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. Support the show Become a premium member to gain access to premium content, including the Techniques and Mindsets Videos, visual concept summaries of each episode, community ...
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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. Support the show Become a premium member to gain access to premium content, including the Techniques and Mindsets Videos, visual concept summaries of each episode, community ...
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 Become a Premium Member to get Premium Content and More science-in-perspectve.com or https://www.patreon.com/8431143/j...
Science in Perspective
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. Support the show Become a premium member to gain access to premium content, including the Techniques and Mindsets Videos, visual concept summaries of each episode, community ...
