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Showing posts from July, 2025

GM ignition switch issue causing 109-124 deaths

 The fault involved a defective ignition switch installed in several GM models (notably the Chevy Cobalt, Saturn Ion, Pontiac G5/Solstice, and Chevy HHR) between roughly 2003–2007. Here's what happened: --- 🧩 What the problem was The switch could unexpectedly move from the “Run” to “Accessory” or “Off” position if jostled by heavy keychains or vibrations, causing the engine to shut off while driving. That disabled: Power steering Power brakes Airbags—since airbags needed electrical power to deploy   GM engineers knew as early as 2001 (Saturn Ion prototype) and by 2004 (production vehicles) that the switch failed torque specifications, yet chose not to fix it, citing cost and inconvenience . --- ⚠️ Delayed recall and misclassification For years, GM classified it as a “customer convenience” issue—not a safety defect, which delayed urgent action . The first recalls occurred only in February 2014, after nearly a decade of ignoring internal warnings . --- 💔 Deaths, injuri...

Obsolescence risk and skill longevity in ECE. Compared with CSE

 We have covered **chip design, AI hardware, 6G, embedded systems, robotics**, and key tools (Verilog, Cadence, MATLAB, LTspice), alongside strategies to stay relevant.   --- ### **Classification of ECE Skills by Obsolescence Risk for 2030**   #### **1. Chip Design (VLSI/Semiconductors)**   - **Obsolescence Risk**: **Low-Moderate**   - **Half-Life of Skills**: **~7–10 years**   - **Reasoning for 2030**:     - Moore’s Law slowdown shifts focus to **specialized architectures** (e.g., chiplets, 3D ICs).     - Demand for **energy-efficient designs** (AI/edge devices) and **post-silicon tech** (GaN, SiC) grows.     - Tools evolve (Cadence → AI-driven EDA), but core principles (RTL design, verification) persist.   - **Strategies**:     - Master **Verilog/VHDL**, UVM for verification.     - Learn **AI-accelerated EDA tools** (e.g., Synopsys DSO.ai). ...

What part of your BTech CSE course will be relevant till 2030 ?

### **Estimating Obsolescence Risk and Longevity of CSE Skills for 2030** *(As of July 2025, tailored for 2029 graduates)* #### **1. Cybersecurity** - **Obsolescence Risk**: Low-Moderate - **Half-Life of Skills**: ~5–8 years - **Reasoning for 2030**: - Evolving threats (e.g., quantum attacks, AI-driven hacks) ensure sustained demand. - Core principles (encryption, authentication) remain stable, but tools evolve rapidly. - **Strategies to Stay Relevant**: - Certifications (CISSP, CEH, CompTIA Security+). - Learn AI-driven security, post-quantum cryptography, and zero-trust architectures. - Practice on platforms like TryHackMe; follow OWASP/DEF CON communities. - **2030 Outlook**: - Global cybercrime costs may exceed $20 trillion annually. - India’s DPDP Act and global regulations (GDPR, CCPA) will drive compliance roles. - High demand for AI security and quantum-resistant encryption specialists. **My Note**: Cybersecurity is a safe bet, ...

2029 projections for ECE, CSE, and Electrical Engineering BTech graduates

📊 Career Prospects in 2029 for BTech Graduates: ECE vs CSE vs Electrical Engineering As the global and Indian tech ecosystems evolve rapidly, students graduating in 2029 must choose their BTech specialization with insight and foresight. This article compares the three key streams— Computer Science Engineering (CSE) , Electronics & Communication Engineering (ECE) , and Electrical Engineering —with updated data for 2029, analyzing salaries, job opportunities, industry trends , and future potential. 💰 Salary Comparison (2029 Estimates) Stream Entry-Level Avg (India) Mid-Level (5–8 yrs, India) Entry-Level Avg (US/Abroad) Key Drivers Computer Science (CSE) ₹10–15 LPA ₹25–60 LPA $110K–160K Software, AI/ML, cloud, cybersecurity, product engineering Electronics (ECE) ₹5–8 LPA ₹12–25 LPA $80K–110K VLSI, semiconductors, AI hardware, 6G telecom, IoT Electrical Engg. ₹4–6 LPA ₹10–18 LPA $75K–105K Renewable energy, EVs, smart grids, infrastructure 🔍 In...

Tips to Learn Any Skill Effectively

Top 20 Evidence-Based Tips to Learn Any Skill Effectively Mastering a new skill — whether it's coding, painting, public speaking, or playing the piano — is not just about putting in the hours. It’s about how you spend those hours. Here are 20 science-backed principles and strategies to learn faster, retain better, and reach mastery. 1. Start with Early Wins Why: Early success builds motivation and momentum. Scenario: If you're learning guitar, learn to play a simple song like "Knockin’ on Heaven’s Door" in the first week. Feeling accomplished early keeps you motivated for harder parts later. 2. Tighten the Feedback Loop Why: Immediate and clear feedback helps you correct mistakes faster and reinforce learning. Scenario: A language learner uses an app like Duolingo or practices with a native speaker who immediately corrects their pronunciation or grammar. 3. Visualize Success (Mental Rehearsal) Why: Neuroscience shows the brain activates similar reg...