FWIW that depends on the stores you're looking at. There are three models from different manufacturers available here in a few shops. The prices are a bit ouchier than what i paid for mine around Christmas 2024 though (i got mine on a sale).
at my university in math exams we were only allowed to use 1 specific model of calculator, and most of the exams were answered symbolically anyways, so the calculator usually was not helpful anyways.
I think the oral exam is probably a great way to ascertain a student's ability, but let's be real, undergraduate class sizes numbers in the hundreds, for almost every first year class. I don't think it's possible to administer that. I think I would have loved to see that in my later years at university though, we still just did things by written exam + course work.
> let's be real, undergraduate class sizes numbers in the hundreds, for almost every first year class. I don't think it's possible to administer that
Our first year class was about 250 people. It was fine.
By the 4th year, class sizes were a much more manageable 30 to 50.
You get maybe 10 to 15 minutes with the professor (usually more in later years), they ask 3 questions with some followup. That’s 1 work week for the professor. And less than half the students even make it that far for every exam season (3 per school year) so you’re looking at something like 3 days of work. It’s fine.
yeah that distinction is pretty important, and in general that guy I believe IS making the point - if you can not control it with guaranteed outcomes - you cannot control it.
You can't control it any more than you can control a draw from a deck of cards, but you can absolutely control the deck of cards that you choose to draw from.
The problem is that nobody really does that? Like, as far as I'm aware, even simple stuff such as not considering tokens that would result in a syntax error when writing code isn't being done.
That's silly. My car is not absolutely guaranteed to turn left when I turn the steering wheel left, but you wouldn't say I can't control my car on that basis.
Steering an LLM with a prompt is way less reliable than steering a car with a steering wheel, but there's still control. It's just not absolute.
if your car doesn' turn left when you turn the steering wheel left, the problem is that the car is broken, if an LLM does something unexpected after you gave it instructions, that's possible when the LLM is functioning entirely correctly.
Nothing in this world is guaranteed. That doesn't mean it's uniformly random either. LLMs can still do something unexpected if you give them clear instructions, but that doesn't mean it'll be arbitrary and unpredictable in scope. The same way C/C++ undefined behavior technically means program can give you nasal demons, but in reality it won't do anything unusual (like format your C:/ drive) unless someone purposefully coded it to do that.
This is all going to flash through your mind when your car mysteriously doesn't turn left. I would prefer to think of machines as things with defined outputs and failure is failure, more than as fluffy little kittens who might do the wrong thing, if the consequences are going to fall on someone who doesn't deserve it.
wait till you hear about how we standardized RF bands. We have gems such as "High frequency", "Very High Frequency", "Ultra High Frequency", "Super High Frequency", and the cherry on top, "Extremely High Frequency". Then they went with the boring" Teraherz Frequency", truly a disappointment.
These are all mirrored on the low side btw, so we also have "Extremely Low Frequency", and all the others.
It should be noted that JLPT is not a direct equivalent to CEFR. CEFR requires you to pass speaking and writing, JLPT does not demand you to be able to write, or speak, at all. IT only tests listening and reading. This ironically means that while yeah, you will be able to read a LOT of kanji with JLPT N2, you might not be anywhere near B2 level at speaking and conversation, and probably not at all when it comes to writing (writing Kanji is a whole other thing beyond being able to read, it requires dedicated practice, but anyways a lot of people now don't need to since you can type it out on your phone or computer, and just copy that onto the form or whatever you are writing on)
Speaking as someone who reads around N2 level but can barely ask for directions, this is on the mark. I self-study and have few means or reasons to practice speaking, so it's never been a priority for me.
But I think this arrangement is actually quite...realistic? Charitable? It's very hard to become conversationally fluent in a language - especially one as foreign for most learners as Japanese is - without the kind of serious immersion you can most easily get just by living in the country (though maybe I'm just making excuses for myself). Asking learners to do the groundwork and get the foundations at home before getting hit with that immersion is going to set them up for success, facilitate their smooth integration, and demonstrates a candidate's seriousness. My impression is that in such a situation most learners will improve their speaking skills quickly, but there's no getting around months and years of drilling kanji.
There's probably not much value in JLPT adding a writing component, however, I do believe that the lack of a speaking component is really disappointing. Being able to consume a language is one thing, being able to produce in it, is another, and vital for someone who will be working and living there.
I agree with you, this is a huge concern, and we are still in an age where most content on the internet isn't ai generated yet. What about 10 years from now? We have many instances of people writing posts on reddit or uploading videos and blogs using AI generated text. What happens when that is a significant percentage of content?
I recently saw a video discussing a researcher who published a fake scientific article about a fictitious disease, with bogus author names, even a warning IN the article itself that stated "This is not a real disease, this article is not real" (paraphrasing) but still AI ended up picking up this article and serving information from it as if it was a real disease.
It even got cited in papers (which were later redacted of course), but the fact those papers got published in the first place is a serious issue.
> I recently saw a video discussing a researcher who published a fake scientific article about a fictitious disease, with bogus author names, even a warning IN the article itself that stated "This is not a real disease, this article is not real" (paraphrasing) but still AI ended up picking up this article and serving information from it as if it was a real disease.
Isn’t a lot of pretraining done by chopping sources up into short-context-window-sized pieces and then shoving them into the SGD process? The AI-in-training could be entirely incapable of correlating the beginning with the end of the article in its development of its supposed knowledge base.
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