kazamaloo

For a company to be as successful as OpenAI, two people won't cut it. OpenAI arguably has the best ML talent at the moment. Talent attracts talent. People come for Sutskever, Karpathy, and alike -- not for Altman or Brockman.

Not sure how the article knows "new" employees, but something doesn't click for me. H1B visas kick in on October 1st of each year. August 17th can only be for H1B transfers. Might still be a new employee, but definitely not someone coming from overseas.

I still regret not liquidating at the end of 2021 while all CEOs were selling their positions by the 10s of millions.

Flipping that iPad with 20, 22, and 25% tip presets for a takeout really grinds my gears. But even for non-tip services, people tend to use iPhone attachements to scan the card rather than using a POS machine in the US.

Not that the algorithms are impossible to explain but in some cases the real explanations might require explanations, too. But I think companies will probably get away with hand-wavy explanations like you get this recommendation because you watched this movie neglecting all the sourcing/ranking/filtering workflows.

All companies try to get in on it, too.

Not the same thing. Check out other relevant responses here, too. In short, Home Depot or Lowe's are buying products to resell. They are the seller themselves. OP's argument is that Amazon is the platform facilitating the sale -- hence the mall owner.

fwiw, there is substantial randomness in the process (worked at two of FAANG myself). Try to do mock interviews with your friends if it helps. You may be showing patterns that you think is correct, but actually quite the opposite (this is what happened with me).

We used to have 3 PMs in our team of 20ish people. Two of the PMs left and NOTHING changed for us or our project.

The idea of being relieved of process-related tasks is nice, but it rarely happens. You get pulled in to those timewasting meetings by your PM anyway.

do you have good pointers?

Was asking the same question myself. I am also on the same boat -- flipping through the apps to compare the prices. I thought maybe we are the minorities and the general public just downloads a single food delivery app. The same goes for ride hailing apps, too. An aggregator app that combines every delivery app may disrupt the system. Or maybe they will go for restaurant exclusivity instead of user loyalty. I don't know.

I agree with you for almost everything you said. This case is definitely unusual. What I mean by conditional is that the person who approved it initially is not an actual reviewer.

For your last sentence, I think Jeff uses that 2-week policy to state that his position is "technically" right.

what you refer to as "they" are two different entities.

It is common to submit for approvals hours before the deadline. However, if pubapprove process finds something that needs to be redacted, you have to withdraw the paper. That's basically the risk in it.

Technically you can submit it without pubapprove unless somebody rats you out and you might face some repercussions. Otherwise every paper is supposed to go through AI Ethics committee review along with other types of reviews.

Every paper we submitted went through a technical review as well as legal and IP reviews. They were along the lines of cite this, cite that, run these experiments etc.

What's different in her case is that you don't see the names of the people reviewing. Being the devil's advocate, she MIGHT have a pattern of aggressively attacking people who reviewed their work before. So they might have made the reviewers anonymous this time.

It is not exactly a wholesale reject. She submits the paper to the conference first and asks for approvals later, which might be common if you are rushing for a deadline. This has the side effect of approvers forcing you to retract the paper (because the conference deadline has passed and you can't make modifications on it).

it is sort of a placeholder approval. The actual reviews may be done by a legal team, HR/PR, other researchers in the field etc.

She sends for approval 1 day before the conference deadline, proceeds to submit the paper with conditional approval, and waits for the actual approvals. It is common practice with one side effect: if reviewers don't like certain parts of the paper, they can ask you to withdraw it (since you don't have an option to update the paper at this stage). If the paper was submitted for approval before submitting to the conference though, then they would have some room for back-and-forth engagement with updates on the paper.