Tech Questers

Tech Questers

5/18/2025, 7:46:45 AM

I can't believe people still spend hours on problem-solving when there is AI. (And no. I'm not talking about basic problem solving) *Problem solving becomes efficient when humans and AI work together.* ✅ Write a prompt ✅ Get a solution from ChatGPT ✅ Follow up and keep brainstorming till you get the best solution *Problem-solving techniques on which you can collaborate with ChatGPT:* ✅ Decision Matrix: Compare options based on weighted criteria. ✅ Force Field Analysis: Analyze forces for and against a change. ✅ SWOT Analysis: Evaluate strengths, weaknesses, opportunities, and threats. ✅ First Principles Thinking: Break down complex problems to fundamental truths. ✅ MECE Principle: Organize information into mutually exclusive, collectively exhaustive categories. And more covered in the infographic above. *@TechQuesters* *React ❤️ for more*

Tech Questers

5/17/2025, 7:25:50 PM

🚀 Supercharge Your Python Development with Meta's Pyrefly in VSCode 🐍 Meta has unveiled Pyrefly, a cutting-edge, open-source static type checker designed to enhance Python development. Built in Rust, Pyrefly offers lightning-fast performance, capable of analyzing over 1.85 million lines of code per second . Key Features: Speed & Efficiency: Rapid type checking accelerates development workflows. IDE Integration: Seamless integration with VSCode via the Pyrefly extension . Smart Type Inference: Supports both typed and untyped codebases, providing intelligent type suggestions. Early Error Detection: Identifies type errors during development, reducing runtime issues. Open Source: Available on GitHub for community collaboration . Currently in alpha, Pyrefly is set to exit this phase by summer 2025, aiming to replace Meta's existing Pyre type checker . 🔗 Get Started: Install via pip: pip install pyrefly Add the VSCode extension: Pyrefly Extension Explore more: https://shorturl.bz/pAg

Tech Questers

6/4/2025, 3:46:41 PM

*A–Z of Artificial Intelligence (AI)* A – Artificial Intelligence B – Backpropagation C – Classification D – Deep Learning E – Expert Systems F – Feature Engineering G – Generative Models H – Heuristics I – Inference J – Joint Probability K – K-Means Clustering L – Loss Function M – Machine Learning N – Neural Networks O – Overfitting P – Precision Q – Q-Learning R – Reinforcement Learning S – Supervised Learning T – Transfer Learning U – Unsupervised Learning V – Variational Autoencoder W – Weight Initialization X – XOR Problem Y – YOLO (You Only Look Once) Z – Zero-shot Learning *React ❤️ for detailed explanation of each concept*

Tech Questers

5/22/2025, 4:41:14 AM

https://www.linkedin.com/posts/tech-questers_googleio2025-projectastra-aiupdate-activity-7331175987671379968-SXLG?utm_source=share&utm_medium=member_android&rcm=ACoAADbbIRwBRu9z2-GZ4svYTxnAmjNUB9OuQDE

Tech Questers

5/15/2025, 12:16:30 AM

*Ai layoffs* Six months into 2025, over 50,000 tech workers have already been laid off, with giants like Microsoft, Google, Meta, IBM, PwC, and Chegg Inc. making headlines. While AI is often cited as the culprit, insiders say the reality is more complex—part efficiency, part financial recalibration. At Microsoft, nearly 6,000 employees were let go, including a veteran developer who spent 18 years at the company and played a key role in making TypeScript 10x faster. Meanwhile, CEO Satya Nadella revealed that AI now writes 30% of the company’s code, sparking debate on whether fewer engineers are needed to scale. Experts like Deedy Das (Menlo Ventures) say the layoffs are less about AI taking jobs and more about funding massive AI infrastructure bets. “This isn’t about AI replacing humans yet—it’s about restructuring to fund AI initiatives,” echoed Wes Roth, citing Microsoft’s planned $80B AI spend this year. While companies like IBM are replacing HR roles with AI, they’re also hiring more engineers and sales

