115 karma · joined June 2, 2025
But undergrad research has always served two roles: getting my work done and the pleasure of giving the best students the chance to go beyond the curriculum, which is designed for the average student.
I think the impact of AI on undergrad research opportunities will be zero. The bigger impact is reduced science funding. I have directed lots of PhD student grant funding to undergrads who deserved it. I don’t see myself doing that in the near future.
Modern AI has made me a more productive teacher—-I produce higher quality material and have more time for research.
But the impact on most students is negative. It is another thing to engage with, which they won’t unless forced. The only way to learn is to do the work yourself. An AI tutor can get you unstuck faster, but that’s typically bad. Learning to be productively stuck on something for days without making visible progress is an important skill that most people never learn.
"Chain migration" however is more questionable.
Anyway, I don't think the O-1 / EB-1A is the easiest setting. An even easier setting is to become a tenure-track professor at a reasonable university in a technical field, e.g., computer science. That gives you an H1-B without any drama. An EB-1B green card requires a lot of evidence, but maybe a few pages less than an EB-1A green card.
Finally, getting citizenship is trivial. It's the green card that is hard to get.
I guess the ACM fees are paying for stupid things like the new AI summaries.
In my experience, the large influx of foreign students are typically at the masters level. MS classes are typically (not always lol!) more advanced than undergraduate classes. So, you need more qualified instructors, such as your tenured/tenure track faculty to teach them. When you take T/TT faculty out of undergraduate classes and replace them with teaching faculty, you lose a lot. (Let me know if you need what's lost to be spelled out.)
- There is no doubt a large volume of abuse by tech consulting companies. It's likely even worse than it looks, because the H1Bs in the U.S. are to support even larger teams offshore. I don't understand why we can't just blacklist these companies.
- Some of medium-skill hires, e.g., did a 2 year MS degree from random university in the U.S., are also a bit sus, in my opinion.
- I'll bet several of Zuck's recent $10M Superintelligence Team hires were at least briefly on an H1B before getting their EB-1A Green Cards.
- Same for a lot of faculty in computer science -- you can get an EB-1B Green Card quickly, but you have to spend some time on an H1B. You cannot convert directly from a student visa. The O-1 exists, but is not on most people's radars in academia. I think likely because the legal fees are prohibitively expensive. (I have heard $40K+)
However, if you want to allow some immigration, you can make a case PhDs in computer science from Carnegie Mellon, which is what he's talking about.
These are kids who were already world-class coming in and become even better by the time they graduate. It is paid for by taxpayers, for which they should be grateful, and it is done in a context that builds admiration for the country.
This is still true, right?
Overall, the only hard requirement of the H1B seems to be "can you hold down a job 100% of the time, until you choose to depart or receive a green card?" It is quite hard to think of other requirements that are possible to implement at scale, but I do wonder.
Heavily vehicles may be cheaper for whatever reason you cite. But they are still much more expensive than smaller sedans. People still buy the heavier vehicles.
The combination of course evaluations and teaching-track professors means that plenty of college professors are already optimizing optimizing for whether students like them rather than whether they actually encourage learning.
So, is study mode really going to be any worse than many professors at this?
As long as you can tell that you don’t deeply understand something that you just read, they are incredible TAs.
The trick is going to be to impart this metacognitive skill on the average student. I am hopeful we will figure it out in the top 50 universities.
I distinctly recall the following episode when I last taught intro CS in Scheme: I revealed first-class functions. After lecture, the brightest kid in class came up to me and said something to the effect of, "What's the big deal? You can do this in Python."
All that is true, and fewer people should be pushed into pointless colleges.
ACM SIGOPS/SIGARCH does not represent that. This is a group of people doing fundamental work on computing systems, microprocessors, etc. They are largely at very technical schools, and lamenting that they won't be able to pay for PhD students -- who do not take loans, debt, etc.
(CS PhD students are paid well enough and have amazing post-PhD/dropout-PhD opportunities. Happy to have that argument.)
In your computer science classes? What/where were you studying?
The article lists a bunch of old-timers, like Page and Brin. Right now, everyone is talking about the "$100M offers" from Meta, for people who completed (or dropped out) of their computer science PhDs.
What does "not standing for industry" mean to you?