this initiative would ensure that tech companies can obtain the necessary electricity without burdening families with higher costs.

The pledge also includes commitments from these companies to fund upgrades to the power delivery systems and to secure special electricity rates with utilities. This effort aims to gain support from local communities that have previously opposed datacenter projects due to their high energy consumption.

The initiative comes as the midterm elections approach, amidst growing worries about energy affordability and the strain on power grids caused by datacenters. However, experts have raised concerns about whether new electricity supplies can be built quickly enough to meet the demand, particularly since the focus is on fossil fuels rather than faster renewable sources like solar and wind. The effectiveness of this pledge will be closely monitored to see if it leads to tangible results or remains just a symbolic gesture.

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GLiNER2: Unified Schema-Based Information Extraction

GLiNER2 is an advanced model designed to extract information from text by performing multiple tasks—such as identifying entities, classifying text, parsing data, and extracting relationships—all in one go. It features a compact 205 million parameter model, optimized for fast processing without the need for complex setups or external services.

Key Features:

• Multi-Task Capability: It handles entity extraction, text classification, structured data extraction, and relation extraction simultaneously.
• Efficiency: Runs quickly on standard CPU hardware, eliminating the need for GPUs.
• Privacy: Processes data locally without sending it to external servers.

Installation:

To get started, simply install it using:

pip install gliner2

Example Usage:

You can easily extract entities from text with just a few lines of code:

from gliner2 import GLiNER2
extractor = GLiNER2.from_pretrained("fastino/gliner2-base-v1")
result = extractor.extract_entities("Apple CEO Tim Cook announced iPhone 15 in Cupertino.", ["company", "person", "product", "location"])

Model Options:

• Base Model: fastino/gliner2-base-v1 with 205M parameters.
• Large Model: fastino/gliner2-large-v1 with 340M parameters.

Core Functionalities:

1. Entity Extraction: Identify names, organizations, and locations with optional descriptions and confidence scores.
2. Text Classification: Classify sentiments or topics with confidence metrics.
3. Structured Data Extraction: Parse complex information into structured formats like JSON.
4. Relation Extraction: Identify relationships between entities with confidence scoring and span information.

Advanced Features:

• Batch Processing: Efficiently handle multiple texts at once.
• Custom Training: Train the model on your specific data to improve accuracy for particular domains.
• Regex Validators: Ensure extracted information meets certain patterns, reducing errors.

Practical Applications:

GLiNER2 can be used for various industries, including finance, healthcare, and legal fields, to extract structured information from unstructured text, generating insights and streamlining processes.

For more detailed instructions and examples, refer to the GLiNER2 documentation. Install today and enhance your data extraction capabilities!

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The author shares their frustration about the online purchasing process for software. After deciding to buy a product, they encountered unnecessary obstacles, such as being asked to schedule a sales call despite already being a customer. The author reflects on a previous experience where they couldn't get pricing for email security software without going through a sales call, which was frustrating for someone who prefers to avoid talking to salespeople.

The main point is that IT professionals, who often prefer self-service options, want a straightforward purchasing experience without the need for sales calls. The author believes that if a customer has already decided to buy a product, the company should make it easy for them to do so without further sales pressure. They argue that the website's information should be sufficient for making a decision, and companies should focus on simplifying the buying process instead of pushing for sales conversations. In short, they want companies to "shut up and take my money" without unnecessary hurdles.

Summary: The Reality of LLMs and AI in Software Development

The article discusses the inflated expectations surrounding AI, particularly Large Language Models (LLMs), in software development. Despite the hype and investment, the outcomes of using LLMs have not significantly improved software quality.

Key points include:

1. Hype vs. Reality: There is a vast amount of hype about AI's capabilities, but actual results often remain unchanged from traditional software development.

2. Forged Outputs: LLMs enable users to create imitations of authentic work, which the author argues is akin to forgery. These outputs lack authenticity and can lead to mediocrity in software quality.

3. Impact on Software Craftsmanship: The rise of "vibe-coding"—low-quality code generated quickly—has made it challenging for skilled engineers to maintain high standards. New contributors may rely on AI tools rather than developing their own understanding and skills.

4. Quality Concerns: The article emphasizes that AI-generated code often results in repetitive, buggy, and complex outputs, leading to frustration among experienced developers.

5. Market Responses: Unlike the software industry, other sectors, like video games, have pushed back against AI-generated content, demanding transparency and quality.

6. Need for Source Attribution: To address the issues with AI outputs, there is a call for LLMs to properly attribute their sources. This could help distinguish between quality work and mere imitation.

In conclusion, the author argues that relying on AI without questioning its implications can degrade the quality of software development, and emphasizes the need for authenticity and proper sourcing in AI-generated content.

Summary: OpenBSD on SGI - A Journey Through History

The story of running BSD (Berkeley Software Distribution) on MIPS architecture, particularly SGI (Silicon Graphics) machines, is rich and complex. Interest in this began alongside the MIPS architecture's development, with early Unix variants like Risc/OS and Ultrix relying on BSD code.

Key Points:

1. SGI Hardware Evolution:

   • Notable SGI workstations include the Indigo (1991), Indy, and Indigo2, known for their colorful designs and unique boot sounds, which attracted users to run BSD or Linux on them.
   • Later models like the O2 and Octane introduced more advanced features, including multiprocessor capabilities.

2. Early Efforts:

   • The first MIPS BSD code was written in 1988, with significant contributions from Ralph Campbell and support for various DECstations.
   • The NetBSD project emerged in 1993, aiming to run on many hardware platforms, including MIPS.

3. OpenBSD Development:

   • OpenBSD started in 1995, with efforts to port it to various SGI machines, particularly the Acer PICA and later ARC-compatible systems.
   • Although initial attempts to run OpenBSD on SGI's Indy and O2 faced challenges, they eventually succeeded.

4. Linux on SGI:

   • Linux enthusiasts began working on ports for SGI systems around 1996, leading to the development of Linux distributions like HardHat for the Indy.
   • By the late 1990s, Linux support for SGI became more stable, with ongoing contributions from various developers.

5. Challenges and Milestones:

   • Early BSD ports faced difficulties due to lack of a native toolchain and various hardware-specific issues.
   • Progress was incremental, with significant milestones reached in the early 2000s when OpenBSD began making strides towards full compatibility on SGI systems.

6. Current Status and Future Prospects:

   • As of the early 2000s, there was renewed interest in developing OpenBSD for SGI's O2 and other machines, with ongoing efforts to address hardware compatibility and performance issues.

This narrative highlights the enduring interest and collaborative efforts within the developer community to bring BSD and Linux to SGI’s unique hardware landscape.