Taking LLMs out of the Black Box: A Practical Guide to Human-in-the-Loop Distillation

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As the field of natural language processing advances and new ideas develop, we’re seeing more and more ways to use compute efficiently, producing AI systems that are cheaper to run and easier to control. Large Language Models (LLMs) have enormous potential, but also challenge existing workflows in industry that require modularity, transparency and data privacy. In this talk, I'll show some practical solutions for using the latest state-of-the-art models in real-world applications and distilling their knowledge into smaller and faster components that you can run and maintain in-house.


Ines Montani

Co-Founder & CEO @Explosion, Core Developer of spaCy

Ines Montani is a developer specializing in tools for AI and NLP technology. She’s the co-founder and CEO of Explosion and a core developer of spaCy, a popular open-source library for Natural Language Processing in Python, and Prodigy, a modern annotation tool for creating training data for machine learning models.

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Thursday Sep 26 / 10:20AM CEST ( 50 minutes )


Ballroom BC