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Изворен канал @pythonotes · Post #324 · 23 сеп.

Я нашел самый быстрый способ поднять свой независимый и бесплатный VPN Сразу оговорка, платить придётся только за хостинг. 1️⃣ Покупаем сервер где-то на просторах интернета. Конечно же сервер должен находиться за пределами страны. Например я закупился на https://eurohoster.org/ (не реклама). Проверяйте лимиты по трафику, в идеале - без ограничений. 2️⃣ Ставим docker sudo apt install docker.io Если удобней с DockerCompose то ставим и его sudo apt install docker-compose 3️⃣ Ставим WG-EASY Самый простой способ поднять сервис WireGuard c WebUI это проект wg-easy Код и документация здесь https://github.com/weejewel/wg-easy Запускаем контейнер: https://github.com/weejewel/wg-easy#2-run-wireguard-easy Для тех кто с DockerCompose, забираем файл здесь: https://gist.github.com/paulwinex/be87f79687b96786098ec8fa6a8e251c В обоих случаях потребуется поменять две переменные: WG_HOST - внешний статичный IP вашего сервера PASSWORD - придумайте пароль для WEB UI Остальные параметры указаны ниже на странице github https://github.com/weejewel/wg-easy#options 4️⃣ Ставим клиента Все доступные клиенты здесь https://www.wireguard.com/install/ Есть возможность добавить клиента в Network Manager для управления подключением через UI. Установка зависит от вашей системы, ищите мануалы в сети, их много. https://github.com/max-moser/network-manager-wireguard Скрипт установки для RasperryPi https://gist.github.com/paulwinex/c2c4090f19dbe8bd1253c5744f3f06e1 ЗЫ. Конечно же это не "самый простой" и далеко не единственный способ. А просто тот, который использую я сам. #offtop#linux

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AI & Law

@ai_and_law · Post #147 · 25.10.2023 г., 07:04

Proposed Chinese AI Safety Standards: A Closer Look Hey there, AI & Law community! On October 11, the National Information Security Standardization Technical Committee in China released a draft document outlining precise regulations for evaluating generative AI models. Unlike the often vague AI regulations, this document provides a clear blueprint for compliance. This standards proposal sets forth rigorous criteria for assessing AI data sources and their content. The document covers topics like training data diversity, moderation, and prohibited content. It emphasizes the need for diversified training corpora and the assessment of data quality. If more than 5% of data is "illegal and negative information," the corpus is flagged for future training. The proposal also suggests that AI companies employ moderators to enhance generated content quality, aligning with national policies and third-party complaints. This implies a potential expansion of the human-driven moderation and censorship workforce in the AI era. Companies are tasked with identifying hundreds of keywords for flagging unsafe or banned content, with separate categories for political and discriminative content. They must also generate more than 2,000 prompts, ensuring fewer than 10% of responses breach the rules. Interestingly, the document encourages subtler censorship measures, such as not refusing to answer sensitive prompts but allowing AI models to respond to specific, non-sensitive inquiries. It's crucial to clarify that these standards are not laws, and non-compliance doesn't result in penalties. However, proposals like these can significantly influence future regulations or work alongside them. The standards receive input from tech experts hired by companies, giving corporations like Huawei, Alibaba, and Tencent a say in shaping these regulations. Their influence could have far-reaching implications for the global AI industry and how AI technologies are regulated worldwide. #AISafety#AIRegulations#GenerativeAI#ContentModeration#ChineseTech#AIInfluence#GlobalAI