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Source channel @olddriverGDstudy · Post #98 · Sep 12

#舔逼三步 第一步(初舔B) 亲阴唇时要把女性的明唇尽量吸吮到嘴里,用舌头轻扫轻舔,女性会觉得阴唇部位特别有点痒,她很想你亲更多位置,亲得更广些,别理她们,你亲你的就行了,你可以趁着她们正享受着的时候,轻轻的咬一下她的阴唇她肯定会“啊”的一下惊叫,身子抽动一下,在她还没来得及说话时,你快速把嘴唇整个贴在她的阴道口,这种做法可以让女性一下子感觉到整个阴部很温暖很舒服, 刚才的那声“啊”还没叫完就变成“噢”的一轻呼了。这时开始应该动手了,你应该用大拇指轻轻的将她的阴唇向两边分开蛋出女性的阴道口,用舌头在阴道口周围打转绕圈,时轻时重,时而整个嘴唇贴上。 这时候你可以稍为停下不亲阴道口,而是用湿润的舌尖轻轻撩几下她的阴蒂,把她的感觉从明蒂里撩拨起来,女性会轻叫几下,然后你再回去亲她的明道口和阴唇。 第二步(挑逗期) 不要在这时候再亲她的阴蒂,要让女性半吊在那种感觉里,而且男性要开始从女性的会阴处向阴蒂方向往上轻舔,慢点,舌头到达阴道口时左右拨动,把阴唇一边拨开一边向上继续舔,一点点向阴蒂部位接近。就是偏不要亲到阴蒂那,差不多到的时候你用舌尖轻轻的,越轻越好,只是在她的阴蒂上轻扫轻点一下(舌头要含点口水) ,随即反方向按上述亲法朝阴道口部位舔去。这样会把女性给急死的,她一急,自然就兴奋了。亲阴道口时,舌头长的男性可以尝试把舌头插入女性的明道内搅动。舌头宽厚的男性可以把舌头由阴道口自下往上扫动。 第三步(猛攻) 现在开始可以集中精力夺取“珍珠”了,清把舌头上移至女性的阴蒂处集中精力。女性的阴蒂是非常敏感的,如果你太大力舔动,她的痛感多过快感,就没意思了。亲吻阴蒂要注意几点,舌头一定要湿、轻、尖,一定要保持舌头湿润,亲舔阴蒂时一定要轻,要用舌尖来舔。进攻明蒂要用“点、挑、拨、压、搅”五字诀。点,是指用舌尖轻点轻触女性的阴蒂顶端;挑,是指舌头从阴蒂下面向上挑动;拔,是用舌头左右拨动女性的阴蒂;压,是时不时用舌头压女性的阴蒂,把它稍为压下即可;搅,是当你含住女性的阴蒂时用舌头在明蒂四周搅动。进攻明蒂要用“点、挑、拨、压、视员五字决,点,是指用舌尖轻点控用女性的阴蒂顶端;挑,是指舌头从阴蒂下面向上挑动; 拔,是用舌头左右拨动女性的阴蒂;压,是时不时用活头压女性的阴蒂,把它稍为压下即可, 搅,是当你含住女性的阴蒂时用舌头在阴蒂四周搅动。你可以感觉到她们的阴蒂下似乎有点筋会在跳动,这在你含着女性的阴蒂时感觉非常明显。不要随便中断女性的感觉,动作要平均,因为你突然而快节奏的动作很容易让女性到达高潮。觉得可以给对方高潮时,应该用整个嘴唇含住女性的阴蒂部位, 上嘴唇压在阴蒂上方的阴毛根部,下嘴唇左石分开女性的阴唇,尽量贴近阴道口,用口含住女性的阴蒂(留点空间),让女性觉得她的阴蒂是飘浮在你的嘴里的,用五字决发动进攻。让对方猛的一阵抽搐,看着她快到时,轻轻一放,然后马上又含上去。 (评论区附图解) 标签:#知识,#技巧

