Challenging the Average With Open-Source AI: Hugging Face’s Thomas Wolf

Challenging the Average With Open-Source AI: Hugging Face’s Thomas Wolf

Author: MIT Sloan Management Review September 16, 2025 Duration: 34:24
Thomas Wolf is the cofounder and chief science officer of open-source AI platform Hugging Face, which provides access to thousands of pretrained AI models that can be downloaded and run locally. With over 10 million users, getting started on the site can be a daunting task. Thomas explains how the company aims to improve its accessibility through documentation on the company blog as well as community feedback, similar to social media likes and upvoting. Thomas and Sam discuss the benefits and trade-offs of both open-source and closed-source AI models, as well as the evolution of microchips and the future of hardware and software development — as well as the hopes Thomas has for the future of coding with AI, starting with his children’s generation. Read the episode transcript here. Guest bio: Thomas Wolf is cofounder and chief science officer of Hugging Face, a collaborative AI platform. Wolf likes creating open-source software (OSS) that makes complex research, models, and data sets widely accessible. He can also be found pushing for open science in research in AI and machine learning, to try lowering the gap between academia and industrial labs through projects like the BigScience Workshop. He also writes and produces education content on AI, machine language, and natural language processing, including the reference book Natural Language Processing with Transformers, The Ultra-Scale Playbook, his blog, and videos. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Ever wondered how some organizations manage to turn artificial intelligence from a buzzword into a genuine engine for growth, while others struggle to move beyond the pilot phase? Me, Myself, and AI, a production from MIT Sloan Management Review, goes straight to the source to find out. Instead of theoretical discussions, this podcast features candid conversations with the people who are actually building and implementing AI systems at scale. You'll hear directly from leaders at prominent companies like YouTube, Cisco, and Hugging Face as they recount their journeys-not just the polished successes, but the real-world challenges, strategic decisions, and sometimes surprising lessons learned along the way. Each episode digs into the practicalities of creating measurable business value, cutting through the noise to reveal what effective AI leadership and integration truly look like. It’s a focused exploration for anyone in technology, business, or education who wants to understand the human and operational stories behind the algorithms. Tune in for an unvarnished look at the future being built, one practical application at a time.
Author: Language: English Episodes: 100

Me, Myself, and AI
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