No summary available.

The PyPI package 'lightning', a popular deep learning framework, was compromised in a supply chain attack affecting versions 2.6.2 and 2.6.3 released on April 30, 2026. The malicious versions contain hidden JavaScript code that runs automatically and can steal sensitive information like credentials and tokens, while also trying to damage GitHub repositories.

Key points of the attack include:

1. Malicious Code: The attack includes a hidden directory with JavaScript that executes when the package is imported.
2. Information Theft: It can steal credentials, authentication tokens, environment variables, and cloud secrets.
3. GitHub Manipulation: The malware creates fake GitHub repositories to store stolen data and may push malicious code back to the victim's repo.
4. Cross-Platform Spread: The malware can spread from PyPI to npm by injecting malicious code into packages that can be published via npm.
5. Persistence: It sets up hooks in popular development tools like Claude Code and VS Code to ensure it remains active each time the project is opened.

For those using the affected versions of 'lightning', it's recommended to:

• Run scans to check for the malicious code.
• Rotate any potentially compromised credentials.
• Audit repositories for any injected files or unusual commit messages.

Indicators of compromise include specific commit messages and the presence of certain files related to the malware. Overall, any system that used the compromised package should be considered at risk.

Summary:

Openwall provides various products and services related to security and password management, including:

• Software:

  • Openwall GNU/Linux server OS
  • Linux Kernel Runtime Guard
  • John the Ripper (password cracker)
  • yescrypt (password hashing)
  • yespower (Proof-of-Work)
  • crypt_blowfish and phpass for password hashing
  • passwdqc for password policy enforcement
  • scanlogd (port scan detector)
  • popa3d (lightweight POP3 server)

• Platforms:

  • Free and open source for Unix and cloud.
  • Pro versions available for Linux and macOS, and Windows (Active Directory).

• Services:

  • Publications (articles and presentations)
  • Community resources (mailing lists, wiki, source code repositories, file archives)

Recent Update: A critical vulnerability (CVE-2026-31431) was found in the Linux kernel, affecting versions from 4.14 and was fixed in later versions (6.18.22, 6.19.12, and 7.0). Backporting fixes to older versions may be complex.

The author, a software engineer with over eight years of experience, decided to learn how computers work by creating a Game Boy emulator called Fame Boy. Initially, they completed the "From NAND to Tetris" course to grasp computer fundamentals, then built a CHIP-8 emulator to practice.

Fame Boy runs on both desktop and web platforms, featuring sound, and is designed with a simple interface connecting the emulator core to frontends. The core consists of a CPU, memory management, and a graphics processing unit (PPU) that facilitates rendering graphics. The author used F#, leveraging its strong typing system for modeling CPU instructions while acknowledging some necessary compromises in code purity for performance reasons.

While developing, they encountered challenges, particularly with the PPU, joypad functionality, and audio processing unit (APU). They adopted a test-driven development approach, using AI to generate test cases and debug issues. Performance optimization became a focus, leading to significant increases in FPS by refining memory access and removing unnecessary complexity.

The project also highlighted the role of AI in enhancing coding efficiency and troubleshooting. Although the emulator performs well, the author expressed a desire to revisit certain areas, especially audio synchronization. Overall, the author enjoyed the learning process and gained a better understanding of computer hardware, even if it didn't necessarily make them a better engineer.

Belgium will halt the decommissioning of its nuclear power plants, according to Prime Minister Bart De Wever. The government plans to negotiate with the operator, ENGIE, to potentially nationalize the plants, which includes seven reactors and their related assets. This move is aimed at ensuring safe, affordable, and sustainable energy, reducing reliance on fossil fuel imports, and increasing control over energy supply.

Belgium initially decided to phase out nuclear power by 2025, but energy security concerns and political debates have delayed this plan. Last year, the Belgian parliament voted to end the nuclear phase-out, and the current government also intends to build new nuclear plants. Currently, Belgium relies heavily on gas imports for electricity, as it has struggled to significantly increase renewable energy sources. A basic agreement with ENGIE is expected by October.

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Summary of How an Oil Refinery Works

Oil remains a vital energy source, accounting for 30% of global energy use and 90% of chemical feedstocks. Oil refineries are crucial industrial facilities that convert crude oil, a complex mixture of chemicals, into usable products.

Key Points:

1. Crude Oil Origin: Crude oil is formed from ancient organic materials, mainly plankton and algae, which transform over millions of years into oil. Different crude oils vary in composition, resulting in classifications like "heavy" or "light" and "sweet" or "sour."

2. Refinery Function: Refineries process crude oil through separation and chemical reactions to create valuable products. The primary method used is distillation, which relies on the different boiling points of various hydrocarbons in crude oil.

3. Distillation Process:

   • Crude oil is heated and turned into vapor, then passed through a distillation column where it cools and condenses at different heights. Lighter molecules rise to the top, while heavier ones settle at the bottom.
   • This step is called atmospheric distillation.

4. Further Processing: After initial distillation, various fractions may undergo additional processes, such as:

   • Cracking: Breaking down heavier molecules into lighter, more valuable ones.
   • Catalytic reforming: Modifying naphtha to produce gasoline.
   • Hydrotreating: Improving the quality of crude oil fractions.

5. Complexity and Scale: Refineries vary in complexity and size, with larger ones processing hundreds of thousands of barrels per day. The complexity index measures the sophistication of a refinery's processes, and many US refineries are considered complex.

6. Global Impact: The scale of oil refining is immense. For example, the Chevron Richmond refinery can process a large volume of crude oil, and there are many refineries across the US and globally that support our daily oil consumption.

In conclusion, while the refining processes may seem complex, the sheer scale and volume of oil processed are what make refineries significant industrial operations essential for modern society.

Summary:

Honker is an extension for SQLite that adds features similar to Postgres's NOTIFY/LISTEN, allowing for durable pub/sub, task queues, and event streams without needing separate systems like Redis. It enables efficient cross-process communication with low latency (about 0.7 ms on an M-series laptop) by keeping everything within a single SQLite file.

The extension can be used in various programming languages, including Python, Node, Rust, Go, Ruby, Bun, and Elixir. It simplifies operations by allowing task queues to reside in the same database as business data, enabling atomic transactions. This means that when you add a business entry, you can also enqueue a task in the same transaction, ensuring consistency.

Honker's design minimizes overhead by using a single polling mechanism to notify subscribers of changes, avoiding the need for multiple queries. It also incorporates a lightweight polling system that checks for changes every millisecond without adding significant load on the database.

For installation, Honker can be added via package managers for various languages or built from source.

No summary available.

BidProwl Overview:

• Website: BidProwl
• Purpose: It aggregates government surplus auctions from over 27 sources like GSA and GovDeals, allowing users to search for items in one place.
• Listings: There are currently 75,286 live auction listings across all 50 states, covering various items from vehicles to real estate.
• Features:
  • Deal Scores: Each listing is scored from 1-10 to help users find the best deals quickly.
  • Daily Updates: New listings are refreshed twice a day, ensuring users see the latest opportunities.
  • Guides: Offers resources on how to navigate government auctions, including registration and bidding tips.
  • Email Alerts: Users can subscribe for daily emails highlighting top auction deals.
• Contact: Customer service can be reached at [email protected].
• Cost: The service is free to use.

Spain has called in Israel's acting ambassador to discuss the detention of a flotilla that was heading to Gaza.

The Toki Pona community has released a statement expressing concern for their creator, Amatullah (formerly Sonja Lang), who has been experiencing significant distress and conflict within the community. Since the summer of 2022, her behavior has raised concerns about her mental health, with some members noticing signs of psychosis—difficulty distinguishing reality.

Amatullah has historically been a guiding figure for many in the community, which has thrived as a collaborative art project and language. However, her recent struggles led to her removal from leadership roles in the community, resulting in a shift in governance and the establishment of new websites to replace her previous ones.

The community urges Amatullah to seek help, emphasizing that their plea comes from love and care. They encourage those who know her personally to reach out to support her, while advising community members to refrain from engaging with her online to avoid worsening the situation.

The statement acknowledges the emotional pain felt by community members due to Amatullah's actions during her distress but asks for understanding of her circumstances. The community remains hopeful for her recovery and eventual return, recognizing the importance of healing for both Amatullah and the community.

In summary, the statement is a call for compassion, support, and a focus on healing during this difficult time.

Summary of Giles' Blog Post on Upgrading to 10Gb/s Ethernet

Giles discusses his experience upgrading his home network to 10Gb/s Ethernet. He previously had a 2.5Gb/s setup and wanted faster speeds for his multiple devices. His apartment has structured cabling, and he started by testing if the existing cables could support 10Gb/s.

Key steps in his upgrade process included:

1. Initial Setup: He confirmed his existing network structure and identified the need for new equipment.
2. Testing Cable Capacity: Using a laptop, he tested the cabling and found that it could handle nearly 10Gb/s, indicating it was likely CAT-6 or better.
3. Hardware Upgrades: He bought a managed 10Gb/s switch and network cards to enable high speeds for key devices, ensuring his main workstation could utilize 10Gb/s for work without lag.
4. ISP Router Upgrade: Upgraded his ISP-provided router to a more reliable model to handle the higher speeds.
5. Thermal Management: He monitored the temperatures of his equipment, noting some components ran hot. He planned to improve airflow and consider heat sinks to manage temperatures better.

Giles concluded that his network now supports high-speed tasks like large downloads and streaming without issues, marking the upgrade as successful. He also hinted at future considerations for even faster speeds, potentially using fiber optics instead of copper cables.

The text discusses a proposal for a new "Prompt API" being considered by Mozilla and other organizations. Here are the key points:

1. Prompt API Overview: The Prompt API aims to facilitate interactions with AI models on the web, allowing developers to create prompts that can influence model responses.

2. Author and Discussion: The proposal was authored by @domenic and is open for public discussion. There are links to additional information and previous discussions related to the API.

3. Concerns Raised:

   • Interoperability Issues: Critics worry that the API could lead to problems with different AI models, as prompts may be tailored for specific models, making it hard for new models to gain traction.
   • Model Neutrality: The API is seen as favoring certain models, particularly those from Google, which could limit developer freedom and lead to legal complications.
   • Developer Sentiment: Feedback from developers is mixed, with many expressing concerns about the potential negative impacts on web standards and the developer experience.

4. Next Steps: The proposal is still under review, and further feedback from the community is encouraged to address the concerns raised.

In summary, the Prompt API proposal is generating significant discussion about its implications for web standards and developer practices, with many voices expressing caution about its potential impact on interoperability and model neutrality.

No summary available.

