jltsiren

All reasonable high-stakes electoral systems assume that election officials cannot be trusted. There is no central database that can be manipulated.

Traditionally there are people representing different parties watching over each other, until they eventually publish the intermediate results from whatever region they are responsible for. And all aggregate results beyond that are based on public information. Some people want to replace that with cryptographic systems with provable properties. But any system that lets you vote anywhere remains vulnerable to voter coercion.

Social pressure can make it scale pretty well. For example, there could be a neighborhood election day party. You vote when you enter, the organizers observe how you vote, and then you leave your devices in a storage locker. The party continues until voting has ended and the results have been announced.

I've seen claims that the median full-time income is ~€4500/month in Germany. That's around $60k/year, or ~$70k/year after adjusting for purchasing power. Which is a bit more than the equivalent figure in the US.

Many jobs pay really well in the US, but many more pay poorly. The top 10% are responsible for ~50% of consumer spending, and the typical American is not that well off.

Germany, like many other European countries, relies more on exports and less on domestic demand than the US. As a natural consequence, its immigration policy favors skilled immigration to keep top wages down. If the wages grow too quickly, your exports become more expensive than those of your competitors, and the entire economy suffers. And when the economy grows, it's better to use the surplus to raise typical wages than top wages.

If you go that way, then there is definitely a civilizational split between Protestants and Catholics, as well as between Europe and America.

Looking from a Finnish perspective, Sweden and Estonia are culturally closest to us, but Russia is also pretty close. Britain and France already feel less familiar, not to speak of something like Italy or the US.

You are confusing mechanisms and statistical outcomes.

It's a bit like crowd dynamics. Each individual human is sentient, but if you observe a large enough crowd, there is no sign of sentience in its behavior.

People who are actively involved in politics and advocacy, as well as some terminally online people, often end up adopting the views of their peers. Because they are stuck in their bubbles, they don't consider other viewpoints plausible.

But most people are not like that. In most issues, they are exposed to multiple viewpoints they could plausibly adopt. The choices they make are ultimately their own. Of course, if you know the distribution of people's opinions and situations and the messaging they are exposed to, you can try to predict the distribution of choices. But those are still people's individual choices.

I think much of the opposition to data centers is because companies are rushing to build them as quickly as possible. When you are building a traditional factory, you probably expect it to remain operational for 30+ years, so it makes sense to get the local community on board first. But a data center building could be obsolete in 10–20 years, if the requirements change enough that it's not feasible to retrofit it for new hardware.

The first decade after the Russian Revolution was characterized by a power struggle and search for direction in the communist party. First there was "war communism" with forced socialization and central control. Towards the end of the civil war, there was a switch to a form of market socialism, for both ideological and pragmatic reasons. Many people even got wealthy during that time. Then Lenin died and Stalin started consolidating his power. The first five-year plan marked the beginning of the kind of communism we now know.

During the civil war, communists saw kulaks as enemies, as their loyalties were at best unclear. And because they were convenient scapegoats. Most Russians were peasants, and kulaks were the neighbors who were better off than you. When things were bad, you could blame kulaks for your misery, because they had more than you.

Later kulaks were tolerated as a necessary evil in market socialism. Then Stalin started his "dekulakization" campaign. Millions of kulaks were deported (mostly to Siberia and Kazakhstan), which was a major contributing factor to the famine in the early 1930s. And when Stalin's purges started, most of the victims were from former kulak families.

Blockades are a legitimate tool in warfare. Their status under international law is a bit unclear, as the precedent is mostly about wars with a clear separation between belligerents and neutral parties, which is not that common anymore.

In any case, neutral ships are expected to comply with the blockade. Typically by staying out of the region or by approaching visibly and subjecting themselves to inspection. If they don't stop voluntarily and resist capture, they can be attacked.

Intelligent people are often stupid.

Or, more accurately, people make stupid mistakes when they lack the experience. Intelligent people often succumb to the fallacy that because they can learn things quickly, they can skip the learning part just figure things out as they go.

There is a middle ground, but class consciousness does not lie that way. Once you start thinking in terms of class interests, the natural conclusions are unpleasant.

Class consciousness is an interesting term. Not too long ago, people were trying to figure out what it would mean in practice to build a society based on that. It turned out that the answer was in class interests. In particular, whether it would be in someone's interests to support communist revolution and the subsequent abolition of private property.

