I think I speak for most people when I say that I’m a good representative of the general population.

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Joined 6 years ago
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Cake day: June 29th, 2020

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  • Eastward is an indie game I actually first learned about here on lemmy, just a couple weeks after its release. I went back and replayed it just a month ago and it’s so good. I can acknowledge that it’s not for everyone, it almost feels like the target audience is me specifically.

    The dialogue is really wonderful and you fall in love with the characters. When I play games I generally am talking to every npc, Eastward made that feel rewarding for me. There’s not much for tangible benefits, it’s just that to me the dialogue feels very…human (the robots included). If you’re inclined to check in with the npcs you’ll catch wind of little dramas and occasionally see them resolved, and none of it really affects gameplay or the story but it makes the world feel more alive.

    My personal favorite, and one I wouldn’t have found without going out of my way to talk to the npcs - the train attendant robot talking shit about the repair-worker robot:

    The most frequent complaint I’ve seen about Eastward is too much dialogue and too little game, so ymmv. Slight oversimplification, but the gameplay is basically Zelda but with a frying pan instead of a sword. It’s not innovative but I still find it fun.

    The story was heartwarming at times and (with help from the environmental visuals) creepy at other times. I will say it was a bit of a letdown just how much was left open-ended at the end though, there were a few plot points where I was looking forward to seeing how they’d be explained or where they were going and the game just never gave an explicit explanation.

    The pixel art is so special. I try to avoid looking up too much before playing a new game and there was one moment in particular that just floored me visually. I do think the game as a whole made a stronger impression on me because I went in mostly blind, some of the ways the environments change and evolve visually as you move forward really impressed me.

    tl;dr the appeal is lots of emotion captured in the details


  • What good is an alternative to Reddit if almost nobody adopts it?

    Dude the number of daily users today is so astronomically higher than I ever would have imagined five years ago. I literally thought it would stay a small community and maybe max out around a hundred daily posts and I was happy with that because I liked the community. A project being worked on for “almost nobody” is still very worthwhile if the existing community is happy to keep participating, but what it is today is not “almost nobody”.


  • You clearly weren’t saying they all are, but what I’m saying is that my impression is that the bar for weirdness isn’t higher at all. There will always be examples of mathematicians behaving weirdly, because there will always be examples of people behaving weirdly. Spending a lot of time thinking about abstract nonsense definitely improves your proficiency at thinking about abstract nonsense, but I can’t see how it could affect the way you process other things any more than frequent practice with sudoku or chess would.

    The mental process in math is no more special than any other intellectual hobby. If you invest decades into chess I’m sure you’ll think about chess in a very different way than a beginner, but in my opinion seeing chess differently should have minimal impact on how someone thinks about things unrelated to chess.





  • Maybe this implies I’m one of the weirdos, but my experience has been wildly different. My experience has been mathematicians are just people, what they have in common is a passion for math. Sometimes they’re weird, but that’s because they’re people and not because they do math. I never got the impression I was talking with a schizophrenic or a Kaczynski type. They exist, but non-mathatician schizophrenics do too.

    There are multiple mathematicians in the modern era who are well regarded, technically homeless and just showed up at people’s houses to collaborate on some math.

    I don’t think heard of this and I’m skeptical. Give me a couple names to jostle my memory?

    One, who coined the phrase “another roof, another proof”, was a staunch proponent of mixing amphetamines, coffee, and 70’s antidepressants.

    I don’t know this quote but I’d give it a 90% chance it’s Erdös.

    Scary Wheels and Super Shrubs is an example of a good title and not-transparent description.

    Come on man, this isn’t weird. It’s representation theory, there literally isn’t a transparent description. It’s weird to think having fun with a title isn’t a normal impulse from time-to-time.

    7, blue, and cat are all equally real or not real, and we don’t need a simulation as the equation defining structure is sufficient to give rise to what we experience, and requiring it to be written or executed is just an odd affectation.

    This reads as partially random to me, what is “the equation defining structure”?



  • I have some math background so have a little insight here, although I don’t have the specifics you might be looking for. This ended up long.

    So, there’s math software that’s been in longterm development for proof verification, such as Coq and Lean. I did read pretty recently that multiple big results were announced proven and verified by one of these, but on human review the AI had exploited undiscovered bugs in the prover. Automating theorem-proving has been in development for a long while as well, and is (was?) often referred to as AI although is definitively not an LLM.

    With that out of the way, whether by LLM or otherwise, legitimate computer-generated proofs are having a lot more success. The caveat is that they’re not innovating and my understanding is they’re not expected to anytime soon. I’ll explain what I mean by that, although you might be able to guess.

