Building on open source AI? Hugging Face’s policy chief on the costs, risks, and trade-offs

Hugging Face's Irene Solaiman joins Equity to explain what startups need to know when building on open AI models, and how to evaluate the tools around them and keep the open ecosystem secure.

作者
Theresa Loconsolo
发布方
TechCrunch
发布时间
篇幅
218 字 · 1 分钟
Building on open source AI? Hugging Face’s policy chief on the costs, risks, and trade-offs
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Open source models are becoming more mainstream as enterprises, governments and startups alike rely on the promise of lower costs, more control, and more flexibility. But as increasingly capable models become more freely available, how do companies capture value? And with Chinese open models gaining ground, can American players keep up? 

On this episode of TechCrunch’s Equity podcast, Rebecca Bellan caught up with Irene Solaiman, Chief Policy Officer and SVP of Strategy at Hugging Face, about what startups need to know before building on open models, from choosing the right tools and infrastructure to navigating the trade-offs shaping the future of open AI. 

Listen to the full episode to hear about: 

  • Why startups, enterprises, and governments are switching to open AI models to cut costs, and when it makes less sense to use the most powerful models. 
  • Who makes money when the models are free to use, and whether the companies building them can capture the value they create. 
  • Why the U.S. may need deep-pocketed players like Nvidia to build an open frontier model that can compete with China’s, and what’s at stake if Chinese models become the global default. 
  • How recent attacks on open AI platforms are raising a difficult question: how do you keep an open ecosystem secure without closing it off? 

内容来源

本文由Theresa Loconsolo报道,TechCrunch于2026年11月4日首次发布。HUE Legacy Ventures 并非本文作者。

Carried in full with attribution and a link to the original. Rights remain with the publisher, who may request removal at any time.

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