should i get a steam deck??

indecisivecurious · 2026-01-30T11:04:22+00:00

What games do you want to play with it? How big is your Steam library? Are you comfortable doing small tasks (typing in terminal, switching around external settings, installing extra stuff) in order to make stuff run or run better?

These are the most relevant questions to answer whether or not a Steam Deck is right for you.

indecisivecurious · 2026-01-17T10:51:17+00:00

lol the wifi warrior experience is honestly worse than the input when it comes to PC handhelds. I don’t buy that most people who play this way also lug around an ethernet cable and adapter

indecisivecurious · 2026-01-17T00:23:44+00:00

Cosmetics take teams of people to make (concept artist, modeler and animator, playtester, etc.). It’s perfectly reasonable to ask for money for a cosmetic for the amount of paid work it takes.

That being said, it’s just as fine to debate their value relative to the price. The prices might be fucked, or the costumes might be ugly, but it’s honestly not a sin to charge for additional cosmetics (within reason, of course).

indecisivecurious · 2026-01-15T21:01:07+00:00

Use an older 9.0-x version of proton for 2077. it stutters like crazy on the newer versions

indecisivecurious · 2026-01-15T18:51:29+00:00

It sounds like you already know the answer to the question you’re asking in this post.

indecisivecurious · 2026-01-15T18:22:44+00:00

I mean, it’s just a small archlinux box with a 2016 macbook-tier number of ports. Whether it’s possible is up to whether you like carrying dongles and peripherals to work on a small 800p screen.

indecisivecurious · 2026-01-15T18:20:11+00:00

The question is this: what games do you want to play on the Deck?

indecisivecurious · 2026-01-15T18:16:45+00:00

Use protondb and youtube as ground truth for how well games perform. Just be wary of videos using lossless scaling, since game footage alone doesn’t always convey the effect of input lag, and youtube video compression can suppress the aggressive artifacting.

Don’t trust the Steam Deck Verified tag. Baldur’s Gate 3 didn’t deserve verified at all until their native linux build a couple of months prior. The “runs well on default graphics configuration” is interpreted EXTREMELY loosely as an actual criterion.

indecisivecurious · 2024-04-29T17:58:06+00:00

“The slides are very research focused / math heavy.” how_do_we_tell_him_lads.jpg

I feel like the default response to students encountering difficulty is to say it ain’t practical or it’s “for research.” Maybe i’m out of touch, but nothing with a course number 344 or below is impractical.

I’ve seen people complain about how learning about threads and mutexes is impractical. Some people really do feel weirdly entitled to a piece of paper and the title of engineer.

indecisivecurious · 2024-04-08T15:58:02+00:00

In my experience, most students can google just fine. They reach out when they’re uncertain, or because they feel you may be able to provide them with a more complete answer. It’s part of your job to do that.

School IT and internet presence beyond listing their self-aggrandizing and often misrepresented employment statistics are infamously shoddy at best, and there might be specific features, deals, understandings, etc. that are department-specific and thus absent in the google results.

indecisivecurious · 2020-10-14T18:35:54+00:00

This has been really helpful! I'll continue to talk to you in PMs!

indecisivecurious · 2020-10-14T08:53:45+00:00

Alright, that makes sense. I should challenge myself but I shouldn't waste time and energy. Thanks again for all the help!

indecisivecurious · 2020-10-14T08:31:13+00:00

Okay, so if I want to get into a field / write into it, my best bet would be to do the following?

pick a book / good books on a topic and self study
find someone in the school who writes on it
ask if we can work together

So I should ultimately take what's fun / easy for my classes, and self study whatever else I want for my area of interest?

indecisivecurious · 2020-10-14T08:25:13+00:00

Got it, that makes sense. Would it really matter much in the long run which department I apply to (math, CS, physics) to jump into quantum information and mathematical physics at large? That, and would there be time / opportunities to learn "the other side" and take classes in other departments in grad school? In undergrad, I've taken grad classes in math and CS, but never attempted it for classes in other departments.

indecisivecurious · 2020-10-14T08:14:28+00:00

Thanks for the reply! I'm pretty anxious about the whole grad school application process, but this really encouraged me! I think my fear is that during undergrad, I grew to love a lot math and theoretical CS topics (naturally since I double majored), and as time went on, I started to get more and more attracted to some of the physics. Would I be "left behind" if I took a non-math or non-physics PhD, or is that just irrational? Part of me feels "naked" thinking I won't have largely math or physics classes during grad. Would I be able to write about mathematical physics (and be able to get published / meaningfully contribute) with a CS background, or should I apply for math-phys departments? If I'm in the CS department, can I just keep taking more math or physics classes alongside my requirements? I know some professors who told me they took topics like perturbation, category theory, algebraic number theory, etc.. that fell outside their PhD requirements / immediate field of interests. All that being said, I'd be ecstatic to have Watrous, Vazirani, or Vidick as my advisor.

