Greenwood High achieves stellar results
Bengaluru: Greenwood High International School continued its legacy of academic excellence, with its students achieving an extraordinary feat in Indian Certificate of Secondary Education (ICSE) Class X & Indian School Certificate (ISC) Class XII exam, the results of which were announced on Wednesday. In ICSE, the topper from the school is Pragati Girish Athreya who has scored 99.80%.
The other toppers from the school are Swarna Chaudhary, Aanya P Minnamareddy and Raghav Dixit who each scored 99.60%. In ISC, the toppers from the school are Arnay Gupta from Science with an aggregate of 99.50%, Sanidhya Kapoor from Commerce with 98.75% and Smayana Meswani in Humanities with 98.75 %.
Additionally, Deepthi Menon from Science scored 99.25%, Trisha Shub from Commerce scored 98.25% and Kaustubh Keshav & Ankita Padmanabh from Humanities scored 98.5% respectively.
'I'm truly proud and overjoyed with my ICSE results.
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Time of India
a day ago
- Time of India
Girls from rural India discover science and engineering at IIT Bombay through WiSE program
MUMBAI: In the hushed dawn of late May, buses rumbled into the gates of IIT Bombay. Inside them were not scholars or scientists, but girls—about two hundred of them, aged barely fifteen, their eyes adjusting to a future they had only seen in textbooks. They came from the hills of Karnataka, from the farms of Maharashtra, from homes where ambition often takes a backseat to expectation. For one extraordinary week, the campus would be theirs. The initiative was part of a quiet revolution unfolding at IIT Bombay—a programme called WiSE, or Women in Science and Engineering from Rural Parts of India. Conceived in 2023 and led by Prof. Rajesh Zele, WiSE began with a simple question: what if girls from rural India were given a glimpse—just a glimpse—of what a life in science could look like? While girls in India sit shoulder-to-shoulder with boys in classrooms through primary school, the road thins out after that. Social pressure, early marriage, and the burden of domestic expectations often force them off the path. They turn away from science—not for lack of interest, but lack of encouragement. Many settle for fields that promise flexibility, not fulfilment. WiSE aims to change that. From May 25 to 31, 2025, 200 girls from 68 rural schools arrived on campus, each carrying little more than a schoolbag and a flicker of possibility. Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like People Born 1940-1975 With No Life Insurance Could Be Eligible For This Reassured Get Quote Undo They stayed in Hostel 10, wandered the shaded corridors of an institution they'd only heard about in whispers, and lived a version of the future that might be theirs. What followed was not just a science camp—it was an emotional unlearning of the limits they'd been told to accept. Each day began not with equations, but with stories. Winspirers—a luminous panel of women from fields as wide-ranging as combat, cinema, law, literature, and medicine—shared what it meant to persist. Bollywood stuntwoman Geeta Tandon, with her sinewy grit, spoke of surviving violence and becoming fearless. Major Mohini Kulkarni, battle-hardened and resolute, recounted her tours through the Kashmir Valley. Judge Laxmi Rao brought alive the gravity of courtroom decisions, while Olympian Aparna Popat decoded the loneliness of elite sport. Dr. Dhanshree Lele, with the soul of a poet, reminded them that science and art aren't at odds. Dr. Ratna Raje, nutritionist, offered simple truths about eating well in complex times. Each voice added a new colour to the kaleidoscope of what was possible. Social worker Varsha Parchure spoke of upliftment, while photographer Aabha Chaubal gave courage to wander. Kalyani Deopujari, now a drone researcher with the Indian Military, talked of the many failures that came before success. In moments of tender honesty, psychiatrists Dr. Jahanvi and Rutaja Kedare spoke of adolescent pain—of anxiety, sadness, and the courage to seek help. Their words did not fall flat. They took root. But WiSE was not just about watching and listening. Each afternoon, the girls got to build—and break, and build again. Through the Break-Make-Programme (BMP), they turned screwdrivers with shaking fingers, then surer hands. On Day One, it was a light bulb circuit. Day Two, an FM radio. Then came sensors, actuators, and programming a microprocessor. By Day Five, they were assembling a Crab Rover Robot, a scuttling mechanical marvel they built from scratch, hardware and software alike. For many, it was the first time they'd touched wires, or typed code, or seen their fingers make something come alive. For some, it was the first time anyone told them they could. In between, IIT Bombay students showcased their own work during Demo Hours. The girls gaped at robotic arms mimicking human hands, studied colourful bacteria growing in intricate patterns, and watched underwater vehicles glide like fish with purpose. In these machines, the girls didn't just see engineering—they saw imagination turned real. Then came the evening of 30 May, when the guests became the hosts. The girls threw a felicitation ceremony-cum-talent show—aptly titled Thanksgiving—in honour of those who'd guided them. They danced in bright regional clothes, sang with unapologetic pride, and performed skits that sparkled with humour and wit. It wasn't polish that won the audience over—it was presence. They found their voice, and they were no longer shy about using it. Rajiv Joshi of the IEEE Board of Governors urged them to keep dreaming—boldly, stubbornly. Prof. Zele, whose quiet leadership held it all together, left them with a plea: Stay curious. Stand tall. Don't stop learning. But WiSE does not end when the week ends. IIT Bombay has committed to long-term mentorship. Each girl will continue to be guided through virtual check-ins every quarter—online meetings with students, teachers, and parents to keep the spark lit. The kits they used have been donated to their schools, turning these girls into science ambassadors for their communities. Much of this would not have been possible without the 70+ student volunteers, or the women teachers from Jawahar Navodaya Vidyalayas and Eklavya Model Residential Schools, who worked tirelessly behind the scenes. Nor without the institutional support of IEEE Circuits and Systems Society, and the visionary coordination of Commissioner T. Gopalakrishna (JNV) and Ravi Lad (EMRS). WiSE is not a campaign. It is not a box checked. It is a beginning. One week may not change the world, but it can change the way a girl sees herself in it. Especially when she learns that her hands can build, her voice can speak, and her future need not be decided for her. Especially when science finally begins to feel like home.
