Its frequently used on general elective courses because they're big enough (often hundreds of students) that the statistical variation between student cohorts fits normal curves pretty well.

That doesn't even make sense. The defining characteristic of a credential mill is that it passes everyone who goes. A curve grading system assigns Fs and Ds and C- to the bottom of every class.

Meanwhile, at Harvard, right now, everyone who goes and shows up to class passes, and half of them get As. How is that not "essentially a credential mill" right now?

Even more damning, a generation ago 25% of them got As. What's your theory on that? Harvard students this generation are just a lot smarter and more studious and they're mastering the material at a much higher rate? Or that Harvard is handing As out like participation trophies now?

I know where my money is at. And Harvard's own teaching staff agrees.

Ah, gotcha. You were referring to the comment from the summary, not mine. Yeah, it's fun to watch the young'uns realize that they are absolutely going to spend their whole lives realizing they forgot something they used to know. It's even more fun to watch them the first time they look at code they wrote two months ago and say "Who wrote this stupid shit? Oh....".

Really? Doesn't feel that way at all to me. What it feels like is that LLMs are a massive force multiplier for the skills I already have.

Your splitting hairs. The OP complained that having your grade affected by the grades of your peers was wrong. Then you said, well it would be fine if they based the grades on the "top score" which is still having your grade determined by what (one of) your peers did.

If your 40% on the exam would be an A if the brightest kid got a 44% but would be a B+ if the brightest kid got a 48%, I doubt the OP would be any "happier" with that situation.

Why the scare quotes? Are you uncertain if she's a woman? Or do you not understand how to use quotation marks?

Did they steal stuff worth millions?

Though, of course, this raises the question of why someone would leave valuable masters in a suitcase in an unoccupied core.

My daughter recently took a course where the average final exam score was around 30%. Nobody hit 50%. Nobody completed the test. They were graded on the curve, as everyone expected they would be, and the A's, B's and C's were distributed pretty appropriately in the end.

In your world, apparently this was simply the dumbest cohort of 4th year university students ever to walk the halls, and they all deserved an F ??

Or maybe, just maybe, it was a brutally difficult exam.

Grading on the curve works perfectly fine if you realize that the student cohorts tend to be more consistent than the tests are from professor to professor, year to year.

The only way "your way" makes any sense at all at approaching fairness is if the tests are standardized... but that creates a whole whack of new problems. -- If the test is standardized, then students are incentivized to just study the test, not the material. Meanwhile, In many advanced degree courses, the material taught from semester to semester varies by professor and year for the same course. How do you standardize the test when even the material is variable?

Unsurprisingly the teaching staff at Harvard know a lot more about this than you do.

High level undergrad course work, and graduate level course work isn't like a primary school arithmetic or spelling test.

Dude, I've been writing code for 40 years. I've used so many different tools, stacks, libraries and APIs that at this point I don't remember any of them, and I haven't remembered them for years, and it doesn't matter at all. Sure, I have to look everything up, but that's fine, that doesn't matter. What matters is that I know when something looks wrong, or hard to maintain, or inefficient, or insecure, or... pick the axis. And I can dig in and find the problem. Anyone can tell if code works, that's easy. Understanding when and why it might break or otherwise impose additional costs, that's the real skill.

Which, as it happens, is exactly the skill you need to use an LLM effectively. Also the skill you need to understand legacy code, review colleagues' commits, etc., etc., etc. I used to say that the ability to read and understand code is an underrated skill, but an old friend corrected me at lunch a couple of weeks ago, saying that the ability to read and understand code is the most important software engineering skill, and always has been. Upon reflection, I agreed. And LLMs make this clearer than ever before.

I'm confused by all of these posters who've never heard of "the curve". I wonder if it's because they're all young'uns who went to school during an interval when progressive educators had decided to abandon it... with the inevitable grade inflation that was totally predicted.

When I was in college 40 years ago every class that had more than ~30 students in it was graded on the curve, and even some of the smaller ones (though in a smaller class it becomes statistically questionable). I used to love the groans when a buddy and I walked in the first day of class, because they knew we were going to "bend the curve". :D

Though in all seriousness, the whole point of using a curve is that in a sufficiently large class, it's statistically guaranteed (to very high probability) to be "unbendable". Inserting a couple of students at the top would mean that students who might be just above a cutoff might fall just below it, but it's not going to make a difference to many.

College isn't like tee-ball, where every player gets a participation trophy, and it shouldn't be. Especially not at elite schools. Part of the purpose of a university education is to act as a filter, and not just to filter out those who can't cut it at all, but to rank all of the students by performance, so graduate schools and potential employers can make use of that information.

Don't be so sure about the "shipped off". Google is heavily investing in on-device AI that runs in a trusted enclave (e.g. TrustZone on ARM). I left the company in August of last year but I doubt this has changed since it's been a major area of focus for quite some time.

And what about the computer that was used to write to the floppies?

Which hearing aid brand and model is that?

I don't need 1000 miles. 600 (unencumbered) is definitely sufficient, and 500 might be okay. The thing is that I'll lose half to 2/3 of that range when towing my camp trailer, and that's not even considering that I'm typically towing it up into the mountains, gaining ~5000 vertical feet. I also need minimum 12k pounds of towing capacity and I'd like a little headroom, so call it 16k, and the bed payload has to be able to take at least 2000 pounds, because that's how much the trailer puts on the fifth-wheel hitch.

I'm anxiously awaiting an EV pickup that can do this. I'd love to have essentially unllimited electricity to buffer cloudy days (I have 1 kW of solar panels on the trailer and on sunny days they generate way more than enough, but consecutive cloudy days can leave be difficult).

3/4 ton and 1-ton gas and diesel pickups typically have oversized fuel tanks that provide about 600 miles of range, because that's what you actually need when you start hauling or towing significant loads. I don't think an EV pickup needs to have more range, but it needs to be comparable, and to be able to tow and haul comparable loads.

I'm not anti-EV by any means. I bought my first EV in 2011, and have had electric cars ever since. Trucks are a different sort of problem, though.

That's getting there, though I'd like to see some driving tests with a good-sized fifth wheel at highway speeds. The towing capacity is probably okay, though it provides very little headroom for when I'm towing both my camp trailer (~8k) and my boat (~3.5k), which I actually do several times each summer. But I think the payload capacity is too small to tow the trailer, which puts about 2000 points on the truck.

Will that work?