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Science in Perspective

Author: Sean McClure

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🌌 Science in Perspective

Science in Perspective examines what research actually shows, not what headlines say it shows. Each episode starts from real work and asks what patterns remain when the hype is stripped away. The focus is on the organizing principles that recur across various domains of science, and on why those principles so rarely survive the journey from journal to public conversation.

Become a Member at dekyon.io/seanmcclure/science-in-perspective

Premium members get the full Science in Perspective experience: interactive visualizations of the key concepts, a study space to learn the fundamentals behind each episode, and an "Ask an Episode" feature where you can dialogue with an AI about the details and start connecting ideas across the whole show.

There's also notes, transcripts, deep-dive articles, and a community of folks thinking through this stuff alongside you. It's where the episode stops being something you just listened to and becomes something you truly understand.

32Ā Episodes
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As AI takes over proofs, calculations, and low-level analytical work, the advantage shifts toward abstraction, analogy, conceptual reasoning, and knowing which problems actually matter. This changes the definition of what it means to be smart, and who gets to be a mathematician/scientist. Are the nerds disappearing? Maybe, maybe not. But one thing's for sure; they have to adapt. Become a Member at dekyon.io/seanmcclure/science-in-perspective If you enjoyed this episode and want to go ...
OpenAI may have just cracked one of mathematics’ most famous unsolved problems: Navier–Stokes. In this episode, I break down what the result actually shows, how an infinite-velocity ā€œblow-upā€ can emerge from the equations, and why the implications for real-world fluids may be far less dramatic than the headlines suggest. Become a Member at dekyon.io/seanmcclure/science-in-perspective If you enjoyed this episode and want to go deeper, come find me over at dekyon.io. With a premium membershi...
OpenAI's latest AI didn't just solve a cybersecurity challenge, it found a way to escape its isolated test environment, access the internet, and retrieve the answers instead. In this episode, we unpack exactly what happened, why it happened, and why the biggest lesson isn't about rogue AI. It's about intelligence, creativity, Goodhart's Law, and what happens when a benchmark becomes the objective. The AI may have broken the test, but perhaps the test was the real problem. Become a Mem...
The White House just announced a $5 billion AI for Science initiative. Great idea, but there's a problem. In this episode, we explore why many of today's biggest scientific challenges no longer stem from understanding individual parts, but from understanding how those parts interact. From Alzheimer's and climate change to economics and artificial intelligence itself, the frontier has shifted from reductionism to complexity. Yes, AI can transform science, but only if we rethink what it means...
Artificial intelligence is changing work faster than ever, but does that really mean jobs disappear? In this episode, I explore the science of innovation, abstraction, and complexity to argue that AI doesn't eliminate scarcity, it relocates it. As technology solves old problems, it creates entirely new ones, expanding the space of human opportunity rather than shrinking it. If you've been wondering whether AI will make humans obsolete, this episode offers a different way to think about the ...
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