The jump is very likely due to AI usage and lack of skills in mathematics. It seems like prerequisite classes are not being fulfilled.
"Ranade said students are expected to enter the course having taken classes on linear algebra, vector calculus and mathematical proofs. However, she found out in office hours that many students struggled with linear algebra, and was even more shocked when one student told her the linear algebra class they took at UC Berkeley had an “open-internet, open-AI policy” for homework and exams."
Also, this professor doesn't grade on curves? Could be very specific to this teacher. I don't know. Would be great to have more data but it is a big jump and could be very specific to this professor or perhaps this class.
"Also, this professor doesn't grade on curves? Could be very specific to this teacher. I don't know." Someone has to hold standards up -- they seem to be falling down across the board in education.
Actually, when I read they usually graded on a curve, I lost all interest. I don't respect teachers that grade on curves.
You should be graded by how well you know the material - not how well your peers don't know it. I'm always grateful both my undergrad and grad professors didn't curve on a grade.
In my first company, I had 4 different jobs. It was a common adage: Go into a low performing team that does simple work and you'll get promotions much quicker than in a high performing team doing challenging (but fun) work.
It was right. I had 2 "dream" jobs where I did cool, challenging stuff, but where everyone was more than competent. They turned out to be career killers. The promotions I got were all in the other 2 jobs where I did boring business logic coding, and where my peers were barely competent (one had trouble navigating directories using the command line).
That's what happens when you grade on a curve. Smart people begin to work on boring stuff, and not the real challenges.
For failing grades sure, there must be some sort of minimum competence. For sorting out >= B/3.0 grades, a curb can work since you are getting evaluated against your peers to see he is standing out vs just doing acceptable.
If you wanted to grade purely off a curve, you would be stuck with old test problems that were thoroughly vetted and calibrated, an impossible task for smaller classes where the material changes rapidly.
> For sorting out >= B/3.0 grades, a curb can work since you are getting evaluated against your peers to see he is standing out vs just doing acceptable.
I'm still not getting it. For a standard course, the criteria for what is "good" vs "great" should be pretty clear, and it should be independent of your peers. You have a syllabus, and a set of abilities for each grade level. If you hit those targets, you get the grade. If half the class gets an A, then it means they're pretty smart, or you did a great job in teaching. Of course, there's the chance the class was too easy, but you can always fix that.
No, I don't see why you're stuck with old test problems. For standard engineering classes, there's a huge (almost infinite) set of problems one can create.
For smaller classes, grading on a curve is even sillier, as the variance is always higher when the population size is small. For example, a lot of my small classes consisted of highly motivated students (all "A material"), because they're usually obscure electives where the content is challenging. You then pointlessly penalize students who sign up (just like they do at work). In fact, my professors were usually much more lenient on small classes for this very reason (i.e. lowering the standard needed to get an A).
I once took an Intro to Analysis course. It was moderately challenging. I got the highest score in the class, and my grade was A-. Everyone else got B+, B, or lower. A friend of mine (who didn't take the course) got really upset that I didn't get an A (or A+) given that I was the top scoring student.
But I knew my level of understanding/performance. It wasn't that great. I felt even an A- was too high a grade for me. And the teacher did a pretty good job in teaching. Why should I get a higher grade just because the other students were worse?
> For a standard course, the criteria for what is "good" vs "great" should be pretty clear, and it should be independent of your peers.
Do you think upper division college classes are somehow like high school classes with well developed curriculum and teaching professors who teach the same thing every quarter? Now you expect the professor to not only come up with new test material, but also extensively calibrate it before students take it, maybe for a 15-hour per week class (3 hours of teaching + 12 hours of studying), with maybe 15 students? Well, thank God we have AI for these kinds of things now.
Ok, let's exclude upper devision classes and just focus on lower division courses (since you mentioned an Intro to Analysis course). Here you have a relatively better chance of a well understood enough curriculum and testing material to actually not grade on a curve. BUT these are also usually weed out classes, with the idea that they only have N spots for students to proceed on to the upper division course, so curving serves an actual purpose that is aligned with the intended result.
