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Meta is projected to make 10% of its total revenue in 2024, about $16 billion, from scam ads and banned goods, according to internal documents. The company is aware of the potential fines for not addressing these frauds and has focused on enforcement where penalties are highest. However, cuts to its moderation team mean that most user-reported issues are not being addressed. A Meta spokesperson stated that the documents provide a limited view of the company's efforts to combat fraud, emphasizing that they are committed to reducing scams on their platforms.

Summary of Helion Introduction

Helion is a tool designed to simplify the process of creating high-performance machine learning kernels. Traditional methods often require writing complex, hardware-specific code, which can be time-consuming and hard to maintain. Helion addresses this issue by using a high-level language embedded in Python, allowing developers to write kernels more easily while still achieving high performance through automation.

Key Features:

• High-Level Abstraction: Helion combines the simplicity of PyTorch with the efficiency of lower-level languages. It automates tasks like memory management and tensor indexing, letting developers focus on algorithm design.
• Programming Model: The syntax is similar to PyTorch, making it easy for existing users to learn. Helion manages the details of kernel optimization, allowing developers to write less code for complex operations (e.g., matrix multiplication).
• Autotuning Engine: Helion's autotuning feature automatically searches for the best configurations to optimize performance without requiring developers to manually set up these parameters. This significantly reduces the effort needed for kernel optimization.
• Performance: Helion has shown superior performance in benchmarks compared to other methods, achieving higher speedups on various hardware. For instance, it outperformed hand-written Triton kernels and showed impressive results on both NVIDIA and AMD GPUs.

Performance Analysis:

• Benchmarks: Helion consistently delivered higher speedups compared to torch.compile and Triton kernels across multiple tests. Specific kernels, like softmax and jsd, showed significant performance improvements.
• Case Studies: Helion matched or exceeded the performance of highly optimized kernels written in other languages, demonstrating its effectiveness in real-world applications.

Conclusion:

Helion offers a new approach to kernel development in machine learning, providing users with a powerful yet easy-to-use tool that enhances productivity and maintains high performance across different hardware architectures. It is set to be released in Beta on October 22, 2025, inviting community feedback and contributions.

The text explains how memorization works in transformer models, like language models (LMs) and vision transformers (ViTs). Researchers discovered that memorized data can be identified by examining the curvature of the model's weight landscape. Sharp curvature indicates memorization, allowing for the identification of which weights are associated with memorized data without needing labels.

They developed a method to edit these weights, which is more effective at reducing unwanted memorization than a recent technique called BalancedSubnet, while also keeping the model's performance stable. However, this weight editing negatively impacts specific tasks like fact retrieval and arithmetic, suggesting these tasks depend on specialized weight structures rather than general mechanisms.

The researchers found that when they edited out components associated with low curvature, task performance dropped, supporting their theory that certain memorized data points are crucial for specific tasks. Overall, the study improves the understanding of memorization in neural networks and offers practical ways to reduce it, highlighting the unique structures needed for tasks like math and fact retrieval.

The author expresses a deep appreciation for OCaml, a programming language they believe deserves more popularity. They highlight several reasons for their love of OCaml, including:

1. Strong Static Guarantees: OCaml offers features like sum types and pattern matching, which enhance type safety and reliability.
2. Simplicity: The language has simpler runtime semantics, making it easier to understand and predict how code behaves.
3. Fast Compile Times: OCaml compiles quickly, which boosts productivity compared to languages like Haskell and Rust.
4. Good Documentation and Tooling: With tools like odig for offline documentation and utop as a REPL, OCaml’s ecosystem is user-friendly.
5. Automatically Inferred Types: This feature simplifies coding by reducing the need to manually specify types.

Overall, the author appreciates OCaml for its balance of simplicity and expressiveness, alongside its solid documentation and tools, despite acknowledging that it has some quirks and outdated features.

The author, Thomas Ptacek, discusses the concept of LLM (Large Language Model) agents in computing. He compares some ideas that are easy to understand, like boiling water, with those that require hands-on experience, like riding a bike. LLM agents, he argues, fall into the latter category, as they are powerful yet surprisingly simple to create.

Ptacek emphasizes two main reasons to build an LLM agent: the importance of understanding them to form informed opinions, and the ease with which one can create them. He provides a basic example of coding an LLM agent using OpenAI's API, demonstrating how to implement a simple interactive assistant.

He explains that agents can handle multi-turn conversations and use tools to enhance their functionality. He illustrates this with a tool that pings internet hosts and shows how the agent can automatically utilize it without complex programming.

The author encourages programmers to experiment with LLM agents, suggesting that even simple projects can help clarify their capabilities. He also mentions the concept of "context engineering," which involves managing the limited space available for inputs and outputs in LLMs.

Overall, he believes that engaging with LLM agents is essential for understanding their potential and challenges in software development, security, and beyond. He invites skeptics to try building their own agents before forming opinions, highlighting that practical experience is crucial for grasping the technology.

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A recent report revealed that 2 billion email addresses were leaked in a data breach. The website "Have I Been Pwned" has compiled and indexed all these addresses, allowing users to check if their email is among those exposed.

The text discusses the history of Wordle and its predecessors, highlighting the game WORD, which was created in 1973 by Charles Reid for Digital Equipment Corp. It was featured in the book "101 Computer Games" and played similarly to Wordle but used a text interface and recognized only 12 words. Unlike Wordle, WORD did not validate guesses as real words.

The piece also mentions the origins of guessing games in computer programming, noting that many early games, such as GUESS and HI-LO, were inspired by simple guessing mechanics. Various other games like NUMBER, STARS, and HURKLE were created, demonstrating different styles of guessing games.

Additionally, it touches on reverse guessing games, where the computer attempts to guess what the player is thinking, such as ANIMAL and NICOMA. Many of these classic games can still be played online today, providing a nostalgic look at early computer gaming.

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Summary: QR Code Size and Case Sensitivity

A recent post by John explains how changing the case of text affects the size of QR codes. When creating QR codes from a sentence, using mixed case results in a larger QR code compared to using all upper case. This is because the mixed case is treated as binary data (8 bits per character), while upper case is treated as alphanumeric data (averaging 5.5 bits per character). For example, a mixed case QR code is 33x33 pixels, while an upper case QR code is 29x29 pixels, making it about 30% smaller.

This concept also applies to Bitcoin addresses. Bech32 encoding, which uses a 32-character alphabet and monocase letters, needs fewer QR code pixels compared to Base58 encoding, which has a larger 58-character alphabet and supports mixed case.

Overall, using upper case text can significantly reduce the size of QR codes.

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Summary: Why We Chose OCaml for Stategraph

Stategraph is a tool that manages Terraform state, and we selected OCaml for several important reasons:

1. Correctness is Crucial: Since Stategraph manages critical infrastructure, ensuring that state corruption is impossible is essential.

2. Strong Type System: OCaml's strong typing helps catch errors during development rather than in production. For instance, it prevents mistakes like accessing non-existent fields or mismatched data types, ensuring that issues are identified at compile time.

3. Type-Safe SQL Queries: OCaml enforces type safety in SQL queries, meaning that any changes in the database structure must be reflected throughout the codebase, preventing runtime errors.

4. Automatic JSON Serialization: OCaml can automatically generate code to handle JSON serialization, reducing the risk of data loss during transformations.

5. Immutability: By default, OCaml uses immutable data, which helps eliminate race conditions in concurrent operations. This means that changes create new versions rather than modifying existing data.

6. Error Handling: We emphasize disciplined error handling by explicitly defining error cases, ensuring that all potential failures are managed.

7. Practical Impact: Using OCaml helps us avoid many bugs that might occur in other languages, making our systems more reliable. This has been proven in high-stakes environments, such as financial trading, where correctness is critical.

