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AI in the Lab: How GPT-4 is Changing Molecules and Models
Manage episode 448567256 series 3584638
A tartalmat a Breaking Math, Gabriel Hesch, and Autumn Phaneuf biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Breaking Math, Gabriel Hesch, and Autumn Phaneuf vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.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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