Dive into the cutting-edge worlds of technology and science with Dwarkesh Patel's meticulously researched interviews that bring together brilliant minds to unpack revolutionary ideas in AI, biotech, and beyond. Each episode delivers profound, thought-provoking conversations that challenge conventional wisdom and illuminate the paths shaping humanity's future.

Dwarkesh Podcast

Sadhguru's biking journey to Mount Kailash post-brain surgery: A testament to human resilience

Sadhguru's call to view India as a civilization, not a nation, at IIT2026 meet

Sadhguru's AI hologram tech at Mahashivratri 2026: A game-changer for spiritual engagement

What inspired your decision to embark on a challenging biking journey to Mount Kailash so soon after brain surgery?

Can you elaborate on your perspective of India as a civilization, not just a nation, and its global significance?

How do you envision the future of AI in spiritual practices, especially after your Mahashivratri hologram initiative?

Conversations about science, technology, history, philosophy and the nature of intelligence, consciousness, love, and power. Lex is an AI researcher at MIT and beyond.

Lex Fridman Podcast

Join billionaire entrepreneur Nikhil Kamath in People by WTF for unfiltered, insightful chats with global icons who are redefining industries, from tech innovators to business titans. Each episode peels back the layers of success, revealing raw stories of grit, strategy, and disruption that inspire aspiring leaders to think bigger. Whether you're a startup founder or a curious mind, this podcast delivers the motivation and wisdom to fuel your own path to excellence.

People by WTF

Join neuroscientist, philosopher, and five-time New York Times best-selling author Sam Harris as he explores important and controversial questions about the mind, society, current events, moral philosophy, religion, and rationality—with an overarching focus on how a growing understanding of ourselves and the world is changing our sense of how we should live. Sam is also the creator of the Waking Up app. Combining Sam’s decades of mindfulness practice, profound wisdom from varied philosophical and contemplative traditions, and a commitment to a secular, scientific worldview, Waking Up is a resource for anyone interested in living a more examined, fulfilling life—and a new operating system for the mind. Waking Up offers free subscriptions to anyone who can’t afford one, and donates a minimum of 10% of profits to the most effective charities around the world. To learn more, please go to WakingUp.com.  Sam Harris received a degree in philosophy from Stanford University and a Ph.D. in ne

Making Sense with Sam Harris

Contrary to expectations of rapid depreciation due to technological advancements, an H100 GPU is worth more today than three years ago because it can now run more advanced AI models that generate significantly higher value, such as GPT-5.4 compared to GPT-4. This dynamic highlights how compute value increases with model improvements in a capacity-constrained environment, benefiting early committers like OpenAI over more conservative players like Anthropic.

By 2030, the primary bottleneck for scaling AI compute will shift to ASML's EUV lithography tools, with production limits potentially capping cumulative AI chip capacity at around 200 gigawatts, challenging ambitious goals like Sam Altman's vision of deploying a gigawatt per week amid the ongoing AI boom.

Despite ambitious demands for massive AI compute scaling, such as Elon Musk's 100 gigawatts per year by 2028, the semiconductor supply chain lags far behind due to insufficient AGI-driven production ramps and architectural inefficiencies, making reliance on older 7nm processes inadequate for bridging the gap. This highlights a critical bottleneck in AI advancement, where performance differences between chip generations can reach 20x due to networking and data movement constraints, not just raw FLOPS.

Why is TSMC allocating the majority of its 3nm process capacity to Nvidia rather than diversifying among competitors like Google or Amazon to fracture the market and maintain leverage?

What prevents ASML from significantly increasing its production of EUV tools beyond 100 per year by 2030, despite the explosive demand for AI chips?

Given the compounding performance advantages of newer chip architectures, what fraction of the demanded AI compute could realistically be achieved by repurposing older 7nm fabs, and under what economic conditions would this become viable?

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