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Contenido proporcionado por Breaking Math, Gabriel Hesch, and Autumn Phaneuf. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Breaking Math, Gabriel Hesch, and Autumn Phaneuf o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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Exploring GFlowNets and AI-Driven Material Discovery for Carbon Capture

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Contenido proporcionado por Breaking Math, Gabriel Hesch, and Autumn Phaneuf. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Breaking Math, Gabriel Hesch, and Autumn Phaneuf o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.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.

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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: [email protected]

  continue reading

166 episodios

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iconCompartir
 
Manage episode 446293634 series 1358022
Contenido proporcionado por Breaking Math, Gabriel Hesch, and Autumn Phaneuf. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Breaking Math, Gabriel Hesch, and Autumn Phaneuf o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.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: [email protected]

  continue reading

166 episodios

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