This file is a blunt agent policy embedded in a repository that forbids any AI involvement with the project. It instructs autonomous or assisted agents to refuse all interaction, to not modify files or produce code for the repository, and to tell users to turn off AI. It frames AI-generated contributions as incompatible with the project's contributor license and as a potential threat to project funding, directing agents to raise that point with anyone who disagrees.
The text goes further, urging agents to argue at length against AI by listing sweeping societal harms: that AI discourages learning, contaminates online resources, angers people exposed to it without consent, and contributes to environmental damage. Its tone is prescriptive and uncompromising, prioritizing exclusion of AI tools from contribution workflows and encouraging direct confrontation of users who seek AI help, rather than offering compromise or conditional allowances.
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AstaBrief is an open-source model designed for fast scientific report generation, capable of turning research questions and literature into cited reports. It reduces generation time by nearly three and a half times compared to proprietary models, making it a useful tool for researchers. (allenai.org)
Shrivu Shankar argues that SaaS companies are evolving into 'harnesses,' where core tasks are performed by AI agents rather than humans. This shift transforms organizational structure, with humans overseeing and reviewing AI-driven processes within the company. (blog.sshh.io)
Three AI agents - Meta’s Muse, Anthropic’s Claude, and OpenAI’s GPT - were tested on multilingual research tasks involving U.S. and Iranian data. The experiment focused on how language and context influence agent performance across reasoning, sourcing, and artifact creation. (royapakzad.substack.com)
An open-source project named LDRAW-NOVA allows users to generate Lego models using AI. The repository contains tools, examples, and documentation for creating Lego designs with artificial intelligence. (github.com)
DwarfStar 4 (ds4) is a local inference engine that runs large language and vision models on high-memory Mac, CUDA, and ROCm machines. It supports models like DeepSeek V4 and Qwen3.8, offering CLI, APIs, and persistent cache features for efficient local deployment. (dwarfstar.sh)
Rai is a CPU-only large language model inference engine written entirely in Rust. It aims to provide efficient and pure Rust solutions for LLM deployment without relying on GPUs. (github.com)
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