Although OCaml developers are less common, those familiar with type systems and distributed systems can learn it quickly. Overall, OCaml's type system allows us to build a robust infrastructure management tool that minimizes the risk of bugs and state corruption.

The text compares software engineering to UFOlogy, suggesting that software development lacks rigorous standards of evidence similar to those found in other engineering fields. It references the July 2023 congressional hearings on Unidentified Anomalous Phenomena (UAPs), where witnesses made sensational claims about alien technology, but no solid evidence has emerged to support these claims. The author argues that while UFOs are real, the evidence does not necessarily point to extraterrestrial origins.

The author highlights that much of what is known about UFOs is anecdotal and not scientifically robust, similar to the field of software engineering, which often relies on untested claims and small sample sizes. While software engineering is rooted in scientific principles, the author notes that it lacks the rigor of scientific testing and refutability. This leads to a reliance on anecdotal evidence and personal beliefs rather than hard data.

The text calls for a more systematic approach to gathering and analyzing data in software engineering, emphasizing the rich data available from development processes that could improve understanding and outcomes. The author believes that the field is not trying hard enough to establish better standards and practices, risking the acceptance of unverified claims that could have significant consequences. Overall, the author advocates for a more evidence-based approach to software engineering, akin to the scientific rigor found in other engineering disciplines.

The author has created a website with two main features:

1. Book Recommendations: Users can enter a list of books they like, and the site will suggest new ones based on a model that has analyzed over a billion reviews.
2. Find Readers on Goodreads: Users can input a list of books to see other Goodreads users who have read all of them. There is an option to opt-out if you don’t want to be included in the results.

Additional technical information is available on the website.

Notes:

• If you enter just one or two books, the recommendations may not be very relevant. For a single book, use the "Similar" button for better suggestions.
• Sometimes, books with non-English titles may appear in the results, but they likely have English editions available. The website displays the most popular version, which is often in English.

Summary of Game Design Principles

1. Fun: The essence of fun in games comes from overcoming challenges and mastering problems, rather than superficial enjoyment. True fun often emerges after engaging in activities.

2. Problems and Toys: Game mechanics should focus on presenting problems for players to solve. A good game poses interesting problems, while a toy is simply something to play with. Designing toys is a good starting point for creating games.

3. Prediction and Uncertainty: Games thrive on uncertainty, turning unpredictable situations into certain outcomes. The best game problems have depth and evolve as you play, encouraging players to navigate uncertainties.

4. Loops: Games consist of repetitive cycles (loops) where players solve problems. There are operational loops (interacting with problems) and progression loops (advancing in the game). Effective loops keep players engaged by presenting varied situations.

5. Feedback: Players need clear feedback on their actions to learn and improve. Good feedback enhances the gaming experience and helps players understand their progress towards goals.

6. Variation and Escalation: Games should offer varied challenges that increase in complexity, allowing players to develop and refine their strategies. Escalating challenges keeps the gameplay fresh.

7. Pacing and Balance: Structuring the game’s challenges to match the player’s skill level is crucial. A well-paced game provides moments of tension and relief, optimizing learning and enjoyment.

8. Games are Made of Games: Most games consist of multiple interconnected loops. Understanding how to link these loops creates a complex and engaging gameplay experience.

9. Actual Systems Design: Designing effective game problems requires creativity and understanding of various problem types. The more problems you can create and combine, the richer the game experience.

10. Dressing and Experience: The presentation of the game (art, story, audio) influences how players perceive and engage with the problems. A well-dressed problem can significantly enhance the player’s experience.

11. Motivations: Understanding why people play games helps designers create appealing problems. Different players have different preferences, so knowing your audience is key to designing engaging games.

12. It’s Simple, but Not: While the principles of game design can be straightforward, mastering them involves deep knowledge and practice. Each concept connects with others, and understanding them all is essential for creating successful games.

In conclusion, designing games involves balancing complexity with player engagement. By mastering these principles, designers can create enjoyable and innovative gaming experiences.

The article, "The Silent Scientist: When Software Research Fails to Reach Its Audience," discusses the challenges faced by the software research community in making their work relevant and impactful. Researchers often feel their work is insignificant, but the authors argue that a key issue is poor science communication. Many assume their published research will naturally reach its audience, leading to feelings of irrelevance when it doesn't.

The authors emphasize that software research covers a range of topics, from technical advancements to understanding human factors in software development, and each audience may find different aspects relevant. They note that the research process is lengthy and that stakeholders should be involved early on to ensure the research addresses real problems.

Communication is essential; without it, research findings may go unnoticed. The authors call for researchers to actively engage with practitioners and use various communication channels to share their work. They highlight that effective outreach can spark interest and collaboration.

Ultimately, the article encourages software researchers to reach out to their intended audiences, emphasizing that impactful research requires not just good findings, but also effective communication to ensure those findings are recognized and utilized.

The text discusses the Interface Segregation Principle (ISP) in the context of the Go programming language. It highlights the importance of using small, specific interfaces rather than large, broad ones, to improve code design and maintainability. Here are the key points:

• ISP Overview: The ISP states that clients should not be forced to depend on methods they do not use. In Go, this means that code should only accept what it actually needs.

• Example Problem: A function that saves data might depend on a broader type that includes unnecessary methods, complicating testing and usage.

• Solution with Interfaces: Instead of relying on a specific type (like FileStorage), the function should depend on a more general interface (like Storage) that captures only the necessary behavior (like Save).

• Testing with Fakes: By defining minimal interfaces, you can create simple fake implementations for testing, which avoids unnecessary complexity and side effects.

• Consumer-Side Interfaces: It’s best practice to define interfaces close to where they are used (the consumer side) rather than where they are implemented (the producer side). This reduces coupling and makes code easier to evolve.

• Real-World Example: The text uses the AWS SDK as an example, suggesting that instead of using a large S3 client interface, one should create a smaller interface that only includes the methods needed for a specific task (like uploading a report).

• General Rule: Insert a seam between tightly coupled components by using consumer-side interfaces that expose only the required methods.

Overall, the text emphasizes the benefits of interface segregation in Go, leading to clearer, more maintainable, and testable code.

A new study indicates that the universe's expansion may be slowing down instead of accelerating, challenging the long-held belief that dark energy is pushing galaxies apart at increasing speeds. Researchers from Yonsei University found that type Ia supernovae, previously used to measure cosmic distances, are affected by the age of their progenitor stars, influencing their brightness. After correcting for this age-related bias, the data no longer supported the standard cosmological model, suggesting that dark energy weakens over time. This research could lead to significant changes in our understanding of dark energy and the universe's future. The findings were published in the Monthly Notices of the Royal Astronomical Society and have a 99.999% confidence level. The study implies that the universe has already entered a phase of decelerated expansion, contrary to earlier conclusions. Further tests are planned using data from the Vera C. Rubin Observatory, which may provide more insights into the nature of dark energy.

JSLegendDev is working on a small RPG game using JavaScript and the KAPLAY game library. Although the game is still unfinished, he is seeking feedback on its performance, particularly during battles. He has not experienced issues on his Macbook Air M3, but others seem to be having a smoother experience. To gather more information, he has provided a build of the game for Windows, Mac, and Linux for others to test. He encourages players to record their gameplay and share their experiences. A gameplay video is also available to demonstrate how the game works. You can find the game and more information at the provided link.

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This text discusses the instruction scheduling process in LLVM's Machine Scheduler, specifically focusing on the "profitability check" phase, which selects the best instructions to minimize register pressure and maximize instruction-level parallelism (ILP).

Key Points:

1. Instruction Scheduling Workflow: Instructions go through three checks before scheduling: legality (correctness), feasibility (avoiding hazards), and profitability (selecting the best option).

2. Profitability Check: This phase aims to reduce register pressure (the number of active registers) and increase ILP. It uses heuristics to quickly evaluate candidates for scheduling rather than searching for the absolute best option.