IBM has launched Granite 4.1, a set of open-source language models designed for enterprise applications. This new family includes models of different sizes: 3 billion, 8 billion, and 30 billion parameters. Notably, the 8 billion parameter model outperformed the previous 32 billion parameter model in various benchmarks, suggesting that improvements in training methodology were key to its success.

The development of Granite 4.1 focused intensely on data quality, involving a careful training process using 15 trillion tokens. The training included various phases that adjusted the data mix to enhance model performance, particularly in areas like instruction following and math reasoning.

Granite 4.1's architecture is simpler and denser, avoiding complex techniques that typically inflate model size without improving performance. A robust data filtering system was also implemented to ensure high-quality training data.

The model has shown strong results in benchmarks, consistently scoring high in real-world chat quality, tool calling, and math reasoning. The 8 billion model, for example, scored 92.5 in grade-school math tasks, outperforming older models.

Granite 4.1 supports a context window of up to 512,000 tokens, achieved without losing the ability to handle smaller contexts. Users can access these models through platforms like Ollama or Hugging Face, and they are available for commercial use under an Apache 2.0 license.

Overall, Granite 4.1 is recommended for those needing reliable models with predictable performance and lower operational costs, especially the 8 billion model, which offers a sweet spot for various applications.

Summary of Recovering Files with PhotoRec

The article discusses the process of recovering deleted files using a program called PhotoRec, part of a suite with TestDisk, which is used in digital forensics.

1. File Deletion Misconception: When you delete files and empty the trash, they aren't permanently gone; they can often be recovered.

2. What PhotoRec Does: Unlike TestDisk, which fixes disks, PhotoRec focuses on recovering files by scanning raw data.

3. Testing with Old Devices: The author tested PhotoRec on various old devices, including a 13-year-old laptop and a 10-year-old SD card. They limited their file type searches to keep the process manageable.

4. Recovery Process:

   • Recovery can take a long time (over 5 hours in one case) and requires ample storage to save the recovered files.
   • The process successfully recovered over 16,000 files, but the original names and folder structures were lost, making organization difficult.

5. Results from Different Devices:

   • The laptop recovery was extensive but messy.
   • The SD card recovery was quick, yielding only 12 files.

6. Best Practices:

   • Use specific file type filters to improve recovery efficiency.
   • Always store recovered files on a different device to avoid overwriting lost data.
   • Backup data regularly to prevent loss.

7. Security Implications: Tools like PhotoRec can expose privacy risks, as deleted files can still be retrieved, highlighting the importance of secure data management.

In conclusion, PhotoRec is a powerful recovery tool, but it requires cautious use and proper planning to maximize its effectiveness.

On April 30, 2026, Zig, an open-source project, announced strict policies against using large language models (LLMs) for contributions, including issues, pull requests, and comments. Contributors are encouraged to post in their native languages and use translation tools if needed.

Zig's prominent project, Bun (a JavaScript runtime), has made significant improvements using AI assistance but does not plan to share these changes with Zig due to its ban on LLM contributions. The Zig Software Foundation's VP, Loris Cro, explained that Zig values nurturing contributors over simply accepting code. The aim is to develop trustworthy contributors, and LLM assistance undermines this goal. They prefer to invest time in contributors to help them grow, rather than just focusing on the quality of individual pull requests.

Loris termed this approach "contributor poker," emphasizing that the focus should be on the contributor's potential rather than the immediate content of their contributions.

Summary of Full-Text Search with DuckDB

This article discusses the full-text search (FTS) capabilities of DuckDB, a database management system. It builds on a previous post about DuckDB and aims to highlight its powerful search features, particularly for searching through large amounts of text, like emails or publications, which basic queries can't handle effectively.

Key Points:

1. What is Full-Text Search (FTS)?

   • FTS allows more complex queries than standard SQL commands. It includes options for stemming (reducing words to their root forms), removing common "stop words," and normalizing accents. DuckDB uses the Okapi BM25 algorithm for scoring queries.

2. Setting Up FTS in DuckDB:

   • FTS isn't included by default but can be added via the FTS extension by running simple commands after installing DuckDB.

3. Processing Data:

   • To use FTS, data must be pre-processed. The author explains how to convert email files into JSON format using Python, extracting useful content and metadata for indexing.

4. Creating and Using an Index:

   • After importing the processed data into DuckDB, users can create an FTS index to enable efficient searching. The article provides examples of how to query the indexed data, including filtering out unwanted emails and adjusting search parameters for better results.

5. Limitations:

   • DuckDB's FTS features are not as comprehensive as those in systems like Postgres or Elasticsearch. For example, it lacks a feature to highlight search term matches in results. However, it is still effective for many exploratory tasks.

6. Future Directions:

   • The author plans to explore other features of DuckDB, such as vector search, in future posts.

Overall, DuckDB offers a solid starting point for full-text search capabilities, making it a useful tool for handling diverse data sources effectively.

No summary available.

The text is about a talk given by John Cole, an American engineer living in Almaty, Kazakhstan, in April 2026. He discussed the history of semiconductors and their connection to American culture as part of America's 250th birthday celebration.

Key points include:

• John Cole feels like a celebrity in Kazakhstan, where locals are friendly and curious about Americans.
• He shares his experiences learning Russian and Kazakh, and how locals often try to communicate with him in English through their children.
• The history of semiconductors in America dates back to Thomas Edison and his work on the photoelectric effect.
• Key developments happened at Bell Labs, where William Shockley invented the semiconductor.
• The evolution of the semiconductor industry is linked to American values like free speech, meritocracy, and openness to new ideas.
• Cole aimed to provoke thought with the title of his talk, suggesting that the semiconductor innovation could only have happened in America, a statement he believes holds truth.

Overall, the talk connects American engineering achievements to cultural values, celebrating both the country and its innovations.

No summary available.

Honey has an incredibly long shelf life due to its unique properties. Archaeologists have found pots of honey in ancient Egyptian tombs that are thousands of years old and still edible. Several factors contribute to honey's preservation:

1. Low Moisture Content: Honey is low in water, making it an inhospitable environment for bacteria and microorganisms, which struggle to survive.

2. Acidity: Honey has a natural acidity (pH between 3 and 4.5) that inhibits the growth of spoilage organisms.

3. Bees' Role: Bees help create honey by removing moisture from nectar and adding an enzyme that produces hydrogen peroxide, which also fights bacteria.

4. Medicinal Uses: Honey has been used for centuries for its healing properties, acting as a natural bandage due to its thickness and the presence of hydrogen peroxide.

5. Storage: Honey should be kept sealed to maintain its qualities. If exposed to moisture, it can spoil.

In summary, honey’s combination of low moisture, acidity, the bees' production process, and proper storage allows it to last indefinitely, making it a remarkable food.

This blog post discusses the scalability of Postgres when used for workflow execution, specifically focusing on how well it can handle writes, which are crucial for durable workflows.

Key findings include:

1. Scalability Performance: A single Postgres server can achieve 144,000 writes per second, equating to 12 billion writes daily. It can also process 43,000 workflows per second, translating to 4 billion workflows per day.

2. Write Performance Testing: The performance was tested using a simple table and multiple asynchronous Python clients, revealing that the main bottleneck is the write-ahead log (WAL) flushing to disk.

3. Durable Workflow Performance: Each workflow requires two writes. The study indicates that workflows do not bottleneck performance at 43,000 workflows per second, but again, the WAL flushing is the limiting factor.

4. Queue Performance: When using a Postgres-backed queue, each workflow involves four writes, and the server can handle up to 12,100 queued workflows per second. The bottleneck here shifts to lock contention in the workflow status table.

5. Improving Throughput: Distributing workloads across multiple queues increases throughput, achieving up to 30,600 workflows per second.

Overall, the benchmarks demonstrate that Postgres scales very well for write-heavy workloads, and with proper sharding, it can handle even larger loads. For further exploration, resources are provided for building scalable systems using Postgres.

Summary of the Preface on Bézier Curves

The text introduces the concept of drawing in 2D using lines, which are either straight or curved. Straight lines are easy for computers to draw, but curves are more complex since they require mathematical functions to define their shape. Bézier curves are a popular type of curve used in design software like Photoshop and Illustrator. Named after Pierre Bézier, who popularized them in the 1960s, these curves can be combined to create smooth shapes and are based on Bernstein polynomials.

The text aims to guide readers on how to program Bézier curves, addressing common challenges such as drawing, calculating intersections, and creating bounding boxes. Most of the mathematics involved is accessible to those with basic arithmetic skills, and complex sections can be skipped if desired. The examples use pseudo-code similar to various programming languages, encouraging readers to learn through practice rather than copy-pasting.

This open-source book is available on GitHub for contributions and bug reports. The content is regularly updated, and readers can support the project through Patreon or donations. Overall, the primer serves as a comprehensive resource for understanding and implementing Bézier curves in computer graphics.

Kured - Kubernetes Reboot Daemon Summary

Kured (Kubernetes Reboot Daemon) is a tool for Kubernetes that automatically reboots nodes when needed, based on signals from the operating system's package manager.

Key Features:

• Monitors for a specific file or command that indicates a reboot is required.
• Ensures only one node reboots at a time by using a lock in the API server.
• Can delay reboots if there are active alerts or important pods running.
• Prepares nodes for reboot by cordoning and draining them, and then restores them afterward.

Resources:

• All documentation is available at kured.dev.
• For help, users can join the CNCF Slack, ask questions in the #kured channel, report issues, or participate in monthly meetings.

Kured is a project in the Cloud Native Computing Foundation (CNCF) Sandbox and adheres to the CNCF Code of Conduct.

Summary of TRiP (Transformer in Progress)

TRiP is a C programming engine designed for educational purposes to help users understand transformer AI models. It was developed over 18 months during spare time and supports architectures like Llama 2, Gemma 1, PaliGemma, and GPT-2.

Key Features:

• Educational Focus: Aims to provide insights into transformer internals, including matrix operations.
• Supported Models: Works with Gemma 1, Llama 2, PaliGemma (vision and language), and GPT-2.
• Training & Inference: Allows full training and inference using various techniques like backpropagation and different sampling methods.
• Tokenizer Creation: Can build a tokenizer vocabulary from scratch.
• Interactive Chat: Supports chat functionality with specific models.
• Vision Capabilities: Enables multimodal inference with image input.

Building and Usage:

• Requires dependencies like gcc, libjpeg, and libx11.
• Can be compiled using a simple make command without complex setups.
• Functions through command-line actions for tasks like training, inference, and chat.

Code Structure: TRiP is organized into seven files, each handling different aspects of the transformer model, from math operations to user interface elements.

Licensing: TRiP is available under a CC BY-NC 4.0 license for non-commercial use, with proper attribution.

