cs_throwaway

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.

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.

I don’t understand why we cannot just blacklist these consulting companies as a first step. The 100K fee may effectively do that so it sounds good to me.

I was not accurate in my previous post. The O-1 isn’t on an academic’s radar because they are not subject to H1B caps. So might as well do an H1B with minimal effort.

Yes. As far as I understand it, the EO is not a rule, but will impact upcoming rules. H1B already has exceptions, so there is nothing new being said. It already has a cap exception for doctors and professors, so why not for critical private sector industries.

The "kids" in the original article are likely PhD students. They are not paying tuition. You and I are likely paying for their education with taxes. (This is likely a small part of the overall higher education picture.)

I think a lot of people arguing about the H1B visa are talking past each other.

- 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+)

Curious what this will do for faculty. Common to use H1B as a bridge for a few months before green card. New CS faculty salaries cap out at 180K at the high end.

This won't convince anyone who wants to pause all immigration.

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.

It used to be that if you lost your job as an H1-B, you had 30 days to uproot your life and get out of the US otherwise you'd be in violation of immigration laws.

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.

As I said, they already cost more than smaller and cheaper alternatives. But people buy them anyway.

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.

Evidence suggests people want these cars. They already cost more than smaller and cheaper alternatives. But people buy them anyway.

It is hard to take the ACM's take on publishing seriously, when virtually all significant publications in machine learning, natural language processing, and computer vision are not being published in ACM venues.

The risk of products like Study Mode is that they could do much the same thing in an educational context — optimizing for whether students like them rather than whether they actually encourage learning (objectively measured, not student self-assessments).

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?

I agree. We are talking about technical, mathy stuff, right?

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.

A lot of this boils down to what you can convince the prof to teach. For most professors, teaching CS1 is a service and does not advance their research. Fewer faculty today are willing to learn Scheme just because it may be marginally better for students, according to some people.

Don’t worry, aforementioned kid is doing just fine, machine learning PhD IIRC. There is a lot of other remarkable stuff in modern computing.

It is possible that this doesn't work anymore.

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."

Do you think it may be feasible to do this and maintain the FFI?

It seems like no more than a year ago the prevailing narrative was problems with higher education and science: how predatory and insidious the student loan industry is, and how it traps people in a cycle of debt with special treatment from the government to not let them escape; the replication crisis revealing just how deeply flawed the incentives in science are, and how safeguards like peer review have failed to stop the slide.

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.)

Every day at class I would keep a tally of how many lies and incorrect statements and explainations would get made every day.

In your computer science classes? What/where were you studying?

We in computer science departments are very happy to send our students to industry, whether or not they bother finishing their degree.

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?

Funny this is here. Apptainer is Singularity, described here:

https://journals.plos.org/plosone/article?id=10.1371/journal...

If you ever use a shared cluster at a university or run by the government, Apptainer will be available, and Podman / Docker likely won't be.

In these environments, it is best not to use containers at all, and instead get to know your sysadmin and understand how he expects the cluster to be used.

CS professor with 15 years experience.

The massive boom in computer science enrollment over the last 20 years has been driven mostly by people chasing tech salaries, not by any real interest in computing itself. These students often show up completely unprepared for how difficult CS actually is, and universities have responded by dumbing down their programs to keep everyone happy and enrolled.

If this weeds out the people who are just there for the paychecks, it might actually be a relief to get back to teaching students who genuinely want to learn about computing.