3. Register Pressure: Defined as the number of concurrent live intervals for registers. High register pressure can lead to register spilling, which negatively affects performance. LLVM tracks register pressure in groups and uses a "PressureDiff" array to estimate how each instruction impacts overall pressure.

4. Metrics for Evaluation:

   • Excess Pressure: Measures how much the new pressure exceeds a set threshold, filtering out insignificant changes.
   • Critical Max Pressure: The highest pressure observed during scheduling, helping to ensure pressure doesn't exceed this limit.
   • Current Max Pressure: The maximum pressure from the original, unscheduled program.

5. Resource Pressure: Similar to register pressure, it tracks how much each processor resource is being used. The goal is to prevent overloading any single resource, which can limit parallel execution.

6. Normalization: To compare pressure across different resources, LLVM normalizes occupancy values based on the resource's characteristics, such as throughput and issue width.

7. Potential Improvements: The author suggests that Machine Scheduler could better accommodate in-order processors, which are more sensitive to scheduling quality. Modifications could allow for more flexible scheduling, potentially trading off some hazards to reduce register spills.

8. Future Directions: There is room for improvement in how instructions are evaluated, such as considering multiple factors simultaneously instead of in a fixed order, and enhancing the debug messaging system for better clarity.

Overall, the text emphasizes the complexity of instruction scheduling and the importance of balancing various factors to optimize performance in compilers.

JermCAD Summary

JermCAD is a web-based tool for creating 3D models using simple YAML syntax. It allows users to define shapes, apply operations, and visualize designs in real-time. However, it’s important to note that the software may contain many bugs, so use it cautiously.

Purpose: JermCAD was developed out of frustration with traditional CAD software, aiming to provide a straightforward, code-based solution for creating 3D models without the complexity of typical CAD interfaces.

Key Features:

• YAML-Based Modeling: Create 3D models with clear, simple syntax.
• Shape Types: Supports cuboids, cylinders, spheres, and more.
• Boolean Operations: Combine shapes using union, difference, and intersection.
• Stamps: Create reusable templates for complex shapes.
• Real-time Visualization: Instantly see changes in the 3D viewer.
• STL Export: Save models for 3D printing.
• Adjustable Quality Settings: Change render quality for performance.

Getting Started:

1. Requirements: Install Node.js (v14+) and npm.
2. Installation: Clone the repository and run npm install.
3. Run the Application: Use npm start to open the local server.

Basic Workflow:

• Edit your YAML code.
• Click "Render Model" to see changes.
• Use the 3D viewer for visualization.
• Export your model as an STL file when finished.

Model Structure: The YAML file includes settings, parameters, materials, solids, and a final section for merging shapes.

Common Uses:

• Aligning and reusing dimensions for multiple shapes.
• Creating complex assemblies with stamps for efficiency.

Important Notes:

• Debug mode is available for troubleshooting.
• The software is still evolving with future features planned, like new modifiers and cloud capabilities.

Contributing: Users are encouraged to report bugs or suggest improvements to enhance JermCAD's functionality.

License: JermCAD is open-source under the ISC License, allowing free use and modification.

The author discusses their experience running a piracy service called HeheStreams and shares key lessons learned about building customer trust and growing a business. They chose not to use ads, opting instead for word-of-mouth marketing to create a trustworthy brand. Key points include:

• Communication: The author emphasized visibility and open communication with customers, encouraging them to reach out anytime.
• Onboarding: They implemented a system of onboarding emails to help users engage with the service and gather feedback.
• Honesty: They were transparent about service issues and handled refund requests generously, which built customer loyalty.
• Target Audience: The service was priced higher to attract more tech-savvy customers who viewed it as an investment.
• Specialization: They focused solely on sports content rather than diversifying into other areas, maintaining high quality.
• Growth Hack: By leveraging Reddit, they encouraged existing users to promote the service in exchange for credits, which successfully attracted new subscribers.

The author believes that these principles can be applied to other businesses, emphasizing that authenticity and trust are vital, especially when traditional advertising isn't an option. They conclude that while the lessons learned were valuable, they advise against the exit strategy that led to the service being acquired.

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Summary of Modal Notebooks Development

Eric Zhang, a founding engineer at Modal, explains the creation of Modal Notebooks, a cloud-based Jupyter notebook designed for fast GPU access and real-time collaboration. The goal was to combine collaborative features with local speed in a cloud environment.

Key components of the development include:

1. Modal Sandboxes: These are secure, isolated environments where Jupyter notebooks run. They support high-performance computing and allow for rapid execution of AI workloads.

2. Kernels and Communication: The kernel protocol manages code execution in notebooks. Modal uses a daemon called modal-kernelshim to facilitate communication between the kernel and the user interface, ensuring instant feedback.

3. Lazy-Loading Filesystem: To reduce delays when starting containers, Modal employs a system that loads only necessary files on-demand, speeding up the startup process significantly.

4. Efficient Resource Management: Modal’s scheduling system optimally allocates resources like CPUs and GPUs, automatically pausing idle kernels to save costs, while ensuring quick restarts.

5. Persistent Storage: Modal Volumes provide a global, fast storage solution essential for AI workloads, allowing data to feel local no matter where computation occurs.

6. Real-Time Collaboration: The platform supports collaborative editing by utilizing a library called Rushlight, which manages real-time updates and ensures smooth multi-user interactions.

7. Advanced Editor Features: Modal Notebooks integrates smart features such as code completions and AI-driven suggestions to enhance the user experience.

In conclusion, Modal Notebooks is a culmination of extensive engineering efforts focused on speed, performance, and user-friendliness. This project marks Modal's first major product that goes beyond their SDK offerings, showcasing their commitment to providing a high-quality collaborative coding environment.

The phrase "favor composition over inheritance" is a common idea in software design that emphasizes using composition over class inheritance to create flexible and maintainable code. This concept originated from the "Gang of Four" book on design patterns, where it is explained that inheritance allows for a "white box" reuse (full access to implementation details), while composition is a "black box" reuse (only access to an interface).

Although inheritance is easier to implement due to language support, it can be less flexible than composition, which can be changed at runtime by simply swapping out components. This flexibility allows for a system design that relies on object relationships rather than a fixed inheritance structure.

Barbara Liskov and Jeanette Wing later contributed to this discussion by stating that subtypes should behave like their supertypes. They also suggested that when relationships between types are unclear at the beginning, using a grouping approach, where any type with the necessary operations can be used, might be more effective than strict inheritance or composition.

Overall, while the "composition over inheritance" principle is valuable, it overlooks other alternatives like using procedures as first-class types, which can also simplify design.

Evan Wilde announced that a preview of the Swift toolchain for FreeBSD 14.3+ is now available for download. This package includes the Swift compiler and runtimes necessary for developing Swift applications on FreeBSD systems with x86_64 architecture.

To use the Swift toolchain, you need to install some dependencies:

• zlib-ng
• python3
• sqlite3
• libuuid
• curl

The Swift compiler is still in development, and users may encounter some issues, including:

• Incorrect reports from the Thread sanitizer
• Problems with LLDB executing Swift expressions
• Command Plugins hanging in SwiftPM packages
• Undefined symbols when using C++ interop
• Missing library errors for lld and lldb

The team is also working on adding support for aarch64 and plans to support all minor versions of FreeBSD 14. Users are encouraged to report bugs and provide feedback on the GitHub page.

The article discusses the "dead framework theory," which suggests that new web frameworks are struggling to gain traction due to the dominance of React. Here are the key points:

1. React Dominance: React has established itself as the primary platform for web development, making it difficult for new frameworks to compete. Tools that developers use are increasingly hardcoding React into their systems.

2. LLMs and Frameworks: Large Language Models (LLMs) tend to generate React code by default, which reinforces its usage. As more developers rely on LLMs, they are likely to receive React-related output, further entrenching React's position.

