Geometry is one of the oldest disciplines in human history, yet the worlds it can describe extend far beyond its original use. What began thousands of years ago as a way to measure land and build pyramids was given rigor by Euclid in ancient Greece, became applied to curves and surfaces in the 19th century, and eventually helped Einstein understand the universe.Yang-Hui He sees geometry as a unifying language for modern physics, a mutual exchange in which each discipline can influence and shape the other. In the latest episode of The Joy of Why, He tells co-host Steven Strogatz how geometry evolved from its practical roots in ancient civilizations to its influence in the theory of general relativity and string theory — and speculates how AI could further revolutionize the field. They also discuss the tension between formal, rigorous mathematics and intuition-driven insight, and why there are two types of mathematicians — “birds” who have a broad overview of ideas from above, and “hedgehogs” who dig deep on one particular idea.
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Will AI Ever Understand Language Like Humans?
Large language models (LLMs) are becoming increasingly more impressive at creating human-like text and answering questions, but whether they can understand the meaning of the words they generate is a hotly debated issue. A big challenge is that LLMs are black boxes; they can make predictions and decisions on the order of words, but they cannot communicate the reasons for doing so.Ellie Pavlick at Brown University is building models that could help understand how LLMs process language compared with humans. In this episode of The Joy of Why, Pavlick discusses what we know and don’t know about LLM language processing, how their processes differ from humans, and how understanding LLMs better could also help us better appreciate our own capacity for knowledge and creativity.
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Can Quantum Gravity Be Created in the Lab?
Quantum gravity is one of the biggest unresolved and challenging problems in physics, as it seeks to reconcile quantum mechanics, which governs the microscopic world, and general relativity, which describes the macroscopic world of gravity and space-time. Efforts to understand quantum gravity have been focused almost entirely at the theoretical level, but Monika Schleier-Smith at Stanford University has been exploring a novel experimental approach — trying to create quantum gravity from scratch. Using laser-cooled clouds of atoms, she is testing the idea that gravity might be an emergent phenomenon arising from quantum entanglement.In this episode of the Joy of Why podcast, Schleier-Smith discusses the thinking behind what she admits is a high-risk, high-reward approach, and how her experiments could provide important insights about entanglement and quantum mechanical systems even if the end goal of simulating quantum gravity is never achieved.
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What Is the True Promise of Quantum Computing?
Quantum computing promises unprecedented speed, but in practice, it’s proven remarkably difficult to find important questions that quantum machines can solve faster than classical ones. One of the most notable demonstrations of this came from Ewin Tang who rose to prominence in the field as a teenager. When quantum algorithms had in principle cracked the so-called recommendation problem, Tang designed classical algorithms that could match them.So began the approach of “dequantizing,” in which computer scientists look at quantum algorithms and try to achieve the same speeds with classical counterparts. To understand the ongoing contest between classical and quantum computing, co-host Janna Levin spoke to Tang on The Joy of Why podcast. The wide-ranging conversation covered what it was like for Tang to challenge the prevailing wisdom at such a young age, the role of failure in scientific progress, and whether quantum computing will ultimately fulfill its grand ambitions.
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How Did Multicellular Life Evolve?
At first, life on Earth was simple. Cells existed, functioned and reproduced as free-living individuals. But then, something remarkable happened. Some cells joined forces, working together instead of being alone. This transition, known as multicellularity, was a pivotal event in the history of life on Earth. Multicellularity enabled greater biological complexity, which sparked an extraordinary diversity of organisms and structures.How life evolved from unicellular to multicellular organisms remains a mystery, though evidence indicates that this may have occurred multiple times independently. To understand what could have happened, Will Ratcliff at Georgia Tech has been conducting long-term evolution experiments on yeast in which multicellularity develops and emerges spontaneously.In this episode of The Joy of Why podcast, Ratcliff discusses what his “snowflake yeast” model could reveal about the origins of multicellularity, the surprising discoveries his team has made, and how he responds to skeptics who question his approach.
“The Joy of Why” is a Quanta Magazine podcast about curiosity and the pursuit of knowledge. The mathematician and author Steven Strogatz and the cosmologist and author Janna Levin take turns interviewing leading researchers about the great scientific and mathematical questions of our time. New episodes are released every other Wednesday.Quanta Magazine is a Pulitzer Prize–winning, editorially independent online publication launched and supported by the Simons Foundation to illuminate big ideas in science and math through public service journalism. Quanta’s reporters and editors focus on developments in mathematics, theoretical physics, theoretical computer science and the basic life sciences, emphasizing timely, accurate, in-depth and well-crafted articles for its broad discerning audience. In 2023, Steven Strogatz received a National Academies Eric and Wendy Schmidt Award for Excellence in Science Communications partly for his work on “The Joy of Why.”
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