Tech Questers

6/2/2025, 2:30:48 AM

♟️🇮🇳 Historic Checkmate Moment for India at Norway Chess 2025! At just 18, India’s rising chess sensation D Gukesh has stunned the global chess world by defeating World No. 1 Magnus Carlsen in a classical game — for the very first time in his career! 🎯 In Round 6, playing with the black pieces, Gukesh: 🔸Showcased brilliant strategy under pressure. 🔸Held strong in the endgame. 🔸Capitalized on a rare blunder by Carlsen. 🔸Sealed a historic classical win 🏆 👏 This victory is more than a game — it’s a statement from the youngest-ever world championship challenger, and a proud moment for Indian chess 🇮🇳 As Gukesh’s coach Grzegorz Gajewski shared, this is a massive confidence boost that fuels his path ahead. 💬 “India’s chess revolution continues — and Gukesh is leading the charge.” Jai Hind. Jai Bharat. 🫡 #TechQuesters #Dgukesh #MagnusCarlsen #NorwayChess2025 #ChessHistory #IndianChess #YoungChamp #MadeInIndia #ProudMoment #NextGenChampions #IndiaRising #HardWorkPaysOff #Gukesh #ChessVictory #YouthPower #Gukesh

Tech Questers

6/8/2025, 4:40:39 PM

🚨 India’s BIGGEST GenAI Challenge Is LIVE – and It’s 100% FREE! 🇮🇳⚡ OpenAI Academy 🧠 + NxtWave (NIAT) 💥 have just launched a nationwide Generative AI Innovation Challenge — and it’s exploding across campuses! 🎯 What’s happening? 🔸25,000+ students 🧑‍🎓 🔸500+ colleges 🏫 🔸7 states 🌏 🔸6 hours of expert AI workshops 📚 🔸GPT+ credits, certificates, and mentorship 🔥 And yes... NO registration fee! 🙌 This is your chance to learn, build, and shine in the world of Generative AI with backing from OpenAI’s learning ecosystem. 💥 Whether you're a beginner or a builder — this is where your AI journey begins. 📅 Register now → https://academy.openai.com/public/clubs/india-gkubq/events Let’s build India’s GenAI future. One student, one model at a time. 🇮🇳✨ #TechQuesters #OpenAI #NxtWave #NIAT #GenAIChallenge #AIBuildathon #FutureOfAI #FreeForStudents #AIForIndia #StudentInnovators #GPT #OpenAIChallenge #AIWorkshop #MadeInIndia

Tech Questers

6/7/2025, 2:01:08 AM

*Here's the detailed A–Z of Artificial Intelligence (AI)* A – Artificial Intelligence The broad field of computer science focused on building smart machines capable of performing tasks that typically require human intelligence, such as reasoning, learning, and decision-making. B – Backpropagation A core algorithm for training neural networks. It calculates the gradient of the loss function and updates the model’s weights to reduce error, using the chain rule of calculus. C – Classification A type of supervised learning where the goal is to assign input data into predefined categories (e.g., spam vs. not spam). D – Deep Learning A subfield of machine learning involving neural networks with many layers (deep neural networks). It’s powerful for tasks like image and speech recognition. E – Expert Systems Early AI systems designed to emulate the decision-making ability of a human expert using rules and logic (if-then statements). F – Feature Engineering The process of selecting, modifying, or creating new input features to improve the performance of machine learning models. G – Generative Models Models that can generate new data samples that resemble the training data, such as GANs (Generative Adversarial Networks) or VAEs (Variational Autoencoders). H – Heuristics Problem-solving techniques that use practical methods or shortcuts to produce good-enough solutions when exact methods are impractical. I – Inference The phase where a trained model is used to make predictions or decisions based on new input data. J – Joint Probability The probability of two or more events happening together. Important in probabilistic models like Bayesian Networks. K – K-Means Clustering An unsupervised learning algorithm that partitions data into K distinct clusters based on similarity. L – Loss Function A function that measures how well a machine learning model performs. Lower loss means better predictions. Common examples: MSE, Cross-Entropy. M – Machine Learning A subset of AI that allows systems to learn from data and improve from experience without being explicitly programmed. N – Neural Networks Inspired by the human brain, these are networks of interconnected nodes (neurons) used in deep learning for tasks like image and language processing. O – Overfitting A modeling error that occurs when a model learns the training data too well—including noise and outliers—resulting in poor performance on new, unseen data. P – Precision A metric used to evaluate classification models: the ratio of true positives to all predicted positives. Measures how accurate positive predictions are. Q – Q-Learning A reinforcement learning algorithm where agents learn to take optimal actions by maximizing expected future rewards using Q-values. R – Reinforcement Learning A type of learning where an agent interacts with an environment, learns from rewards and penalties, and aims to maximize cumulative reward. S – Supervised Learning A machine learning approach where the model is trained on labeled data, learning the mapping between input and known output. T – Transfer Learning A technique where a model trained on one task is reused or fine-tuned for a related task—especially useful in deep learning. U – Unsupervised Learning Learning patterns from data without labels. The model tries to uncover hidden structures, like clustering or association rules. V – Variational Autoencoder (VAE) A type of generative model that encodes input into a distribution, allowing it to generate new similar data. Useful in image generation and anomaly detection. W – Weight Initialization Setting initial weights in neural networks. Proper initialization helps speed up training and avoids issues like vanishing gradients. X – XOR Problem A classic problem in AI that shows the limitation of simple perceptrons. It can’t be solved without introducing hidden layers (non-linearity), which led to the development of modern neural networks. Y – YOLO (You Only Look Once) A fast, real-time object detection algorithm that processes an image only once to detect multiple objects with high speed and accuracy. Z – Zero-shot Learning A technique where a model can recognize objects or perform tasks it has never seen during training, by learning from relationships or descriptions. *React ❤️ for more*