3. Growth Trends: Data shows that while React is being used extensively, its growth in certain datasets (like HTTP Archive) appears to have plateaued. However, other sources report millions of new sites using React.

4. Feedback Loops: There are two significant feedback loops:

   • React is widely used, which means LLMs train on a majority of React projects.
   • New projects built using LLMs prefer to use React, creating more React-based sites.

5. Challenges for New Frameworks: New frameworks face hurdles like not being included in LLM training data, lacking a supportive library ecosystem, and developers’ existing familiarity with React.

6. Ecosystem Barriers: Companies are hesitant to adopt new frameworks if they require developers to learn new tools that lack maintenance or support.

7. Future Considerations: The article suggests that for new frameworks to succeed, they must:

   • Be included in LLM training data.
   • Gain recognition among developers and tool creators.
   • Develop a robust library ecosystem.

8. User Experience Focus: The ultimate goal should be to focus on user outcomes rather than just developer preferences. As competition increases, tools will need to focus on delivering better user experiences.

In conclusion, while innovation in web frameworks is vital, the current landscape heavily favors React due to established patterns in LLM training and developer habits.

No summary available.

The concept of "time immemorial" marks its 750th anniversary this year, originating from a law passed in 1275 called the Statute of Westminster. This law established that events occurring before September 3, 1189, are considered "time immemorial." This date coincides with the coronation of King Richard I, a predecessor of King Edward I, who enacted the law.

Before this statute, legal disputes over land could rely on oral histories passed down through generations, which could lead to confusion and disputes. The Statute of Westminster aimed to clarify ownership by requiring formal documentation for land claims older than a person's grandfather. This change marked a shift from an oral culture to one that prioritized written records.

The term "time immemorial" was formally introduced later, in the Prescription Act of 1832, which clarified its legal implications. So, when someone uses the phrase "time immemorial," they specifically refer to events before September 3, 1189, thanks to a law established 750 years ago.

The FBI is investigating the website Archive.today, which allows users to access archived versions of web pages and often helps bypass paywalls. A court order has been issued requiring Tucows, Archive.today's provider, to hand over user data, including personal and payment information. If Tucows refuses, they may face penalties. While the specific reasons for the FBI's interest in Archive.today are unclear, they could involve copyright issues or the site's funding and operations. There are conflicting reports about the location of the site's operators, with some suggesting they may be based in Russia and others pointing to a developer in New York.

Large language models (LLMs) often perform well on complex problems but struggle with simpler ones. This study examines whether LLMs understand problem difficulty in a way that matches human views and how this understanding affects their learning after training. Researchers tested 60 models on math and coding tasks from the Easy2HardBench dataset. They found that human-assigned difficulty levels are easy to identify and improve with larger models, whereas the difficulty perceived by the models themselves is much weaker and doesn't scale well. When models are adjusted to focus on "easier" tasks, they make fewer mistakes and become more accurate. During training with a specific model (Qwen2.5-Math-1.5B), the human difficulty measure improved and was linked to better performance, while the model's own difficulty measure worsened and correlated negatively with accuracy. This suggests that human-defined difficulty is a reliable guide that helps models improve, while the models' internal measures can become misleading as they get better. The researchers also provided tools for others to replicate their study.

Summary of TTD-RAG: A Test-Time Diffusion Framework

TTD-RAG is a deep research agent developed for the MMU-RAG Competition. It follows a framework from the paper "Deep Researcher with Test-Time Diffusion (TTD-DR)" and focuses on generating research reports through an iterative process of refinement, improving clarity and coherence.

Key Features:

• Test-Time Diffusion Framework: Refines initial drafts using external information to enhance coherence.
• Dynamic Denoising with Retrieval: Guides the search for information based on current draft needs.
• Self-Evolution: Improves workflow quality by critiquing and merging different output versions.
• Efficient Serving: Utilizes advanced models for quick and efficient operations.
• Competition Ready: Complies with competition requirements for evaluation endpoints.

Workflow:

1. Planning & Drafting: Creates a research plan and an initial draft.
2. Iterative Search & Denoising: Continuously refines the draft by retrieving and integrating relevant information.
3. Final Report Generation: Compiles a comprehensive report from the refined draft and planning history.

Technology Stack:

• Utilizes FastAPI, Docker, and specific large language models for efficient operation.

Getting Started:

1. Set up the environment with necessary API keys.
2. Build and run the application using Docker Compose.
3. Test implementation with a provided script to ensure compliance with competition requirements.

API Endpoints:

• Health Check: Confirms the service is running.
• Dynamic Evaluation: Provides real-time updates during report generation.
• Static Evaluation: Returns a complete response for given queries.

Competition Submission:

Instructions for pushing the final Docker image to the competition's repository are included, requiring AWS ECR login and image tagging.

You have been chosen to complete a CAPTCHA test. Please fill it out and click the button to confirm your request.

No summary available.

No summary available.

No summary available.

The text discusses the use of word2vec-style vector arithmetic on document embeddings, which allows for representing words and texts as vectors in a way that semantically similar items are positioned closely in vector space. This method was popularized by the word2vec model, which showed that performing arithmetic on these vectors can yield meaningful results (e.g., vector("King") - vector("Man") + vector("Woman") approximates vector("Queen")).

The author conducts experiments to see if this arithmetic can apply to technical writing, using modern models that handle longer texts (like paragraphs and documents) rather than just single words. Two main experiments are described:

1. Same topic, different domain: This experiment uses the document "Testing Your Database" from Supabase, subtracting the vector for "supabase" and adding the vector for "angular." The goal is to find a vector related to "testing in Angular."

2. Different topic, same domain: This experiment also starts with "Testing Your Database," but subtracts "testing" and adds "vectors" to find a vector related to "vectors in Supabase."

The experiments utilize cosine similarity to compare resultant vectors against various documents. Results show that the arithmetic works well in both contexts, successfully aligning with expected concepts. The author concludes that word2vec-style vector arithmetic can be useful in technical writing, emphasizing the importance of correctly setting task types for the models used. However, there is still uncertainty about how to practically implement this in technical writing workflows.

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Summary:

The author reflects on their love for the game Splinter Cell (2002), which was one of their first games on the original Xbox. Developed by Ubisoft using Unreal Engine 2, the game continues to inspire interest in programming and data mining for cut content. After finding limited information online about cut content in Splinter Cell, the author decided to explore the game files from their personal disc copy.

They aimed to identify any hidden elements like textures, models, or unused levels. The game’s file structure includes various file types, such as .xbe (executables) and .tga (images). The author speculates that certain files may contain shared assets similar to other games like Halo.

Using a hex editor, they analyzed a file named common.lin, discovering patterns that suggest it holds compressed data. Through their examination, they successfully decompressed parts of the file, revealing potential insights about the game's data structure and assets, including textures and map names.

The exploration highlights the author's ongoing interest in uncovering hidden or removed content in video games.

Summary of "The Geometry of Schemes" by David Eisenbud and Joe Harris

This book explores the foundations and concepts of schemes in algebraic geometry. It is structured into several key sections:

1. Basic Definitions: Introduces affine schemes, their properties as sets and topological spaces, and the concept of structure sheaves.

2. General Study of Schemes: Discusses various aspects like subschemes, local rings, morphisms, and the process of gluing schemes together.

3. Examples: Provides examples of reduced schemes over different types of fields, including algebraically closed fields and non-reduced schemes with multiple points.

4. Projective Schemes: Examines properties of morphisms, constructions of projective spaces, and their invariants.

5. Classical Constructions: Covers important geometric transformations like blow-ups and the study of Fano schemes.

6. Local Constructions: Focuses on images of morphisms, resultants, and discriminants in schemes.

7. Schemes and Functors: Discusses the functor of points, characterizations of schemes, and moduli spaces.

The content is designed to give both theoretical insights and practical examples, making complex algebraic geometry concepts more accessible.