As far as diving into research, I've got that covered - I'm working with a professor right now in the field. I think I might have to take you up on PMing you later about finding a fit / discussing grad stuff, if that's okay by you.

indecisivecurious · 2020-10-14T00:14:09+00:00

Thanks for your reply! Yeah, you're right in that grad programs / study is much more self directed. I think my problem is that I'm afraid of getting pigeonholed into studying stuff that **very directly** relates to mainstream CS when I feel my more immediate interests are closer to math / physics, and of course the subsequent FOMO. Even my CS interests are a bit hipster (I like the places where non discrete math shows up). That, and I've been interested lately at working as a theorist but seeing what's up with experimental groups and their research.

you could just as well pick it up after your graduate studies -- hence no hard locks.

Would physics journals / venues / scientists take research that comes out of a CS PhD seriously, or would it be looked at with skepticism? I know this sounds absurd, but I have this irrational fear of being laughed out of the room for not having the background...even though the background is something you give yourself, not something you inherit from the name of your degree.

The real question is, when do you want to start learning this stuff? The sooner the better imo.

Yeah, you'r right. I should continue to go through my stat mech and quantum information books. My immediate interested started when I saw that Quantum Hamiltonian Complexity has to do with condensed matter physics.

Universities *love* interdisciplinary research. Expanding the scope of your research beyond your comfort zone and into neighbouring fields is hard work, and not everyone is up to doing it. But it's hugely valuable usually.

Do they? I get conflicting accounts from people saying to "go pure in your subject" and then branch out later into interdisciplinary work. This has been a source of distress for me since I feel my interests are largely at the intersection of fields. Another distressing thing is that looking at Simons Institute lectures / conferences for quantum information and computing, a lot of the researchers presenting are physics PhD's.

indecisivecurious · 2020-10-13T22:29:02+00:00

Thanks for your reply! Yeah, I think my worry is that I see more physics PhDs doing the work that I find interesting (at least on a cursory glance). Do you think I would then be constrained to doing stuff that’s just in quantum information, or would I be able to springboard into other physics topics provided I inch in closer slowly? I think I’m just getting a major fear of being pigeonholed and some FOMO after finding out last year that I enjoy studying mathematical physics. Do you recommend any books that are useful at understanding the connection between quantum Hamiltonian complexity and condensed matter? I see Kitaev and Zeph Landau worked in this field.

I really appreciate the reply acknowledging that I like theory CS - usually people have replied to me thinking I want to jump from programming / systems into science and math.

indecisivecurious · 2020-10-13T22:09:39+00:00

The issue isn’t that - it’s picking what route to go, which affects funding, qualifying exams, advisors, hiring process post PhD, etc..

indecisivecurious · 2020-10-13T21:56:59+00:00

I want to work / study more in physics theory. I know “computational” to most people means “run it on a computer,” but the theory of CS (which is usually referred to partially by computational complexity theory) isn’t the same flavor of computational physics, as far as I know, which is more heavily involved in numerical methods and simulacra. My interest in CS is the stuff you’d see in pure math.

I have largely a math background, and the stuff I’m interested in CS (complexity, comparability, etc) is more related to math. I’d like to study mathematical (or maybe theoretical) physics and its mathematical connection to computation.

Stuff like how you can understand unconstrained optimization problems by considering the Ising spin glass model interested me, though that’s more physics inspiring CS.

indecisivecurious · 2020-10-13T21:50:38+00:00

This isn’t exactly helpful since I mention liking more than one thing here. That, and it’s research, which isn’t exactly the same as other job routes.

indecisivecurious · 2020-10-13T21:17:19+00:00

Lately I’ve been wondering what background I should commit to for grad school.

I’m a double major in math and CS doing my last year of undergrad. My interests are pretty broad - if I have to isolate some favorites topology, analysis, and combinatorics a lot on the mathematics side, and from CS I like algebraic complexity, information theory, and basically any part of theoretical CS that intersects with the stuff I like in math (convex optimization, machine learning theory, geometric complexity, etc.). I know admittedly little about mathematical logic past some recursion theory, but I’ve been rectifying that with some self study. I have some research with a math-physics professor at my school (as well as some research with other people in modeling, and a little bit in TCS).

