Magistral — the first reasoning model by Mistral AI

Mistral AI has announced Magistral, a reasoning model that excels in domain-specific, transparent, and multilingual reasoning, addressing limitations of early thinking models. Magistral is released in two variants, Magistral Small (open-source) and Magistral Medium (enterprise), and is designed to think through complex problems in a transparent and step-by-step manner, with applications in various industries and use cases.

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Low-background Steel: content without AI contamination

John Graham-Cumming has created a website called "Low-background Steel" that aggregates online resources that have not been contaminated with AI-generated content, aiming to preserve content created prior to the widespread use of AI in 2022. The site currently links to sources such as a pre-ChatGPT Wikipedia dump, the Arctic Code Vault, and Project Gutenberg, and invites users to submit other sources of non-AI contaminated content.

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AI Saved My Company from a 2-Year Litigation Nightmare

The US legal system, particularly in Delaware, is biased against defendants, allowing plaintiffs to file frivolous lawsuits with little risk of penalty, and forcing defendants to spend large sums of money to defend themselves, even if they ultimately win. The author's own experience with a lawsuit against their firm, Calm Company Fund, became a "masterclass" in using AI to level the playing field against well-funded opponents, and they share lessons learned that could help other entrepreneurs navigate the system.

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Show HN: A “Course” as an MCP Server

This hands-on course, Mastra 101, teaches students to develop and deploy AI agents using Mastra, with guidance from an MCP agent that assists with coding and building working agents. The course covers three main lessons: building a first agent, adding tools and MCP, and adding memory, with the goal of creating agents that can read data, use custom tools, and remember previous interactions.

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Teaching National Security Policy with AI

Stanford's international policy class, Technology, Innovation and Great Power Competition, has integrated AI into its curriculum to prepare students for an AI-enabled world, with students using AI tools to summarize content, identify key themes, and analyze policy documents. The students' use of AI tools, such as Claude, Otter.ai, and Mermaid, not only met but exceeded expectations, with teams discovering new and creative ways to apply AI to their policy projects, including generating leads for stakeholder interviews, critiquing their own hypotheses, and creating graphics and presentations.

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JavelinGuard: Low-Cost Transformer Architectures for LLM Security

JavelinGuard is a suite of low-cost, high-performance model architectures designed to detect malicious intent in Large Language Model interactions, with options ranging from 400M parameter classifiers to more complex multi-task frameworks. The architectures are benchmarked across nine diverse datasets and compared to leading open-source models, demonstrating superior cost-performance trade-offs and guiding practitioners in selecting the optimal balance of complexity and efficiency for real-world applications.

ArXiv

Reinforcement Pre-Training

Reinforcement Pre-Training (RPT) is a new paradigm for large language models that reframes next-token prediction as a reasoning task trained using reinforcement learning, allowing for scalable training on vast amounts of text data. RPT improves language modeling accuracy and provides a strong foundation for further reinforcement fine-tuning, with results showing that increased training compute consistently enhances next-token prediction accuracy.

ArXiv

A Family of Non-Periodic Tilings, Describable Using Elementary Tools

A family of non-periodic tilings is constructed using modular arithmetic and vector geometry, exhibiting a unique type of symmetry called modulo-staggered rotational symmetry. This construction is self-contained and doesn't rely on existing tiling theories or systems, offering a distinct approach to creating regular yet non-periodic patterns.

ArXiv

Modern Minimal Perfect Hashing: A Survey

Perfect hash functions map a set of keys to integers without collisions, with modern functions achieving fast query times, space efficiency, and scalability to billions of keys through various trade-offs. These functions have numerous applications, including databases, bioinformatics, and stringology, and significant progress has been made since the last comprehensive survey in 1997, with the latest developments and experimental evaluations now available.

ArXiv

A quantum algorithm for Khovanov homology

Khovanov homology is a topological knot invariant with significant mathematical and physical implications, but its computational complexity is not well understood. This work proposes a novel quantum algorithm to efficiently approximate Khovanov homology, overcoming previous limitations, and establishes connections between Khovanov homology and graph theory to derive analytic bounds on the algorithm's performance.

ArXiv

From Scratch GPT Built with NumPy (Tokenizer, Model, Adam)

This project, NumpyGPT, implements a GPT model from scratch using only NumPy, with explicit gradient computations and a PyTorch-like API, to help understand how modern language models work. The project includes experiments comparing character-level, word-level, and BPE tokenization, with results showing that while the character model had the lowest loss, it produced the worst output, and the BPE model produced the most coherent and readable text.

Repo

Show HN: I built an AI agent for a mobile robot

The TurtleBot3 Agent project enables users to control a TurtleBot3 robot using natural language instructions, interpreting commands to perform tasks such as movement, sensor data access, and navigation. To get started, users must clone and build the project in a ROS 2 workspace, set up LLM models and the TurtleBot3 model, and then run the launch and main files using ROS 2 commands.

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Octomind – AI dev assistant that remembers your codebase

Octomind is an AI-powered development assistant that enables natural language conversations to understand, analyze, and interact with codebases, offering features like built-in development tools, multi-provider AI support, and cost tracking. It allows developers to have interactive AI sessions with their code, providing capabilities such as file operations, code analysis, and error handling, all through simple conversations.

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Show HN: Pyleak – Detect asyncio issues causing AI agent latency

Pyleak is a Python library that detects leaked asyncio tasks, threads, and event loop blocking, providing detailed stack trace information to help identify and fix issues. It offers various usage options, including context managers, decorators, and configuration settings, making it suitable for testing and real-world applications to ensure asynchronous code runs efficiently and without leaks.

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Show HN: We built and open sourced a privacy first PDF Chrome Extension

This Chrome extension is a privacy-focused tool for working with PDF files entirely offline, allowing users to merge, split, fill, sign, and rearrange PDFs without uploading or tracking. The extension is open-source, with all processing happening locally in the browser, and offers features like drag-and-drop reordering, undo and eraser functions, and bundled signature fonts for offline use.

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