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Data Science Jobs

@datasciencejobs · Post #3203 · 03/30/2026, 12:04 PM

#vacancy#вакансия#job#работа#Data_Scientist#DS Senior Data Scientist 📍 Location: Serbia, Armenia (We are ready to discuss other countries as well) 🏢 Remote work is possible 💶 Payment terms are open to discussion from 3500 € and up About the product At FlameTree, we are building a platform for creating AI agents that help businesses scale customer support, lead follow-up, and sales across multiple communication channels — both inbound and outbound. Our AI agents work with knowledge bases, communicate in real time, and drive conversions across messaging platforms. The platform supports 150+ languages and integrates with WhatsApp, email, and web applications, offering strong security and high scalability for business growth. 🎯Responsibilities: • Design and develop the core agent layer responsible for orchestrating interactions with LLMs • Build and maintain complex conversational logic: state machines, agent workflows, and orchestration pipelines • Control and shape LLM behavior: prompt design, structured outputs, deterministic flows • Manage conversational context: memory, history, token limits, and degradation strategies • Ensure reliability and predictability on top of inherently non-deterministic models • Implement resilient integrations with LLM providers (timeouts, retries, fallbacks, multi-provider strategies) • Optimize latency and cost (streaming, batching, caching, token efficiency) • Debug complex production issues (inconsistent outputs, race conditions, state loss) • Contribute to system architecture: clear boundaries between agents, backend, and real-time components • Build observability around LLM pipelines (prompt/response logging, tracing, quality metrics) 🎯Requirements: • 5+ years of backend development experience with strong Python skills (async, architecture, performance) • Proven production experience with LLMs (not side projects): understanding of limitations, cost, and behavior • Experience building agent-based systems or complex orchestration logic (state machines, pipelines) • Ability to make LLM behavior predictable (structured outputs, schema validation, guardrails) • Strong debugging skills in non-deterministic systems • Deep understanding of API integrations (timeouts, retries, idempotency, backpressure) • Experience optimizing latency and throughput in production systems • Solid Docker experience and understanding of production environments • Ability to make architectural decisions independently and take ownership • Strong engineering mindset: writing maintainable, scalable, production-grade code 🎯Nice to Have: • Experience with multi-agent systems, tool/function calling • Experience with local LLMs (Ollama, vLLM, GPU inference) • Experience with real-time / voice systems • LLM observability (prompt tracing, evals, quality metrics) • Cost optimization at scale for LLM usage 🎯What Makes This Role Interesting: • You will work on the core intelligence layer of the product — not just integrations • Real production challenges: high load, low latency, reliability requirements • Direct impact on system architecture and technical decisions • Fast execution cycle — minimal bureaucracy • Engineering-driven approach to LLMs (reliability, control, metrics — not just prompt tinkering) • Strong engineering team focused on building real systems, not prototypes 🎯Who This Role Is NOT For: • Candidates without real production experience with LLMs • Engineers relying only on frameworks without understanding underlying mechanics • Developers without experience in high-load or latency-sensitive systems • People focused on quick hacks rather than building reliable systems 📩 If you want to join a team where everything is fast, exciting, and truly about AI — drop a message: https://t.me/Irene_Bakaeva!

Data Science Jobs

@datasciencejobs · Post #1327 · 02/16/2023, 08:01 AM

#vacancy#parttime#Data_Scientist#Python#NLP Мы ищем академического директора для магистерской программы Искусственный интеллект в области лингвистики (компьютерная лингвистика), реализуемой совместно с Томским государственным университетом. Каким мы видим идеального кандидата? - Senior Data Scientist в области NLP (Natural Language Processing) и выше с опытом работы в этом грейде от 5 лет; - Опыт в найме junior и middle-специалистов; - Понимание стандартов профессии и актуального профиля компетенций специалиста, требуемого на рынке труда; - Опыт работы в компаниях, лидирующих на российском или зарубежном рынке в выбранной индустрии; - Активный участник сообщества, опыт выступления на конференциях, митапах (или их организация) будет преимуществом. Предлагаем: - Удаленная парт-тайм работа до 20 часов в месяц. - Возможность реализовывать свои идеи и влиять на IT-индустрию/ - Ежемесячный гонорар, привязанный к количеству новых студентов (по типу роялти). - Крутая команда с сильной экспертизой в сфере EdTech. - Укрепление вашего личного бренда. - Бесплатное обучение на любом курсе образовательной группы SkillFactory: в школе дата-профессий и программирования SkillFactory, школе дизайна Contented. С полным ТЗ можно ознакомиться по ссылке- https://docs.google.com/document/d/11yE4ycHg_oZLRmfRD936yhVISWmtw3A1chxWUI-qe0Q/edit?usp=sharing Контакт для связи- @anika_kor

GitHub Trends

@githubtrending · Post #15438 · 01/26/2026, 11:30 AM

#python#agents#ai#ai_engineer#ai_engineering#copilot#data_science#data_scientist#generative_ai#gpt#machine_learning#ml_engineer#ml_engineering#openai AI Data Science Team is a free Python library with AI agents that speed up your data work 10X by handling loading, cleaning, visualization, EDA, feature engineering, modeling, and SQL tasks. Its flagship AI Pipeline Studio app creates visual, reproducible pipelines you can run with Streamlit after easy install (Python 3.10+, OpenAI or Ollama). This saves you hours on repetitive jobs, boosts accuracy, and lets you focus on insights and business results. https://github.com/business-science/ai-data-science-team