[InsideOutSanta]

I believe it, because it makes a kind of sense. Post-training has a huge impact on how well LLMs perform, and labeled data is what determines the effectiveness of post-training. This is why companies like Anthropic are so worried about distillation.

So if you have access to a large number of highly skilled people, and you really don't absolutely need them to do other things, why wouldn't you force data labeling tasks on them?

Facebook is also planning a 10% layoff, so this also works as encouragement for people to leave voluntarily.

(Before you downvote me, note that I'm not endorsing this or saying it's a good idea. I'm just saying that I believe it's true, because I can see how Facebook's leadership would think it's a good idea.)

[layer8]

From the article:

> Forced data labeling with 4,500+ engineers is to generate high-quality RLHF

I doubt that you get high quality from forced reassignments where the now-data labelers don’t actually want to do that kind of work.

It’s crazy to think that Meta leadership believed that it makes sense.

[overfeed]

> I doubt that you get high quality from forced reassignments

Their bonuses depend on it. They'll have to play ball unless they have other jobs lined up, are ready to retire early, or prepared to be on the shitlist for the next round of layoffs due to "underperformance"

[xnx]

Do the skills these people have overlap with the skills needed for a good data labeler? I'm guessing being a domain expert is most valuable as a data labeler.

[HDThoreaun]

Because you can just get rid of all those people and do the data labeling tasks for 1/4 the cost?

[vanuatu]

unironically if those engineers were considered to be 'bloat' its better to have them label data because they are smarter and vetted

basically a soft layoff