Sherman Wu: Heavy compute for text model post-training bottlenecks verticalization
Sherman Wu · How OpenAI Builds for 800 Million Weekly Users: Model Specialization and Fine-Tuning · Nov 28, 2025 · at 41:51
Sherwin Wu, Head of Engineering for OpenAI's Developer Platform, explains why product-specific fine-tuning is much harder to execute for text models than for image models.
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“For the text models, there's always going to be this like really big fat free training step that like you have to invest in here. And then even the post training side is like, You know, it's not the, it's not like the easiest thing. Like it's, you know we all, we like just from a compute perspective, obviously it's much smaller, but like, it's still pretty heavy to do like a full mid train or like a post training run. And so I actually think like that's one of the biggest, bigger bottlenecks.”
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