Бессмертие рядом: стартап Retro Biosciences разрабатывает таблетку от старости. Это та самая компания, в которую Сэм Альтман инвестирует миллионы долларов.

Это будет таблетка для перезапуска естественного процесса аутофагии — самоочищения клеток от повреждений, в том числе в головном мозге.

Со слов гендиректора: таблетка позволит предотвращать развитие болезней Альцгеймера и Паркинсона, а в итоге поможет добавить +10 лет к средней продолжительности жизни человека.

По плану первый пациент получит препарат уже к концу этого года.

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Учим Python с помощью ChatGPT

Опытный промпт-инженер подготовил запрос, который создаст целый курс с нуля:

Interactive Python Course: LLM-Generated & Browser-Based
Create an Al-powered Python course that generates everything dynamically in the browser, like Codecademy but powered by LLM:
LLM Course Generation Requirements
Dynamic Content Creation: LLM generates lessons, exercises, projects, and feedback in real-time based on student progress and needs Adaptive Curriculum: Course structure adjusts automatically if student struggles with loops, LLM creates extra practice problems and explanations Personalized Projects: LLM designs custom projects based on student interests (gaming, finance, social media, etc.) Interactive Code Review: Al mentor provides instant, detailed code feedback and suggests improvements Smart Hint System: Context-aware hints that guide students without giving solutions
6-Phase Structure (LLM-Adaptive)
Phase 1: Basics - LLM teaches variables, data types through interactive examples Phase 2: Control flow - Al generates custom logic puzzles and games Phase 3: Data handling - LLM creates exercises with real datasets student chooses Phase 4: Libraries & APIs - Al builds lessons around APIs student wants to explore Phase 5: Advanced concepts - LLM adapts complexity based on student mastery Phase 6: Specialization - Al creates custom track based on career goals
Browser-Based Interactive Features
* LLM Code Tutor: Al explains every error, suggests fixes, teaches debugging * Dynamic Exercise Generator: Unlimited practice problems created on-demand
* Interactive Explanations: LLM breaks down complex concepts with custom analogies *Live Code Execution: Run Python directly in browser with Al-powered environment *Smart Project Builder: LLM guides students through building apps step-by-step Al-Powered Assessment
*Intelligent Testing: LLM creates custom quizzes based on individual knowledge gaps *Code Quality Analysis: Al reviews style, efficiency, and best practices automatically *Portfolio Curation: LLM helps students select and present their best work *Interview Prep: Al generates coding challenges similar to real job interviews LLM Learning Support
* 24/7 Al Mentor: Always-available tutor that knows student's complete learning history *Concept Visualization: LLM creates custom diagrams and animations to explain difficult topics
* Error Prevention: Al predicts common mistakes and provides proactive guidance *Learning Path Optimization: Continuously adjusts curriculum based on performance data Specialization Tracks (Al-Customized)
AI/ML Track: LLM teaches machine learning through building actual Al tools Web Development: Al guides creation of full-stack applications Automation Track: LLM helps automate student's real work/personal tasks Data Science: Al teaches analysis using datasets relevant to student's field
Success Metrics
Students complete 5-10 Al-guided projects, automate real tasks, pass LLM-generated coding interviews, and build portfolio showcasing practical Python skills for Al-enhanced workflows.
Technical Requirements
*Cloud Python Environment: No installation needed, runs entirely in browser
* LLM Integration: GPT-4/Claude-level Al for intelligent tutoring and content generation
* Real-time Feedback: Instant code analysis and educational responses
Progress Tracking: Al monitors learning patterns and adjusts accordingly
* Mobile Responsive: Full course accessible on any device

Забираем и учимся бесплатно.

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Выводим свою продуктивность на новый уровень — эти 3 промта забустят вашу работоспособность.

1. Декомпозиция рабочего процесса:

Break down the process of [task] into: (1) prerequisite knowledge needed, (2) step-by-step workflow, (3) common failure points, and (4) quality checkpoints. Format as an actionable guide.

2. Матрица приоритета задач:

Evaluate these features: [list]. For each, score 1-10 on: user impact, development effort, business value, and technical risk. Calculate a priority score and explain the top 3 recommendations.

3. Ускорение обучения любому навыку:

I want to master [skill/topic]. Create: (1) a 30-day learning roadmap, (2) 5 hands-on projects to build competency, (3) key resources and communities, and (4) milestone checkpoints to track progress.

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Чудеса нового iPhone: ролики на 17 Pro выглядят настолько профессионально, что даже трясущиеся руки и максимальный зум не влияют на качество картинки.

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Студенты, разбираем: OpenAI выложили 100 промтов для учебы, работы и повседневной жизни.

Внутри инструкции для ускорения работы над курсовой, изучения любой темы или поиска нового хобби.

Забираем по ссылке.

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