Tech Questers

5/15/2025, 4:42:37 AM

Anthropic just dropped a Bible for AI Agent Developers — and it’s pure gold. If you're building autonomous agents, this isn't just a good read — it's a must. It’s packed with real-world coding + deployment strategies that separate toy projects from production-grade AI systems. Here’s your quick summary (🔖 save this): 1. Agent design ≠ prompting It’s not just about clever prompts anymore. Build structured workflows: reason → act → reflect → retry → escalate. 2. Memory is architecture Context = power. Use structured summaries, scoped retrieval, and smart storage. Prompt-dumping is obsolete. 3. Planning isn’t optional Multi-step problems need plan → execute → review systems. No matter what model you use — Claude, GPT, or Gemini. 4. Real agents need real tools Shell access. Git. APIs. Plugins. Let your agents execute — not just explain. 5. ReAct & CoT aren’t magic tricks They’re patterns to engineer in. Structure your agents to think first, act later, reflect always.

Tech Questers

5/14/2025, 3:55:04 AM

🖥️ Must-Know VS Code Shortcuts for Faster Coding! 🚀 Boost your coding speed with these powerful VS Code shortcuts! ⌨️💡 ✅ General ➜ Open Command Palette: Ctrl + Shift + P ➜ Open Settings: Ctrl + , ➜ Save File: Ctrl + S ➜ Save All Files: Ctrl + K, S ✅ File & Tab Navigation ➜ Quick Open File: Ctrl + P ➜ Switch Between Open Files: Ctrl + Tab ➜ Close Current Tab: Ctrl + W ➜ Reopen Closed Tab: Ctrl + Shift + T ➜ Split Editor: Ctrl + \ ✅ Code Editing ➜ Copy Line: Ctrl + C ➜ Cut Line: Ctrl + X ➜ Paste Line: Ctrl + V ➜ Duplicate Line: Shift + Alt + ↓ / ↑ ➜ Delete Line: Ctrl + Shift + K ➜ Comment/Uncomment Line: Ctrl + / ➜ Format Document: Shift + Alt + F ✅ Search & Navigation ➜ Find in File: Ctrl + F ➜ Find and Replace: Ctrl + H ➜ Go to Line: Ctrl + G ➜ Go to Definition: F12 ➜ Rename Symbol: F2 ✅ Terminal & Debugging ➜ Open Terminal: Ctrl + ~ ➜ New Terminal: Ctrl + Shift + ~ ➜ Run Current File: Ctrl + F5 ➜ Debug: F5 ➜ Step Over: F10 ⚡ These shortcuts will save you HOURS! Try them now and code like a pro! 🚀 @TechQuesters ❤️😎