The eventual conclusion was that the interests of the upper middle class did not align with those of the working class. Anyone with substantial non-labor income, such as a small business owner with permanent employees or a professional with enough wealth to have a rental property or other investments of similar value, would not want to have their wealth taken away. That made them class enemies of the working class.

It can be instructive to read what happened to kulaks (wealthy independent peasants) in the early USSR.

The field has a lot of names. Computer science is the most common, but you can also find other names such as computing, informatics, datalogy, and data processing science (or their foreign equivalents).

Within computer science, there is a clear mathematical tradition, an engineering tradition, and a social science tradition. There are also plenty of applied computer scientists who use computer science to study topics in other fields.

It looks more like they set a target level for shortages and then try to minimize waste without exceeding that level. Almost every time I go to Safeway, they have run out of some items I intended to buy. Trader Joe's is more reliable, probably because they have fewer items in stock.

> And if you know your history you'd know that Russia had to pull out of WWI because the country literally ran out of men during the conflict.

Russia continued WW1 with a civil war that lasted until 1922. Their military deaths were quite evenly split between the world war stage and the civil war stage.

Breaking the law is a procedural issue.

Logging a few hundred hectares was not a problem. Google could have done that without additional permits, if their intention was to plant a new forest afterwards. Environmental impact assessment was only necessary, because they intended to replace the forest with something else.

The key question is whether Google can comply with the law after the fact. If they complete the assessment and the government finds nothing that would prevent the construction of the data centers, the project can go on. Maybe there will be some minor sanctions, as well as some delays, as they didn't do things properly the first time. And even if there is something that prevents construction, Google can still probably comply by planting a new forest.

The environmental impact assessment requirement is a national law, and the national government is responsible for approving it. But since elections are coming and the issue has become controversial, the government coalition will happily ignore it and let administrators and judges sort it out. They have bigger things to worry about.

This is an amusing little scandal, but it seems to be only a procedural issue. Assuming that Google has some basic competence, it selected locations where it's ultimately possible to build data centers while complying with all legal requirements.

My guess is that the government will eventually find that all requirements have been satisfied and let the projects move on. But because this is now a controversial issue, someone with the standing will very likely file a complaint. Then the projects will be stuck in administrative courts for a year or two.

Because we don't let them learn. Everyone runs the same static generalist models, instead of having every model instance learn from everything it does. New models come out occasionally, but they have not been trained on the private data you have not shared with the AI company.

You can work around that to some extent with explicit instructions, but it doesn't scale nearly as well as actual model training.

That's nonsense. While there are some examples, where the conquerors massacred the existing populations, it was a rare exception. Most of the time, the purpose of a war of conquest was to increase your agricultural surplus, which was the key resource that supported everything else in the society. If you killed the people (or even just the men), it would take generations to restore agricultural production. By that time, your tenure as the Glorious Leader would be long gone.

In present-day Turkey, people typically have 5–15% Turkic ancestry. For the most part, their ancestors called themselves Roman, or Greek, or Lydian, or Phrygian, or Hittite, or whichever culture happened to be dominant at the time. When new conquerors came, they pillaged a bit and put their own people in charge. Most commoners, and even many cooperative elites, would then continue their lives as before. If the new elites managed to stay in power, people would often gradually adopt their language, religion, and cultural identity.

As for the Aztecs, I found it amusing that the previous Mexican ambassador to the US was Esteban Moctezuma. Guess from which ancestor that name came from.

That would just be an inconclusive end to the war. An actual surrender can be conditional (an explicit deal that favors the winning side) or unconditional. In an unconditional surrender, the winner is free to do whathever they want. For example, they can walk in, rewrite your constitution, and dismantle your military and the industry supporting it.

> You'd have to build a fully underground cooling system that goes to a nearby river (or huge lake) and use the cold water from that, which would get costly quick.

Helsinki gets its water from the 120 km Päijänne Water Tunnel, which cost €200-250 million (adjusted for inflation) to build. Peak flow is 10 m^3/s by gravity alone and up to 20 m^3/s with pumps, which should be enough to cool a 1 GW data center. You could increase the cost by 2x (because real wages have gone up), by another 2x (because middlemen have destroyed productivity), and by yet another 2x (because everything is more expensive in America), and it would still be pretty reasonable.

