The best content I have seen in a while. Enjoyed both the theory and the practical notes from both speakers! Huge thanks dlai for organizing this event
This was amazing thank you everyone. One thing though, if thats possible, it would be greatly appreciated if you could record in 1080p where the details/text on the slides are visible and easier to consume. Thanks a lot again
At 29:40 Lewis mentions an algorithm that requires fewer training samples, what is the name of it? I heard "data", but don't think that is correct. If anyone knows, would you mind replying?
I'm wondering why simple techniques, such as sample boosting, increasing errors for high ranked examples, or attention layer wouldn't work in place of RLHF. It seems like a very convoluted and inefficient way of doing a simple thing - which convinces me that I'm missing something :-)
ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-QXVCqtAZAn4.html The details in the Llama3 paper seem to validate the claim that DPO works better than RL at scale.