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Contenuto fornito da Breaking Math, Gabriel Hesch, and Autumn Phaneuf. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Breaking Math, Gabriel Hesch, and Autumn Phaneuf o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
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Exploring GFlowNets and AI-Driven Material Discovery for Carbon Capture

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Manage episode 446296922 series 2462838
Contenuto fornito da Breaking Math, Gabriel Hesch, and Autumn Phaneuf. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Breaking Math, Gabriel Hesch, and Autumn Phaneuf o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

In this episode of Breaking Math, hosts Gabriel Hesch and Autumn Phaneuf dive into the cutting-edge world of Generative Flow Networks (GFlowNets) and their role in artificial intelligence and material science. The discussion centers on how GFlowNets are revolutionizing the discovery of new materials for carbon capture, offering a powerful alternative to traditional AI models. Learn about the mechanics of GFlowNets, their advantages, and the groundbreaking results in developing materials with enhanced CO2 absorption capabilities. The episode also explores the future potential of GFlowNets in AI-driven material discovery and beyond, emphasizing their transformative impact on carbon capture technology and sustainable innovation.

Become a patron of Breaking Math for as little as a buck a month
You can find the paper “Discovery of novel reticular materials for carbon dioxide capture using GFlowNets” by Cipcigan et al in Digital Discovery Journal by the Royal Society of Chemistry.

Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTok

Follow Autumn on Twitter and Instagram

Follow Gabe on Twitter.

Become a guest here

email: breakingmathpodcast@gmail.com

  continue reading

153 episodi

Artwork
iconCondividi
 
Manage episode 446296922 series 2462838
Contenuto fornito da Breaking Math, Gabriel Hesch, and Autumn Phaneuf. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Breaking Math, Gabriel Hesch, and Autumn Phaneuf o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

In this episode of Breaking Math, hosts Gabriel Hesch and Autumn Phaneuf dive into the cutting-edge world of Generative Flow Networks (GFlowNets) and their role in artificial intelligence and material science. The discussion centers on how GFlowNets are revolutionizing the discovery of new materials for carbon capture, offering a powerful alternative to traditional AI models. Learn about the mechanics of GFlowNets, their advantages, and the groundbreaking results in developing materials with enhanced CO2 absorption capabilities. The episode also explores the future potential of GFlowNets in AI-driven material discovery and beyond, emphasizing their transformative impact on carbon capture technology and sustainable innovation.

Become a patron of Breaking Math for as little as a buck a month
You can find the paper “Discovery of novel reticular materials for carbon dioxide capture using GFlowNets” by Cipcigan et al in Digital Discovery Journal by the Royal Society of Chemistry.

Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTok

Follow Autumn on Twitter and Instagram

Follow Gabe on Twitter.

Become a guest here

email: breakingmathpodcast@gmail.com

  continue reading

153 episodi

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