Could you elaborate? How do you see this playing out? Is this unique to disease or do you believe it's also true of other forms of suffering, e.g. poverty?
Well I think anything which gives humans unbounded lifespans is probably going end human civilization long term. So I don't think eliminating poverty is dangerous in a similar way no.
All Watched Over By Machines Of Loving Grace (Richard Brautigan)
I like to think (and
the sooner the better!)
of a cybernetic meadow
where mammals and computers
live together in mutually
programming harmony
like pure water
touching clear sky.
I like to think
(right now, please!)
of a cybernetic forest
filled with pines and electronics
where deer stroll peacefully
past computers
as if they were flowers
with spinning blossoms.
I like to think
(it has to be!)
of a cybernetic ecology
where we are free of our labors
and joined back to nature,
returned to our mammal
brothers and sisters,
and all watched over
by machines of loving grace.
At least in comparison to x86 assembly, MIPS assembly seemed very elegant and rich to me at the time. I wanna say that MIP R4K had 32 integer registers and 16/32 double- or single-precision float registers, but don't quote me on that. Either way, it was an embarrassment of riches :)
Bitwit: Learn CS, logic, and math theory (_not_ DSA) with spaced repetition: https://bit-wit.com/
I was hit by a big wave of depression last year. That crisis gave me a couple of periods of hyperfocus, and I thought I might as well use them to try to improve my mind and my ability to reason.
I haven't had good results learning certain subjects, like CS/math, with Anki or other flash card systems. The only thing that ever seemed to work for me was doing a lot of problems with pencil and paper. But without problems exercising those tools or techniques, they tended to just evaporate from my mind.
So my idea was to combine spaced repetition and problem presentation, and create a system for generating problems and validating their solutions randomly and parametrically. So successive presentations of the same card would present a different problem... and the overall effect would hopefully be that you learn the invariants that each card is trying to present, instead of memorizing some combination of variables and values. Sort of MathAcademy but for CS.
I _think_ it's feature-complete at this point, though I'm still working on validating and publishing cards (and there are a couple of things I wanna do to improve security). I'm pretty early in the dogfooding process, and I'm still the only person using it, and there are definitely bugs. But if anyone would like to try it out, I'd be delighted to hear your feedback (email in profile, also on site). Just maybe go a little easy on me right now, lol :/
The Boolean Logic and Lambda Calculus subjects are free forever, and the first topic of each other subject is also free, so if you're intrigued you can use it for quite some time (literally months) before even needing to provide an email address. No need to pay for anything.
Location: US/Ohio
Remote: Yes
Willing to relocate: No
Technologies: Backend / DevOps / Infra / Platform
Résumé/CV: https://ndouglas.github.io/resume/resume.pdf
LinkedIn: https://linkedin.com/in/nug-doug/
GitHub: https://github.com/ndouglas/
Email: smooth.gift2502 AT tenesm DOT us
Pretty boring dude, 14+ years of experience in various areas of engineering. I'm looking to switch jobs only because I intend to move to Europe in ~2.5 years and that's a no-go with my current employer. I'm very interested in science and research.
My professional work's covered in my résumé, but that's mostly boring. I've also written a NES emulator [1], an ECS-based Lisp machine/rule engine [2], a self-organizing gossip mesh that learns to play Flappy Bird [3], and ported _Zork_ to Clojure for no good reason [4]. I also started working on a Math/CS educational site late last year to combat a wave of depression [5].
I'm a bit of an odd duck and don't fit what many teams are seeking, but I'm always growing and getting better, usually in the weirdest possible way. If you're interested, I'd love to hear from you.
What do you work with (if you don't mind answering)? I'm looking for a change and like low-level stuff about as much as I like any other level. I've done some cycle-accurate NES emulation and VM implementation stuff - I'm not much of a DSA guy but performance and efficiency appeal to me.
I work with pretty much everything (except GPUs I guess). Embedded is extremely relative. To some, embedded means a rack mount server that's idk embedded in a vehicle instead of a datacenter. That's not me. To others, embedded means a 4-bit low power, mask-rom fed micro inside a sensor IC. That's also not me.
So I work with microcontrollers of various vendors, I do FPGA with hard and soft processors, recently did just past the smoke test through embedded Linux on a SoC, and I've done plenty of desktop code on Linux and Windows for interfacing. I get to work with a wide range of devices and a wide range of tasks for them. Might not pay as much but my goodness is it fun
I couldn't make head nor tails of the QBasic help back in the day. I wanted to. I remember reading the sections about integers and booleans and trying to make sense out of them. I think I did manage to figure out how to use subroutines eventually, but it took quite a lot of time and frustration. I wish I'd had a book... or a deeper programming class. The one I had never went further than loops. No arrays, etc.
> And btw, every plate tectonics simulation that I've seen does not look convincing.
It's an amazing problem! I haven't spent much time on it - maybe 20-30 hours spread out over several years - but it _is_ something I come back to from time to time. And it usually ends up with me sitting there, staring at my laptop screen, thinking, "but what if I... no, crap. Or if we... well... no..."
TBH it's one of the things that excites me, because it makes it clear how far we still have to go in terms of figuring out these planet-scale physical processes, simulating them, deriving any meaningful conclusions, etc. Still so much to learn!
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