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Source channel @githubtrending · Post #14731 · May 21

#cplusplus#high_performance#interior_point_method#linear_optimization#mixed_integer_programming#parallel#quadratic_programming#simplex HiGHS is a free, high-performance software that solves large and complex optimization problems like linear, quadratic, and mixed-integer programming. It works fast on many computers, including Linux, MacOS, and Windows, without needing extra software. You can use it through various programming languages like Python, C, C#, and Fortran, making it easy to integrate into your projects. HiGHS supports both serial and parallel computing, and it is advancing GPU acceleration for even faster solutions. This helps you efficiently find the best solutions for planning, scheduling, and decision-making problems in science, engineering, and business. Installation is straightforward, and detailed documentation is available to guide you[1][2][3][4]. https://github.com/ERGO-Code/HiGHS

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AI & Law

@ai_and_law · Post #798 · 04/02/2026, 07:04 AM

📖Wikipedia Restricts Use of AI-Generated Content Wikipedia introduced new guidelines prohibiting editors from using large language models (LLMs) to generate or rewrite article content. The platform allows only two limited exceptions: AI may be used for basic copyediting of existing text with human review, and for translating articles between languages under specific guidance. The policy links AI use to potential violations of core content standards, including verifiability and the prohibition on original research. LLM outputs may lack reliable source attribution and can introduce inaccuracies or synthesized content not supported by published sources. The guidelines also note that detecting AI-generated text cannot rely on stylistic signals and provide no specific detection method. #AIRegulation#AIethics#ContentModeration#KnowledgeGovernance#Wikipedia