GlibMonkeyDeath

A better way to look at this data is the sum of wealth for each percentile (https://www.federalreserve.gov/releases/z1/dataviz/dfa/distr...) The top 10% (90-99%, ~$67T, >= ~$2M in net worth) owns more than the top 1% (99%+, ~$60T, >= ~$15M in net worth). The top 0.1% own ~$27T.

Any yearly tax that exceeds the "4% rule" will essentially be confiscatory, so let's say that a tax of 1% won't bring out the pitchforks (is that tiny?) On the top 0.1%, that generates about $0.27 T compared to 2026 Federal collection of about $5.2T (on a deficit of about ~$2T) https://www.us-debt-clock.com/data/deficit-by-year

As I pointed out in a comment about solar power in another thread, if that money was spent on installing solar+battery, in about 5-10 years we could have more or less converted the US grid with a 1% wealth tax on the 0.1%. Of course, we could also reverse the recent (2016 and beyond) tax cuts as well, which would help fix the giant gaping hole in the US budget. The stock market would probably take a hit, reducing the wealth of the top whatever by far more than a small tax would.

Many will say that the purpose of this tax isn't just to raise revenue for the US government, but to reduce power of the most wealthy. I personally think that taxing wealth is not going to be effective for doing this, without passing laws that limit the effect of wealth in US politics.

And we can sure find those trillions when we want to: https://defensecommunities.org/2026/04/trump-requests-1-5-tr.... Or https://www.budget.senate.gov/chairman/newsroom/press/extend.... Or...

I do sort of worry that an experimentalist like me will become more or less a technician in the next decade or so, with AI suggesting experiments, and doing the calculations and data analysis.

But that said, in physics (and particularly biophysics) there are many things that are simply going to have to be done in the real world. Even the action of the simplest enzymes are pretty much beyond our ability to compute from first principles; and any engineered thing that goes into a living system has to be tested, as there are many pathways that are just unknown. I don't care how "smart" an LLM is, it doesn't know what it doesn't know, just like us monkeys.

Over the years I have seen many beautiful theories murdered by ugly experimental facts. AI isn't going to change this.

But I totally get the anxiety - it's a real John Henry (https://en.wikipedia.org/wiki/John_Henry_(folklore)) moment for the mathematics field. Clearly this is going to restructure how mathematicians are going to be trained and how they work.

This link shows the longitudinal drop in 2022 for the US - almost assuredly pandemic related https://nces.ed.gov/fastfacts/display.asp?id=38. Otherwise the scores are higher than ever.