OpenAI departures: Why can’t former employees talk?

I mean why would anyone be surprised about this is beyond me?

I know many people on this site will not like what I am about to write as Sam is worshiped but let's face it: The head of this company is a master scammer who will do everything under the sun and the moon to earn a buck, including but notwithstanding to destroying himself along with his entire fortune if necessary in his quest of making sure other people don't get a dime;

So far he has done it all it: attempt to regulatory capture, hostile take over as the CEO, thrown out all other top engineers and partners and ensured the company remains closed despite its "open" name.

Now he is simply attempting to tie up all the loos ends and ensuring his employees remain loyal and are kept on a tight leash. It's a brilliant strategy, preventing any insider from blowing the whistle should OpenAI ever decides to do anything questionable, such as selling AI capabilities to hostile governments.

I simply hope that open source wins this battle so that we are not all completely reliant on OpenAI for the future, despite Sam's attempt.

Why is extra respect due? That post just says he is leaving, there's no criticism.

Other companies have done the same. I worked at a company that is 0% related to the tech industry. I was laid off/let go/dismissed/sacked where they offered me a "severance" on the condition I sign a release with a non-disparaging clause. I didn't give enough shits about the company to waste my time/energy commenting about them. It was just an entry on a resume where I happened to work with some really neat, talented, and cool/interesting coworkers. I had the luxury of nobody else giving a damn about how/why I left. I can only imagine these people getting hounded by Real Housewives level gossip/bullshit.

I understand this argument, but I can't help but feel we're all kidding ourselves assuming that their engineers are really living in the future.

The most obvious reason is costs - if it costs many millions to train foundation models, they don't have a ton of experiments sitting around on a shelf waiting to be used. They may only get 1 shot at the base-model training. Sure productization isn't instant, but no one is throwing out that investment or delaying it longer than necessary. I cannot fathom that you can train an LLM at like 1% size/tokens/parameters to experiment on hyper parameters, architecture, etc and have a strong idea on end-performance or marketability.

Additionally, I've been part of many product launches - both hyped up big-news-events and unheard of flops. Every time, I'd say that 25-50% of the product is built/polished in the mad rush between press event and launch day. For an ML Model, this might be different, but again see above point.

Sure products may be planned month/years out, but OpenAI didn't even know LLMs were going to be this big a deal in May 2022. They had GPT-2 and GPT-3 and thought they were fun toys at that time, and had an idea for a cool tech demo. I think that OpenAI (and Google, etc) are entirely living day-to-day with this tech like those of us on the outside.