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AI in the Lab: How GPT-4 is Changing Molecules and Models

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Manage episode 448571148 series 1358022
Content provided by Breaking Math, Gabriel Hesch, and Autumn Phaneuf. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Breaking Math, Gabriel Hesch, and Autumn Phaneuf or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

In this episode of Breaking Math, we dive deep into the transformative power of large language models (LLMs) like GPT-4 in the fields of chemistry and materials science, based on the article "14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon" by Jablonka et al. from the Digital Discovery Journal. Discover how AI is revolutionizing scientific research with predictive modeling, lab automation, natural language interfaces, and data extraction from research papers. We explore how these models are streamlining workflows, accelerating discovery, and even reshaping education with personalized AI tutors.

Tune in to learn about real-world examples from a hackathon where scientists used LLMs to tackle some of the most pressing challenges in materials science and chemistry—and what this means for the future of scientific innovation.

Keywords: GPT-4, large language models, AI in chemistry, AI in materials science, predictive modeling, lab automation, AI in education, natural language processing, LLM hackathon, scientific research, molecular properties, Digital Discovery Journal, Jablonka
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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

166 episoade

Artwork
iconDistribuie
 
Manage episode 448571148 series 1358022
Content provided by Breaking Math, Gabriel Hesch, and Autumn Phaneuf. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Breaking Math, Gabriel Hesch, and Autumn Phaneuf or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

In this episode of Breaking Math, we dive deep into the transformative power of large language models (LLMs) like GPT-4 in the fields of chemistry and materials science, based on the article "14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon" by Jablonka et al. from the Digital Discovery Journal. Discover how AI is revolutionizing scientific research with predictive modeling, lab automation, natural language interfaces, and data extraction from research papers. We explore how these models are streamlining workflows, accelerating discovery, and even reshaping education with personalized AI tutors.

Tune in to learn about real-world examples from a hackathon where scientists used LLMs to tackle some of the most pressing challenges in materials science and chemistry—and what this means for the future of scientific innovation.

Keywords: GPT-4, large language models, AI in chemistry, AI in materials science, predictive modeling, lab automation, AI in education, natural language processing, LLM hackathon, scientific research, molecular properties, Digital Discovery Journal, Jablonka
Become a patron of Breaking Math for as little as a buck a month

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

166 episoade

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