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Fortunately or unfortunately, the Supreme Court has always been willing to do that. This court has been overruling decisions of the Warren Court, just as the Warren Court overruled decisions from the Lochner Era.
If we can’t even build data centers, the least disruptive industrial use possible, there’s no hope to reindustrialize the US or anywhere outside of China.
I think the largest part is either due to being caught up in a bad social set, or straight up because they think crime is fine. Poverty doesn't cause this, at least not primarily - it's rather that personal characteristics such as lack of impulse control and high time preference lead to both poverty and a propensity to crime.
With modern surveillance technology, you could probably get rid of a fair number of cops, but you’d still need some muscle to actually enforce the law. The other option is regulatory penalties, but those tend to work best on middle-class people, not on the classes that commit physical theft and violence, which people hate most of all.
In Canada, measles cases suddenly exploded in 2025 as well, and they don't have RFK Jr. there: https://health-infobase.canada.ca/measles-rubella/
The policies around measles vaccines have shifted a little since RFK became HHS Secretary, but not in a material way. Generally the messaging has focused on putting measles, mumps, and rubella in individual vaccines rather than combined, but at no point has the federal government recommended not to get vaccinated. That, combined with the Canadian data, implies that RFK or other changes to US health policy are not likely to be the cause of the measles outbreaks.
The Nature paper is "Scalable watermarking for identifying large language model outputs"[1]. This method does not separate out tokens into separate classes, but merely uses a seed for the PRNG that selects which among the most likely tokens generated by the LLM will actually be output. This has the advantage that there's no green and red token sets, so no token is systematically favored or disfavored. If a particular token is overwhelmingly predicted to be the most likely candidate, it will almost certainly be selected, so the watermark doesn't affect that. Even if there are several choices of output token at a point that have similar probability of selection, the watermark doesn't systematically bias in favor of one token or the other.
This is actually a quite elegant method of watermarking that, contrary to people's fears, won't adversely affect the model output. The main concern I have with it is that it appears that you can't actually test the watermark locally, without uploading it to Anthropic. I'm not sure why that's the case, since there's no particular reason the watermarking key has to be private, except if you want to prevent others from generating text with their own LLMs that is watermarked to look like it's generated by Anthropic - but everybody wants their text to not have the watermark.
[0]: https://www.anthropic.com/news/claude-text-watermark#:~:text...