A year ago, teenagers at @hackclub set out to build the greatest math game ever.
Today, SineRider enters public beta. Experience a mesmerizing world of puzzles infused with love and inspired by the TI-84 🔎.
Hello, world 💖 this is https://t.co/cE4aCxlp4H
@v_maini@phoebeyao@MythosVentures If only the heal fellowship had been there for me during my fellowship
(now that I am a fully-fledged adult all of my personal problems have been solved, so we good now)
@farrarscott I guess the point is that I rarely bother to sort by controversial, whereas here I’m forced to. But even so it feels like there’s something… culturally different. Like reddit is a series of semi-private conversations at a party, and here people are yelling in the town square
Whenever I open a twitter thread I am instantly hit with radioactive discourse and people hustling their “personal brand”.
I almost never see this on reddit. There are toxic subs but they never spill into my feed.
Maybe it’s worse now but this was true pre-Elon.
@regardthefrost There are a great many people whose thoughts I’d like to hear that nonetheless have terrible replies. It’s particularly bad with journalists and politicians
Is it just that reddit has downvotes? If I could downvote people’s awful behavior here I would, and I’m guessing the same is true of lots of other normal people who I assume (hope) make up the majority of participants. But instead I scroll past with no recourse. It feels bad.
I frequently see takes I disagree with or little spats on reddit, but I never feel like I’ve walked onto some cultural battlefield. Discussion is overwhelmingly civil, and rude people tend to get downvoted into invisibility. Here it feels like aggression is rewarded.
Why?
#puzzle_82 My solution for the #sinerider puzzle of the day took 5 seconds & 32 characters
(((x+2)/(4)))^2+t-2
Try solving it yourself: https://t.co/2G8Gmcv6yo
@FreyaHolmer Honestly, happy for you!! Stimulants are life-changing for me, but there are also so many other interventions that help. Daily exercise and high protein intake first thing in the morning are two of the big ones to pair with pharmacological solutions.
@michael_nielsen The Box Shop. It’s the last remaining large-scale communal industrial art studio in the bay area, and is in a desperate fight to stay alive after the landlord decided to sell the property to a condo developer. A good portion of the big public art you see in the bay was made there
@SamuriFerret@mollygos The bottleneck as a player isn’t writing dialogue, it’s that I have to choose from a limited set of things to say. It’s like transitioning from MYST-style navigation to a true 3D open world.
@mollygos@IwriteOK IDK, I am a game developer and I recently built a small LLM prototype where you have to convince a dim-witted farmer to give you wool. Writing the prompt felt deeply creative, and the result was funny and satisfying. It’s not BG3, but it was a worthwhile “something else” 🤷♂️
Hey US @StateDept pay your United Nations bills!
It's embarrassing as the richest country on earth to be behind on our bills to an org that does so much for the world.
Yes please blog post! I feel like I have a grip on how these are rendered, so mainly I am curious to know how each of these are generated from source images. That part is still a black box to me.
I do a lot of work in this area.
To start off, both methods are used for 3d reconstruction, or the ability to fully reconstruct a scene from any perspective given a few images of the scene.
For people with no graphics background: nerfs predict the color at each individual pixel (point on the screen), whereas splats “splat” a bunch of colored blobs together until the picture is made.
For people with some tech/gaming background: nerfs use ray tracing to create a scene, whereas gaussian splats use rasterization create a scene. they both use machine learning to “remember” the colors in the scene to rasterize or ray trace.
For people with a tech background: nerfs are neural networks that predict each pixel’s color given a ray direction while splats create and modify millions of colored/transparent blobs (3d gaussians) until they form a scene using gradient-based optimization. both are trained from a limited number of viewpoints of a scene (the training data), and allows “novel view synthesis” (the ability to view the scene from new viewpoints not included in the training data).
Still oversimplifying but if there’s interest I can expand on this in a blog post.
"In Mississippi, the percentage of legislative seats with no major-party opposition in the general election has risen steadily from 63% in 2011 to 85% this year."
Ah yes, the magic of single-member districts + geographic partisan polarization.
https://t.co/9SEWSPelpI
@starsandrobots@TerraformIndies Hope you have enjoyed your FLG fun facts for the day 😅
Thank you for sharing the gnome!! Such a trip to see that piece of history on twitter. It was a pioneering work in the history of large fire effects!
@starsandrobots@TerraformIndies Xylophage is a large multi-piece sculpture produced by FLG in 2013 which includes the big tree stump and the big mushrooms. The gnome was placed inside it, but is actually a much older separate piece.