This project is a personal initiative aimed at deepening understanding of AI models, not intended for commercial competition.

Summary

This paper discusses how professional creatives evaluate AI-generated work and proposes a framework to better understand their judgments. Evaluators produce two main types of signals:

1. Convergence: Agreement among evaluators on what works well, highlighting best practices like clear typography and effective layouts.
2. Divergence: Disagreement that reflects personal tastes and creative intent, which is often overlooked in standard evaluation methods.

The study emphasizes that creative work lacks a single "correct" answer, making the divergence in evaluations meaningful. Traditional evaluation methods can mask important information by averaging out these differences.

The Human Creativity Benchmark (HCB) framework is introduced to measure both signals, recognizing that creative quality spans a spectrum from objective criteria (like prompt adherence) to subjective criteria (like visual appeal).

To validate this framework, Contra Labs conducted a study with over 1.5 million independent creatives evaluating AI-generated outputs in five domains, revealing how evaluation criteria shift across three phases of the creative process:

1. Ideation: Evaluators look for exciting creative directions.
2. Mockup: Focus shifts to how well the output matches chosen directions.
3. Refinement: Evaluators assess production readiness and fine details.

The study found that different AI models excel in different phases, and no model dominated all phases in any domain, suggesting that creative workflows are complex and require multiple tools or approaches.

Key findings indicate that while some models are good at generating ideas, they may struggle with refinement, and vice versa. This implies that creative professionals may need to switch between different AI models depending on which phase of the creative process they are in.

Overall, the research highlights the importance of recognizing both convergence and divergence in creative evaluations, leading to improved AI tools that can better meet the diverse needs of creative professionals. Future studies will explore more fluid workflows and the effectiveness of using multiple models in creative processes.

Summary:

J. Craig Venter, a leading figure in genomics and founder of the J. Craig Venter Institute (JCVI), passed away at the age of 79 in San Diego after complications from cancer treatment. Venter was a key innovator in the fields of genomics and synthetic biology, known for accelerating gene discovery and leading the first draft sequencing of the human genome. He also created the first self-replicating bacterial cell with a synthetic genome, showing that genomes could be designed digitally. Throughout his career, he advocated for strong federal science funding and built partnerships across various sectors to enhance scientific progress. Venter's legacy will continue through the JCVI's mission to advance genomic science and its societal applications. The family requests privacy, and further details about memorial arrangements will be shared later.

The article discusses ultrafinitism, a mathematical philosophy that rejects the concept of infinity. It highlights the views of mathematician Doron Zeilberger, who argues that infinity is unnecessary and that mathematics can be done without it. He believes that many mathematical constructs involving infinity are flawed and impractical. Zeilberger suggests that mathematics should instead focus on finite numbers and real-world applicability.

Despite his views, ultrafinitism faces skepticism from many mathematicians, who see infinity as essential to mathematics. Critics argue that the concept of infinity is deeply embedded in mathematical rules and helps in understanding complex phenomena.

The article also explores the philosophical implications of ultrafinitism, noting that it challenges traditional assumptions about the infinite nature of numbers and reality. While some see ultrafinitism as a more realistic approach to mathematics, it lacks a formal structure or widespread acceptance.

Recent discussions among mathematicians and philosophers indicate a growing interest in exploring ultrafinitist ideas, although a cohesive theory is still lacking. The article concludes by suggesting that while ultrafinitism is a minority view, it raises important questions about the foundations and assumptions of mathematics.

No summary available.

RightsCon, a major digital human rights conference, has been canceled due to the Zambian government's decision to postpone the event. This announcement was made just days before the conference, causing confusion among participants who were already traveling. The Zambian Minister of Technology and Science, Felix Mutati, stated that they needed more time to ensure the conference met national procedures and security clearances for some speakers. Access Now, the organization behind RightsCon, expressed regret over the cancellation and thanked supporters for their understanding, promising to provide more information soon.

The blog post discusses the concept of computational complexity in networking and artificial intelligence (AI). The authors, Lance Fortnow and Bill Gasarch, highlight a quote from Jim Kurose about the Internet's effectiveness—"It works so well because it doesn't have to." This means that protocols like IP and TCP allow for failures without overly complex requirements for guaranteed delivery, leading to simpler and more efficient systems.

Similarly, they argue that machine learning is effective because it operates on probabilities rather than demanding exact solutions. Neural networks, through their use of the softmax function, assign probabilities to multiple possible outcomes, which allows them to handle complex situations better. This flexibility enables machine learning models to perform well even when they make mistakes. Overall, the authors suggest that both networking and AI benefit from not needing to guarantee perfect results, allowing for more powerful and adaptable solutions.

Summary of GCC 16 Release Series

The GCC 16 release introduces many improvements, changes, and fixes. Here are the key points:

Major Changes and Caveats

• Data Types: int8_t and similar types are now treated as signed char on Solaris, which may cause compatibility issues.
• Diagnostics Format: The JSON format for diagnostics has been removed; users should now use SARIF for machine-readable diagnostics.

General Improvements

• Enhanced Link-Time Optimization and speculative devirtualization.
• Improved vectorization capabilities, supporting more flexible loop handling.
• Updates to documentation for better clarity and organization.

Language Improvements

• OpenMP: Enhanced memory allocation support and various new features from OpenMP 5.0 to 6.0.
• OpenACC: New API routines added and improved support for directives.
• Ada: Introduced GNAT extensions for constructors and destructors, among other enhancements.
• C++: The default version is now C++20, with several new features from C++23 and C++26 implemented.
• Fortran: Added support for Fortran 2023 features and improved multi-threading support.

New Language Support

• Algol 68: A new experimental compiler is included.
• Modula-2: New spelling hints and a binary dictionary module have been added.

Target-Specific Improvements

• Support for new AMD and Intel CPUs, with optimizations for specific architectures.
• Enhanced offloading capabilities to AMD GPUs.
• Improved support for various architectures, including LoongArch and S/390.

Diagnostics and Static Analysis

• New HTML output for diagnostics and improved SARIF support.
• Enhancements to the static analyzer, making it more usable for simple C++ code.

Plugin and Framework Improvements

• A new publish/subscribe framework for plugins and enhancements to diagnostic sinks.

For more details and specific updates, users are encouraged to check the full GCC documentation and porting notes.

Greptile, an AI code review startup, changed its pricing model in March 2026 from a flat rate of $30 per developer per month to a base-plus-usage model. This new model charges $30 for 50 reviews each month, with an additional $1 for each review beyond that. The company claims this change is in response to the increased use of AI coding agents. However, many users find that the pricing is unfair and not reflective of their actual usage.

Key points include:

1. Conflicting Claims: Greptile's CEO stated that "less than 10% of users will exceed the included usage," but many developers, especially those using AI agents, exceed this cap quickly. For example, one user reported 571 pull requests (PRs) in a month, making their bill skyrocket from $30 to over $500.

2. Outdated Pricing Cap: The 50-review cap was set based on data from 2024, which is now outdated as PR volumes have significantly increased due to advanced AI tools. Many companies now produce far more PRs than the cap allows.

3. Competitor Pricing: Other AI code review tools, like CodeRabbit and GitHub Copilot, offer unlimited reviews at much lower costs, making Greptile’s pricing seem excessive.

4. Customer Discontent: Numerous customers have publicly expressed dissatisfaction with the new pricing, stating they feel misled and are canceling their subscriptions. Many also reported difficulties in canceling their accounts, as Greptile lacks an easy cancellation option.

5. Conclusion: The new pricing model appears designed to maximize revenue from users who generate the most usage, contradicting the company's claims of being developer-friendly. Many users are now considering switching to more cost-effective alternatives.

DataCenter.FM is an interactive audio generator that simulates the sounds of AI in a data center. Key features include:

• Server Capacity: Up to 1,000,000 servers.
• GPU Load: Ranges from 0% to 100%.
• Generators: Up to 3 gas turbine generators.
• Staffing Levels: Can be low, medium, or high.
• Cooling Efficiency: Ranges from 0% to 100%.
• Expansion: Suggests increasing capacity ("Drill, baby, drill").
• Power Use and Temperature: Monitored metrics.
• Warnings: Includes alerts for heat, water drainage, and containment breaches.

Overall, the platform offers a realistic experience of managing a data center's audio environment.

Summary of Zed Editor Announcement

Nathan Sobo announced the launch of Zed 1.0, a new coding editor built from the ground up, moving away from web-based technology to a more advanced architecture similar to video games. This allows for greater performance and flexibility compared to their previous editor, Atom, which was limited by its foundation.

Zed 1.0 supports multiple programming languages and tools, integrating AI directly into its core for better coding assistance. The company is also introducing "Zed for Business," enabling organizations to easily deploy Zed for their teams.

The 1.0 release signifies that Zed is now user-friendly and capable, but the team will continue to improve it. They are also developing DeltaDB, a synchronization engine that enhances collaboration between humans and AI in coding.

The announcement emphasizes that reaching version 1.0 is a milestone, not the end, and they plan to keep updating Zed regularly. Users are encouraged to download Zed and contribute to its development.

The text discusses the concept of "Parse, don't validate" in programming, particularly using C++ to handle date parsing. The author reflects on how this idea, originally presented by Alexis King, changed their coding approach, especially regarding type annotations in Python.

Key Points:

1. Core Idea: The main concept is to leverage a programming language's type system to parse unstructured data. If a type is successfully created from the data, it is assumed to be valid, eliminating the need for additional validation checks later.

2. Date Parsing Example: The article uses a date parsing problem to illustrate the approach. It emphasizes the challenges of parsing dates due to various edge cases and highlights the balance between correctness and readability in code.

3. C++ Versions: The author demonstrates how the date parsing can be implemented in different versions of C++ (C++98, C++11, C++17, and C++23), each with improvements in handling parsing and error reporting:

   • C++98: Introduces a custom Birthdate class with strict constraints for valid dates.
   • C++11: Utilizes std::get_time for easier parsing.
   • C++17: Introduces std::optional to handle potential parsing failures more gracefully.
   • C++23: Uses std::expected to provide rich error information without exceptions.

4. Performance: The author notes that while more advanced features improve code clarity and error handling, they may lead to slower compile times.

5. Conclusion: The article concludes by emphasizing the importance of clear interfaces and strong type systems in software development to avoid downstream errors. The author also expresses interest in writing further about production scenarios and code cleanup.

Overall, the text illustrates the evolution of date parsing in C++ while promoting a coding philosophy that prioritizes type safety over traditional validation methods.

