I’m sure you can, but you can qualify for loans that do not make for a happy life. You start calculating CA taxes and what that monthly house payment is with todays interest rates and I don’t think you’ll be feeling rich. Broad strokes: while salary is double compared to Seattle, home prices are triple or more.
Quick numbers: monthly take home on $800k in CA is $33k (40% tax rate!). Monthly payment on $3M according to Zillow is about $20k a month. That leaves $13k for all family expenses and saving for retirement. In Seattle, our credit card statement averages $8k, so I wouldn’t feel great about that margin.
$800k sounds like a lot of money, and it is of course. I considered chasing it, because it’s within the realm of possibility for me. But when I looked at housing in the area, I was shocked to find that $800k was not enough. Regular ol’ houses are $3M plus, and the schools are shockingly not that great. I live in Seattle, where I own a home that’s expensive compared to most other places, and still I couldn’t make the math work without taking a big drop in quality of life. You could, of course, just rent, but $800k is such a big number that I just assumed if that was my salary, I wouldn’t have to think twice about affording a nice house.
This article works hard to paint one picture, and then presents arguments and evidence to the contrary. It’s basically a sob story about local musicians and ski lift operators not being able to afford housing, as if that’s a new problem. Then:
> Even as Summit County adds waves of remote workers, it has experienced net negative migration since 2020
You click the link of that data and it talks about how the local government is desperate to attract workers and full time residents, rather than having mostly vacant second homes.
I presume they want to attract wealthy workers, given the choice, since that spending will be local and help the economy. So, assuming they get what they want, which is an influx of wealthy, employed people, it’s entirely clear what will happen to real estate prices. I’m sorry, but no one ever said you’re entitled to only having to play guitar in coffee shops to support themselves. That’s what college kids do, who don’t own houses.
I remember reading plenty of thought pieces a few years ago saying this was impossible, and that Uber was a house of cards gaining market share by subsidizing rides with investor money. That there were no economies of scale to bring costs down, etc., etc. I would love to see a "what we got wrong, and what we still have right" post from one of these people, but I won't hold my breath.
Yes, pride -> fall, I get it. Although it's the celebration of the fall from the sidelines that I'm questioning. I can feel the spite in your words--towards me, towards Musk, and the "other side", which are a faceless group you call the Volunteer Musk Defense Brigade, of which I'm apparently an unknowing member, I guess because I don't think some technical glitch is that big of a deal. You seem to feel lots of spite for people you've never met. I think there are plenty of tragedies written of people destroyed by their spite--maybe Notes from the Underground qualifies.
And in an irony of ironies, you crawl through my post history and take objection to me expressing my lack of empathy for those that make repeated bad financial decisions, but you're not only defending that very sentiment, but taking it a step further: enjoyment of the suffering. I hope you find peace, brother. I'm going to put my robes back on and get those last few meditation hours in now.
I’m pretty sure those are supposed to be moral lessons, not misery porn. But hey, you seem to openly accept the idea of enjoying another’s suffering, and I admire that kind of honesty. I hope it doesn’t end up causing you misery.
I watched a few of these a long time ago. Looking at the list of videos, it's funny that nearly half of them are basically, "I've lived here X months now!" I guess not much happens in ghost towns.
That's not how science works though. You generate a hypothesis about how something works, and then you execute an experiment that's designed to directly test the hypothesis as much as possible. If we had to just rely on slicing existing data, we wouldn't get very far. You can find data to confirm or deny about anything. Predicting the results before the experiment, and then confirming it works out that way is the much harder, and more valuable, part.
OK, but for a rapidly emerging super intelligence to occur, it seems like all of the relevant problems would need to be of that second type, and that's far from obviously true, and I would argue is much more likely to not be true.
You hit the nail on the head, and I train transformers for a living. This pervasive axiom that intelligence can just scale exponentially at a rapid pace is rarely questioned or even stated as an assumption. It's far from clear that this is possible, and what you've outlined is a plausible alternative.
My primary argument is that we not only don't have the answers, but don't even really have well posed questions. We're talking about "General Intelligence" as if we even know what that is. Some people, like Yann Lecun, don't think it's even a meaningful concept. We can't even agree which animals are conscious, whatever that means. Because we have so little understanding of the most basic of questions, I think we should really calm down, and not get swept away by totally ridiculous scenarios, like viruses that spread all over the world and kill us all when a certain tone is rang, or a self-fabricating organism with crystal blood cells that blots out the sun, as were recently proposed by Yudkowsky as possible scenarios on Econtalk.
A much more credible threat are humans that get other humans excited, and take damaging action. Yudkowsky said that an international coalition banning AI development, and enforcing it on countries that do not comply (regardless of whether they were part of the agreement) was among the only options left for humanity to save itself. He clarified this meant a willingness to engage in a hot war with a nuclear power to ensure enforcement. I find this sort of thinking a far bigger threat than continuing development on large language models.
To more directly answer your question, I find the following scenarios equally, or more, plausible to Yudkowsky's sound viruses or whatever. 1/ we are no closer to understanding real intelligence as we were 50 years ago, and we won't create an AGI without fundamental breakthroughs, therefore any action taken now on current technology is a waste of time and potential economic value; 2/ we can build something with human-like intelligence, but additional intelligence gains are constrained by the physical world (e.g., like needing to run physical experiments), and therefore the rapid gain of something like "super-intelligence" is not possible, even if human-level intelligence is. 3/ We jointly develop tech to augment our own intelligence with AI systems, so we'll have the same super-human intelligence as autonomous AI systems. 4/ If there are advanced AGIs, there will be a large diversity of them and will at the least compete with and constrain one another.
But, again, these are wild speculations just like the others, and I think the real message is: no one knows anything, and we shouldn't be taking all these voices seriously just because they have some clout in some AI-relevant field, because what's being discussed is far outside the realm of real-life AI systems.
Maybe I'm not "the average HN commenter" because I am deep in this field, but I think the overlap of what these famous experts know, and what you need to know to make the doomer claims is basically null. And in fact, for most of the technical questions, no one knows.
For example, we don't understand fundamentals like these:
- "intelligence", how it relates to computing, what its connections/dependencies to interacting with the physical world are, its limits...etc.
- emergence, and in particular: an understanding of how optimizing one task can lead to emergent ability on other tasks
- deep learning--what the limits and capabilities are. It's not at all clear that "general intelligence" even exists in the optimization space the parameters operate in.
It's pure speculation on behalf of those like Hinton and Ilya. The only thing we really know is that LLMs have had surprising ability to perform on tasks they weren't explicitly trained for, and even this amount of "emergent ability" is under debate. Like much of deep learning, that's an empirical result, but we have no framework for really understanding it. Extrapolating to doom and gloom scenarios is outrageous.
Quick numbers: monthly take home on $800k in CA is $33k (40% tax rate!). Monthly payment on $3M according to Zillow is about $20k a month. That leaves $13k for all family expenses and saving for retirement. In Seattle, our credit card statement averages $8k, so I wouldn’t feel great about that margin.