But there are so many unanswered questions still and the lack of transparency is an issue, as is the cult like behavior that can be observed recently.
https://nitter.net/JacquesThibs/status/1727134087176204410#m
"The early employees have the most $$$$ to lose and snort the company koolaid [...] They were calling people in the middle of the night"
"The before ChatGPT [employees] are cultists and Sam Altman bootlickers"
From anonymous posts on Blind, current/former OpenAI employee
https://nitter.net/JacquesThibs/status/1727134087176204410
Like in a cult.
>"Not this again!"<
I am unenlightened by your short missive. Perhaps there you could point to something clarifying your intent - something like, say:
"This has been previously discussed ad nauseum in the Fortune magazine article at URL..."
or
"Here's a similar post and the details of OpenAI URL."
Thank you.
I have not gathered the statistics that you undoubtedly have compiled. Please feel free to post them here in support of your grammar specificity for the usage of "HN trope".
There was however a post titled "Why big tech companies need so many people" at https://news.ycombinator.com/item?id=34734655
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quickthrower2 says >" Usually because you can build something that looks like it in a weekend"<
Yes, but that is a fair comparison, n'est-ce pas?
Q. How many programmers and engineers does it take to build an LLM and fire it up?
Some here implicitly speak as if they are familiar with LLMs, and so I assumed that the answer could be 1, 2 or possibly a handful of people to do the deed. But it seems I am very wrong.
Nonetheless by the time one has 700+ employees, surely someone in charge would have noticed that the room was crowded.
And why not the same at 500, or 200 or even 50 or fewer?
Perhaps the lack of oxygen has something to do with it? Might I suggest opening a window or two?
Scaling up - static website is enuf.
Site Reliability - ditto.
Front End Web - ditto.
Necessary items:
Ops - Gotta have someone who understands computers! Yes.
Research - Here's the work. Yes.
Training - No. Hire people carefully, fire quickly.
Legal - minimal - hire a small law firm.
So ~700 people mostly in Research and some cash for Legal? The scope of work must far exceed the scope of the task. Time to trim.
Comparisons to Google makes no sense.
"Ego, Fear and Money: How the A.I. Fuse Was Lit"
https://www.nytimes.com/2023/12/03/technology/ai-openai-musk...
In discussing OpenAI the article reveals why OpenAI is the size it is:
OpenAI was created before LLMs were so popular, so OpenAI has a diverse employee pool of AI people. Many, if not most, were hired NOT for LLM or even NN knowledge but for knowledge of the more general field of AI.
Were you an OpenAI exec who fervently believed LLMs would take you to true AI then there would be every reason to dump the non-LLM employees (likely a majority and a financial burden) and hire new staff who are more LLM-knowledgeable. At the same time, current OpenAI staff not familiar with LLMs are undoubtedly cramming!8-))
So that satisfies my question as to why OpenAI has so many people: only a fraction of the company produced the current hot products.