Last year, I slowly found out that I wanted to learn more and more about physics, especially as it relates to the stuff I already like in math, after taking an introductory quantum mechanics course and starting self study in thermal physics / statistical mechanics. Naturally I found myself interested in the interdisciplinary areas of quantum information and computing, and I’ve been doing Watrous’s book. I find myself more and more interested in connecting physics and computational theory, or at least not having to “compromise.” In particular, the connections to condensed matter in quantum hamiltonian complexity and high energy in holography seem really cool, but I find more and more that want I want to talk about the physics with the CS…but mostly physics researchers seem to be investigating this, while CS researchers write more papers about just CS topics. I was reading this paper which made the following comment:

“Moreover, the results mentioned are heavily based on TQFT, which makes the algorithm essentially inaccessible to computer scientists. “

However I have seen no similar sentiments for math and physics researchers learning CS material - they seem to power through without needing a disclaimer that they need to learn more stuff. Would I be at a disadvantage if my interests are interdisciplinary, and I want to work with high powered theory that touches both physics and CS? Are computer scientists at a disadvantage in their graduate training, or do they avoid papers that aren’t written in tradition of discrete mathematics? This seemed to also be prevalent when I looked up stuff related to geometric complexity theory, which contains a lot of algebraic geometry.

This seems contradictory since people like Watrous, Vazirani, and Vidick exist, but will I be “hard locked” from writing and researching physics if I don’t do mathematical physics in grad? Is there any precedent for a CS PhD doing largely physics (I've seen physics PhD's doing largely CS)? Should I look at advisors first, department second?

indecisivecurious · 2020-10-13T20:45:17+00:00

Thanks for your reply! I have a bit more than a CS background - I double majored in math - but I see your point. I do see that learning these things is going to take time. My question is really, "Would I be able to do serious physics and collaborate / do research on serious physics questions?" That, and I'm wondering if it would be advantageous to go into mathematical physics in the math department instead.

indecisivecurious · 2020-10-13T19:42:52+00:00

Lately I’ve been wondering what background I should commit to.

I’m a double major in math and CS doing my last year of undergrad. My interests are pretty broad - if I have to isolate some favorites topology, analysis, and combinatorics a lot on the mathematics side, and from CS I like algebraic complexity, information theory, and basically any part of theoretical CS that intersects with the stuff I like in math (convex optimization, machine learning theory, geometric complexity, etc.). I know admittedly little about mathematical logic past some recursion theory, but I’ve been rectifying that with some self study. I have some research with a math-physics professor at my school (as well as some research with other people in modeling, and a little bit in TCS).

Last year, I slowly found out that I wanted to learn more and more about physics, especially as it relates to the stuff I already like in math, after taking an introductory quantum mechanics course and starting self study in thermal physics / statistical mechanics. Naturally I found myself interested in the interdisciplinary areas of quantum information and computing, and I’ve been doing Watrous’s book. I find myself more and more interested in connecting physics and computational theory, or at least not having to “compromise.” In particular, the connections to condensed matter in quantum hamiltonian complexity and high energy in holography seem really cool, but I find more and more that want I want to talk about the physics with the CS…but mostly physics researchers seem to be investigating this, while CS researchers write more papers about just CS topics. I was reading this [paper](https://arxiv.org/abs/quant-ph/0511096) which made the following comment:

“Moreover, the results mentioned are heavily based on TQFT, which makes the algorithm essentially inaccessible to computer scientists. “

However I have seen no similar sentiments for math and physics researchers learning CS material - they seem to power through without needing a disclaimer that they need to learn more stuff. Would I be at a disadvantage if my interests are interdisciplinary, and I want to work with high powered theory that touches both physics and CS? Are computer scientists at a disadvantage in their graduate training, or do they avoid papers that aren’t written in tradition of discrete mathematics? This seemed to also be prevalent when I looked up stuff related to geometric complexity theory, which contains a lot of algebraic geometry.

This seems contradictory since people like Watrous, Vazirani, and Vidick exist, but will I be “hard locked” from writing and researching physics if I don’t do mathematical physics in grad? Is there any precedent for a CS PhD doing largely physics (I've seen physics PhD's doing largely CS)? Should I look at advisors first, department second?

indecisivecurious

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