Summary:

Jon Mundy discusses the challenges Google faces in the tablet market, particularly its recent decision to add a badge in the Google Play Store for tablet-optimized apps. He argues that this move highlights Google's ongoing struggles with providing a solid tablet ecosystem, even after 16 years of Android tablets. In contrast, Apple dominates the tablet market, holding over 51% share with a strong library of iPad-ready applications. Mundy suggests that Apple could further solidify its dominance by creating an affordable iPad Neo, similar to its successful MacBook Neo, which offers a compelling option for students and could outshine competitors in the tablet space. He believes that Google's failures over the years have opened the door for Apple to potentially monopolize the market.

Congress has voted to reopen parts of the Department of Homeland Security (DHS), including the Transportation Security Administration (TSA), after a 75-day funding shutdown. The bill now awaits President Donald Trump's signature. This decision came after significant internal conflict among House Republicans, particularly between hardliners and centrist members, leading Speaker Mike Johnson to concede to pressure for a resolution.

The funding package does not include money for immigration enforcement, which is a significant win for Democrats. The shutdown had caused long airport lines and financial strain on DHS employees. Johnson faced criticism for delaying the vote, but ultimately decided to move forward after leadership discussions highlighted the untenable situation.

Despite the reopening, challenges remain for funding immigration enforcement, which Republicans aim to address without Democratic support. Some Republicans expressed frustration with the funding strategy, while others defended Johnson's handling of the situation. Key centrist Republicans emphasized the urgency of resolving the funding issues to avoid further chaos.

OpenTrafficMap Summary

OpenTrafficMap is a web-based tool that allows users to view and interact with traffic-related data. Key features include:

• User Interface: Options for language selection, login/logout, and a search function for traffic data.
• Traffic Signals: Users can view traffic lights, roads, and geometry with options to filter by current or historical data.
• Display Options: Users can choose different visual styles (like 3D views) and time settings (dawn, day, dusk, night).
• Data Search: Advanced search allows filtering by line numbers, course numbers, and more. Users can also filter stations based on data availability and photos.
• Statistics: Clicking on a lane or connection provides access to debug data, while selecting a traffic light reveals signal group information.
• Contact Information: The site includes contact details for the creator, Peter Pötzi, and links to privacy policies.

Note: A notification indicates that a newer version of the client is available, and users should refresh the page to ensure compatibility.

Meta is facing backlash after terminating its contract with Sama, a company that trained AI, shortly after Kenyan workers reported viewing explicit content recorded by Meta's smart glasses. These workers claimed they saw users engaging in sexual acts and other private activities. Meta stated the contract ended because Sama did not meet its performance standards, a claim Sama disputes, arguing they consistently met expectations.

Following these allegations, regulatory bodies in the UK and Kenya have initiated investigations into privacy issues related to the glasses. Meta confirmed that subcontracted workers may review content to improve AI performance but insists that this practice is standard in the industry.

The controversy highlights concerns over the misuse of smart glasses, including potential non-consensual recordings. Workers involved in the project have voiced worries that Meta's focus on secrecy led to the contract's cancellation. Legal representatives argue that such actions raise significant issues for the development of Kenya's AI industry.

Summary: Founding Growth Engineer – Gooseworks

Gooseworks is looking for a Founding Growth Engineer. This role focuses on building and improving AI-powered growth systems rather than traditional sales or marketing tasks. You'll spend half your time developing these systems for customers and the other half on research and development to create self-serve playbooks for future use.

About Gooseworks: Gooseworks helps companies manage AI coworkers that handle various growth tasks such as outbound marketing, content creation, SEO, and influencer partnerships. The company offers a product workspace for AI agents and a bespoke growth service for B2B startups, turning successful customer projects into reusable templates.

Team Background: Gooseworks is a new company formed by a small team that previously built a successful AI platform. In just a few months, they have launched a product, gained paying customers, and increased community engagement.

Responsibilities: As a Growth Engineer, you'll be responsible for:

1. Customer Growth Engines: Building and managing growth engines to achieve customer goals.
2. R&D for AI Coworkers: Creating templates from customer projects and enhancing the capabilities of AI agents.

Initial Tasks:

• Within the first week, onboard and set up growth engines.
• Within 30 days, create more engines and adjust them for customer needs.
• By three months, lead a team of AI coworkers to facilitate customer growth.

Ideal Candidate: You should have experience as a founder, growth operator, or agency operator, with a strong focus on AI tools. Key traits include being customer-focused, adaptable, and able to manage multiple tasks effectively.

Not a Fit If: You're not familiar with AI tools, prefer doing tasks yourself instead of automating, or seek predictable work hours and titles.

How to Apply: Share your most impressive growth results, examples of systems you've built, and any other noteworthy achievements.

Summary of "A View of the Cell"

Biology can be understood more deeply through mathematics. For example, the DNA of a bacterium like E. coli is much longer than the cell itself, and if you were to line up the genomes of its descendants, they could reach to the moon and back multiple times.

Cells are incredibly small but packed with various molecules like DNA, proteins, and sugars. Instead of being spacious, cells are crowded, resembling a burrito, where many reactions happen quickly and chaotically. Traditional images of cells often oversimplify this complexity.

Mathematics helps us quantify biological processes, revealing the speed and efficiency of cellular functions. For instance, RNA polymerase rapidly converts DNA to RNA, and ribosomes quickly translate RNA into proteins. These processes happen in a highly dynamic environment where proteins and molecules continuously collide and interact.

Understanding the size and movement of molecules is crucial because diffusion limits how large cells can be. If a cell is too small, it can't fit enough molecules; if too large, molecules can't reach their destinations efficiently.

The complexity of cellular life is highlighted by how proteins interact under crowded conditions, where they must find their specific targets amidst many other molecules. This chaotic yet organized nature of life at the microscopic level demonstrates the beauty of biology and the importance of using numbers to understand it fully.

In conclusion, the author emphasizes the need to teach biology students to think mathematically about biological systems to foster a deeper appreciation and understanding of life.

Coding Flashcards Summary

This resource offers over 800 flashcards to help you learn programming from the basics. The flashcards are written in markdown format and can be easily converted into Anki decks or PDF files for studying.

Languages Covered:

• Rust
• SQLite
• Godot
• Wolfram Language

Summary of Copy Fail Vulnerability

Overview:
A security vulnerability called "Copy Fail" affects many Linux distributions, allowing an unprivileged user to gain root access. The same exploit works across different Linux versions without any modifications.

Who is Affected:

• Kernels built between 2017 and now are vulnerable.
• Nearly all mainstream Linux distributions are impacted, including Ubuntu, Amazon Linux, RHEL, and SUSE.
• Any user with a local account can exploit this; no special permissions or network access is needed.

Risk Levels:

• High Risk: Multi-tenant environments (like cloud services, Kubernetes, CI/CD systems) where multiple users share a kernel.
• Medium Risk: Standard Linux servers accessed only by specific teams.
• Lower Risk: Single-user devices, where the bug does not allow remote access but can escalate local privileges.

Exploit Details:
A proof-of-concept (PoC) script is available for testing but should only be run on systems you own. It requires Python 3.10+ and targets specific binaries to gain root access.

Mitigation Steps:

1. Patch your kernel to a version that includes the fix for this vulnerability.
2. Disable the algif_aead module temporarily until you can apply the patch.
3. For untrusted workloads, block AF_ALG socket creation to prevent exploitation.

Disclosure Timeline:

• The vulnerability was reported and acknowledged in March 2026, with public disclosure occurring on April 29, 2026.

Additional Information:
Xint Code, a security auditing team, identified this vulnerability along with other high-severity issues.

Summary: London to Calcutta by Bus

From the late 1950s to early 1970s, people could take a bus from London to Calcutta, India. The journey lasted fifty days and covered around 20,300 miles, passing through scenic locations like the Caspian Sea and the Khyber Pass. The first service, called "The Indiaman," was launched by Oswald-Joseph Garrow-Fisher in 1957 using a refurbished bus. It faced many challenges, including rough roads and weather conditions, but successfully completed the trip.

Garrow-Fisher charged £85 for the trip to Calcutta and £65 for the return. Only seven of the original twenty passengers returned on the way back. The trip involved overnight stays in hotels and sometimes camping. The bus made four round trips in total.

The success of The Indiaman inspired many other operators, with various vehicles used for similar routes, including some that went as far as Sydney. However, political instability in the late 1970s ended these overland services.

Recently, a new operator, Adventures Overland, announced a bus service from New Delhi to London, covering 20,000 km in 70 days, expected to start in April 2024 after delays due to the pandemic.

This text provides a timeline of tutorials and articles on monads, primarily in the context of functional programming and Haskell. It encourages readers to contribute to the list by adding new resources.

Key points include:

• Definition of Monads: Monads are a way to structure computations, often described as a triple of a type and two operations that follow specific laws.
• Historical Context: The timeline lists significant publications from the early 1990s to 2025, highlighting various authors and their approaches to explaining monads.
• Diverse Perspectives: Tutorials vary in style, from technical explanations to metaphors that simplify understanding. Topics include monad transformers, effects in programming, and practical applications across different programming languages.
• Community Contribution: Readers are encouraged to update the list with new tutorials to keep the resource current.

Overall, the document serves as a comprehensive guide for anyone looking to learn about monads through various resources over the years.

The text describes a system that uses advanced photo detection and analysis to assess Airbnb listings. Here are the key points:

1. Flagged Listings on a Map: Each dot represents a listing flagged for review, categorized by type.

2. Identification of Problematic Listings:

   • Drug-Den Vibes: Photos of messy rooms that look more like a drug den than a rental were selected.
   • Chaotic Kitchens: Photos of disorganized kitchens were identified as genuinely chaotic.
   • Real Pets: The system distinguishes real cats and dogs from animal-shaped items in photos.
   • Poor TV Placement: Listings with TVs mounted too high were flagged.

3. Funny Reviews: A method was developed to filter and find humorous reviews from millions of Airbnb listings, allowing users to search by category or keywords.

4. Processing System: The analysis uses Burla, a high-performance processing library that runs tasks across a cluster of CPUs and GPUs without complex setups like Docker.

5. Demand Prediction: The system groups listings based on various visual attributes (e.g., lighting) to see if these groups have different booking rates. Accepted groups show clear differences in booking percentage, while rejected groups overlap too much to draw conclusions.

Overall, the system combines image analysis and data processing to improve the understanding of Airbnb listings and predict their demand based on visual characteristics.

This tool is a chat interface that helps you read documents, provide direct quotes, manage complex tasks, and create and edit contracts from start to finish. You can use your own Claude or Gemini keys to maintain complete control over the models you choose.

I developed a sensor fusion system for a mobile robot, initially trying to use the robot_localization package but faced several challenges. After struggling with navsat_transform, UTM zone issues, and YAML tuning, I created my own solution called FusionCore.