> Do you think upper division college classes are somehow like high school classes with well developed curriculum and teaching professors who teach the same thing every quarter?
I repeatedly said "standard course", which implies it is a commonly taught course (be it upper or lower division). In my undergrad, Analysis I, II and Abstract Algebra I, II were upper division courses. In the engineering departments, stuff like Electromagnetics I, II were upper division.
Anything that is not an elective (and even some popular electives) were standard courses.
Now I'll grant that in CS, some material like machine learning changes rapidly. But in most engineering, very little in the undergrad material changes. Even my semiconductor courses in undergrad haven't changed much in decades.
So yes - for most of those classes (and that means the vast majority of undergrad engineering) classes, the curriculum is relatively standard.
> Now you expect the professor to not only come up with new test material, but also extensively calibrate it before students take it, maybe for a 15-hour per week class (3 hours of teaching + 12 hours of studying), with maybe 15 students?
First: In my very average undergrad university, professors were always careful not to reuse old homeworks/exams. It wasn't a huge burden. Professors who don't do this (e.g. most professors in top universities) signal very clearly their lack of interest in pedagogy.
Second: You want to do a curve on <= 15 students? Are you aware of basic statistics and the problems you get with small N? Are they using a normal distribution or one that is more appropriate for small N?
And as I already said, for a lot of electives where the material isn't standardized, professors lean towards lenient grading. They offer those classes because they want people to take it, and grading via a curve discourages it.
> since you mentioned an Intro to Analysis course
That was an upper division course. Yes, I know some universities have it as a lower division, but many (most in the US?) treat it as upper division.
> BUT these are also usually weed out classes, with the idea that they only have N spots for students to proceed on to the upper division course, so curving serves an actual purpose that is aligned with the intended result.
It was not a weed out course. Neither my undergrad nor grad math departments had weed out classes. I saw that concept only in the engineering departments. My EE department had only Circuits I, Circuits II and digital logic as "lower division". Circuits II was the weed out course, and you were not allowed to take anything else (e.g. E&M, Electronics, etc) unless you got a B or higher.
In fairness to the article, they are saying there is no evidence on how it will affect teens because all the studies excluded the audience that the ban was for.
"Not a single social media restriction experiment has included people under the age of 16. We do not know how social media bans will affect the young people being targeted by them because we have never tested this with them!"
I know anecdotally my own experience restricting social media has been more of a positive association, but that is because I am not attracted to it anymore. I have been on it for several years and it is no longer novel. To a teenager, it may be the way they relate to their peers and being unable to have access to it could have a negative consequence.
Maybe with all these countries and states that have banned social media, we should see evidence of increased mental health wellness as a proof that banning it was the right thing to do.
The old internet was a more homogenous society, social outcasts and technically capable people who liked interacting with computers. The content was more relatable because it was created by similar types of people. Now the internet is for everyone so the content is for everybody.
It's too easy to blame the algorithms when the algorithms are a necessary evil. TikTok has millions of videos uploaded per day. You are not going to sort through all of those on your own. The algorithm is designed to show you more of what you interact with. If you're not finding joy in what you're seeing, it's because you're not interacting with content that gives you joy. Stop watching the slop, search for the things you like and follow good creators. There are a lot of them out there, depending on what you like. That applies to any social media, not just TikTok.
> It's too easy to blame the algorithms when the algorithms are a necessary evil. TikTok has millions of videos uploaded per day. You are not going to sort through all of those on your own.
I don't necessarily think that people have an issue with the algorithms themselves, more so that all of the platforms that implement them will manipulate and alter it so that you constantly stay engaged. And that boils down to pushing ragebait, low effort clickbait, and shock content over everything else.
Now it is possible to avoid falling into this, but its not the default. If I have to actively fight to not see people dying, asinine political and cultural takes, or ai slop, then its a bad experience and I will yearn for the days when gaming let's plays and video essays were the default. Its easy to say "just don't watch it", but is it really "just" that easy when the whole platform is constantly being tweaked and optimized against the content that someone would prefer to see?