    Different disciplines and subdisciplines have different tools and strategies used as go-tos. If I’m doing categorical homotopy theory and I’m looking to find an appropriate model structure on some category, maybe my category has certain features that would suggest my first attempt start with a transferred model structure from a model category which admits an adjunction to mine. A computer with access to all existing math literature can make these connections, that this approach is used often in this situation.

    Like any subject, math literature is absolutely enormous. There have been instances of teams of mathematicians, people who have devoted lifetimes to understanding existing literature for a single subdiscipline, working together to prove a result for a new paper, and after publication someone from an adjacent subdiscipline reads it and comes out of the woodwork to point out the journal where their result was first proven forty years back as a lemma used in getting another result. Computers can access all of this literature at once.

    This leaves a ton of room for computers to play connect-the-dots in a much more exhaustive way than mathematicians with knowledge limitations can. We want to prove X, well Y technique is a common approach, we’ll need to prove Z to get there, W technique would be where to start… but if Z was published in some obscure journal as a corollary to a little-known result from a seemingly unrelated discipline, a researcher won’t know that, and won’t know that this result somehow fell out of matroid theory instead of algebraic topology, which would have indicated who to collaborate with.

    A computer can also go much much further down rabbit holes that look not worth digging into to a human solely based on inconveniencing people. If I need to ask a graph theorist and she says we need to understand more about finite group theory, and the group theorist takes time to think before saying more knowledge of K-theory would help, and all of this ultimately ends up going nowhere, I’m going to feel pretty silly for taking time from all these people and they might give me less time in the future when I might be more desperate. The computer doesn’t take consideration of whether this is a hassle, it just explores.

    The common tricks and tools of a trade weren’t always there though. Someone has to be the first to realize that taking homology is extremely effective in the contexts I’m working in. Someone has to be the first to say the objects in the dual to the category of rings can be viewed as locally ringed spaces, let’s try doing algebraic geometry by gluing rings together analogously to how open balls glue together into manifolds. Someone has to come up with the concept of a ring as a mathematical tool. I don’t think computers are anywhere close to that.

    Computers becoming good at connect-the-dots could still devastate mathematics as a profession though. A mathematician can make a living by knowing the literature of a hyperspecialized subdiscipline better than anyone else. That knowledge means he needs much less new knowledge to make easy “connect-the-dots” in his specialty. The more practice he gets doing that though, the deeper his understanding grows. Deep insights typically don’t come from thinking better thoughts than everyone else, they come from an intimate understanding of what you’re looking at. Removing all the low-hanging fruit removes a lot of the incentives for a professional to start understanding a discipline better. Grothendieck doesn’t revolutionize algebraic geometry without spending a ton of time doing algebraic geometry first, and being able to publish while getting your feet wet doesn’t hurt with that. If publishing math is my living, why am I going to spend years researching a discipline when people who spent lifetimes doing that couldn’t crack the remaining problems? I’ll need to accept that the time investment probably won’t help me make a living. Being a grad student today must be a nightmare.

    We’ve always understood all these different branches of math are all deeply connected, but I have to think limitations of how much one human can learn have prevented us from grasping just how deep. It’s conceivable that a computer could string together a chain of thousands of very straightforward logical steps pulling from all corners of literature to solve a millennium prize. It would be the analogue of a computer solving an enormous maze by brute-forcing every possible path, while a human would never have the patience to spend that much time on an approach requiring zero intelligence. Evangelists lacking the background needed to comprehend the problem would declare human ingenuity obsolete against the sheer brilliance of the brute-forcing machine.

    In a perfect society, math would be enjoyed as an art and could be pursued as an art without necessity to break new ground regularly to prove your worth. In a perfect society, math in academia would be driven by a desire to learn and do math. If being credited weren’t important, mathematics would still thrive alongside advances in automated theorem-proving. Time investment is the requirement for deep breakthroughs, and there are definitely those of us who would love to invest time into learning without the pressure to be credited with successes. We don’t live in a world where academia is about learning. It’s hard to picture the profession staying the same as long as academia functions as an economic gatekeeper instead.


  • Yes, of course they’re using your code to train their models. That use is in their terms and their licensing.

    It’s irrelevant to your point but this is absolutely not true. As far as I know they don’t have legal basis to violate software licenses of new projects added to github, but even if I’m mistaken on that an enormous number of projects were on github when microsoft purchased it, and almost all of them were at minimum licensed so that code usage required attribution. Microsoft has been very aware that no person or organization behind a project hosted on github has the financial resources to take them to court.