But it's a circular problem. The price wouldn't be exorbitant if these rural areas were left to their own devices. But their utility build outs must be done per rules passed at the behest of the richer urban areas.
We're dealing with this bullshit in my own city in another state. From the parks to the roads to the sidewalks to the library every goddamn thing we touch gets driven up to the point of "can't actually do what we wanted" in cost because some rich assholes 100mi away in the vicinity of the capitol have taken a "build it fancy and rich or don't build it at all" attitude and enshrined that in state law and rules.
Sometimes they'll be so kind as to eat part of the cost with state grants, as long as we sell our freedom away in other ways.
Rural power was always expensive, but now due to wildfire risk, it needs to be ruinously expensive. It's not for the benefit of the cities, and driven by corporate risk management.
But not ruinously so? What changed? The rules (both public and private).
> It's not for the benefit of the cities, and driven by corporate risk management.
Which is driven by laws and courts and precedents and best practices and recommendations and beurocratic rules that come from where?
Regardless this has nothing to do with city and everything to do with rich and out of touch.
I'm sure PG&E would be happy to build worse stuff if they weren't sticking their neck out by doing so.
Kind of like how my city would be happy to simply replace it's infrastructure but the state will take a bunch of money away elsewhere if we did that. Of course, if we weren't paying the state taxes we could afford it from scratch ourselves but I digress.
The complaint here isn't from SpaceX investors. It's from retail investors that are being forced to buy SpaceX stock on an accelerated timeline as part of the ETFs they likely purchased so that they would not be overly exposed to volatile single stock picks. The article isn't explicit on this point, instead vaguely gesturing to the series of mega IPOs coming and pointing out that retail clients need to plan for this.
There is a game being played here where the various indexes (NASDAQ, NYSE, etc.) are trying to sweeten the deal to attract big entries like SpaceX (and later OpenAI, Anthropic). The sugar they are giving is an accelerated timeline and inflated spot in the index (3x float rule). That sugar is paid for by retail investors, who may get squeezed when their index funds pay a high price for a small float of public shares, all on predictable days.
Before you say that retail investors should simply buy SpaceX themselves prior to the 15-day index inclusion, realize that retail investors also don't have access to shares at the IPO offer price. That benefit is reserved for large investors, private equity, etc. While it is possible that some retail investors will take this gamble and win, many will be taking a large risk.
> So a passion tax seems like something that should exist and not really be decried.
To put it the other way, work that is distasteful in some way, should also pay more, but this is missing the point.
I think the point of the unionization is that the monopsony of a small number of AAA game studios gives them excessive market power to reduce compensation and especially to reduce working conditions.
A union can acquiesce to the passion tax and say that top developers at a AAA should make $150k/year (a bit low), while simultaneously saying that that developer should be able to see their children on nights and weekends. The project management that leads to "perma-crunch" is something that ought to be resolved on the employer's side, not by the employees.
I believe you can't put an outlet on the side of a kitchen island anymore because too many toddlers were able to grab an appliance by the cable and pull it down onto their heads. In the USA at least.
The conundrum of "equality of outcome" vs "equality of opportunity" hinges on that core question. It's weird, and possible contradictory, to see a policy claiming to attempt both.
Most would define a "fair" opportunity as everyone getting the same chances to succeed, but a "fair" outcome would segment on merit. If angling towards fair outcomes, there's usually less uproar over lifting the floor (e.g financial aid), versus lowering the ceiling (e.g. limitations on admissions based on ethnic or financial background).
Raising the floor is an equality of outcome. It is arguably equality of oppprtunity too, but only when ignoring intergenerational wealth as a factor. Your kids affordíng school is your outcome, their oppprtúnity.
Present LLMs are quite good at interpolating, in fact, too good.
That's the source of hallucinations. A path can be found between A and B, even if A is the 12th century Chinese royal court and B is the Easter bunny.
Interpolation and rote knowledge are still very useful. Most cognitive tasks are like this.
The thing that LLMs are not presently good at is extrapolation. You can train an LLM on pre-1904 literature, but you won't get special relativity from it, at least not without a human to prompt it in just the right way.
You can have an LLM provide a "novel math proof", but you are necessarily discarding 100 or 1,000 "novel math mistakes". The process is more like a guided walk (like the A* algorithm), with human supervision and intervention, not an autonomous math genius.
"They" are, of course, working on it. But the present implementation has some severe structural limitations (such as an inability for new or discovered information to affect model weights) that make LLMs as a human replacement incomplete.
> You can train an LLM on pre-1904 literature, but you won't get special relativity from it, at least not without a human to prompt it in just the right way.
At least 99.999% of humans aren't capable of producing special relativity either. If the bar for AGI is "must be at least as smart as Albert Einstein", one has to wonder why the deck is being stacked so unreasonably.
> LLMs as a human replacement
"Human replacement" and AGI don't seem like perfect synonyms to me.
It seems to me that "AGI" does a better job of revealing the biases of the people using the term than identifying a specific set of capabilities.
It's not just special relativity that's out of reach. It's generally difficult for an LLM to do anything novel, i.e. produce a new hypothesis from scientific data that fits no existing hypothesis, or create an algorithm with a new lower bound on runtime, or debug a proprietary system that makes unusual design assumptions.
AI for engineering productivity seems to be widely misunderstood to be a magic button that produces the same result, but faster and more cheaply. And based on that reasoning, you should want to force employees to tokenmax, because, why wouldn't you want to get more results but faster and cheaper?
A more nuanced view would be something like:
* AI lets you achieve your roadmap somewhat faster, but:
* You incur tech debt that's similar to if you hired a dev temporarily for the features. You don't necessarily have someone on the team that understands the new code.
* Similarly, you aren't upskilling your junior team members. So you aren't getting skill/wage arbitrage as much as before.
* You will complicate the product. P2 features are P2 for a reason, but AI can cause them to be included and complicate the product for lower marginal gain.
well, once they do, kohberger and who knows how many others will be let loose on the public. sets up a hell of a bargaining chip for the feds to prevent it going to the supreme court.
also makes you wonder if any of this would happen if the usage and post trial application of the death penalty were higher. less of a bargaining chip.
The cities are paying exorbitant prices for electricity to pay for safer infrastructure for rural customers (undergrounding).
Some cities have divested from PG&E and enjoy much lower electricity prices as a result.
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