The missing piece of the AI research puzzle
Almost two years after the release of ChatGPT and the widespread adoption of large language models (LLMs), what have we learned about their relevance in real-world applications? In this episode, Jean-Marc Sevin, senior data scientist at the Learning Planet Institute, joins us to answer some of today's most pressing questions: How can we effectively apply this technology to support learning in the context of the Sustainable Development Goals? And should we reorient the AI research agenda towards new disciplines to better understand the so-called magic behind LLMs? ---More about the speaker Jean-Marc Sevin is a senior data scientist at the Learning Planet Institute. He is part of the R&D department and the Learning Transitions research unit. He works mainly on the development of WeLearn, an AI platform to help people learn about planetary transitions. He holds a postgraduate diploma in Big Data from Télécom Paris and is an expert in machine learning, distributed processing and data visualization. Previously, he accumulated over 15 years' experience in the web industry with major French players such as Chanel and Orange, where he held positions as project manager, webmarketing consultant and developer.