whymauri

Have you worked at BigCo before? This was 1:1 my experience at a large company and within months they were asking for a +1 leveled boomerang.

You can't take denied promos at face value, honestly.

Wait, PyTorch and the ecosystem are much more than just that. You can't be serious?

I work in Trust and Safety (not at Meta). We've never 'randomly' shut down an account and any action involving deactivation or deletion goes through thorough human review with no exceptions.

The lack of respect for the end-user is squarely a Meta problem, not an industry problem.

This is now the 5th comment saying the same thing, so I'll respond. I'm aware of these and they were terrible. In a just world, they would get as much if not more media attention.

The difference is the public nature of the execution. That is what makes it more similar to, say, Colombia or Venezuela _to me._ Within the context of 'magical realism', it is the perspective and mass dissemination of the violence that heightens that feeling.

Going back to the original topic, there is a reason that most of 100 Years of Solitude's pivotal moments happen around the staging of public executions (and not so much the off-screen violence, of which there is some but it's not focal).

On Sunday, I was talking a Mexican friend about how politicians get killed in our countries (Colombia, Venezuela, Mexico). Just in June, presidential hopeful Miguel Uribe was shot and killed in Bogota. In the head, in front of a crowd.

I remember being grateful about how that doesn't really happen in the US (Trump being the most recent, but he survived). I guess I was wrong... and, in that case, Garcia Marquez might agree with you.

The Harvard BIONICS lab is working on neuroprostheses for different forms of paralysis, like intestinal paralysis. They're great.

The most direct, non-marketing, non-aesthetic summary is that this model trades off a few points on 'fundamental benchmarks' (GPQA, MATH/AIME, MMLU) in exchange for being a 'more steerable' (less refusals) scaffold for downstream tuning.

Within that framing, I think it's easier to see where and how the model fits into the larger ecosystem. But, of course, the best benchmark will always be just using the model.

I used to work at a drug discovery startup. A simple model generating directly from latent space 'discovered' some novel interactions that none of our medicinal chemists noticed e.g. it started biasing for a distribution of molecules that was totally unexpected for us.

Our chemists were split: some argued it was an artifact, others dug deep and provided some reasoning as to why the generations were sound. Keep in mind, that was a non-reasoning, very early stage model with simple feedback mechanisms for structure and molecular properties.

In the wet lab, the model turned out to be right. That was five years ago. My point is, the same moment that arrived for our chemists will be arriving soon for theoreticians.

5% success rate might mean: if you get it to work, you are capturing value that the other 95% are not.

A lot of this must come down to execution. And there's a lot of snake oil out there at the execution layer.

To be fair, Trust and Safety workloads are edgecases w.r.t. the riskiness profile of the content. So in that sense, I get it.