If the company just keeps paying the Californian salary but offers relocation to e.g Texas, it may be a significant direct benefit for the employees, worth the move. Just compare:
Tesla only moved their headquarters, it was a PR move.
The people leaving California don't really want to leave, they are just being forced out by high costs. Those who have high incomes and can afford housing, like all those OpenAI employees, are staying.
OpenAI isn't looking for just another person that picked up AI on a whim, they are looking for people that are driving the field forward so that OpenAI stays at the very forefront. These sorts of people could learn quantum physics easily, and many probably have in their undergraduate (or graduate) degrees.
No way. The people at the forefront of AI, most of them will have a much harder time learning quantum physics. Yes ML is hard but it's nowhere near QE, theoretical math or physics.
The reason is simply because ML is incomplete and thus right now is more art then science. We only understand these neural networks from the perspective of an analogy. The curve fitting analogy. Its nowhere near something like general relativity where even an analogy doesn't convey full understanding.
Does Tesla pay any state or federal taxes? From my understanding, their federal tax bill at least was $0 in 2022. If the company was operating in CA and paying little or no taxes, it may have been a net drain on the state.
nine_k|2 years ago
https://www.nerdwallet.com/cost-of-living-calculator/city-li...
https://www.nerdwallet.com/cost-of-living-calculator/city-li...
epistasis|2 years ago
The people leaving California don't really want to leave, they are just being forced out by high costs. Those who have high incomes and can afford housing, like all those OpenAI employees, are staying.
OpenAI isn't looking for just another person that picked up AI on a whim, they are looking for people that are driving the field forward so that OpenAI stays at the very forefront. These sorts of people could learn quantum physics easily, and many probably have in their undergraduate (or graduate) degrees.
corethree|2 years ago
The reason is simply because ML is incomplete and thus right now is more art then science. We only understand these neural networks from the perspective of an analogy. The curve fitting analogy. Its nowhere near something like general relativity where even an analogy doesn't convey full understanding.
kevingadd|2 years ago