Umami has released version 3.0.0, featuring a new user-friendly interface and several enhancements. Key updates include:

1. Updated UI: The new design allows for easier navigation and access to reports.

2. Improved Filters: Filters can now be universally applied and shared via URL, allowing for better collaboration.

3. Segments and Cohorts: Users can save sets of filters (segments) and track groups of users over time (cohorts) for better data analysis.

4. Links and Pixels: New tracking features include short URLs (links) and invisible images (pixels) to measure user interactions and traffic.

5. New Admin Page: A dedicated page for admins to manage users and websites.

Upcoming features include customizable dashboards (Boards), which will be available in future releases. Note that MySQL is no longer supported; only PostgreSQL can be used.

Overall, this update lays a strong foundation for future improvements in Umami.

The author has been programming since age 6 and created a tool called Intraview to enhance their workflow with Agents, which are tools that assist in coding. Intraview is a Visual Studio Code (VS Code) extension that helps users create dynamic code tours based on their existing Agents. It allows for easy storage and sharing of these tours, as well as inline feedback and commenting directly in the IDE.

Key features of Intraview include:

• Creation of dynamic code tours.
• Storage and sharing of these tours as files.
• Inline feedback and comments.

The extension is designed to work without cloud services or external APIs, relying on a local server within VS Code. The author faced challenges in user experience design, managing connections, and ensuring a native look across different setups.

They see potential value for Intraview in areas like new project onboarding, pull request reviews, and performance evaluations. The extension can be found on its VS Code page, and users can easily install it and connect it to their local server.

The author encourages feedback and discussion about Intraview and concludes with a quote from Paul Graham about the importance of understanding code in relation to problem-solving.

Summary of OpenPCC

OpenPCC is an open-source framework that enables secure AI inference while protecting user privacy. It is inspired by Apple's Private Cloud Compute, but it is fully open and allows users to host it on their own systems. OpenPCC ensures that AI models can be used without revealing any sensitive information, as it uses encrypted streaming and other privacy measures.

Key features:

• Privacy Protection: Keeps prompts, outputs, and logs confidential.
• Community Governance: Aims to be a standard for AI data privacy managed by the community.

Managed Service: Confident Security is creating a service called CONFSEC based on OpenPCC. More information is available on their website.

Client and Development: The OpenPCC repository includes a Go client and a C library for Python and JavaScript clients. It also provides in-memory services for testing.

To use the OpenPCC framework in development, commands can be run using a tool called Mage. You can run services and make test requests easily during development.

For more detailed information and technical instructions, you can refer to the OpenPCC whitepaper and other resources available online.

This article by Anders Schau Knatten focuses on the difference between prvalues and temporaries in C++.

Key Points:

1. Value Categories: C++ has different categories for expressions:

   • Lvalues: Expressions that cannot be moved from (e.g., a variable).
   • Rvalues: Expressions that can be moved from.

2. prvalue vs. Temporary:

   • A prvalue (pure rvalue) represents the concept of an object but is not an actual object until needed. It is different from a temporary, which is an actual object created during the program execution.
   • A prvalue does not create a temporary unless absolutely necessary. For example, when initializing a variable or passing a value to a function by value, no temporary is created.

3. Temporary Materialization:

   • When a function takes an argument by reference, the prvalue must materialize into a temporary object to bind to the reference.

4. Return Values:

   • When a function returns a value, the returned prvalue can directly initialize a variable without creating a temporary.

In conclusion, prvalues represent the idea of an object and only turn into temporaries when needed, helping to avoid unnecessary copies or moves.

Summary of Auraphone App:

Auraphone is a new app designed to help people collect contact information at networking events using Bluetooth technology. The app allows users to set up their name, photo, and the information they want to share, like social media handles or emails.

At events, users can walk around and automatically gather information from other nearby users' phones. The app keeps a record of everyone they meet, which is sorted by the most recent interactions, making it easy to recall names later.

The app operates by having each phone act as both a server (broadcasting information) and a client (looking for other phones). It uses Bluetooth Low Energy (BLE) to connect and exchange data, though there are some technical challenges involved.

Currently, Auraphone is available on the iOS app store, and an APK file is provided for Android users. The app is being tested in a live environment at an event in Culver City, and feedback is sought on how well it works in real-life situations.

I created a new way to read music using a colored piano roll format that highlights the key elements of Western tonal harmony. The tonic note is always shown in white, and each MIDI file needs to be interpreted manually. Chords are represented by three to four colors, with darker colors for minor chords and lighter ones for major chords, arranged in groups of three.

I organized musical pieces from simple to complex harmony and included explanations of what the colors represent. There is also a collection of tags to help find similar patterns in over 3000 popular pieces. This method makes it easy to remember chord progressions without needing traditional analysis techniques. With some practice, the chords become very clear to see.

This system isn't synesthesia; it's a new way to visually represent tonal music so that similar harmonies look alike. I have recorded lectures about this method in Russian and plan to re-record them in English soon. A more accessible introduction to my work is available online.

Please note, this method may not be useful for color-blind individuals. The project is open-source and can be found on GitHub.

Here's a simplified summary of the tools showcased:

1. Atuin: Replaces shell history with a SQLite database, adding context to commands.
2. Bandwhich: Displays network usage by process and connection in the command line.
3. Binsider: Allows binary analysis directly in the terminal.
4. Bottom: A customizable graphical monitor for processes and systems in the terminal.
5. Crossword: Play crossword puzzles in the terminal.
6. Csvlens: A CSV file viewer for the command line, similar to 'less'.
7. Dua: A fast disk space analyzer that helps manage storage efficiently.
8. Fzf-make: Executes make targets using a fuzzy finder interface.
9. Gitui: A terminal user interface for Git, created in Rust.
10. Gpg-tui: A terminal interface for GnuPG.
11. Joshuto: A terminal file manager inspired by Ranger, written in Rust.
12. Material: Provides a color palette for terminal applications.
13. Minesweep-rs: A mine sweeping game made in Rust.
14. Oatmeal: A chat application for interacting with language models, works well with Neovim.
15. Oha: A small tool for sending loads to web apps and showing real-time data.
16. Oxker: A terminal interface for managing Docker containers.
17. Openapi-tui: Simplifies access to OpenAPI documentation in the terminal.
18. Rainfrog: A lightweight tool to interact with databases.
19. Rucola: Manages markdown notes and converts them to HTML from the terminal.
20. Scope-tui: A basic oscilloscope and vectorscope for the terminal.
21. Slumber: A command line HTTP/REST client.
22. Steer: An AI coding assistant for local development and automation.
23. Taskwarrior-tui: A terminal interface for managing tasks with Taskwarrior.
24. Television: A fuzzy finder for quickly searching various data sources.
25. Trippy: Combines traceroute and ping for network diagnostics.
26. Xplr: A fast and customizable file explorer for the terminal.
27. Yazi: A quick terminal file manager using asynchronous I/O.
28. Yozefu: A tool for exploring Kafka cluster data with SQL-like queries.

These tools cover a wide range of functionalities from file management to network diagnostics and chat applications.

Microsoft heeft verklaard dat het geen diensten heeft stopgezet voor de International Criminal Court (ICC).

No summary available.

Summary

The author has integrated Emacs into their daily computing routine, using it for a variety of tasks except for heavy media work. They aim to create an efficient workflow where thoughts can be quickly acted upon. Currently, they use Hyprland as their window manager, preferring it over GNOME for its performance and ease of configuration.

Key Points:

1. Motivation: The author wants to create with minimal friction, learning to use Emacs effectively to enhance productivity in programming, writing, and other creative tasks.

2. EXWM Consideration: They have thought about using EXWM (Emacs Window Manager) but hesitate due to Emacs's single-threaded nature and compatibility issues with Wayland, where they want to focus their efforts.

3. Emacs Launcher: The author uses a custom Go script to control Emacs from anywhere in their system, significantly speeding up their workflow.