If the waiter interrupts you when you don't need anything, it's bad service. If the waiter is not there when you need something, it's bad service. American restaurants tend to err too much in one direction and European restaurants in the other. It's up to you to choose which way you prefer.

I personally prefer going to restaurants when I'm in Europe and using delivery in the US.

A lot of bugs are essentially that the code does something plausible correctly, but it's the wrong thing to do. People who are familiar with the codebase and its purpose can often spot those bugs. Those with less experience usually can't.

The issue is tacit knowledge, or implicit context. Most details are never written down. If you don't know them from experience, you have to guess. If you guess, you often guess wrong. And even if you know something from experience, you are often not aware of it, until you see something that violates it. So it's not possible for you to write it down in advance.

You can replace people with AI in the above, and nothing fundamentally changes.

Theoretical fields like mathematics inherently suffer from a form of Goodhart's Law. The progress in mathematics you hear of is almost never the kind of progress non-mathematicians would care about.

It's always easier to measure progress according to the internal metrics of the field than to evaluate the contributions to the wider understanding of the topic. In theoretical computer science (which I'm most familiar with), people have long complained about results focusing on shaving sublogarithmic factors from complexity bounds (while making the algorithm worse in practice) and about reviewers being impressed by the technical difficulty of proofs. But progress like that is easier to measure than new algorithmic ideas or conceptual understanding.

But it's not all bad. The researchers chasing the metrics are almost always genuinely interested in the topics they study. Their actual contributions mostly come from the ideas they explore while trying to achieve measurable progress. And because they are not expected to produce anything of direct value (Goodhart's Law for applied researchers), they can explore a wider range of ideas.

I personally noticed this when I moved from theoretical computer science to algorithmic bioinformatics. When I start a new project, the expectation is that researchers in genomics should be using sofware that uses the new algorithms five year from now. That expectation is useful, but it's also a strict constraint on what I can afford to try.

Talent isn't enough for O-1, because the criteria are mostly about individual achievements. An established professional can fulfill them easier than a more talented junior. The criteria are about demonstrating that it has to be this specific individual, who would bring something more than the generic talent you can always get from the market by paying more than your competitors.

O-1 is also easier to get in fields like academia and entertainment, where everyone is building their individual brand. Corporate employees have a harder time qualifying, because their contributions are rarely attributed to them in public.

In some countries, imputed rent used to be taxable income. If you owned your home, you basically calculated the market rent for a similar home, subtracted your expenses, and paid taxes for the rest. It was one of those policies economists considered justified (because it made the choice between owning and renting tax neutral) but the general public didn't.

Those times are gone, but the theoretical justification that makes homes income-producting assets remains.

CS got that idea from mathematics. Theorems (with the definitions required to state them) are supposed to be self-contained units. Once the general consensus is that a theorem has been proven correct, people can use it without understanding the proof. Of course, people still want to understand how things work, and it often makes sense to understand them a couple of layers below the one you usually work at. But at some point, you should stop distracting yourself with irrelevant details and focus on your actual work.

Hilbert's program was ultimately about humans studying the nature of mathematics. People had different opinions about whether the idea even made sense and what would be a desirable outcome.

Gödel's incompleteness also constrains human and AI mathematicians. Both just strive to prove whatever can be proven in the system they are working in.

Isn't that just the default experience with AI these days? In small enough scale, AI models can express their ideas clearly. But the larger and more complex the ideas are, the less suitable the outputs are for human consumption. I guess AI models think too different from humans, and nobody has trained them to communicate complex ideas in the way human experts in that particular topic expect.

I edited my comment just as you answered, but I'll also say it here in a different way.

The actual conditional result was "if problem A is essentially this difficult, problem B is essentially that difficult". A specific formulation of it was proven, but it depended on a specific assumption that was just shown false. But the general result is still probably valid, because the general assumption holds. But there may be no point in going through the effort of proving another specific formulation, when the automatic theorem factory could just come up with another technical improvement targeting that formulation.

I started in theoretical computer science, but I quickly drifted to more applied areas, because I was annoyed with how often theoreticians would confuse the map for the territory. But if AI can now do that much more efficiently than any human, perhaps theoreticians will have to rethink how much they should focus on specific provable statements.