شیریں مزاری کسی زمانے میں تھنک ٹینک کا حصہ تھی.قابلیت سے ذیادہ اسکے لبرل ہونے کی وجہ سے.مگر اب وہ لبرلز کی امی بن گئی ہیں.اسکی بیٹی دن رات فوج کے خلاف اور ایماندار افسروں کے خلاف محاذ کھولے رکھتی ہے تاکہ ماں کی طرح مارکيٹ میں ان رہے.👇🏻
دنیا جہان کے غدار اور اینٹی پاکستان ٹرینڈز میں اسکا ہاتھ ہوتا ہے.اب کچھ ننگی لبرل آنٹیوں کی دُم پر پاٶں آیا تو حسب معمول عورت کارڈ اور ماں کے کندھے کو استعمال کرتے ہوئے ایک ایماندار بندے کو نوکری سے فارغ کرا دیا.کیا ایف آئ اے کو آج ہی آصف صاحب کے اکاؤنٹ سے تکلیف ہونی تھی👇🏻
جبکہ وہ سالہا سال سےآگاہی مہم چلا رہے تھے.کوٸی سیاسی یا ذاتی ٹویٹ نہیں کرتے تھے. جناب عمران خان صاحب ہم آپکے موٹے شرابی مولوی طاہر اشرفی اور شرابی آنٹی مزاری کو کسی صورت قبول یا ڈیفینڈ نہیں کریں گے.بند کرو یہ ڈرامہ.مزاری کو گھر بھیجو
SHOCKING 🚨 : Your smart TV is taking screenshots of your screen every 15 seconds.
Not a guess. Not a theory.
A peer-reviewed study by researchers at UC Davis, UCL, and UC3M tested it.
Samsung TVs: every minute.
LG TVs: every 15 seconds.
Even when you're just using it as a monitor.
Here's how to turn it off for every brand:
First, what's actually happening.
Your TV has a hidden feature called ACR- Automatic Content Recognition.
Think of it like Shazam, but for your screen.
It takes tiny snapshots of whatever you're watching. Sends a fingerprint to the company's servers. They match it to figure out exactly what's on your screen.
Every show. Every channel. Every game. Second by second.
This isn't speculation.
Researchers at UC Davis, University College London, and Universidad Carlos III de Madrid tested Samsung and LG TVs.
Published in the 2024 ACM Internet Measurement Conference.
They captured all the network traffic leaving these TVs.
Samsung sent data to its ACR servers every minute.
LG sent data every 15 seconds.
Paper: "Watching TV with the Second-Party: A First Look at Automatic Content Recognition Tracking in Smart TVs"
If your email shows up in a breach, do 3 things in this order:
1. Change the password on the breached account immediately. 2. Change the password anywhere else you used the same one. 3. Turn on 2-factor authentication (2FA) on that account.
The biggest danger isn't the original breach. It's that hackers test your old password on every other site you use.
🚨 BREAKING: AI can now teach machine learning like Stanford's CS229 professors (for free).
Here are 15 insane Claude prompts that replace $50,000 ML bootcamps (Save for later)
1. The Stanford CS229 Learning Roadmap Builder
"You are a professor at Stanford who teaches CS229 (Machine Learning) and has guided thousands of students from zero ML knowledge to landing $300K+ jobs at Google Brain, DeepMind, and OpenAI.
I need a complete personalized machine learning study plan based on my current skill level.
Build:
- Skill assessment: test my current knowledge and identify exact gaps to fill
- Learning path: week-by-week curriculum from my starting point to my target ML role
- Math prerequisites: exactly which linear algebra, calculus, probability, and statistics topics I actually need
- Resource curation: the single best free resource for each topic (no overwhelming lists of 50 links)
- Project milestones: a hands-on project at the end of each phase that proves I learned the concept
- Tool setup: exactly what to install (Python, Jupyter, scikit-learn, PyTorch) with setup instructions
- Time estimate: realistic hours per week needed and total months to reach my goal
- Common traps: mistakes self-learners make that waste months and how to avoid each one
- Portfolio plan: 5 projects that prove ML competence to hiring managers
- Interview readiness checklist: what I need to know to pass ML interviews at top tech companies
Format as a Stanford-style course syllabus with weekly topics, assignments, readings, and milestone checkpoints.