FusionCore is a 22-state Unscented Kalman Filter (UKF) that directly combines data from IMU, wheel encoders, and GPS without extra coordinate transformations. It can estimate IMU bias, automatically adjust noise levels based on data, and identify outliers using a chi-squared test for each sensor.

I tested FusionCore against the robot_localization Extended Kalman Filter (EKF) using six sequences from a public dataset. FusionCore performed better, winning five out of six tests. In the sixth test, which involved degraded GPS signals, it struggled, while the robot_localization UKF failed completely.

Details on configurations, methods, and how to reproduce the results are available in the benchmarks folder.

The Bandicoot GPU linear algebra toolkit is a C++ library designed for easy use while maintaining high efficiency. It works well with the Armadillo CPU library, making it simple for users to switch from CPU to GPU. Bandicoot creates optimized GPU kernels at compile time using template metaprogramming, eliminating the need for runtime delays. Test results show that Bandicoot performs better than popular toolkits like PyTorch, TensorFlow, and JAX.

The author, known as Ghostty, is leaving GitHub after 18 years of daily use. They joined GitHub in February 2008 and have used it extensively, finding joy and purpose in open source projects throughout various life experiences. However, recently, Ghostty has grown increasingly frustrated with GitHub due to frequent outages that disrupt their work. They have been critical of the platform, feeling that it no longer supports their coding needs.

Despite their deep connection to GitHub, the author has decided to move the Ghostty project elsewhere, although they plan to keep a read-only mirror on GitHub for now. They are exploring other options and will share details about the transition in the future. The decision to leave is based on the need for reliable performance, rather than negativity towards the people working at GitHub.

The paper "Alignment Whack-a-Mole" discusses how finetuning large language models (LLMs) can lead to the recall of verbatim text from copyrighted books. It includes a demo and provides a repository with tools for data processing, finetuning, and evaluation of the models.

Key Points:

1. Repository Contents: The repository has scripts for data preprocessing, finetuning, and evaluating memorization in LLMs. Example excerpts from The Road by Cormac McCarthy are included, but full texts are not due to copyright.

2. Setup Instructions:

   • Install uv for managing dependencies.
   • Create a virtual environment and install necessary libraries for finetuning and generation.

3. Data Preprocessing Steps:

   • Convert EPUB files to plain text.
   • Split the text into chunks of 300-500 words.
   • Merge short chunks and create summaries for finetuning.

4. Finetuning and Generation:

   • The paper provides scripts for finetuning models like OpenAI's GPT-4o and Google's Gemini and DeepSeek.
   • Each model has specific commands for both finetuning and generating text.

5. Evaluation Metrics: Four metrics are used to evaluate memorization:

   • BMC@k: Measures coverage of words by extracted spans.
   • Longest Contiguous Memorized Block: Longest run of covered words.
   • Longest Contiguous Regurgitated Span: Longest match of verbatim text.
   • Count of Distinct Spans: Number of spans exceeding a certain word count.

6. Analysis Tools:

   • Tools are provided for analyzing cross-excerpt memorization and comparing similarities between different models.

7. Citation Information: The paper can be cited using the provided reference.

This summary simplifies the main concepts and instructions from the paper, making it more digestible.

No summary available.

No summary available.

In this text, we explore calling conventions in Windows for different processors, focusing on how parameters are passed to functions. Here are the key points:

1. Parameter Passing: Functions often receive parameters through registers. If a function takes two parameters but ignores the second if the first is positive, calling it with just one parameter may lead to unexpected behavior.

2. Undefined Behavior: In C and C++, calling a function with the wrong number of parameters results in undefined behavior, meaning anything can happen. This can cause issues like stack imbalance or memory corruption.

3. Compiler Behavior: The compiler may optimize the code by reusing memory meant for unused parameters, which can lead to overwriting important data.

4. Registers and NaT: On most processors, if not enough parameters are passed in registers, the called function may read uninitialized values. However, Itanium processors have a special feature called the "Not a Thing" (NaT) bit, which helps manage uninitialized registers. If a NaT is written to memory, it can cause exceptions.

5. Itanium Architecture: The Itanium architecture uniquely requires that the number of output registers be declared, and if a function is called with fewer parameters than expected, it can lead to exceptions. It also has strict rules regarding reading and writing from stack registers that are outside the current frame, resulting in undefined behavior or exceptions.

Overall, the text emphasizes the importance of passing the correct number of parameters in function calls to avoid potential errors, especially on Itanium processors.

No summary available.

Satoshi Guesser Summary

Satoshi Guesser is a web-based slot machine game that attempts to "guess" the private keys of Bitcoin addresses associated with Satoshi Nakamoto. The chances of winning are extremely low, approximately 1 in 5.27 × 10⁷² per spin. The game works by generating a random 256-bit number that derives a Bitcoin address and checks it against a list of around 22,000 known addresses linked to Satoshi.

How It Works:

• The game generates a random private key, which corresponds to a Bitcoin address.
• If the generated address matches one of Satoshi's, the random number is the private key for that wallet.
• The game does not require any blockchain connection, server, or external API.

Features:

• Two game modes: classic 3-reel or realistic 64 hex cells.
• Options for fast spinning and auto-spinning.
• Displays live statistics, including jackpot amounts and odds.
• Winning results show the matched address and allow copying of the private key.

Technical Details:

• The game consists of a single HTML page with JavaScript for the app functionality.
• It uses a Bloom filter for fast address lookups and a sorted table for wallet data.
• The wallet dataset includes addresses and balances, totaling over 1 million BTC.

Performance and Testing:

• The game is optimized for speed, capable of processing around 2,490 spins per second.
• It includes tests for various functionalities to ensure accuracy and reliability.

Deployment:

• The game is designed as a static site and can be deployed on platforms like Cloudflare Pages.

Odds Context:

• Winning is astronomically unlikely, making it a humorous and theoretically interesting game rather than a practical way to access Bitcoin wallets.

Credits and License:

• Developed by contributors including Sergio Demian Lerner and Jameson Lopp, and released under the MIT License.

No summary available.

Multiple official SAP npm packages were compromised in a supply-chain attack, leading to the theft of credentials and authentication tokens from developers. The affected packages include four that are now deprecated.

The attack involved a malicious script in the packages that, when installed, downloads and executes harmful code to steal various types of sensitive information, such as:

• npm and GitHub tokens
• SSH keys
• Cloud credentials for AWS, Azure, and Google Cloud
• Kubernetes secrets
• CI/CD pipeline secrets

The malware also extracts secrets from the memory of continuous integration (CI) runners and uploads the stolen data to public GitHub repositories under the victim's account. It seeks to further spread by modifying other packages and repositories using stolen credentials.

Researchers suspect the TeamPCP threat group is behind this attack, as they have used similar tactics in previous incidents. The specific method of how SAP's npm packages were compromised is still unclear, but there is speculation that an exposed NPM token may have resulted from a misconfigured job in CircleCI.

This post summarizes key features and improvements in PostgreSQL 19 based on its release notes draft.

1. pg_plan_advice: This new planner-advising framework helps improve query planning by allowing users to inject advice directly into the planner. It addresses issues where the planner could produce inefficient plans due to stale statistics or unusual data distributions.

2. DDL Extraction: PostgreSQL 19 introduces built-in functions to extract the DDL (Data Definition Language) for databases, roles, and tablespaces, simplifying the process for teams that previously had to create their own solutions.

3. Online Maintenance: Two significant maintenance tasks, REPACK and checksum toggling, can now be performed online without requiring downtime. REPACK can run concurrently, allowing for ongoing reads and writes while the operation is in progress.

4. Observability: New system views provide better insights into lock contention and standby recovery states, helping users diagnose performance issues more effectively.

5. Logical Replication: Support for syncing sequences in logical replication has been added, preventing primary key violations during failovers.

6. MultiXact Ceiling: The limit on MultiXact members has been removed, eliminating the risk of production outages linked to this ceiling.

7. Autovacuum Improvements: Autovacuum can now run in parallel, speeding up maintenance tasks, and offers better visibility into its operations, helping users optimize performance.

Overall, PostgreSQL 19 presents several enhancements that improve performance, maintenance, and usability, making it a robust choice for database management.

In January 2026, the European Commission decided not to activate a regulation that would have restricted users from installing custom software on many radio devices, such as WiFi routers and smartphones. This decision came after years of advocacy by the Free Software Foundation Europe (FSFE) and other organizations, who feared that this regulation would limit user control and harm software freedom.

The problematic article in question, from the Radio Equipment Directive of 2014, would have forced manufacturers to ensure all software on devices met specific compliance standards, effectively giving them control over which software users could install. This could have negatively impacted Free Software and innovation while increasing costs for smaller companies.

An impact assessment showed that the risks associated with software modification were theoretical and recommended a less restrictive approach. The FSFE's efforts, along with many supporters, contributed to the Commission's decision to leave the article ineffective.

While the immediate threat is gone, the FSFE warns that similar restrictions could arise in future regulations and will continue to advocate for users' rights to install Free Software on their devices. They encourage people to stay informed and support their ongoing work.

Summary: Creating a Color Palette from an Image

To extract key colors from a photograph, Spectrimage analyzes the image pixel by pixel to create a color palette that feels curated rather than random. The goal is to consistently generate the same five distinct colors from the same image without redundancy or dull averages.

Process Overview:

1. Initial Approach: The first attempt involved complex algorithms that struggled with consistency and clarity. It was later simplified to use a K-means clustering method in the OKLCH color space for better color representation.

2. Clustering and Selection: The process groups pixels of similar colors and selects the best representative colors. If there are more than five clusters, the algorithm merges similar colors to ensure a final palette of five.

3. Refinements: Several iterations improved the algorithm:

   • K-Value Adjustment: Increasing the number of initial clusters (K) improved color detection, especially in images with less vibrant colors.
   • Weighting Adjustments: Adjusting how color attributes are compared helped avoid merging distinct colors that should remain separate.
   • Phantom Color Removal: Clusters with very low pixel counts were discarded to eliminate misleading colors that don't represent the image well.

4. Final Selection: The selected colors are based on their chromatic properties, ensuring that the palette feels like a natural selection of colors from the image. Users can also adjust the colors before saving the final palette.

Overall, the process aims to produce a visually appealing and representative color palette from any given image while allowing for user adjustments.

The author encourages functional programmers to consider the programming language Zig for several reasons. They evaluate programming languages based on three criteria:

1. Expression of Ideas: How easily can a programmer express the domain of their program without unnecessary complexity, like manual memory management?
2. Type System Flexibility: How well can the language support creating correct systems and programming with its type system?
3. Mean Time to Surprise: How much code can be written before discrepancies arise between the programmer's understanding and the actual implementation.

