The Quanta Podcast

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Quanta Magazine
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Life Sciences #78 in Science Physics Society & Culture
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9.4K - 15.7K listeners Female/Male 4.6 rating 627 reviews 268 episodes USA
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30s Ad: $276 - $314 60s Ad: $326 - $364 CPM Category: Science
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Exploring the distant universe, the insides of cells, the abstractions of math, the complexity of information itself, and much more, The Quanta Podcast is a tour of the frontier between the known and the unknown. In each episode, Quanta Magazine Editor-in-Chief Samir Patel speaks with the minds behind the award-winning publication to navigate through some of the most important and mind-expanding questions in science and math. Quanta specifically covers fundamental research — driven by curiosity, discovery and the overwhelming desire to know why and how. Join us every Tuesday for a stimulating conversation about the biggest ideas and the tiniest details.

(If you've been a fan of the Quanta Science Podcast, it will continue here. You'll see those episodes marked as audio edition episodes every two weeks.)

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Recent Hosts, Guests & Topics

Here's a quick summary of the last 5 episodes on The Quanta Podcast.

Hosts

Previous Guests

Ben Brubaker is a computer scientist who recently published a paper titled 'For Algorithms, a Little Memory Outweighs a Lot of Time,' contributing to the progress on a famous question in computer science.
Jordana Cepelewicz is a science writer and journalist who has contributed to Quanta Magazine, focusing on topics at the intersection of mathematics, science, and technology.

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Episodes

Here's the recent few episodes on The Quanta Podcast.

0:00 23:38

Singularities in Space-Time Prove Hard to Kill

Hosts
Samir Patel
Keywords
singularities space-time black holes Big Bang theorems gravity

Black hole and Big Bang singularities break our best theory of gravity. A trilogy of theorems hints that physicists must go to the ends of space and time to find a fix.

This is the fourth episode of The Quanta Podcast. In each episode, Quanta Magazine editor in chief Samir Patel speaks with the minds behind the award-winning publication to navigate through some of the most important and mind-expanding questions in science and math.

0:00 8:41

Audio Edition: Heat Destroys All Order. Except for in This One Special Case.

Hosts
Samir Patel
Keywords
heatproof magnetism physics magnetism heat

Heat is supposed to ruin anything it touches. But physicists have shown that an idealized form of magnetism is heatproof.




0:00 19:17

In Computers, Memory Is More Useful Than Time

Hosts
Samir Patel
Guests
Ben Brubaker
Keywords
computer science memory algorithms proof history of computer science

One computer scientist’s “stunning” proof is the first progress in 50 years on one of the most famous questions in computer science.

This is the third episode of our new weekly series The Quanta Podcast, hosted by Quanta Magazine editor in chief Samir Patel. This week's guest is Ben Brubaker; he recently published "For Algorithms, a Little Memory Outweighs a Lot of Time.”

(If you've been a fan of Quanta Science Podcast, it will continue as 'audio edition episodes' in this same feed every other week.)

Historical Recording © Jack Copeland and Jason Long

0:00 20:46

Math and Beauty in the Age of AI

Hosts
Samir Patel
Guests
Jordana Cepelewicz
Keywords
Mathematical Beauty AI Mathematics Proof Truth

Mathematicians have started to prepare for a profound shift in what it means to do math.

This is the second episode of our new weekly series The Quanta Podcast, hosted by Quanta magazine Editor-in-Chief Samir Patel. This week's guest is Jordana Cepelewicz; she recently published "Mathematical Beauty, Truth and Proof in the Age of AI" for Quanta's AI special package.
(If you've been a fan of Quanta Science Podcast, it will continue as 'audio edition episodes' in this same feed every other week.)

0:00 18:44

Audio Edition: Can AI Models Show Us How People Learn? Impossible Languages Point a Way.

Hosts
Samir Patel
Keywords
artificial languages neural networks language learning linguistics AI models

Certain grammatical rules never appear in any known language. By constructing artificial languages that have these rules, linguists can use neural networks to explore how people learn.

The post Can AI Models Show Us How People Learn? Impossible Languages Point a Way first appeared on Quanta Magazine

Ratings

Global:
4.6 rating 627 reviews

USA

4.6 ratings 469 reviews

UK

4.7 ratings 73 reviews

Canada

4.4 ratings 43 reviews

Australia

4.3 ratings 27 reviews

New Zealand

4.6 ratings 7 reviews

Ireland

5.0 ratings 3 reviews

Singapore

3.7 ratings 3 reviews

South Africa

3.0 ratings 2 reviews