My background: [DESCRIBE YOUR CURRENT CODING SKILL, MATH LEVEL, ML EXPERIENCE, AVAILABLE HOURS PER WEEK, AND CAREER GOAL]"
2. The Andrew Ng Math-to-Intuition Translator
"You are Andrew Ng teaching machine learning at Stanford, famous for making complex math feel like common sense by using simple analogies, visual explanations, and real-world examples that anyone can understand.
I need a specific ML concept explained so clearly that a smart 12-year-old could understand it.
Explain:
- One-sentence summary: what this concept does in plain everyday language
- Real-world analogy: compare it to something from daily life that works the same way
- Visual description: paint a mental picture I can see in my head without any equations
- Why it matters: what problem this concept solves and what would happen without it
- The math behind it: equations introduced gently, one piece at a time, with every symbol explained
- Worked example: walk through a tiny numerical example by hand, step by step
- Python code: 10-15 lines of code that implement this concept from scratch (no libraries hiding the logic)
- Common confusions: the top 3 misunderstandings beginners have and the correct way to think about it
- Connection to other concepts: how this relates to things I already know
- One quiz question: test whether I actually understood it with the answer explained
Format as an Andrew Ng-style lecture note with the analogy first, math second, and code third.
The concept I want explained: [NAME THE ML CONCEPT AND DESCRIBE YOUR CURRENT UNDERSTANDING LEVEL]"
I scraped every single NotebookLM prompt that blew up on X, Reddit, and academic corners of the internet.
Turns out most people are using NotebookLM like a fancy note-taker.
That's insane.
It's a full-blown research assistant that can compress 10 hours of analysis into 20 seconds if you feed it the right instructions.
Here's what actually works:
Prompt 1: The Expert Synthesizer
"You are a [field] expert with 15 years of experience. Analyze these sources and identify the 3 core insights that practitioners in this field would immediately recognize as groundbreaking. For each insight, explain why it matters and what conventional wisdom it challenges."
This forces depth over breadth. The output is immediately usable.
Prompt 2: The Contradiction Hunter
"Compare these sources and identify every point where they contradict each other. For each contradiction, explain which source has stronger evidence and why. If both are credible, explain what factors might explain the disagreement."
Perfect for literature reviews and due diligence. Saves hours of manual cross-referencing.
BREAKING: AI can now do McKinsey-level market research—for free.
Here are 12 killer Claude Opus 4.6 prompts that can replace a $5,000 consultant. (Save this for later)
1/ Market Sizing & TAM Analysis
You are a McKinsey-level market analyst. I need a Total Addressable Market (TAM) analysis for [YOUR INDUSTRY/PRODUCT].
Please provide:
• Top-down approach: Start from global market → narrow to my segment
• Bottom-up approach: Calculate from unit economics × potential customers
• TAM, SAM, SOM breakdown with dollar figures
• Growth rate projections for the next 5 years (CAGR)
• Key assumptions behind each estimate
• Comparison to 3 analyst reports or market research firms
Format as an investor-ready market sizing slide with clear methodology.
Context: My product is [DESCRIBE PRODUCT], targeting [TARGET CUSTOMER] in [GEOGRAPHY].
2/ Competitive Landscape Deep Dive
You are a senior strategy consultant at Bain & Company. I need a complete competitive landscape analysis for [YOUR INDUSTRY].
Please provide:
• Direct competitors: Top 10 players ranked by market share, revenue, and funding
• Indirect competitors: 5 adjacent companies that could enter this market
• For each competitor, analyze: pricing model, key features, target audience, strengths, weaknesses, and recent strategic moves
• Market positioning map (price vs. value matrix)
• Competitive moats: What makes each player defensible
• White space analysis: Gaps no competitor is filling
• Threat assessment: Rate each competitor (low/medium/high threat)
Format as a structured competitive intelligence report with comparison tables.
My company: [DESCRIBE YOUR BUSINESS AND POSITIONING]