Mint
3 days ago
- Mint
Siddharth Pai: Can AI beat quantum computing at its own game?
For decades, quantum computing has been described as the 21st century's technological lodestar—with its unfathomable computational power poised to solve problems beyond the ken of classical machines. Quantum computers promise to crack cryptographic codes, simulate the quantum dynamics of molecules in material science, aid drug discovery and more. Yet, as the quantum race drags on, an unexpected challenger has emerged, not to dethrone but outpace it in precisely those domains where it was expected to shine the brightest: AI. To grasp the possibility of this disruption, begin with what quantum computing is. Unlike classical computers that encode information in binary bits—0s or 1s—quantum computers use quantum bits, or qubits, which can exist in a superposition of states. Also Read: Will AI ever grasp quantum mechanics? Don't bet on it Through entanglement and quantum interference, quantum computers can process a vast space of possibilities in parallel. This lets them model quantum systems naturally, making them ideal for simulating molecules, designing new materials and solving certain optimization problems. Among its most touted applications is its potential to transform material science. Advances with high-temperature superconductors, catalytic surfaces or novel semiconductors often require modelling the interactions of strongly correlated electrons—systems where the behaviour of one particle is tightly linked to that of many others. Classical algorithms falter in such simulations because the complexity of the quantum state space rises exponentially with system size. A full-fledged quantum computer would handle all this with ease. But the practical realization of quantum computing remains vexed. Qubits, whether superconducting loops, trapped ions or topological states, are exquisitely fragile. They 'decohere' (lose their quantum state) within microseconds and must be kept at temperatures colder than deep space. Error correction remains an uphill battle. Most of today's quantum machines can manage only a few hundred noisy qubits, far short of the millions needed for fault-tolerant computing. Also Read: Is Google's Willow really a 'wow' moment for quantum computers? In the meantime, artificial intelligence (AI), particularly deep learning, has made remarkable incursions into the same spaces. A turning point came in 2017 with a paper in Science by Giuseppe Carleo and Matthias Troyer ( Startling scientists, they found a neural network-based variational method to approximate the wave-function of quantum systems. This approach employed restricted Boltzmann machines to represent complex correlations among quantum particles, modelling the ground states of certain spin systems that had been hard to simulate classically. That paper didn't just introduce a new tool; it signalled a paradigm shift. 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Google's DeepMind, for instance, has begun integrating machine learning tools directly into quantum chemistry workflows. Startups in the quantum space often include AI-based pre-processing or error mitigation in their pipelines. Also Read: Underdelivery: AI gadgets have been a let-down but needn't be A complementary field is fast becoming a competing one. AI will not make quantum computing irrelevant in the absolute sense, as there will always be quantum phenomena that only quantum devices can fully capture, but AI may take the lead in many practical problems before quantum hardware matures. If machine learning models can deliver 90% of the performance at 5% of the cost and infrastructure, industrial users may not wait for perfection. Moreover, there's a subtler factor at play: a shift in intellectual capital. The more investment AI-based methods attract, the more resources will flow into neural modelling over quantum error correction. By the time quantum machines mature, many of the use-cases originally envisioned for them may have been absorbed by AI tools that ironically use quantum data or theory. Quantum computing risks becoming a beautiful idea outpaced by a merely competent but deployable alternative. There is an irony here that would not be lost on Schrödinger or Feynman: that the classical world, once deemed too simplistic in the face of quantum reality, might be reasserting itself through the statistical abstractions of machine learning. We set out to build a machine that thinks like nature. Instead, we taught our machines to imitate nature well enough to move forward without grasping it fully. Quantum computing may still prove indispensable. But it will have to justify its place in a world where its promise is being appropriated by its upstart cousin AI. The author is co-founder of Siana Capital, a venture fund manager.
Time of India
5 days ago
- Time of India
What is taurine, the anti-aging supplement going viral — and is it worth the hype?
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