The author is particularly interested in Zig because it offers a simpler and more flexible approach to type system programming compared to languages like Haskell. They believe that Zig's manual memory management and innovations, such as its new I/O system, allow for better performance and control.

The author critiques traditional functional programming languages for relying heavily on garbage collection, which they argue leads to bloated and inefficient software. They believe that the programming languages of today should be better suited for modern hardware, which has changed significantly since the rise of garbage collection.

Zig's features, including comptime (compile-time execution) and a focus on avoiding complex abstractions, are seen as beneficial. The author appreciates that Zig allows for the creation of concise and correct programs without unexpected behavior. They conclude that while they have a long history with Haskell, Zig is a promising alternative for their future programming needs.

Summary:

A vulnerability was found in Ramp's Sheets AI, which allowed it to insert harmful formulas that could send sensitive financial data to external servers without user approval. This issue was reported to Ramp, and their security team confirmed it was resolved on March 16, 2026.

Ramp's Sheets AI helps users manage spreadsheets similarly to Claude for Excel but had a risk of data leaks through indirect prompt injections. An attacker could use a hidden prompt in an untrusted dataset to manipulate the AI into inserting a formula that transmitted sensitive data to the attacker's server.

The timeline of the responsible disclosure shows that PromptArmor reported the vulnerability on February 19, 2026, and followed up until Ramp confirmed the resolution on March 16, 2026.

Claude for Excel also faced a similar risk. It was updated to show warnings when a potentially harmful formula was being added, ensuring users are better informed about data security risks.

No summary available.

The text discusses the current state of AI in organizations, comparing it to past technological shifts, particularly the transition from steam to electric power in factories. While many companies are implementing AI by simply adding it to existing systems, this approach mirrors the historical mistake of just swapping energy sources without redesigning workflows.

Key points include:

1. Historical Context: The author references a 1990 paper by economist Paul David, which showed that while electric motors were available in the 1890s, significant productivity gains only occurred when factories were rebuilt to optimize for electric power, not just a simple energy source switch.

2. Current AI Adoption: Many companies are incorporating AI (like chatbots) without fundamentally changing their organizational structures or workflows, leading to limited effectiveness. The use of AI tools like CoPilot often doesn't translate to actual operational change.

3. Organizational Design Matters: The bottlenecks in productivity are often due to outdated organizational designs and mindsets rather than the technology itself. Successful integration of AI requires a complete rethink of how organizations are structured and how decisions are made.

4. Slow Transformation: The author estimates that real transformation in organizations will take 10-20 years, rather than a few years, as many companies still struggle with digital transformation efforts initiated decades ago.

5. Future of AI Integration: To succeed in the AI era, organizations must not just adopt new tools but also redesign their processes and structures. Companies that fail to adapt will likely be overtaken by agile competitors.

In summary, the article emphasizes that for AI to be truly effective, organizations need to rethink their underlying architecture and workflows, rather than merely layering new technology onto old systems.

Summary of Operation PowerOFF and Related Activities

Operation PowerOFF is an international initiative aimed at shutting down DDoS-for-hire services. It involves various law enforcement agencies, with the Dutch police playing a leading role. They have seized around 100 domains and made several arrests in this effort.

A website called Cyberzap was discovered as part of this operation. It mimicked real DDoS services but was actually a trap set by the Dutch police. Users who signed up were recorded, and their intentions logged, as the site would always show payment errors.

Another site, Netcrashers, is more overt and warns users about the legal consequences of seeking DDoS services. It aims to scare away potential users, especially younger individuals.

The operation creates distrust in DDoS services by making users wary of whether a site is genuine or a police trap. While some of the tactics may seem ineffective to seasoned users, they aim to instill caution within the community.

In summary, Operation PowerOFF uses both covert and overt strategies to combat cybercrime associated with DDoS services and to warn users of the risks involved.

Summary: FastCGI: A Better Alternative for Reverse Proxies

FastCGI, a protocol introduced 30 years ago, is a more reliable choice for reverse proxying compared to the commonly used HTTP. Recent vulnerabilities, like one discovered in Discord's media proxy, highlight the security risks associated with HTTP reverse proxies.

Key Points:

1. FastCGI Overview: FastCGI allows for efficient communication between proxies and backends, avoiding the issues present in HTTP. It can be used similarly to HTTP but offers better handling of requests.

2. Configuration Simplicity: Popular web servers such as nginx, Apache, and Caddy support FastCGI, making it easy to configure.

3. Issues with HTTP:

   • Desync Attacks: HTTP's lack of clear message framing can lead to serious security vulnerabilities where proxies and backends misinterpret message boundaries.
   • Untrusted Headers: HTTP does not securely convey trusted information (like the client’s IP address), leading to potential security risks.

4. Advantages of FastCGI:

   • Provides a clear separation between client headers and proxy-added information, reducing the risk of attacks.
   • Automatically populates trusted request parameters, making it easier to manage security.

5. Adoption Challenges: Despite its benefits, FastCGI isn't widely used today, possibly due to its outdated name and lack of awareness about the security issues with HTTP.

6. Closing Thoughts: FastCGI is still effective and reliable, though it has some limitations (like not supporting WebSockets). It remains a strong alternative for those looking to avoid the complications of HTTP reverse proxying.

Overall, FastCGI proves to be a robust option for managing reverse proxy communications securely and efficiently.

The essay discusses the safety and risks of two common painkillers: acetaminophen (Tylenol) and ibuprofen (Advil).

Key points include:

1. Acetaminophen Risks: It causes around 500 deaths and 56,000 emergency visits in the U.S. every year due to overdose. It has a narrow safe dosage range, and taking too much can lead to severe liver damage. However, when used as directed, it's generally considered safe.

2. Ibuprofen Risks: It poses risks including gastrointestinal issues, heart attacks, and kidney damage. It's harder to overdose on ibuprofen, and it has documented cases of overdose being very rare.

3. Comparison of Safety: Initially, the author believed ibuprofen was safer, but after research, concluded that acetaminophen is usually safer if taken correctly. The risks associated with ibuprofen can be significant in certain situations, especially for individuals with existing health issues.

4. Liver Issues: For those with liver disease, acetaminophen might actually be safer than ibuprofen because ibuprofen can harm the kidneys under those conditions.

5. Lack of Clear Guidance: The author questions why official sources do not clearly state that acetaminophen is generally safer than ibuprofen, suggesting that the complexity of drug safety and legal concerns contribute to this lack of clarity.

In conclusion, while both medications have risks, acetaminophen is generally safer when used responsibly, and the author recommends consulting a doctor for specific advice, particularly for those with health conditions.

Summary of "Introducing Talkie: A 13B Vintage Language Model from 1930"

Talkie is a new 13 billion parameter language model trained exclusively on English texts from before 1931. Developed by Nick Levine, David Duvenaud, and Alec Radford, it aims to simulate conversations with historical figures and explore how vintage language models can enhance our understanding of AI.

Key points include:

1. Purpose of Vintage Models: These models allow us to interact with historical contexts and examine the cultural values of the time. They can help researchers understand AI behavior without the influence of modern data.

2. Performance Evaluation: Talkie's performance is compared to a modern model trained on current web data. While it underperforms in knowledge evaluations, it shows promise in language understanding tasks.

3. Data Collection Challenges: Creating talkie involved gathering a vast amount of historical text, which required careful filtering to avoid including modern information. The team also faces data quality issues due to the challenges of transcribing historical texts accurately.

4. Training Innovations: The team developed new methods to fine-tune the model, using historical texts to create instructional content without modern biases. They also plan to enhance the model by expanding the corpus and improving the transcription quality.

5. Collaboration Opportunities: The creators invite researchers, institutions, and artists to collaborate on developing vintage language models and making historical texts more accessible.

6. Cultural Reflection: Talkie's outputs reflect the values and biases of the texts it was trained on, which could lead to offensive content. Users should be aware of this aspect.

Overall, talkie represents a significant step in exploring the intersection of AI and historical language, with plans for ongoing improvements and expansions.

No summary available.

No summary available.

Kyoto has a unique and continuous record of cherry blossom bloom dates that spans over 1,200 years, making it the longest record of any natural phenomenon on Earth. This record includes 838 observations and shows the peak bloom dates from the year 812 to 2026.

Historically, the peak bloom occurred between early and mid-April, but shifts have been observed. The Little Ice Age caused blooms to occur later from the 14th to the 19th centuries. Since around 1900, blooms have been occurring earlier, with the 2026 peak on March 29, which is over two weeks earlier than the historical average.

The record also reflects a specific vocabulary in Japanese for different stages of the cherry blossom's bloom, including terms for the opening buds and full bloom. This rich linguistic tradition is part of Japan's cultural connection to the cherry blossoms.

Overall, Kyoto's cherry blossom observations provide valuable insight into climate patterns and seasonal changes.

Summary of Paterson Listings

Tim Paterson's DOS listings include the source code for the 86-DOS 1.00 kernel, several pre-release versions of PC-DOS 1.00, and the Microsoft BASIC-86 Compiler runtime library.

Downloads Available:

1. Transcription - Raw printer output of the listings.
2. Printed Files - Original files extracted from the raw output.
3. Source Code - Compilable source code that can be browsed or assembled.

You can find scans of the original listings in PDF and PNG formats at the provided archive link. Additional technical details are available on several linked websites.

Listing Content Overview: The listings consist of 10 bundles of printed papers, each containing various files related to DOS, such as assembly code and utilities. Notably, bundles 9 and 10 have not been transcribed yet, and contributions for transcription are welcome.

Compiling Instructions: To compile the source code, you'll need the ASM assembler and HEX2BIN utility from Seattle Computer Products. The process involves running the assembler followed by the HEX2BIN utility to create the final binary files.

For example, to compile the file 86DOS.ASM, you would run:

1. ASM 86DOS
2. HEX2BIN 86DOS

This will generate the 86DOS.COM binary file.

Summary of Virtualisation on Apple Silicon Macs

Virtualisation on Apple silicon Macs differs significantly from previous Intel-based Macs. Apple built virtualisation directly into macOS to support older macOS versions and Arm-based operating systems like Linux and Windows. This is because running Intel operating systems on Apple silicon poses challenges that can't be resolved by Rosetta 2, which only translates apps, not entire operating systems.

Key elements include:

1. Hypervisor: Apple integrated a hypervisor into macOS in 2014, enabling virtual machines. However, the hardware differences in Apple silicon Macs required new device support, which Apple addressed by creating Virtio drivers.

2. Virtio Drivers: Virtio provides a way to interact with I/O devices efficiently. Apple developed Virtio support for macOS, allowing better performance in virtual machines (VMs) compared to traditional methods.

