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Few years back when I was working as a QA engineer for a MNC, a Devops Engineer casually asked me a question that really made me to pause. “Is QA even a technical job?” He didn’t mean to insult me. But this question made me to think about my role that I am working. Sure, I’m not into developing— like writing a complicated code for a feature. I don’t build or maintain CI/CD pipelines like devops engineers do. The more I thought about it, the more I realized — while my tasks may differ, the depth of technical understanding required in QA is just as significant.
In today’s fast-moving work culture, we’ve come to rely on our calendars to keep everything in order — meetings, tasks, appointments, deadlines. But somewhere along the way, the calendar that was meant to help us has started hurting our productivity. It’s become common to see a workday fully booked with back-to-back meetings, leaving little to no time for actual work. A few days ago, I was chatting with a friend who works at a large tech company. He sounded frustrated. He said, “I’ve been stuck in meetings all day — I don’t even have time to start the task I was supposed to finish by EOD.” That really stuck with me, because it’s not just his story — it’s a reality for so many professionals today.
The problem when we generate image is that we use it like a slot machine, we keep prompting and prompting, hoping the AI spit out an image that’s close to our imagination. You need to engineer prompts, just like cinematographers plan a scene.
Building a cost-efficient AI coding assistant doesn’t have to mean paying for expensive subscriptions. This article explores how developers can combine Continue.dev with DeepSeek’s affordable cloud API and Ollama’s local CodeLlama models to create a lightweight, hybrid coding assistant. The setup balances cloud power for complex reasoning with local models for fast autocompletion, all while keeping costs under control. Along the way, it highlights practical lessons—like avoiding config pitfalls, monitoring token usage, and leveraging discount pricing—that make AI-driven coding both effective and budget-friendly.
Solo Leveling is easy to binge because it wraps a familiar self-improvement fantasy in a slick action package. The world is overrun by “Gates” (dungeons), and “Hunters” with fixed ranks—from E to S—fight back. Sung Jin-woo begins as an E-rank, the weakest of the weak, until a mysterious System appears and gives him video-game-style quests, stats, and an inventory. From there, he does the most unglamorous thing imaginable: daily work. Reps. Miles. Recovery. It’s anime, not a documentary, but the appeal is real: the show zooms in on incremental change until it’s visible. That’s the core productivity lesson—small, consistent upgrades compound into transformation.
NASA’s Perseverance rover has uncovered its strongest hints yet that Mars may once have supported life, drilling a rock core (“Sapphire Canyon”) that shows mineral and organic patterns resembling Earth’s microbial biosignatures. While not definitive proof, the find strengthens the case for ancient habitability and underscores the importance of returning samples to Earth for deeper study. The evidence is tantalizing, but true confirmation awaits further analysis.
A nostalgic reflection on childhood summers spent at a grandmother’s home, filled with laughter, family bonding, and simple joys. Contrasted with today’s fast-paced, screen-driven lives, this piece is a gentle reminder to slow down, breathe, and cherish the small moments that truly matter.
existential crisis and burning out
Nano Banana, Google’s Gemini 2.5 Flash Image model, sets itself apart in the crowded AI image space with unmatched speed, realism, and subject consistency. Delivering lifelike edits in 1–2 seconds, it outpaces rivals like DALL·E 3, Midjourney, and ChatGPT-5, excelling at tasks like outfit swaps, background changes, and multi-step edits without losing identity details.
This is an article related with Chromium Embedded Framework