Maybe someone on the NYU team forgot to opt out of “improve the model for everyone”.

If you know how to use an agent, and I do, you can have do in minutes what would take a undergrad all summer to do.

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.

This is a good use of TIP division funding. Whatever they were doing before seemed pointless.

Right. Most people are deeply uninterested in learning anything, not just in K-12, but at pretty good colleges like mine.

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.

> An AI tutor can get you unstuck faster, but that’s typically bad.

I like struggling with interesting problems. But spinning your wheels is not progress. So, IMO, getting you unstuck is a generally good thing.

I have always thought of it like this: U.S. citizens have the right to marry and bring home anyone they want. It is not about the immigrant. For example, if you're stationed on a military base on Japan or Germany, you can meet a local girl, fall in love, and bring her back home.

"Chain migration" however is more questionable.

It is counter-intuitive that the more accomplished you are, the more evidence you need to provide. The part about the child not getting a naturalization certificate even though they are naturalized is very weird -- that should be fixed administratively.

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.

The computer science that matters the most today —- machine learning, vision, NLP —- is open access without the fees because the main confs are not ACM. (Vision has some in IEEE.)

I guess the ACM fees are paying for stupid things like the new AI summaries.

Surprising it is necessary, given no such fees for machine learning and associated areas. (Which are all not ACM.)

More money, more income. That's why flood of foreign money is good for a university. But, it is a fallacy to think that this has no cost.

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.)

Exactly the same.