You can only make money if you produce value. If you stop producing value because your old industries decline/collapse and you miss out on new industries, your wealth will trend towards that of a third world country.
Let's say an agent needs to do 10 brain surgeries on a human to remove a tumor and a human doctor can do it in a single surgery.
I would prefer the human.
"steps" are important to optimize if they have negative externalities.
(Based on AI research) fossile fuel production takes a few years to recoup investment. Only refineries seem quite long term (15-20 years). I'm sure the companies have projections about future demand to decide which projects are worth pursuing. If they miscalculate, the oil companies loose money (oh no! /s).
Anyway, you won't loose money on this.
There is of course also an argument about national security, not being at the whim of some Iranian dictator. So some form of government investment would be justified, but not necessary IMO.
Voters in the US have the ability to actually change the course of their country.
Voters can say they want Obama or Trump in charge and the government has to obey that choice.
In Europe you only have the same parties/"uniparty" in power all the time. Many people never had a representative they voted for.
I understand the nuance about the US voting system. But when I look at the outcomes, the US seems way more democratic than Europe.
Re gas demand:
Renewables are cheaper than fossile fuels. They will obviously win out in a free market. No subsidies needed.
Building out fossile fuel production shifts oil revenue from various dictatorships around the world to the US in this case. That's a good thing. I wish we in Europe produced more gas ourselves instead of being highly dependent on other countries.
This does not mean higher gas demand, which is what matters for CO2 reduction.
They only had to comply with EU laws when they were already a big player in China. EU manufacturers need their new vehicles to be compliant on day one. That is, if they want to launch in the EU market first. Audi recently launched a China-only car (AUDI E5 Sportback).
The mere existence of regulation is part of the problem. Without precise understanding of the law, you don't know if your use cases are fine/excempted. The safe default assumption is that your site is not compliant with regulations until you can prove otherwise, involving a lawyer.
Once you have a technological breakthrough that requires lots of exploration to figure out which products will succeed, regulation is a competitive disadvantage.
For established industries regulation just increases prices.
... Until a new technology comes up that allows new competitors to enter the market. Like Tesla, SpaceX.
But then you don't have a company that can afford to build a 100b training cluster for example.
If that becomes the new sota you are again left behind.
When I do a Google search for the example query "postgresql query analysis" on mobile chrome (no ad block), I get 0 ads.
Same thing if I select the "Example" filter as shown in the demo image.
Ideally you can only retry error codes where it is guaranteed that no backend logic has executed yet.
This prevents retry amplification.
It also has the benefit that you can retry all types of RPCs, including non-idempotent ones.
One example is if the server reports that it is overloaded and can't serve requests right now (loadshedding).
Without retry amplification you can do retries ASAP, which has much better latency. No exponential backoff required.
Retrying deadline exceeded errors seems dangerous. You are amplifying the most expensive requests, so even if you only retry 20% of all RPCs, you could still 10x server load.
Ideally you can start loadshedding before the server grinds to a halt (which we can retry without risk of amplification).
Having longer RPC deadlines helps the server process the backlog without timeouts.
That said, deadline handling is a complex topic and YMMV depending on the service in question.
The loop itself is claimed to be the problem. It doesn't matter whether you use an AR or non-AR model. They both have a certain error probability that gets amplified in each iteration.