Using Large Language Models in Sustainability – with Tobias Schimanski, University of Zurich

Large language models (LLMs) have the potential to analyze and generate sustainability data, particularly in forward-looking areas.

In this episode of the Data Culture Podcast, Carsten interviews Tobias Schimanski, a researcher and an expert on generative AI in sustainability. They discuss the intersection of generative AI and sustainability, looking at the challenges of working with sustainability data and the applications of large language models (LLMs) in this area.

Tobias explains the concept of retrieval augmented generation and he emphasizes the importance of expert knowledge for effective and suggests that fine-tuning LLMs with domain-specific data can lead to better results than relying solely on basic models.

Enjoy this episode!

Here's the Episode on sustainability with data featuring Ridwan Bhuiyan from Zalando.

The Episode with Mathias Münch from Merck can be found here.

Tobias Schimanski on LinkedIn.

Carsten Bange on LinkedIn.

Follow BARC on LinkedIn.

Subscribe to the Data Culture Podcast for more insights into the intersection of Data Culture, AI, and sustainability! #DataCulture #Sustainability #AI #GenerativeAI #LargeLanguageModels #Podcast