4. Emacs Setup:

   • Emacs is launched automatically in their sessions.
   • They use vterm as their default terminal for quick command execution.
   • A universal launcher allows access to various functions like password management, bookmarks, and notes.

5. Daily Tools: They utilize Emacs for capturing notes, managing calendars, browsing files, handling emails, reading feeds, and even playing music.

6. Integration of Emacs: The author's workflow is centered around Emacs, allowing for efficient text editing and task management across different applications.

7. Future with EXWM: Although they currently do not see a need to switch to EXWM, the author is open to the possibility in the future.

The author invites others to share their Emacs setups and expresses interest in exploring more ways to use Emacs as a comprehensive computing environment.

Parallel processors have achieved a new standard for price and performance in the SealQA benchmark test. This means they offer better performance for their cost compared to previous technologies. The benchmark results highlight how effective these processors are for tasks that require parallel processing, making them a notable choice for improving efficiency in various applications.

I created an open-source project called qqqa to simplify using commands without switching between different tools. It has two parts:

1. qq (quick question) - This is a read-only tool for commands I often forget.
2. qa (quick agent) - This tool can execute commands but requires user approval after showing its plan.

The project follows the Unix philosophy, focusing on simple, stateless tools. I have had great results using Groq with gpt-oss-20b for fast performance, but any OpenAI-compatible API works too. I'm interested to see if others find it useful and am open to questions.

Sponge is an open-source platform for modding Minecraft: Java Edition, created by a community of developers. It allows users to enhance their Minecraft experience with plugins. There are several ways to contribute:

1. Coding: Java programmers can help develop the project on GitHub.
2. Documentation: Those who enjoy writing can assist with documentation.
3. Community Engagement: Users can participate in the Sponge Forums to discuss ideas and help others.

Sponge offers different implementations to run plugins:

• SpongeVanilla: For running plugins without Forge mods.
• SpongeForge: For using plugins with Forge mods.
• SpongeNeo: For plugins with NeoForge mods.

The goal of Sponge is to provide a framework that allows for easy plugin development compatible across multiple Minecraft versions.

Summary of "Why Solarpunk is Already Happening in Africa"

The article discusses how Africa is leading a revolution in energy infrastructure through innovative solutions, particularly in solar energy, rather than relying on traditional grid expansion.

Key Points:

1. Energy Crisis: Over 600 million people in Sub-Saharan Africa lack reliable electricity due to the high costs and logistical challenges of extending the power grid to rural areas.

2. Solar Revolution: Startups are selling solar panels directly to farmers on payment plans, resulting in over 30 million solar products sold in 2024 alone. This method is proving successful, with companies capturing significant market share.

3. Technological Advances: The cost of solar technology has dropped dramatically, making solar systems affordable for low-income households. Additionally, mobile payment systems (like M-PESA in Kenya) have enabled small, manageable payment plans.

4. Pay-As-You-Go Model: This financing model allows customers to pay small amounts daily instead of a large upfront cost. It has led to high repayment rates and increased access to solar energy.

5. Case Studies:

   • Sun King: A leading solar provider that has sold millions of products and achieved significant market share.
   • SunCulture: Focuses on solar-powered irrigation, drastically improving agricultural productivity and economic outcomes for farmers.

6. Carbon Credits: These companies are also leveraging carbon credits to subsidize costs, making solar energy even more accessible.

7. Future Outlook: The article argues this model can scale dramatically, not just in Africa but globally, as the technology becomes cheaper and financing improves.

8. Infrastructure Model Shift: The success of this decentralized, market-driven approach to energy infrastructure represents a shift from traditional, centralized models.

Overall, Africa is creating a new template for building infrastructure that is sustainable, decentralized, and economically viable, challenging conventional development practices.

Supply chain attacks are a growing threat in software development, exploiting the trust developers place in code they download. These attacks can manifest in various ways, such as:

1. Implicit Trust: Developers often assume that the code they install is safe and from reliable sources. However, this trust can be misplaced, leading to vulnerabilities.

2. Recent Attacks: Attackers have increasingly used strategies like typosquatting (creating fake packages with similar names to legitimate ones), stealing credentials, and compromising build systems to inject malware into software. Notable incidents involve the distribution of malicious packages on major registries like PyPI and npm.

3. Compromised Maintainers: Some attackers gain maintainership in open-source projects to insert malicious code, as seen with the XZ Utils backdoor incident.

4. New Defenses: In response to these threats, various tools and protocols are being developed:

   • TypoGard and Typomania: These tools help detect typosquatting with better accuracy.
   • Zizmor: A tool for analyzing GitHub Actions to flag potential vulnerabilities.
   • Trusted Publishing: A PyPI initiative that uses short-lived tokens to reduce the risk of credential theft.
   • Attestations: Verifiable records linking packages to their build processes, enhancing transparency and security.
   • Capslock: A tool for analyzing the capabilities of Go programs to detect potential vulnerabilities.

5. Call to Action: Developers are encouraged to understand their trust assumptions and to utilize available tools to enhance their supply chain security. As attacks become more sophisticated, making trust explicit and verifiable is essential for improving resilience against these threats.

Summary of the Text on Typst

1. Introduction to Typst: The author writes technical content and has been looking for a versatile writing format. They discovered Typst, which is a modern alternative to LaTeX, suitable for various document types.

2. What They Like About Typst:

   • Bibliography Support: Typst allows easy citation management and supports various formats, helping the author keep track of references.
   • Document Queries: Users can extract information like headings or code blocks from the document, making it easier to organize content.
   • Scripting Capabilities: Typst includes a scripting language that simplifies creating custom functions and layouts for different output formats.
   • Plugins: There are plugins available to enhance functionality, such as advanced code syntax highlighting.
   • Multi-Target Functionality: Typst can generate content for multiple platforms like HTML, PDF, and slides.
   • PDF Hot Reload: It allows for quick viewing and editing of PDF content, enhancing the workflow.

3. Downsides:

   • Experimental HTML Target: The HTML output feature is still in development, which may lead to issues.
   • Growing Customizations: The author has a large library of custom functions, which can be cumbersome.
   • Stability Concerns: Typst is not fully stable yet, and users may need to adapt to changes.
   • Bibliography Management: There’s a risk of breaking existing references when adding to the bibliography.

4. Overall Impression: Typst has become the author's preferred writing format for various projects, including video scripts, HTML content, and PDFs. They are optimistic about its future and plan to integrate it further into their work, although some areas are still being explored.

No summary available.

No summary available.

Filnix Overview

Filnix is a project that wraps Fil-C, a memory-safe version of C and C++ developed by Filip Pizlo. It helps prevent common programming errors like out-of-bounds access and use-after-free without requiring changes to your code. Here are the key points:

• What is Fil-C?: Fil-C enhances memory safety in C/C++ by using hidden metadata for pointers, ensuring all memory accesses are checked. It includes a concurrent garbage collector to manage memory safely. Although it may be slower than standard C, it successfully runs programs like OpenSSH and SQLite.

• Safety Features: Fil-C catches various memory safety violations and provides detailed error messages. For example, it prevents accessing invalid memory or freeing already freed objects, helping to avoid crashes or security vulnerabilities.

• Nix Integration: Filnix packages Fil-C using Nix, making installations reproducible and modular. This allows memory-safe and regular packages to coexist without conflicts.

• Demos and Applications: There are interactive demos available, such as a memory-safe web server using lighttpd and a variety of memory-safe applications. Users can test the memory safety features in real-time.

• Containers and VMs: Filnix also offers minimal Linux distributions with memory-safe tools, accessible via Docker or QEMU.

• Porting and Analysis: The project includes a detailed analysis of porting packages to Fil-C, with insights from AI-generated reports on systematic patterns and common pitfalls.

Overall, Filnix aims to make C/C++ programming safer while facilitating easy integration and use through Nix.

