Nearly every officer that Trump has appointed this term is unqualified. That doesn’t make them necessarily culpable for everything that happens in their portfolios, especially for projects underway before they took office.
I think the main reason you haven't seen a lot of changes on the surface is that corporations as currently constructed largely cannot use them efficiently.
I have a personal project where I am merging 100+ PRs a week and at work I would be lucky to merge 8. I spend 20x as much time trying to get PRs merged as I do actually doing the work.
I'm on a project with 4 other people working on 4 or 5 microservices and I would get more, better, work done if I were on a team alone managing all 4 or 5 microservices myself.
Yep, and we've known this since the Mythical Man Month, but the biggest slowdown is coordination overhead. However, if one person can do much more work, you need fewer people overall which means even lesser coordination between them, which is when broader organizational productivity gains will be unlocked.
So the answer to why we don't see AI productivity gains more broadly is, unfortunately, enough people have not been "re-orged" away.
I think this is not as interesting a philosophical problem as he is making it out to be. If you are standing next to the brake and someone says 'hit the brake his arm is stuck', then you hit the brake. You don't work out some complicated moral calculus.
> I think this is not as interesting a philosophical problem as he is making it out to be. If you are standing next to the brake and someone says 'hit the brake his arm is stuck', then you hit the brake.
If it's expected/uninteresting for someone to hit the brake when someone shouts at them to do so, then is it not interesting to consider why the opposite happened in this case? ("I pointed to the person next to it and shouted [...] They didn't, so I ran down the train")
> You don't work out some complicated moral calculus.
Which I think is one of the author's points, that "morality problems often suggest a frame of mind where we have time to fully reason out the likely effects of each of our options" and that doesn't match reality.
I don't think the author was describing it as an interesting philosophical problem; rather as the difference between the real world and philosophy class. Indeed the real-world problem is not one of moral calculus. It's reacting in a decisive & timely manner with partial information. Most of us are not well-prepared for emergencies, and philosophy class is kinda laughable as an idea of adequate preparation.
What if it results in another high speed train rear-ending yours, and dozens of deaths?
The reason you think about things ahead of time is so you don't make an instinctual or socially-pressured decision in the moment which may be bad.
In this specific case, it's whether you even have a brake available for passengers to use, or you decide that having a brake there would usually make the situation worse. Passengers are ignorant of most of the consequences, they can only react to what they see in front of them. The reason you put a brake there is because the driver would likely brake if they could see what was going on, but they can't have and process all the information about everything in the train at all times.
i.e. "If you are standing next to the brake and someone says 'hit the brake his arm is stuck'," and there's a brake for you to use, somebody has already made the decision that your ignorant decision will likely be a good one.
Anyway, somebody's arm getting torn off, a scene spread over a quarter-mile of train tunnel is certainly going to delay trains a lot more than a quick stop, and leave a bunch of people in the train traumatized, with large dry-cleaning bills. There's a way to make this into an interesting problem by changing a bunch of stuff, but it actually isn't. Not pulling the brake isn't going to avoid anything if somebody's arm is stuck in the door. The reason they put the brake there is because they've already calculated this.
Trains do not simply slam into the back of other trains. The recent incident in Spain occurred because the system that would have prevented that was broken, so they turned it off (as it would not have allowed the train to go while it was broken). This reminded the whole world of train operators why they Do Not Do That Ever Ever Ever.
Have you been on a train station and heard an announcement that a train is delayed due to a signaling fault? That is because they are not allowed to ignore a signal even if they know they are broken. The signal must be repaired, no exceptions. When you create an exception you get a train crash, like in Spain, so the rule is No Exceptions Ever.
I have NVDA stock, I think this is neutral at worst. Obviously bad short term, but the fundamentals are what they are. They are gonna print money for at least the next 5 years no matter what happens.
The reality of the situation is they can be guilty as fuck, but they are so important to the world and us economy, that any sanctions they have will be symbolic. Nobody wants to kill the golden goose, even democrats.
There will be a lot of noise, it will be embarrassing, but I just can't imagine a situation where it significantly impacts their bottom line.
The bear case here is pretty much that you think AI is a bubble anyway, and this just accelerates it.
In order to see this as a bad thing you have to first agree with the export controls. Like Jensen, HN loves chinese models, that's why the outrage does not resonate.
It would be hypocritical to both use DeepSeek and also be outraged at the (alleged) mechanisms through which China acquires GPUs.
One way to take this is that this shows that the agents can't discover anything new, another way to take this is as confirmation that the AI can correctly identify the same sites that human experts can, and just suck at searching literature.
The corollary to 'agents suck at searching literature' is that if they truly identified a previously-undocumented site, they might then categorise it as 'already discovered', which is a bad optimal outcome!
Or they might be bad at identifying sites that aren't similar to documented sites, or they might allow amateurs to generate a huge volume of noise that they enthusiastically drown archaeologists with...
https://en.wikipedia.org/wiki/The_Great_American_Road_Trip_(...
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