Yep. CAFE-style regulation is the wrong way to attempt to reduce carbon emissions. The right way is to impose a carbon tax, then let consumers vote with their wallets and engineers work to make the right tradeoffs to meet customer demand. My guess is that consumers would choose to buy the more fuel-efficient vehicles and engineers might make the same tradeoffs... but now it would be clear that those tradeoffs are worthwhile.

Gas is pretty much exactly at its long-term, inflation-adjusted average price, and right where it was in the 1950s. Since then, it was a little higher in the 70s, a little lower in the 90s, a little higher in the early 2000s, but we're now back at the long-term normal price.

See https://afdc.energy.gov/data/1...

Whether the normal price of gas is "cheap" or "expensive" depends on your income and lifestyle, I'd think.

This is an appropriate place for tariffs. Not ridiculous, exclusionary tariffs like we have, but tariffs carefully calibrated to offset the subsidies as precisely as possible, putting BYD's cars on a level playing field against US EVs. I have great faith in free market capitalism and dislike anything that distorts the market, but sometimes you need to use regulation to correct for external market distortions.

How so? I don't see how hovering makes any difference at all... it's just a waste of fuel, increasing gravity loss. It's nicer from a controllability standpoint, but SpaceX has clearly perfected the hoverslam maneuver and once you have that down it makes more sense than to waste fuel hovering and translating. Bolting itself into the deck helps with rough seas, I suppose, but it seems unlikely you'd want to try landing in very rough conditions anyway.

Nah. They do it when it makes sense. They don't do it for Starlink launches because it's cheaper to launch a slightly lighter load and shorten turnaround time, to avoid waiting for the droneship to ferry the rocket back to land. Plus their launch cadence is so high that they'd need a big fleet of droneships. So they reserve those for paying customers who need the greater capacity. I don't think anything about New Glenn's capabilities changes those calculations.

The AI is significantly more aware of other cars around it. Unlike a human, the self-driving system has continuous 360-degree visibility.

While I agree that it *should* always be safe to hit the brakes, the truth is that when you're driving on busy roads most of the time it's not safe to brake hard. People follow too close more often than they maintain proper separation.

I also agree that drivers should always have sufficient situational awareness to know whether or not it's safe to brake, they often don't, and they often react without considering the consequences. This isn't a "man vs woman" thing, it's a human thing.

AFAICT, people with ink generally have more kids than those who don't.

It's worth noting that the way you remove them is by making them stop just sitting there, to the degree they do. The various approaches ultimately just try to break the ink up into smaller pieces that can be absorbed into the bloodstream and carried throughout the body... hopefully to get filtered out by the kidneys and liver and then excreted, but who knows? It seems likely to me that tattoo removal may create exactly the same effects as tattoo application, but moreso.

Have you ever been rear-ended? I have, twice. Both times while I was stopped at a red light, so fault was absolutely incontestable. It's their fault, but you end up without a car. Sure, their insurance has to pay, but they only have to give you what it's worth, not what it will cost you to replace it, and the difference is significant. Not to mention that you could be injured. Your hospital bills will be covered, but you were still injured and have to deal with pain, the recovery, and maybe even some amount of permanent damage. My neck has never been quite right after the second time I was rear-ended.

They would have done that after slamming on the brakes in a vain attempt to avoid hitting the dog, possibly losing control of their vehicle, and possibly causing a collision with other cars or objects. If their reaction failed to cause a serious accident, then maybe they'd have sped away.

Until last month, Waymo only allowed their cars to drive on city streets, no freeway driving. Even now, freeway usage is limited, only for selected riders (I'm not sure what the selection criteria is).

So, basically all of Waymo's millions of miles are on streets that often have animals on them.

Sure, there would be concern, but unless you're dumb you will still pick the option with the 90% lower mortality/harm rate. Yeah, it's good to investigate and fix the problem (assuming fixing the problem doesn't increase the mortality rate), but you should still use the provably better option.

Also, why it didn't attempt to stop (if it didn't). If it didn't attempt to stop because it correctly determined that attempting to stop would risk causing a more serious accident with other vehicles on the road, that's not only good, it's better than the vast majority of human drivers.

Well said.

Most use cases of LLMs/GenAI are actually just process automation by another name. The pivot point of nearly all automation efforts is process control, especially in the handoffs between systems or between systems and humans. Because humans are so adept at handling exceptions, most automation projects I've seen deal with only the most common exceptions. Well-run projects think carefully about how to structure handoffs such that the exceptions don't eat up all the labor saved by automating the base case (which is easy to do). Poorly-run projects just focus on throughput of the base case, and leave exception handling for later, resulting in extremely cumbersome situations that either degrade quality or require nearly as much labor to handle as the pre-automation state. I think many enterprises are about to get a crash course in this, which will dramatically affect how their labor picture looks going forward.

Another area where the job loss analysis is pretty thin is that it assumes that the jobs that are linked to the so-called AI-exposed jobs (e.g upstream and downstream in the process) are implicitly assumed to stay the same. This is almost certainly false.

One example I know well from healthcare is clinical documentation and payment. There are a bazillion AI companies who make the claim that applying AI to clinical documentation "allows healthcare providers to focus more on clinical tasks". The latter part is mostly marketing fluff, supported by a few trial studies. But most of the assertion of saving labor is what people hope for or think should happen.

What really happens is that when AI documents something, the provider can code for those services and try to get paid more. That's the quickest way to get an AI rollout to pay for itself. But insurers don't just sit still, they adjust their payment rules and systems to deal with this, and now somebody on the provider side has to deal with THAT. The system has changed, but often toward more complexity rather than less effort.

I've never seen any of these job loss models try to account for that phenomenon.

I think this view gives the crypto bros too much credit. They might now be thinking about taking advantage of the opportunity to wrestle the system away from the Wall Street bros, but there was no such plan.

To intercept them you still have to identify them, which you can't do until after they perform the sabotage. Given that, what's the benefit in sinking them rather than seizing them? Sinking them gains you nothing, seizing them gains you the sabotage vessel. It probably won't be worth much, but more than nothing. I guess sinking them saves the cost of imprisoning the crew, but I'd rather imprison them for a few years than murder them.