In this episode I discuss Google’s new Willow chip and its claim of quantum supremacy — what the experiment actually did, why the benchmark still reflects classical thinking, and why forcing quantum systems to behave like deterministic machines misses their true potential. Instead of celebrating speed alone, we explore the deeper question: should quantum computing aim to mimic classical algorithms, or unlock genuinely emergent behavior the way nature does?

Suggested Reading
https://www.nature.com/articles/d41586-025-03300-4 (nature announcement)
https://arxiv.org/abs/2510.19550 (Google's echo paper)

https://www.nature.com/articles/s41557-025-01908-7.pdf (Vibronic coupling paper)

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In this video I discuss how three seemingly unrelated studies—from quantum time crystals to galactic vortices to heart rhythms—reveal the same underlying pattern of emergence, where mathematics itself generates new structures through feedback and interaction.

Suggested Reading:
https://arxiv.org/pdf/2503.16141
https://arxiv.org/pdf/2501.02297
https://bmcsystbiol.biomedcentral.com/articles/10.1186/s12918-017-0422-4

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In this episode I discuss geoengineering, focusing on the UK’s proposed aerosol project to reflect sunlight and reduce global temperatures. I explain the greenhouse effect and why gases like CO₂ and methane trap heat, before turning to the deeper issue of naive intervention—our tendency to assume linear, one-to-one outcomes in inherently complex systems. I discuss the concept of causal opacity, where true causes in interconnected systems are inaccessible, and emphasize nonlinear dynamics as the universal mechanism driving unpredictable side effects and potential collapse. The larger point is that policy and science must respect complexity rather than oversimplify it.

Suggested Reading

https://www.theguardian.com/environment/2025/apr/22/uk-scientists-outdoor-geoengineering-experiments

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In this episode I discuss how governments are adopting AI, the tradeoff between predictability and creativity, and how debate-inspired meta structures could guide AI toward more reliable truth.

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In this episode I discuss how math’s usefulness often comes from our gamified world rather than nature’s complexity, and why real learning depends on memory and abstraction. True progress, I argue, comes from raising levels of abstraction and operating at higher layers of thought rather than focusing on low-level tricks.

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In this episode I discuss two complementary forms of resilience: the delocalization that allows systems to spread out and resist noise, and the pattern formation that provides stability and meaning. Using random matrix theory as a lens, I show how both forms must work together across physics, biology, AI, and even daily life.

Suggest Reading
https://arxiv.org/abs/2506.06441

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In this episode, I talk about the phenomenon of dark electrons in exotic materials, how they emerge from hidden states of matter, and why they may play a central role in superconductivity. I also explore the broader idea that much of nature operates in ways that remain hidden from our usual scientific tools.

Suggested Reading:
https://arxiv.org/pdf/2507.07533

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Suggested Reading
https://arxiv.org/pdf/2411.11568
https://tinyurl.com/y2wdred5

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