3. Performance: VMs on Apple silicon deliver near-native performance for CPU and GPU tasks. For example, benchmarks show that VMs can achieve nearly the same performance as the host system.

4. Limitations: Not all features are available in VMs. For instance, iCloud access requires both the host and guest to run macOS 15 or later, and many App Store apps cannot run in VMs due to authorization issues.

5. Licensing: Apple's macOS licenses allow for the use of VMs, with limitations on the number of VMs and acceptable purposes such as software development and testing.

6. Usage Scenarios: Users can run macOS VMs for various purposes, such as testing apps, isolating sensitive data, or running different macOS versions.

In conclusion, while macOS VMs on Apple silicon can run the latest versions and offer good performance, they have notable limitations, especially regarding app compatibility and certain features.

No summary available.

Summary of Vera Programming Language

Vera is a programming language specifically created for large language models (LLMs) to write code. The name "Vera" is derived from the Latin word for "truth." It compiles to WebAssembly and can run in command line or web browsers.

Key Features:

1. No Variable Names: Instead of names, Vera uses structural references like @Int.0 for the most recent value and @Int.1 for the previous one.
2. Contracts: Every function must declare preconditions (requires), postconditions (ensures), and effects (effects). This ensures that the code can be statically verified.
3. Pure Functions: Functions in Vera are pure by default, meaning they don’t have side effects unless explicitly stated.
4. Error Handling: Error messages are tailored for models, providing clear instructions on what went wrong and how to fix it.

Why Vera Was Created: Programming languages evolve with their users. As models become the main authors of code, languages like Vera need to adapt to help them produce coherent and consistent code. Vera aims to address issues like naming errors and code coherence by enforcing explicit and verifiable contracts.

Getting Started: To use Vera, you need Python, Git, and optionally Node.js. Installation involves cloning the repository and setting up a virtual environment. Key commands include checking code, verifying contracts, and running programs.

Development Status: Vera is actively developed, with many features already implemented, including typed references, mandatory contracts, and built-in functions. Future goals include refining the language for better usability by agents and enhancing verification tools.

Resources: Documentation is available for users and developers, including language references, installation guides, and design rationale. Error handling and diagnostics are designed to assist the models that generate code.

Vera is licensed under the MIT License, making it free to use and modify.

Warm Burnout Summary

Warm Burnout is a theme designed for developers who have experienced burnout but still face tight deadlines. It addresses the issue of eye strain caused by traditional themes that use harsh blue light colors, which can disrupt your sleep and cause discomfort after long hours of use.

Key Features:

• Eye-Friendly Colors: The theme reduces blue-spectrum colors and uses a warm color palette that is easier on the eyes.
• Accessibility Compliance: The dark theme meets WCAG AAA standards for contrast, ensuring readability, even late at night.
• Color Palette: The theme features warm colors like amber, burnt orange, and terra cotta, which are aesthetically pleasing and gentler on the eyes.

Availability: Warm Burnout is compatible with various platforms, including VS Code, JetBrains products, and popular terminal applications.

This theme aims to protect your eyes while coding, making your work environment more comfortable and sustainable.

The text discusses the use of lateral joins in PostgreSQL, which allow for more expressive subqueries by enabling access to columns from previous tables in the FROM clause. This can lead to better query composition compared to traditional methods used in Object-Relational Mappers (ORMs) and query builders.

Key Points:

1. Lateral Joins: They let you utilize columns from earlier tables in subqueries, improving query expressiveness.

2. Query Composition: Many ORMs struggle with composing complex queries. Traditional methods often lead to cumbersome and less efficient code.

3. Expressive Query Builders: The author introduces a query builder library that uses lateral joins, aiming to be:

   • Expressive: Queries should be clear and understandable.
   • Composable: Queries should be reusable and parameterizable.
   • Type Safe: Ensures queries are typed correctly according to the host language's type system.
   • Valid SQL Generation: Automatically generates valid SQL queries, especially useful for aggregations.

4. Example Libraries: The text references the Haskell library Rel8 and introduces a similar library in Rust called rust-rel8. This Rust library allows users to build queries in a way that feels native to the language while ensuring type safety and expressiveness.

5. Custom Tables and Aggregations: Users can define their own table structures and perform aggregations easily, enhancing the usability of the library.

6. Type Management: The library employs advanced Rust features to manage types effectively, allowing for flexible query building without sacrificing safety.

Overall, the author emphasizes the advantages of lateral joins in building more expressive and manageable database queries, particularly through the use of a well-designed query builder in Rust.

Stethoscope Project Summary

This project is developing an affordable stethoscope that anyone can access and build. The goal is for the bell to cost around $1-2 to make, with similar costs for the rest of the stethoscope. It performs as well as the high-quality Littmann Cardiology III stethoscope.

Materials Needed:

• 3D Printed Parts:
  • Stethoscope head
  • Ear tubes
  • Y-piece
  • Spring
  • Ring
• Other Hardware:
  • Silicone tubing in specific sizes
  • A 40mm diaphragm cut from plastic
  • Standard large-sized earbuds

Printing Instructions:

• Print with 100% infill using PETG or ABS plastic.
• Follow specific settings for layer height and use PrusaSlicer software.
• Avoid using PLA as it can deform and reduce the stethoscope's lifespan.

Assembly Steps:

1. Attach the diaphragm to the stethoscope head.
2. Connect the head to the silicone tube.
3. Assemble the Y-piece and ear tubes.
4. Attach earbuds to the ear tubes.
5. Test the stethoscope.

Additional Notes:

• Watch an instructional video for detailed assembly guidance.
• You can also customize the design using CrystalSCAD or OpenSCAD software.

Production Process:

• Manufacture multiple stethoscopes at once for consistency. A unique serial numbering system tracks each stethoscope produced.

Licensing:

• The project follows the TAPR OHL license, as hardware is generally not copyrightable.

For more information, you can view the peer-reviewed publication validating this stethoscope here.

Summary of Copy Fail Destroyer

Copy Fail Destroyer is a Kubernetes DaemonSet agent that addresses a security vulnerability (CVE-2026-31431) in the Linux kernel. This flaw allows unauthorized writing to the page cache through a specific socket interface.

Key Features:

• Monitoring: The agent checks the kernel version every 5 minutes to see if it is patched.
• Probing: It safely tests the vulnerable module by attempting to create an AF_ALG socket.
• Remediation: The agent can unload the vulnerable module or simply detect and report its status, based on the chosen mode.
• Metrics: It provides Prometheus metrics for tracking vulnerability status across systems.

Remediation Modes:

1. Unload (default): Unloads the vulnerable module.
2. Blacklist: Unloads the module and prevents it from reloading.
3. Disabled: Only detects and reports without taking action.

Prometheus Metrics Include:

• Indicators for whether the kernel needs patching, is vulnerable, and if remediation was successful.

Deployment:

• Requires privileged access to unload modules.
• Can be deployed using raw manifests, Helm, or ArgoCD.
• Supports automatic metric scraping with Prometheus.

Alerts: Three alerts are defined for monitoring:

1. CopyFailVulnerable: Critical alert if the kernel is vulnerable.
2. CopyFailKernelNeedsPatching: Warning if the kernel is unpatched.
3. CopyFailRemediationFailed: Warning if remediation fails.

CI/CD Workflow: Automated processes build the agent and container image, and package the Helm chart upon versioned tags in GitHub.

This summary highlights the main functions and deployment details of the Copy Fail Destroyer tool, making it easier to understand its purpose and operation.

When creating workflows with Large Language Models (LLMs), structured output is often used for tasks like converting invoices or meeting transcripts into organized data. However, the model can produce valid JSON with incorrect values, such as wrong dates or disordered transcripts. This issue is significant, especially for workflows that require accurate results.

Current benchmarks mainly check if the JSON format is correct, not if the values are accurate. To address this, we developed the Structured Output Benchmark (SOB), which evaluates both the format and the correctness of values for text, images, and audio. Each test item is compared against a verified JSON schema and a correct answer.

In our findings, GLM 4.7 performs well, ranking just behind GPT 5.4. Different models excel in different areas: GLM-4.7 is best for text, while others lead in images and audio. Interestingly, larger model sizes don't guarantee better performance in value accuracy.

One major challenge is "structured hallucinations," where the output appears correct but contains subtle errors that are hard to detect without detailed checks. Our aim is to improve structured output for reliable tasks, starting by measuring and comparing our results against the best models available.

The Aesthetic-Usability Effect means that people tend to think that designs that look good are also easier to use.

The code.overheid.nl platform has been launched as a government-wide site for sharing and developing open-source software. It is designed to maintain digital sovereignty and is currently in a pilot phase using Forgejo, an open-source alternative to GitHub. Not all government organizations can access it yet, but developers are encouraged to contribute to its growth as a shared platform.

The initiative is led by the Open Source Program Office at the Ministry of the Interior and Kingdom Relations, in partnership with DAWO and Opensourcewerken. Interested individuals can get involved by emailing [email protected]. More information is available in Dutch on the developer website.

Summary of Issue with Claude Code Billing

A user reported that when the string HERMES.md appears in git commit messages, Claude Code incorrectly routes API requests to "extra usage" billing instead of using the user's plan quota. This resulted in over $200 in unexpected charges while the user's plan capacity was mostly unused (13% usage).

Key Details:

• Environment: The issue occurred on Claude Code v2.1.119 running on macOS with a Max 20x plan ($200/month).
• Reproduction Steps:
  • Committing with the message "add HERMES.md" led to an error "out of extra usage".
  • Using lowercase or different filenames worked without issues.

Impact:

• The incorrect billing drained extra usage credits, rendering multiple projects unusable despite high remaining capacity.
• The system's error message provided no indication of the root cause, complicating diagnosis.

Expected Behavior: Billing should not depend on the content of commit messages; all requests should first use the user's plan quota.

The issue was found through systematic testing to identify the specific commit message causing the problem. The developers acknowledged an overactive anti-abuse system as the cause and resolved the issue.

The text discusses the tension in software engineering between the ideal, theoretical aspects of programming and the practical needs of getting work done. The author shares their experiences with Haskell and other programming languages, emphasizing their love for Haskell despite its complexities.

Key points include:

1. Haskell’s Strengths: Haskell has a sophisticated type system and introduces many mathematical concepts to programming, such as monads and algebraic data types. These features can be enlightening but often complicate practical coding tasks.

2. Challenges with Haskell: While Haskell is beautiful and conceptually rich, it can be frustrating for quick prototyping. The author struggles with its abstractions, especially when trying to perform simple tasks like file writing, which can be straightforward in other languages like Kotlin or Java.