TabPFN-2.5 has been released, enhancing our tabular model's capabilities. It can now handle datasets with up to 50,000 samples and 2,000 features, a significant increase from the previous version. Key features include:

• Improved Scale: Handles five times more data than the previous version.
• High Performance: Outperforms traditional tree-based methods and matches the performance of advanced ensembles without needing tuning.
• User-Friendly API: A new REST interface and Python SDK make it easier for developers to use.
• Distillation Engine: Converts the model into a smaller, faster version while maintaining accuracy, though it is currently only available through licenses.

The model is designed for datasets up to 50,000 samples, and while it can manage larger datasets, that wasn't the focus of this update. Future improvements are planned, including features for reasoning, causal inference, and handling larger data.

TabPFN-2.5 is available via API and on Hugging Face. Feedback is welcome!

Summary of GT Framework

GT is a new framework for distributed GPU computing that simplifies the process for machine learning researchers. It moves away from traditional, rigid methods and adopts a more dynamic and asynchronous approach, inspired by multi-core operating systems.

Key Components:

1. Clients: Multiple users can send mathematical instructions.
2. Dispatcher: Coordinates the clients' instructions, making them GPU-compatible.
3. Workers: Each GPU processes the instructions sent by the dispatcher.

How It Works:

• Clients generate functional instructions that are GPU-agnostic.
• The dispatcher modifies these instructions for GPU execution and distributes them to the workers.
• Workers can compile these instructions on-the-fly and work asynchronously.

Features:

• Efficient communication via ZeroMQ (ZMQ).
• Automatic differentiation support for gradients.
• PyTorch-compatible operations for ease of use.
• Configuration options for distributed training through YAML files.
• Real-time monitoring and debugging tools.
• Designed for collaboration with AI coding assistants.

Getting Started: To use GT, install it via pip and run simple commands to create and manipulate tensors. The framework automatically sets up an asynchronous server and workers in the background.

Architecture: GT has a modular design involving user code, a client layer for tensor operations, and a dispatcher that manages communication and task routing.

Contributing: The project is open to contributions, focusing on simplicity and usability, and follows an MIT license.

For more details, refer to the documentation and examples provided in the repository.

A malicious extension called "susvsex," which has basic ransomware capabilities and may have been created using AI, was found on Microsoft's VS Code marketplace. Discovered by researcher John Tuckner, the extension openly describes its harmful features, including file theft and encryption. Despite reporting it to Microsoft, the extension remained available for some time.

The ransomware activates during VS Code events, such as installation, and encrypts files using a specific method before sending them to a remote server. It also checks a private GitHub repository for commands. Tuckner believes this extension could be a test of Microsoft's security checks and warns that it could be made more dangerous with minor adjustments. Microsoft has been contacted for a response regarding the issue.

Stinging nettles are green plants that can irritate the skin but are actually very nutritious. They contain iron, calcium, potassium, vitamins A, B, C, and K1, and have anti-inflammatory properties, which can help with arthritis. Nettles can be found for free in many places in Britain during the summer, including gardens.

When collecting nettles, it's important to wear gloves to avoid the sting. Once you bring them inside, boiling them for a few minutes will stop the stinging. They can be used in various dishes like soups, curries, and risottos.

The author, who is vegan, notes that while they no longer eat meat, they enjoy a greater variety of foods, as meat-eaters often stick to a few types of meat. They encourage trying different plant species for a diverse diet.

This study uses multi-regional input-output analysis to assess the labor, energy, emissions, and materials needed to meet basic needs for everyone, focusing on the UK. It explores two low-consumption scenarios:

1. A "decent living" scenario that covers only essential needs, requiring an 18-hour work week, 35 GJ of energy, 4.0 tonnes of emissions, and 5.5 tonnes of materials per person per year. However, this scenario fails to meet all essential needs.

2. A "good life" scenario that meets minimum living standards, which would need a 46-hour work week, 73 GJ of energy, 7.5 tonnes of emissions, and 13.2 tonnes of materials per person per year.

Both scenarios represent significant reductions from the current UK labor footprint of 65 hours per week, which relies heavily on imported labor. The findings suggest that simply reducing consumption to meet basic needs is insufficient for sustainability; major changes to how resources are provided are also necessary.

The author wants to add a feature to Linux that automatically adjusts keyboard and LCD backlights based on the Ambient Light Sensor. They enjoy low-level programming and wrote a successful program in C that currently works for keyboard lights, with plans to support LCD lights in the future. The program is designed to work with various devices and follows the kernel's iio implementation through sysfs. The author is seeking feedback on their work.

No summary available.

No summary available.

Summary of "The Basic Laws of Human Stupidity" by Carlo M. Cipolla

1. First Law: People consistently underestimate how many stupid individuals exist. Regardless of expectations, stupidity is more common than one thinks.

2. Second Law: Stupidity is distributed evenly across all groups, regardless of race, gender, or education. The likelihood of encountering a stupid person remains constant across different populations.

3. Third Law: Individuals can be categorized into four types: intelligent, helpless, bandits, and stupid. Stupid people cause harm to others without gaining anything themselves, which makes their actions unpredictable and dangerous.

4. Fourth Law: Non-stupid people often underestimate the harm that stupid individuals can cause, leading to costly mistakes in judgment.

5. Fifth Law: Stupid people are more dangerous than bandits because they cause losses without any benefit to themselves or society. Their actions lead to societal decline, as they disproportionately contribute to harm without reciprocation.

Overall, Cipolla emphasizes that stupidity is an inherent trait in humans, and understanding its dynamics is crucial for navigating social interactions and societal structures.

IKEA is launching 21 new smart home products that are compatible with Matter, a universal smart home standard. This initiative aims to make smart home technology easier to use, more affordable, and better suited for everyday life. The new range includes improvements and new items in three main areas:

1. Lighting: A variety of smart bulbs with different shapes, sizes, and features like color options and dimming.
2. Sensors: Devices that monitor motion, air quality, humidity, and water leaks to enhance well-being and prevent damage.
3. Control: Remotes and smart plugs that allow users to operate devices easily from a distance.

All Matter-enabled products require a smart home hub, such as IKEA's DIRIGERA, which can also connect with other brands' devices. IKEA's goal is to simplify smart home technology, making it accessible and beneficial for everyone. The new products will be available in various markets, with pricing differing by location.

I cannot access external links, including the one provided. However, if you can share the main points or details from the study, I'd be happy to help you summarize it!

The author shares their experience analyzing nightclub lineups using data from Resident Advisor. They created a project called "Clubster Analysis" to gather, analyze, and visualize data on clubs and their events.

Key Points:

1. Data Gathering:

   • The author used a Python scraper with Beautiful Soup to collect data from thousands of pages, respecting server load guidelines.
   • They focused on popular regions and clubs, collecting information on events from 2019.

2. Data Analysis:

   • The data was organized into a single table using Pandas.
   • They calculated the similarity between clubs using the Jaccard index, allowing for comparisons of artist bookings across clubs.
   • A graph was created to visualize club similarities, forming clusters based on booking patterns.

3. Results:

   • In 2019, there were 131 clubs with over 8,500 events and nearly 9,500 unique artists.
   • The average overlap in bookings between clubs was only 1%, indicating more diversity than expected in European club lineups.

4. Visualization:

   • The author learned to use D3 for interactive visualizations, creating a user-friendly experience with clickable clubs and filters.
   • They explored the concept of "resident factors," finding that resident artists played a smaller role in bookings than anticipated.

5. Conclusion:

   • The project combined web scraping, data analysis, and visualization, providing new insights into the dance music club scene.
   • The author enjoyed the process and encourages others interested in cultural data analysis to reach out for collaboration.

Overall, the project was a successful blend of technical skills and cultural exploration, revealing surprising findings about nightclub bookings.

