I agree, very odd they did not comment on any theories for the degradation here. Dip and then rebound at max effort is pretty interesting too. Overthinking is bad, but you can overthink so much it starts to be better again?
> So I would rather share a match with the occasional cheater than run un-auditable ring-0 software on the same machine I use for anything private.
The article makes an argument that anti-cheat is not worth the trade-off, yet the author admits they are a non-gamer. Then they go on to present one example of anti-cheat that tells us all we need to know about actual gamers' preferences—FACEIT. For those who don't know, FACEIT is a third-party matchmaking service, primarily for CS2. People choose to go through the hoops of using third-party service that installs kernel-level anti-cheat on their computer because it helps to keep cheaters out of their games. This seems like pretty strong evidence that the author's argument is not a good representation of gamers' thoughts on this. I don't know what the actual solution is. I suspect if Valve made their own kernel-level anti-cheat people might trust it more, but it's still the same problem.
I'm basically restating what you said, but it's amazing to me that the vast majority of people you will meet, even educated people, are casual dualists and free-will libertarians. If they happen to acknowledge materialism in some way (i.e. the acceptance of the idea that the brain's processes are just the interaction of physical matter), there is still zero chance they draw determinist conclusions from that acknowledgement. But I guess that tracks, given that most professional philosophers are apparently compatibilists for some reason I have never understood (the arguments get really confusing).
Because, as the OP said, working hours are powered by norms. There are salaried positions and companies and teams that certainly will make you work 6 days a week, or make you feel like a bad worker if you don't do anything on a Saturday. But the vast majority of companies (and employees within those companies) would consider the expectation of working a 6th day to be completely unacceptable.
The real question is: Why are people designing benchmarks that, if a model is trained on them, it won't improve the performance of the model at any real-world tasks? Why would anyone care about such benchmarks?
But there is a way for even an aligned federal government to fight back against the slide into authoritarianism, even with an authoritarian president expanding the powers of the executive, and that is for the other branches to strongly advocate for their own power. The problem as I see it is that Congress literally does not care that they are ceding more power than ever before to the executive. Mostly I think this is due to the cult of personality aspect of Trumpism and the idea that you're basically either with him and in the party or against him and out of the party, so it's impossible to drum up support within the party to fight back against the wresting of power. But also it's because the Republican party has no interest in actually passing legislation because most non-budgetary directions they can go will result in incredible cross-pressure (healthcare reform, federal abortion bans, etc). They believe they are better off not doing policy and letting Trump do whatever.
> “In my trips to Wall Street,” Dyer told the panel, “one of my analyst friends took me to lunch one day and said, ‘Joe, you have to get iRobot out of the defense business. It’s killing your stock price.’ And I countered by saying ‘Well, what about the importance of DARPA and leading-edge technology? What about the stability that sometimes comes from the defense industry? What about patriotism?’ And his response was, ‘Joe, what is it about capitalism you don’t understand?’”
I find this article a pretty compelling critique of the extractive incentives of Wall Street and a good argument for government stepping in from time to time to adjust those incentives. Where is the societal good in the engine of capitalism prioritizing short-term extraction over long-term value creation?
Sure, but the author is arguing that the outcome you're describing is tightly coupled to the perverse incentives that he describes in the article. Investors pushed the company towards extraction over innovation and the end product suffered as a result.
I'm not so sure I buy the premise that engineers are really dismissing AI because it's still not good enough. At the very least, this framing does not get to the heart of why certain engineers dislike AI.
Many of the people I've encountered who are most staunchly anti-AI are hobbyists. They enjoy programming in their spare time and they got into software as a career because of that. If AI can now adequately perform the enjoyable part of the job in 90% of cases, then what's left for them?
Low mileage used cars don't come with a warranty, or probably have a more limited warranty if they're CPO.
Leases can be better, but again they are usually better choices in high depreciation scenarios (like luxury vehicles or EVs, as you point out), not low depreciation scenarios.
Have you seen the prices of pre-owned Honda/Toyota sedans that are less than 5 years old? There are absolutely cars out there where trading in your new car after 3-4 years can make sense depending on the cost of the car, the depreciation curve, and whether you want to always be driving a relatively new car. Of course it's almost always going to be a better value proposition to drive the car for 10 years if you can, but that can still depend on depreciation.
Those things also require more willpower than taking a medication. Willpower is generally determined by your particular psychology which is determined by genetics and environmental factors. People don't have a choice in the matter as much as your comment seems to imply. Getting GLP-1s to everyone who could benefit from them is extremely important for overall health.
"Real industry" also has quite a hard time getting things done these days. If you look around at the software landscape, you'll notice that "getting things done" is much easier for companies whose software interfaces less with the real world. Banking, government, defense, healthcare etc. are all places where real-life regulation has a trickle-down effect on the actual speed of producing software. The rise of big tech companies as the dominant economic powerhouses of our time is only further evidence that it's easier to just do a lot of things over the internet and even preferred, because the market rewards it. We would do well to figure out how to get stuff done in the real world again.
I think the problem is false positives, not false negatives. The people you interact with during the interview process have all sorts of reasons to embellish the experience of working at their company.
You hit the nail on the head. There is no place on the internet more broadly susceptible to the same kinds of "founder brain" malaise that has afflicted so many in Silicon Valley--i.e. "I am good at software development so therefore I am confident I have a good understanding of (and opinion on) all sorts of intellectual topics".
Maybe it that's an apt analogy in more ways than one, given the recent research out of MIT on AI's impact on the brain, and previous findings about GPS use deteriorating navigation skills:
> The narrative synthesis presented negative associations between GPS use and performance in environmental knowledge and self-reported sense of direction measures and a positive association with wayfinding. When considering quantitative data, results revealed a negative effect of GPS use on environmental knowledge (r = −.18 [95% CI: −.28, −.08]) and sense of direction (r = −.25 [95% CI: −.39, −.12]) and a positive yet not significant effect on wayfinding (r = .07 [95% CI: −.28, .41]).
I think it's a bit fallacious to imply that the only way we could be in an AI investment bubble is if people are reasoning incorrectly about the thing. Or at least, it's a bit reductive. There are risks associated with AI investment. The important people at FAANG/AI companies are the ones who stand to gain from investments in AI. Therefore it is their job to downplay and minimize the apparent risks in order to maximize potential investment.
Of course at a basic level, if AI is indeed a "bubble", then the investors did not reason correctly. But this situation is more like poker than chess, and you cannot expect that decisions that appear rational are in fact completely accurate.
> According to this view, justice demands that variations in how well-off people are should be wholly determined by the responsible choices people make and not by differences in their unchosen circumstances. Luck egalitarianism expresses that it is a bad thing for some people to be worse off than others through no fault of their own.
When I see this line of reasoning, it leads me down the road of determinism instead. Who is to say what determines the quality of choices people make? Does one's upbringing, circumstance, and genetics not determine the quality of one's mind and therefore whether or not they will make good choices in life? I don't understand how we can meaningfully distinguish between "things that happen to you" and "things you do" if the set of "things that happen to you" includes things like being born to specific people in a specific time and place. Surely every decision you make happens in your brain and your brain is shaped by things beyond your control.
Maybe this is an unprovable position, but it does lead me to think that for any individual, making a poor choice isn't really "their" fault in any strong sense.
https://artificialanalysis.ai/models?cost=intelligence-vs-co...
Here is another data point for output token efficiency:
https://artificialanalysis.ai/models?cost=intelligence-vs-co...