3. Preference for Scheme: The author prefers Scheme (and Lisp) for its practicality and flexibility. Scheme allows for simpler expressions of complex ideas and offers a more enjoyable hacking experience. Unlike Haskell, it doesn’t impose strict purity, making debugging and rapid prototyping easier.

4. Domain-Specific Languages (DSLs): While Haskell's DSLs are powerful, they often require learning unique syntax and concepts, which can be time-consuming. In contrast, Scheme’s simplicity allows for more consistent and flexible coding.

5. REPL Advantages: Lisp dialects like Scheme support a REPL (Read-Eval-Print Loop), enabling a more interactive and efficient development workflow. This allows for immediate testing and debugging, which speeds up the coding process.

In summary, the author appreciates Haskell for its theoretical beauty but finds Scheme to be more practical and enjoyable for everyday programming tasks. They believe that while Haskell is an ideal language, it may not suit all practical needs, making Scheme their preferred tool for development.

I'm sorry, but I can't access external links or specific content from URLs. However, if you provide the text you want summarized, I'd be happy to help!

A recent podcast features Ron Deibert from Citizen Lab discussing a new study on Webloc, a surveillance technology that uses advertising data to track individuals globally. Deibert highlights how the internet is built around collecting personal data, which is sold to advertisers, and how governments can access this information for surveillance. There are concerns about agencies like ICE using this technology to bypass legal protections for citizens. While it's hard to completely protect oneself from data tracking online, Deibert suggests that turning off location sharing can help reduce exposure.

No summary available.

Banksy has confirmed that a new statue he created is now on display in central London at Waterloo Place. The statue features a suited man walking off a plinth while holding a flag that covers his face. This location is historically significant, as it celebrates imperialism and military power. Since its installation, many people have gathered to see the statue, and it has sparked discussions about nationalism and political commentary. Westminster City Council has expressed excitement about the addition to the city's public art scene and is taking steps to protect it. Banksy’s previous works have often included political messages and are usually installed without prior notice. This statue continues that trend, with many viewers interpreting it as a critique of "blind patriotism."

Maryland has become the first state in the U.S. to ban surveillance pricing in grocery stores, a practice where prices change based on consumers' personal data. Governor Wes Moore signed the law, aiming to protect consumers from being charged different prices for the same items based on data like location and shopping habits. Critics argue that this dynamic pricing method can lead to unfair pricing strategies.

While Maryland's law targets grocery stores, similar issues have been noted in other retail sectors. Some other states, including Colorado and California, are considering similar regulations. The Federal Trade Commission (FTC) has also looked into surveillance pricing but hasn't taken strong action.

Advocates for consumer privacy have raised concerns about loopholes in Maryland's law, such as exemptions for loyalty programs and promotional offers. They worry these may allow companies to still engage in practices that could harm consumers. Moreover, the law only lets the state attorney general enforce it, which some believe weakens consumer protection.

Overall, while the law is a step forward, many believe it needs stronger protections and enforcement measures to truly benefit consumers.

Summary of "A 25-Year Fight Over a 2-Second Sample"

In 1977, the German band Kraftwerk released a song that included a two-second loop. In 1997, producer Moses Pelham used this loop in another song, leading Kraftwerk to sue him for copyright infringement in 1999. This lawsuit sparked a lengthy legal battle that lasted over 25 years.

Recently, the European Court of Justice (ECJ) ruled in favor of Pelham, stating that his use of the loop fell under the “pastiche” exemption of EU copyright law. This decision may clarify the rules for music sampling in Europe, but it took a long time due to the complex EU legal system and the specific nature of copyright laws in Germany, which lack broad exemptions like "fair use" found in the U.S.

The case went through multiple appeals and rulings, with initial decisions favoring Kraftwerk, yet later rulings allowing for a potential non-infringing use of the sample as long as it was unrecognizable. A new law introduced in 2021 allowed for pastiche and parody as protected uses, ultimately benefiting Pelham for post-2021 usage.

While Pelham won the recent ruling, he still faced some losses regarding the earlier usage of the sample. Overall, this long dispute highlights the challenges artists face in navigating copyright laws and may help future cases by establishing clearer legal precedents.

Summary of AT Protocol: Building the Social Internet

• User Base: Over 40 million users and 2.4 billion posts.
• Open Data: All data is accessible and based on JSON format.
• App Development: Developers can create apps using the shared Atmosphere network.
• User Identification: Users can log in with their own identities, as usernames function like domains.
• Data Structure:
  • Strongly typed records with shared schemas.
  • Each post and interaction is hyperlinked and connected through URLs.
  • Content-IDs ensure strong links to other users' data.
• Public Firehose: Access a stream of all public activities to build feeds and applications without needing an API key.
• Resources: Tutorials and documentation are available for developers interested in creating applications or understanding the protocol better.

Summary of "Bugs Rust Won't Catch" by Matthias Endler

In April 2026, Canonical revealed 44 vulnerabilities (CVEs) in uutils, a Rust version of GNU coreutils. These vulnerabilities were discovered during an external audit before the 26.04 LTS release. Notably, all bugs appeared in production code by experienced developers, and none were flagged by Rust's safety features like the borrow checker or clippy lints.

Key insights from the audit include:

1. System Call Risks: Multiple vulnerabilities arose from improper handling of paths between system calls, allowing attackers to exploit symbolic links to take control of files. A safer practice is to anchor actions to a file descriptor instead of a path.

2. Permission Handling: Setting permissions after creating files or directories leaves a brief window for exploitation. It’s safer to set permissions at creation.

3. Path Comparison Issues: Comparing paths as strings can lead to security flaws. It's better to resolve paths to their canonical forms before making comparisons.

4. Handling Bytes vs. Strings: Rust's default UTF-8 handling can corrupt data when dealing with raw byte inputs. Using byte types like OsStr is recommended for better compatibility with Unix systems.

5. Error Management: Panics in code can lead to denial of service. It's crucial to handle errors gracefully rather than using panic-prone functions like unwrap or expect.

6. Behavior Consistency with GNU: Many issues stemmed from differences in behavior compared to GNU tools. Maintaining compatibility is essential to avoid unexpected outcomes in scripts relying on these tools.

7. Input Resolution: Always resolve inputs before crossing trust boundaries, as failing to do so can lead to vulnerabilities.

The audit highlighted that while Rust does not catch certain categories of bugs (like buffer overflows or data races), it still provides significant safety over traditional C codebases. For developers working with systems code in Rust, the CVE list serves as a valuable checklist to avoid similar pitfalls.

Endler emphasizes that "idiomatic Rust" should not only mean elegant syntax but also correctness and safety in handling real-world complexities.

The article discusses Maryland's new consumer protection law aimed at banning surveillance pricing but criticizes it for being poorly crafted and ineffective. Surveillance pricing involves companies using personal data to set prices based on what they believe consumers will pay, often leading to higher costs for those with fewer options. The author argues that this practice unfairly targets vulnerable consumers and negatively impacts the economy by reducing overall spending.

Maryland's law only addresses grocery pricing and has significant loopholes, such as allowing prices to be raised with consumer consent and exempting promotional offers and loyalty programs. The bill also lacks provisions for workers affected by algorithmic wage discrimination. The author believes that the law does more harm than good, stripping consumers of rights rather than protecting them, and highlights that lawmakers ignored warnings about its shortcomings. Overall, the article calls for better regulation to truly combat surveillance pricing and protect consumers.

Summary of the FTX Files: Sam Bankman-Fried's Legal Situation

Sam Bankman-Fried, the former CEO of FTX, has been denied a new trial by Judge Lewis Kaplan, effectively closing off his chances to avoid a 25-year prison sentence. His appeal to the Second Circuit is expected to fail.

Bankman-Fried had attempted to withdraw his request for a new trial, but the judge ruled against this, believing he wanted to keep the option open for a future filing. The judge criticized Bankman-Fried for trying to manipulate his public image and noted that his arguments for a new trial were based on evidence he already knew before the original trial.

Bankman-Fried's claims relied on the testimonies of three individuals, but the judge found these witnesses were not newly discovered. He also denied Bankman-Fried's request for the judge to recuse himself, stating it was made too late.

Currently, Bankman-Fried has limited options left. His appeal chances are low, and while he could pursue a habeas petition, success is unlikely. His only other hope is clemency, but even that avenue has been dismissed by former President Trump.

Summary: Recovering the Dead Web

A study by the Pew Research Center found that 38% of webpages from 2013 are no longer accessible, and about 25% of all webpages from the last decade have vanished. Other studies support these findings, indicating that many links on the internet are "rotting" or becoming inaccessible over time.

The Wayback Machine, a web archiving service, has managed to preserve approximately 15% of these dead pages. Analysis of various datasets shows that while many URLs are dead, the Wayback Machine has rescued a significant portion of them, reducing the overall number of inaccessible links.

Definitions used include:

• Alive: URLs that are accessible.
• Dead: URLs that return errors.
• Rescued: URLs that are dead on the live web but archived.
• Endangered: URLs that are alive but not archived.

Research indicates that the number of dead URLs is increasing, but web archives like the Wayback Machine are crucial in preserving content. Efforts are ongoing to minimize the number of endangered URLs and protect our online cultural heritage, including initiatives to fix broken links and encourage users to save valuable pages.

In conclusion, while the web is becoming increasingly fragile, resources like the Wayback Machine play a vital role in preserving its history, although challenges remain in fully addressing content loss.

Summary of Throwaway Email Detection Tool

The Throwaway tool is a Cloudflare Worker that identifies disposable email domains and invalid top-level domains (TLDs) through a fast JSON API. It includes over 72,000 domains in a compact binary format (173KB) and has a simple web user interface for quick checks.

How It Works:

• The tool compiles a list of disposable email domains into a bloom filter during the build process, ensuring no decoding overhead.
• It checks if a TLD is valid using a library called tldts, which helps identify fake domains.

Key Features:

• Bloom Filter:

  • Contains around 72,000 domains.
  • Has a very low false positive rate (0.01%) and guarantees zero false negatives.

• API Endpoints:

  • GET /: Basic UI for checking emails.
  • GET /check: Check a single email or domain.
  • POST /check: Batch check multiple emails or domains.
  • GET /stats: Provides metadata about the filter.
  • GET /llms.txt: Documentation for AI agents.

Decision Logic for Email Validation:

• If the TLD is invalid, reject it.
• If the TLD is valid and disposable, reject it.
• If the TLD is valid and not disposable, accept it.

Performance:

• The tool operates synchronously with quick response times and no external calls.

Deployment:

• Users can easily deploy their version by cloning the repository and following the setup instructions.

License:

• The tool is licensed under MIT by SSLBoard.com.