Ace Your JEE Mains

Category: Technology / Future Trends Reading Time: 12 Minutes Look around you right now. Whether you are squeezing onto the Delhi Metro during rush hour, sitting in a bustling café in Bengaluru, or even gathering around the dinner table with family, the scene is identical. Heads down. Necks bent at an unnatural 45-degree angle. Eyes glazed over, glued to glowing rectangular slabs of glass and aluminum. For the last 15 years, the smartphone has been the undisputed center of our universe. It is our map, our wallet, our television, our therapist, and our connection to the world. It is a "Black Mirror" that demands our undivided attention. But if you look closely at the hardware trends of early 2026, a massive, tectonic shift is underway. The era of the screen-obsessed "smartphone zombie" is peaking, and we are entering the age of Invisible Computing . For the readers of Atharv Gyan , who look beyond the hype of the latest iPhone release, this is not just about new ga...

Ethical Considerations in AI Development Artificial Intelligence (AI) is a rapidly evolving field that promises significant advancements across various sectors, including healthcare, finance, transportation, and education. However, the development and deployment of AI technologies also raise substantial ethical concerns. These concerns include issues of bias, privacy, and the necessity for stringent ethical guidelines in AI research and development. Addressing these ethical considerations is crucial to ensure that AI technologies are developed and used responsibly, fairly, and for the benefit of all. Bias in AI One of the most pressing ethical issues in AI development is bias. AI systems learn from data, and if the data used to train these systems is biased, the resulting AI can perpetuate and even exacerbate these biases. Bias in AI can manifest in various ways, from discriminatory hiring algorithms to biased law enforcement tools. Sources of Bias Bias in AI can originate from several...

Explore how quantum algorithms can enhance cybersecurity through quantum random number generators and other advanced cryptographic techniques. Discuss the potential for quantum computers to break current encryption methods and the future of quantum-resistant cryptography. Quantum computing is a rapidly advancing field with significant implications for cybersecurity. Exploration of how quantum algorithms can enhance cybersecurity and the potential impact of quantum computers on current cryptographic methods, along with the future of quantum-resistant cryptography. Quantum Random Number Generators (QRNGs) Enhancing Security with True Randomness: Traditional Random Number Generators (RNGs): Most current RNGs are pseudo-random, meaning they rely on algorithms to generate numbers that appear random but are actually deterministic if the initial conditions are known. Quantum Random Number Generators: QRNGs leverage the inherent unpredictability of quantum mechanics to produce true randomnes...