I think that's fair, the algorithms are manipulative and one has to be very aware of their own susceptibility to it. Everything you specifically mentioned is why I don't go on Twitter to scroll anymore. I will use the platform to search something or I will click links to it but Twitter is not my go-to for scrolling dopamine because it is too negative.
The branch name is "claude/phase-a-port", there was zero indication this was an experiment until Jarred commented. The more accurate title might have simply been "there is a branch in the official repo of bun describing a port to rust from zig". No amount of soft titles would have prevented the discussion. People have their opinions about Bun, about Zig, about Rust and it's all going to come out in a discussion board.
Can’t every branch be considered an experiment? I have a ton of experimental branches that I don’t label «experimental». One of the reasons you use git…
Sure, but then how does it change anything around the discussion? You are still running an experiment to port to Rust, it still gets posted, the Rust-heads and Zig-heads still make their comments.
> there was zero indication this was an experiment
The goal of Phase A is a **draft** `.rs` next to the `.zig`
that captures the logic faithfully — it does **not** need to compile. Phase B
makes it compile crate-by-crate.
I mean, it would be hard to spell it out any clearer than that! Code that fails to compile is just not very useful for real work.
Phase B clearly says compilation is the next goal. The first goal is to get a like for like logic, the second goal is to get it to compile. Can you guess what the third goal will be? Throw out the code?
Yes, but that would require people to read past the title. You can't get a proper knee-jerk first post in if you do that! Completely unfair to expect people to make that sacrifice/effort.
[there was some sarcasm there, BTW, if anyone has a faulty detector that didn't pick up on it]
I couldn't use that title because I didn't know if it an experiment at the moment. Even now the correct title would be "Bun author says that he is entertaining the idea of porting it from Zig to Rust, creates an experimental branch".
This entire article is basically saying "What are we doing? What's going on?" and I could not agree more. My own experience with coding agents has been FOMO cause if I don't have fifteen claude tabs running with OpenClaw, I'm not going to make it. I much prefer keeping myself in the loop and being active with the process than handing it off to deus ex machina and seeing the eventual results that may be what I like and maybe not what I like.
I do like the tips on how to work with agents for delegation. Let it do boring things. The deterministic things where you know what the result should look like each time.
I recently turned to list making for offloading all the mental tasks and organizing my life better. Running low one ggs? "Hey siri, add eggs to my groceries list". Random thought I want to google? "Hey Siri, remind me later to look up XYZ topic". I've even setup a few iOS shortcuts that connect into my Obsidian notes so that I can quickly dictate notes about books I'm reading or ideas I want to capture for later writing.
I don't know if it makes me sharper but I am able to remain focused on the present and offload the thought to future me. This has been enormously helpful and makes me wonder why I never did it regularly beyond grocery lists. Even those lists would be a mad scramble of "what do I need" looking around and almost always forgetting something I need.
The prices on Ali Express for e-ink are not that bad, but certainly can't get anything as big as the Mira Pro. The Boox premium is plug and play compatibility, high fidelity/refresh rate and support.
GPT is impressive with a consistent 0% false positive rate across models, yet its ability to detect is as high as 18%. Meanwhile Claude Opus 4.6 is able to detect up to 46% of backdoors, but has a 22% false positive rate.
It would be interesting to have an experiment where these models are able to test exploiting but their alignment may not allow that to happen. Perhaps combining models together can lead to that kind of testing. The better models will identify, write up "how to verify" tests and the "misaligned" models will actually carry out the testing and report back to the better models.
Rerun it for "high" and "xhigh" effort settings, and GPT-5.2-Codex still get 0% false positive, while getting at the level of other best models for localization of backdoors: https://quesma.com/benchmarks/binaryaudit/
"Ranade said students are expected to enter the course having taken classes on linear algebra, vector calculus and mathematical proofs. However, she found out in office hours that many students struggled with linear algebra, and was even more shocked when one student told her the linear algebra class they took at UC Berkeley had an “open-internet, open-AI policy” for homework and exams."
Also, this professor doesn't grade on curves? Could be very specific to this teacher. I don't know. Would be great to have more data but it is a big jump and could be very specific to this professor or perhaps this class.
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