wadd1e
Joined 4 years ago
Joined 4 years ago
The point that the person who you're replying to is making is that you dont know the distinction between maths done for its own sake and maths that has applications until potentially hundreds of years later.
For me, understanding pointers to data types was not the hard bit(int* or some_struct*), but wrapping my head around *array being a pointer to the first part of a contiguous segment of memory took a lot of time. Once that idea(and what ++array_pointer really did) settled in my head, pointers felt fairly normal to deal with.
Funnily enough, I am the exact opposite; I struggle with statistics and mechanics since they are very linked to the real world and I seem to thrive in understanding abstract ideas. The more abstract, the better :)
I like to think of abstract mathematics as a bunch of code in a library, the code on it's own is vast and has no real purpose when it is standalone, but it becomes immediately useful when a program with a purpose uses it in tangible ways. I would definitely love to make abstract mathematics make sense as a part of the project.
>To answer your question, I’d be interested in analytic geometry and similar concepts which would related to computer graphics.
Those are good suggestions that I didn't think about at first; function transformations and polar coordinates are definitely worth exploring, and a lot of computer graphics involves calculus and linear algebra that I do plan on covering already.
>Where would you post? Is there a feed we could subscribe to?
Still figuring details out, but probably on my .github.io domain(and if the project receives enough attention, I might move it onto it's own domain) and I'll likely use an email based system or an RSS feed after I tackle the "make good learning resources" problem.
Yeah I do totally see that, and my idea is to make a resource that gives you the value that you extract out of it, although it's a fine line between making yet another boring textbook and a resource that is engaging but also informative.
>For your own interest ... what would you start with?
This is where I am a bit torn, because on one hand, I'd love to jump in to cool stuff that people learnt _how_ to do but were never taught the ideas behind them. For example, integral substitution seem to be taught in this rather boring way where you're told to mechanically execute a bunch of steps that people just need to memorise to pass their exam.
I'd love to jump right in and derive the idea of a substitution from the Reimann integral definition, and go into some detail about the intuition behind it. And then perhaps I can explore more calculus like the idea of limits(which are typically another terribly explained) and then move on to Taylor series expansions etc.
But at the same time I don't want the barrier of entry to be really high, so mabye starting with the idea of derivatives, and then approaching higher level topics might be a better structure?
Also the problem isn't necessarily about understanding the tech, but more about how it will be perceived at first. As long as every big player hypes up the tech as if it's perfect and revolutionary, I can't blame people for blindly trusting it at first(because it might as well work for most things they use it for, it will take some time before the pitfalls become apparent).
(edit) how many people do you think are aware of LLM hallucinations as opposed to inaccurate google results
The experience I get as a user of the app? Is it that hard to believe that people at the very top can be out of touch with the average user of their product? I'd be surprised if any of those people have even seen the Reddit homepage once. We've seen plenty of companies go down because they made an incredibly out of touch change which caused mass migration to a better product(the example floating around is Digg). All this happening right as they prepare to go public is really all the indication one needs to deduce what's going on.