Show Notes
In this episode of SparX, Mukesh Bansal takes a hard look at the state of India’s deep tech ecosystem. While the world races ahead with AI, semiconductors, and frontier science, India is at a crossroads: will we be creators of technology, or just consumers? Mukesh argues that true deep tech is only possible when rooted in deep science, a culture of research, curiosity, and discovery. He unpacks why India risks being left behind if we don’t invest in science the way the US, Europe, and China have, and what it will take for India to build original IP, Nobel-worthy science, and globally competitive deep tech companies. He explores: Why India’s dependence on foreign tech poses a strategic risk.
The looming threats to IT services and startup ecosystems.
How India can move from “Make in India” to “Discover in India, Invent in India, then Make in India.”
Lessons from history: how breakthroughs in physics, AI, and the internet all started with curiosity-driven science.
What it will take for India to aspire to Nobel Prizes, original IP, and world-class innovation.
This is not just about technology, it's about India’s future. If you care about Viksit Bharat, scientific ambition, and the next wave of innovation, this video is a must-watch.
More from SparX by Mukesh Bansal
AI is getting better at answering questions. But what happens when it starts asking and solving the questions scientists haven’t answered yet?In this episode of SparX, Mukesh Bansal sits down with Paras Chopra, founder of Wingify and Lossfunk, to explore AI research, scientific discovery, consciousness, and India’s place in the global AI race.
AI is getting better at answering questions. But what happens when it starts asking and solving the questions scientists haven’t answered yet?In this episode of SparX, Mukesh Bansal sits down with Paras Chopra, founder of Wingify and Lossfunk, to explore AI research, scientific discovery, consciousness, and India’s place in the global AI race.
What will it take to build robots that can truly operate in the real world? 🤖
What does the roadmap to a "Viksit Bharat 2047" look like from the very top? 🇮🇳In this special episode of SparX, Mukesh Bansal is joined by Professor Ajay Sood, the Principal Scientific Adviser to the Prime Minister of India. As a key architect of India’s scientific policy and a Padmashri awardee, Professor Sood offers an exclusive look into the government’s strategic vision for technology as the ultimate pillar of national sovereignty and economic growth.From the explosion of space-tech startups like Skyroot to the revolutionary ₹1 Lakh Crore R\&D fund, we dive deep into the missions that are positioning India as a global leader. We explore the critical convergence of AI and Quantum Computing, the strategic importance of Semiconductor Mission 2.0, and how India is navigating complex geopolitical supply chains.Whether you are a deep-tech entrepreneur, a student of science, or curious about India's technological future, this conversation provides a masterclass on the "Golden Age of Indian Science."In this episode, we discuss:The Vision for 2047: How Science & Tech are the primary engines for a developed India.Deep Tech Sovereignty: Why India must choose its global partners carefully while building indigenous strength.The Quantum Leap: India’s proactive National Quantum Mission and its synergy with AI.Semiconductors & Nuclear Energy: Building a full-fledged ecosystem and the future of Fusion energy.Democratizing Science: The "One Nation One Subscription" initiative and creating a culture that celebrates science like a festival.
Description- Is superintelligence a few years away, and would we even notice if the systems we built started to matter morally?- Nick Bostrom is the philosopher who put superintelligence on the map. His 2014 book defined the field, and his recent Deep Utopia asks the harder question: what is life for once machines can do everything better than us?- In this episode of Sparks, he tells [Host] that we don't have superintelligence yet but are seeing limited forms of AGI, that frontier labs using AI to accelerate their own research could trigger recursive self-improvement, and that he can no longer rule out timelines of just a few years. He argues the outcome is likely to be either very good or very bad, walks through the three ways it fails, and explains why he now works on problems that only matter over the next 6 to 18 months — philosophy, as he puts it, with a deadline.-We also get into full unemployment as a destination rather than a disaster, what an education system looks like when it isn't producing workers, why suppressing deception in a model makes it more likely to claim consciousness, and why building trust with AI systems now may be a safety measure rather than sentiment.