For a country that prides itself on CapItAlIsM, U.S. healthcare is the farthest thing from it.
- Doctors and hospitals don't compete on price
- Prices aren't just opaque, they are unknowable
- Shopping around is not possible
- Insurer incentive is to maximize billing (cost). They pass along cost as increased premiums to an employer. Employer passes along increased costs to employee as below-inflation wage increases
Capitalism doesn’t work well for goods with inelastic demand. Every other developed country understands this and has a nationalized system. The only reason we don’t have universal healthcare is basically unlucky flukes.
> The only reason we don’t have universal healthcare is basically unlucky flukes.
You think its a fluke and not intentional corruption of the system? These companies pays both parties a lot so nobody will ever fix this, that isn't a fluke that is just plain old corruption.
Voters don’t want universal healthcare. There is some lobbying, but an entire party’s voters are composed of people who only care about taxes and ensuring that those less than them do not benrfit from wealth redistribution.
This is why even the meager amount of wealth redistribution we got (which was really young to old and not wealthy to poor) came about due to a fluke 6 months in 2009 that one party had 60 senate votes, and 58 or so votes supported a taxpayer funded option, but 42 did not, so the taxpayer funded option did not make it into the final bill.
I think this is a cool tech demo. But the commonality I see in all of these "let the agent run free" harnesses is that the output is never something I would want to use/watch/play.
I think minimizing the amount of human effort in the loop is the wrong optimization, and it's the reason we end up with "slop".
It's the dream of a lot of people to have a magic box that makes you things you can sell, or enjoy for personal leisure. But LLMs are not the magic box. And there may not ever be a magic box. The sooner we can accept that the magic box isn't in the room with us, then the sooner we can start getting real utility out of LLMs.
TLDR: Human taste is more important than building things for the sake of building them.
Maybe OP could try an angle where at various points, the process presents the user with 2-6 options, and they choose their favourite. With a bit of intentional chaos in there, the user and tool could potentially discover interesting game concepts and eventually build them as prototypes.
Are you implying that landlords are naturally incentivized to build homes? Because in most circumstances, the exact opposite is true. In the U.S., the government has a number of programs that offer landlords vouchers in order to encourage them to build out more homes.
I was not conflating the two - I literally meant that there are incentives in place to encourage landlords to develop new homes. I am not referring to groups whose primary interest is to develop and sell - but to develop and own.
I know a lot of landlords think they are a persecuted class that is providing a necessary service - but that largely isn't true.
Broadly you can imagine two scenarios for simplicity sake.
1) Housing supply is abundant. Landlords have to compete on service superior maintenance, better units, better locations, etc.). Renting a home behaves like any other service industry that we come to know and love.
2) Housing supply is constrained. The situation plaguing much of the modern world. Land is limited. Landlords earn a higher IRR from jacking rents than they do from buying additional units. The landlords profit from control of the access to a scare resource rather than from providing anything of value.
"You're absolutely right" is a dead LLM giveaway. It's just not something that people use in every day English, especially on the Internet where no one ever admits they're wrong lol
> Planning, alignment, scoping, code review, and handoffs—the human parts of the SDLC—remain largely untouched
Seems likely that process is holding things back. Planning has always been a "best-guess". There's lots you can't account for until you start a task.
Code review mostly exists because the cost of doing something wrong was high (because human coding is slow). If you can code faster, you can replace bad code faster. I.e., LLMs have cheapened the cost of deployment.
We can't honestly assess the new way of doing things when we bring along the baggage of the old way of doing things.
The cost of doing something wrong still is high. Even if bad code is produced instantaneously, its detrimental effect on production remains the same. Yes, yes, what fell on the floor and was picked up in five seconds is still considered fine to eat! Does not apply to eggs though. Customer trust is usually such an egg.
Writing code has become much faster. Writing correct and reliable code has become somehow faster, but not nearly as much. Understanding what code to write has barely become faster.
The more novel is the code you're writing, the smaller are gains from AI writing it.
Sundar was at the helm when the decision to worsen search results for the sake of ad revenue was made.
Previously, the two concerns were "firewalled" so as to prevent the money-generating side of the company from eroding the user experience.
This is a theme that's been at the core of every Titan of Industry's decline. That is: chasing of short-term results with disregard for the long term consequences. Alphabet is just so big and dominate in search that it will likely take quite a long time for the negative effects to appear. And they have other large businesses that haven't been as aggressively enshitified (Youtube, GCP).
It's like when the Titanic struck the iceberg and the crew mostly thought the ship would be fine.
Just because they're still making money doesn't mean the company hasn't already been damaged beyond repair. But in this case by the time it's clear the damage is fatal, those at the helm have jumped ship with piles of cash.
Yeah this always get's completely glossed over in these conversations.
People always say: "Things ended up working out in the end"
Things only worked out in the sense that society carried on without all the people who lost their jobs.
The U.S. has recent examples of large scale job destruction.
Michigan: From 2000-2009. Massive job destruction. 330,000 auto workers in 2000. Down to 109,000 in 2009. Estimates are that 1/3-1/2 of all those affected never achieved equal/similar employment. That is, somewhere around ~70k-120k workers never earned as much as they previously did. Since this was msotly contained within one city (Detroit), it's pretty easy for the country to ignore it and go on with their lives.
(Detroit was in decline since the 50's really. 2000-2009 is just a particularly bad snapshot.)
Coal mining towns have experienced the same phenomenon but more gradually. The poverty left behind by the destruction of those jobs has never been addressed.
With AI, we are heading into a situation where potentially a much larger amount of people will be affected. So maybe that changes the calculus on the government stepping in and fixing the problem. But I wouldn't count on it.
> Since this was mostly contained within one city (Detroit)
It's concentrated in Detroit but also distributed throughout the state, as you can observe in the census.gov slides.
The devastation is regional. It's been a wild experience, watching it all fall apart over the last 40+ years. The decay is immense and impossible to convey to someone from a rich state. Someone from the Eastern Bloc might get it, but I've never been able to communicate it to a Californian. Hop in a car and drive from town to town. Once-prosperous communities are boarded up and gradually reclaimed by nature. Department stores are converted into soup kitchens or marijuana dispensaries.
"Things will work themselves out" is not a law of nature, unless we broaden our definition of "things working out" to include outcomes like "everyone young enough flees, everyone else clutches their savings until they eventually die impoverished."
But with AI, even outcomes like that might be overly optimistic. Where will young people flee to? Where can they go, what trade can they learn, to be safe enough to eventually die in comfort?
When I look at Michigan I see both the past and the future, and I am planning accordingly.
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