ilikegreen
It really sucks, but I'd rather pirate and know I'm at fault with the artist – maybe I'll buy some tracks off Bandcamp to make up for it – rather than let Spotify cover the transaction with a legal blanket, while the artists get almost nothing in return.
It might not be as friendly as last.fm on the surface, but it is surely richer in content, and more diverse. It's a gem, and I hope Sonemnic (?) doesn't drive it to the ground.
On one hand, it is clear that the mathematical tools for confidently attributing authorship of texts were already present without LLMs. But it is striking that LLMs seem to very accurately identify authorship, through whatever process it might be, with no need for a data scientist in the loop.
Other than the uncannyness, I wonder what implications this will have. Public writing is still public; maybe we will require stronger proof of authenticity from an author (but this is arguably in place already; eg. personal websites, social media profiles, etc.). But for, say, public writing that must conserve anonymity, would people pipe their thoughts and writing pieces through a sort of fuzzing (local) LLM, that would strip text of identifying characteristics?
In general, I'd argue that Spotify will be more toxic to the industry (or the artists' livelihood) than piracy. Streaming is even more predatory and centralized than labels in the 90's, but with an important caveat: it's legal. When people engage in piracy there is at least some awareness of, say, the pirate being at fault in the transaction — even though, as someone else already mentioned, people who pirate might contribute, or engage in other ways, with the creators. But with streaming, it got normalized to pay artists a fraction of a cent per stream (and the terms get progressively worse). I've countless times heard the argument "at least they get paid something!"
Bandcamp, for example, seems like a much fairer ideal for the industry. Luckily, the Epic buyout a few years ago did not immediately ruin the business.
As for the music in the 90's...music has changed. Naturally, one could argue that these are also exciting times: one can singlehandedly produce a record, distribute it independently, and be touring all over Europe without ever having to sign off to a major label. Is this not a good thing — or at least, a notable one? Of course, there's still great music around.
I don't use a Mac anymore, but the first thing I'll do on a Linux build is configure my modifier key in such a way to produce — easily.
Not to deny that discourse on the internet, and reddit of all places, might be getting infested with LLM output. I just don't think focusing on the em dash is a good strategy to predict a tell.
I did not know about c-base either. Are there similar associations throughout Europe? I'd love to join one — seems to have a very cool hacker-y spirit :)
Does anybody feel the same? I feel like nobody touched upon this, but it's always very nice to feel interfaces are responsive.
I still find some problems with the navigation of the problems, but I am not even sure where to go to fix that. It has to do with the difficulty of each problem, but also with how large each topic is: algebra encompasses both linear algebra and linear equation solving, which is a very wide bracket.
But you're making progress. That's great! Congratulations on that, and I'll be sure to keep visiting the website.
I read a lot of books on my Kobo e-reader and I wanted a way to retrieve the highlights of each book (a highlight is the result of gesturing over a piece of text, locally saving it on the device). But a given sentence could flow over to the next page, or a highlight could have been poorly taken (due to the previous reason, or sausage fingers, etc.) — and so I needed to retrieve context for each highlight as well.
Since I use TiddlyWiki for my personal "second-brain", I created a simple tool (using Textualize, a terminal user interface framework for Python) that retrieves highlights, provides context and allows for live-manipulation of context to achieve the correct highlight to save; it then makes a tiddler out of it. It's neat!
Here's the github if you want to have a look. It's not really anything professional, but it has been doing the job for me.
If you want to read more on the condition, Gabor Maté's Scattered Minds is a good introduction to ADHD (he's apparently very good at conveying what it feels like, which might be helpful to you at this point).
All the best!
I think there would be value in knowing a given exercise comes from chapter X of book Y; it might even help track knowledge dependencies, so to say (to solve exercise Z, student probably needs exposure to all chapters between X-3 and X). And it could also be possible to build thorough different levels of exercises in different areas: a set of basic computation exercises (invert this matrix; solve this simple integral) - and these exercises, as you probably know, can be generated easily; some intermediate exercises of theorem applications; and then groups of higher difficulty material (which are probably somewhat more creative exercises).
Anyway, this is really an inspiring project and I hope it brings you lots of joy! and, in case it helps anyone, I've found a good trove of mathematics resources over at https://math.libretexts.org/Bookshelves.
Not in the spirit of spoiling the fun or bring any unnecessary tension, I can't help asking: considering that these exercises are being scraped from .pdf sources, would you consider having the source for any given exercise? Of course, it brings problems of exposing possibly copyrighted material. I'm just wondering what your stance is on that.