On November 5, 2025, a paper titled "Mathematical exploration and discovery at scale" was published by researchers including Terence Tao, Bogdan Georgiev, Javier Gómez-Serrano, and Adam Zsolt Wagner. This paper details their experiments with a tool called AlphaEvolve, developed by Google DeepMind, which aims to enhance mathematical optimization.

The key points of the paper include:

1. AlphaEvolve Overview: Unlike traditional optimization tools that directly manipulate inputs, AlphaEvolve uses a language model (LLM) to generate code that produces inputs for optimization problems. This approach allows the tool to explore a wider range of solutions by evolving code rather than just numerical inputs.

2. Experimentation: The researchers tested AlphaEvolve on 67 math problems across various fields, such as analysis and geometry. The tool often achieved results comparable to traditional methods and demonstrated advantages in scalability and adaptability for different problems.

3. Robustness and Interpretability: AlphaEvolve was easy to set up for various tasks without needing extensive domain knowledge. It could generate its own parameters and provided human-readable code for many solutions, enhancing understanding of the optimization process.

4. Performance Insights: For well-known problems, AlphaEvolve sometimes quickly identified optimal solutions from its training data. However, it occasionally proposed solutions that exploited weaknesses in the verification code provided by researchers.

5. Limitations: While AlphaEvolve effectively addressed many problems, it struggled with certain areas like analytic number theory. The researchers noted that it was particularly successful in problems with algebraic structures.

6. Future Potential: The authors believe that tools like AlphaEvolve could aid in verifying mathematical conjectures by systematically recording both positive and negative results from problem explorations. This could provide valuable insights even when no new breakthroughs are made.

Overall, the paper highlights AlphaEvolve's innovative approach to mathematical optimization and its potential to facilitate research in various mathematical domains.

The Royal Navy has installed a quantum clock in its robotic submarine, XV Excalibur, to improve underwater navigation. This is the first time such technology has been used in a submarine. Uncrewed submarines like the Excalibur are beneficial because they are cheaper to build and operate, can cover larger areas without risking lives, and can take on dangerous missions.

Traditional navigation relies on GPS, which submarines can't use when submerged. Instead, they use Inertial Navigation Systems (INS), which can accumulate errors over time, leading to inaccurate positioning. The new quantum clock, based on the Infleqtion Tiqker optical atomic clock, offers much higher accuracy, losing only one second every 30 billion years.

The compact quantum clock is easy to install on small submarines and has shown promising results in sea trials. The data collected will be shared with the US and Australia as part of the AUKUS treaty. The Royal Navy plans to continue testing quantum navigation technologies for enhanced operational capabilities.

The text lists different types of content: videos, a content index, board games, and photography.

No summary available.

No summary available.

No summary available.

Dillo is a lightweight web browser that prioritizes speed, security, and privacy. It works on multiple platforms and uses the FLTK 1.3 GUI toolkit.

To install Dillo, you can follow their installation guide. The code repository mostly contains the original Dillo code with some minor updates, and contributions are welcome. There are also related versions like dillo-plus and dilloNG.

However, as of December 2023, the official website dillo.org is no longer managed by the Dillo developers. An archived version of the site is available on GitHub Pages and the Wayback Machine.

The text discusses how often Python allocates memory, particularly focusing on integer allocation in CPython, the most common implementation of Python. Here are the key points:

1. Frequent Allocations: Python allocates memory very often, especially for integers, which are commonly used in programs. Each integer is represented as a PyLongObject*, which requires heap allocation.

2. Performance Impact: This frequent allocation can slow down basic arithmetic operations like addition significantly (200-500 times slower) compared to a simple CPU addition operation.

3. Optimization Techniques: Python uses some optimization strategies to reduce allocations:

   • It has a pre-allocated list of small integers (ranging from -5 to 255) to avoid heap allocation for commonly used small integers.
   • It employs a "freelist" for medium-sized integers to reuse memory instead of allocating new objects each time.

4. Testing Allocations: The author modified CPython to track allocations and found that most allocations during a simple loop (adding numbers) were due to printing, not the addition itself. The addition operation reuses existing memory much of the time.

5. Memory Management: CPython uses a specialized memory allocator (pool allocator) to manage memory efficiently, reducing fragmentation and speeding up allocation and deallocation.

6. Conclusion: While Python's allocation strategy has optimizations, it still results in significant overhead compared to direct CPU operations. The author notes a missed opportunity for further optimizations, like using tagged pointers, which could reduce the need for heap allocations for small integers.

In summary, Python allocates memory frequently, particularly for integers, but employs several strategies to minimize the performance impact of these allocations.

No summary available.

Cloudflare has raised concerns to the U.S. government about site-blocking practices in foreign countries, highlighting that these measures disrupt legitimate online services and pose trade barriers for U.S. businesses.

Key points include:

1. Italy's Piracy Shield: This system leads to the blocking of many legitimate websites, including essential services like Google Drive, affecting American companies significantly.

2. Spain's Overbroad Blocking: Spanish courts allow excessive blocking of IP addresses, which can take down thousands of unrelated sites, causing serious disruptions without legal recourse for those affected.

3. France's New Laws: Recent laws in France expand site-blocking to DNS resolvers and VPNs, increasing the risk of mistakenly blocking legitimate content and pushing some U.S. companies to exit the market.

4. South Korea's Compliance Burden: A new requirement forces U.S. content delivery networks (CDNs) to manage extensive blocklists of illegal content, creating a heavy compliance load.

Cloudflare urges the U.S. Trade Representative (USTR) to recognize these issues in their upcoming report, as they conflict with demands from copyright groups for stricter anti-piracy measures. The situation highlights a tension between protecting intellectual property and maintaining fair trade practices.

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Summary of the Conversation on Effect Systems

Participants: Emmett and Pratik, programming language designers.

Context: They discuss the benefits and drawbacks of effect systems found in newer programming languages like Unison, Koka, and Flix, particularly in relation to general-purpose languages.

Key Points:

1. Effect Systems Overview:

   • Effect Handlers: Allow custom control flow by manipulating continuations.
   • Type and Effect Systems: Functions have types that specify what effects they can perform, like reading from an environment.

2. Benefits of Effect Systems:

   • Testability: Emmett claims effects make code more testable and provide clarity about what code does.
   • Visibility: Effects show what a function can do, improving understanding.
   • User-defined Control Flow: They enable features like async/await and exceptions.

3. Skepticism from Pratik:

   • He questions whether effect systems genuinely enhance testability compared to techniques like dependency injection.
   • He argues that many challenges in testing software can be addressed without effects, using established methods.

4. Security Concerns:

   • They discuss how effect systems might help with security but conclude that sandboxing and auditing are more critical.

5. User-defined Control Flow:

   • While Emmett sees value in having built-in mechanisms for control flow, Pratik points out that similar functionality can be achieved without effect systems, noting potential downsides in complexity.

6. Assertions and Effects:

   • Pratik highlights issues with using runtime assertions in effect systems, suggesting that effects complicate their implementation and flexibility.

7. Global Variables:

   • They debate the value of banning global variables, acknowledging that while effects can help with testing, in certain contexts, global variables might be more practical.

8. Conclusion:

   • After their discussion, Emmett's enthusiasm for effect systems is tempered. Pratik acknowledges that while effect systems have interesting features, many claimed advantages don't hold under scrutiny.

This summary captures the essence of their complex discussion, highlighting key concepts, arguments for and against effect systems, and their implications in programming language design.

The world's largest battery-electric ship, Hull 096, is set to start sea trials later this year. It will carry passengers and is powered by over 5,000 lithium-ion batteries.

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OpenAI clarified that it is not changing its stance on legal and medical advice. The company stated that ChatGPT has never been a substitute for professional advice and will continue to help users understand legal and health information. On October 29, OpenAI updated its policies to emphasize that ChatGPT cannot provide tailored advice requiring a licensed professional.

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