Interview

Open-source AI vs. frontier models: DataCamp’s real-world test

Jonathan Cornelissen

Co-Founder & CEO, DataCamp

Yusuf Saber

Chief AI Officer, DataCamp

51 minHosted by Kim Isenberg and Peter Thum

Watch on YouTube

About this conversation

Open models can be dramatically cheaper than frontier APIs — but the price per token is only one part of the real cost of running AI in production. Kim Isenberg and Peter Thum talk with Jonathan Cornelissen, Co-Founder and CEO of DataCamp, and Yusuf Saber, DataCamp’s Chief AI Officer, about the technology behind DataCamp’s AI-native tutor on a learning platform serving more than 19 million people.

Rather than discussing open-source AI in theory, the conversation focuses on what happens when real users, infrastructure costs, teaching quality, latency, privacy and vendor lock-in enter the equation.

Topics

  • How DataCamp’s AI tutor generates and personalizes lessons
  • How tasks are routed between open-weight and frontier models
  • Whether open models are really around 10x cheaper
  • The hidden engineering and infrastructure costs behind self-hosting
  • How an AI tutor avoids confidently teaching incorrect information
  • Privacy, data residency and dependence on model providers
  • What companies should measure before choosing their AI stack

Kim Isenberg is co-founder and Editor-in-Chief of Superintelligence, an AI newsletter published every weekday.

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