Your second query is more subjective. Most people would probably point you at the U6 underemployment number as that’s the most famous one. I like the employment projections series for this kind of question though https://www.bls.gov/emp/
Your second query is more subjective. Most people would probably point you at the U6 underemployment number as that’s the most famous one. I like the employment projections series for this kind of question though https://www.bls.gov/emp/
And that is before we talk about alternative signals like the ADP number this like references.
Anytime someone says “we need better ways” you should just read it as “I should do more reading”, because this is a very well studied, understood and measured set of data.
* a metric that measures if people's jobs are paying enough to put food on the table
* a metric that measures whether people's employment matches their education?
LLMs are great as assistants. Just today, Copilot told me it's there to do the "tedious and repetitive" parts so I can focus my energy on the "interesting" parts. That's great. They do the things every programmer hates having to do. I'm more productive in the best possible way.
But ask it to do too much and it'll return error-ridden garbage filled with hallucinations, or just never finish the task. The economic case for further gains has diminished greatly while the cost of those gains rises.
Automation killed tons of manufacturing jobs, and we're seeing something similar in programming, but keep in mind that the number of people still working in manufacturing is 60% of the peak, and those jobs are much better than the ones in the 1960s and 1970s.
And also, manufacturing jobs have greatly changed. And the effect is not even, I imagine. Some types of manufacturing jobs are just gone.
My argument really had nothing to do with you and your hobby. It was that AI is signficantly modifying society so that it will be hard for people to do what they like to make money, because AI can do it.
If AI can solve some boring tasks for you, that's fine but the world doesn't revolve around your job or your hobby. I'm talking about a large mass of people who enjoy doing different things, who once were able to do those things to make a living, but are finding it harder to do so because tech companies have found a way to do all those things because they could leverage their economies of scale and massive resource pools to automate all that.
You are in a priveleged position, no doubt about it. But plenty of people are talented and skilled at doing a certain sort of creative work and the main thrust of their work can be automated. It's not like your cushy job where you can just automate a part of it and just become more efficient, but rather it's that people just won't have a job.
It's amazing how you can be so myopic to only think of yourself and what AI can do for you when you are probably in the top 5% of the world, rather than give one minute to think of what AI is doing to others who don't have the luxuries you have.
They were busy doing things like bringing freedom and democracy to Afghanistan, having a financial crisis, stuff like that. Very important stuff. Social media? Oh yes I think my grandson told me about that.
I've been annoyed over the years because (not having an account) sometimes Twitter won't let me look at Tweets. Hopefully none of them contained useful info.
I'm not in HEP, but my graduate work had overlap with condensed matter physics. I worked with physics professors/students in a top 10 physics school (which had Nobel laureates, although I didn't work with them).
Things may have changed since then, but the majority of them had no idea what pre-registration meant, and none had taken a course on statistics. In most US universities, statistics is not required for a physics degree (although it is for an engineering one). When I probed them, the response was "Why should we take a whole course on it? We study what we need in quantum mechanics courses."
No, my friend. You studied probability. Not statistics.
Whatever you can say about reproducibility in the social sciences, a typical professor in those fields knew and understood an order of magnitude more statistics than physicists.
For pre-registration, this might be debatable, but what I meant was that we have teams of people looking for specific signals (SUSY, etc). Each of those teams would have generated monte carlo simulations of their signals and compared those with backgrounds. Generally speaking, analysis teams were looking for something specific in the data.
However, there are sometimes more general "bump hunts", which you could argue didn't have preregistration. But on the other hand, they are generally looking for bumps with a specific signature (say, two leptons).
So yes, people in HEP generally are knowledgeable about stats... and yes, this field is extremely strict compared to psychology for example.
It's possible that other factors might be more important in driving California's economic success...