It’s not that complicated. Recreating training data via distillation is basically asking structured questions and recording the responses and reformatting that to use as cleaned “good” training data. Much less energy and compute intensive than creating the training data on your own.
I think I remeber reading somewhere how Chinese research’s do this by basically using bots and spreading out the distillation to many source queries.
The process takes time because even when you’re distilling answers, you still need to actually do reinforcement training on the model. And given that Fable and GPT 5.6 just came out there simply hasn’t been much time to do that. However, models like Kimi also do better than Fable or GPT on a lot of tasks, which means it’s not just distillation but also difference in architecture. You can watch this talk from Kimi founder to see how Kimi was actually trained and why it performs well.
It’s also absolutely hilarious that people think only Chinese companies use distillation, as if Anthropic or OpenAI are above that or something. Not to mention that they basically ignored copyrights on all the data the siphoned and are now crying that people aren’t respecting their terms of use.
You can’t distill models that fast lmfao. People just keep parroting this without having any clue how any of this works.
It’s not that complicated. Recreating training data via distillation is basically asking structured questions and recording the responses and reformatting that to use as cleaned “good” training data. Much less energy and compute intensive than creating the training data on your own.
I think I remeber reading somewhere how Chinese research’s do this by basically using bots and spreading out the distillation to many source queries.
The process takes time because even when you’re distilling answers, you still need to actually do reinforcement training on the model. And given that Fable and GPT 5.6 just came out there simply hasn’t been much time to do that. However, models like Kimi also do better than Fable or GPT on a lot of tasks, which means it’s not just distillation but also difference in architecture. You can watch this talk from Kimi founder to see how Kimi was actually trained and why it performs well.
It’s also absolutely hilarious that people think only Chinese companies use distillation, as if Anthropic or OpenAI are above that or something. Not to mention that they basically ignored copyrights on all the data the siphoned and are now crying that people aren’t respecting their terms of use.
Yeah I know they’re not the only companies doing distillation, it’s just currently in the news and on peoples minds.