Senator Mark Kelly, former astronaut, explains his top 3 space movies.
Do they overlap with your favorites?
#Space #MarkKelly #movies
My friend and I went to see *Project Hail Mary* today. A hearty recommendation from me. I haven't been to the movies for ages but this one was definitely worth the admission (especially when it's half price on Cheapie Tuesday).
#Movies #ProjectHailMary
Started writing about #selfhosting #movie #streaming using @…
Geologists on the silver screen—the sequel: #movies, too ...
Aadam Jacobs ging 1989 mit einem Rekorder zu einem Konzert von #Nirvana. Seitdem hat er sich seinen Spitznamen "Taper Guy"" redlich verdient. Mittlerweile nahm er mehr als 10.000 Konzerte auf Band auf. Jetzt werden die Aufnahmen digitalisiert und bei
Got movies on my Linux laptop. But my AirPods don't connect to the laptop and I want to enjoy the audio. So I'm installing JellyFin server now to stream to my iPad ... I love it when open systems allow me to solve problems on my own.
Kate Beckinsale to star in 'Twilight of the Dead' -- George Romero had written a treatment for it before he passed in 2017 and regarded Twilight of the Dead as the conclusion to his epic saga (six movies and various spinoffs and remakes). The most recent movie in the franchise came out in 2009.
https:/…
Watched #Idiocracy (2006) today for the first time while at the gym. It's one of these movies that are both great and horrible at the same time. It also kinda feels like a prophecy... 🥴
Graduation Day (1981)
Speaking of graduations...
The new wave band Felony performs “Gangsters of Rock” at the 55min mark in this slasher movie. I love that band!
This film was made for about $250k but grossed more $24million 🤯
Oh and Vanna White makes an appearance.
#music #movies
I’m pivoting to my agentic era*
*rewatching James Bond movies
dbpedia_starring: DBpedia film-actor network
A bipartite network of movies and the actors that played in them, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 157184 nodes and 281396 edges.
Tags: Economic, Employment, Unweighted
https://network…
QUESTION:
What is your favorite order to see starwars if you would recommend it to a women that never watched it?
#starwars #movies #letterboxd
In the movies, when aliens cut power to a whole city, they do so at night, neighborhood by neighborhood. And when they reach a prison, they take out power block by block, adding the sound of old-timey switches pulled down so the inmates hear the progression.
Fascinating. 😳
#entertainment #movies #aliens #effects
I've finally watched #SoylentGreen, and oh my. I mean, I've seen it coming, it was kinda predictable, but still, shit, that is one heavy movie. Probably not a good time to be watching movies like that.
How Hollywood support staff are integrating AI into workflows, from mundane tasks to creative development, amid cost-cutting and workload demands (Mia Galuppo/The Hollywood Reporter)
https://www.hollywoodreporter.com/movies/movie-featur…
dbtropes_feature: Artistic works and their tropes
A bipartite network of artistic works (movies, novels, etc.) and their tropes (stylistic conventions or devices), as extracted from tvtropes.org. The date of this snapshot is uncertain.
This network has 152093 nodes and 3232134 edges.
Tags: Informational, Relatedness, Unweighted
https…
I realize I may not be the average viewer but shows and movies that show tiny text for text messages (like expecting us to read off a phone someone is holding, that is usually not shown in close up) are frustrating.
This issue has been solved well. Just show a large text graphic with the text. That works well, looks good and is readable. Without the solutions I am not sure I would have thought of it (after the fact is seems obvious), but after it has been solved, use the good idea.
…
Aadam Jacobs has secretly recorded over 10,000 local concerts since 1989.
Now, they are cleaned up and ready to listen to for free online:
https://archive.org/details/@aadam_jacobs_collection
Don't tell me that a film has a twist. That is in itself a spoiler.
#films #movies
FINALLY a reason to watch Disney , other than to rewatch Andor S1-S2 for the 7th time.
✅ Punisher One Last Kill review: The perfect antidote to Marvel's messy multiverse
https://www.polygon.com/punisher-one-last-kill-review-marvel/
james cameron didn't make these shitty avatar movies with over the top messaging for you to repeat exactly what was criticized
Didn‘t watch this yet but ARTE already had another great doc by the same director ( @ sixtus@mastodon.social ) about AI slop and fakes on the internet. If know German or you‘re francophone. This latest one might even be English. https://chaos.social/@Katika/116534409768887613
douban: Douban friendship network (2009)
A friendship network among users on Douban.com, a Chinese website providing recommendations for books, music, and movies.
This network has 154908 nodes and 327162 edges.
Tags: Social, Online, Unweighted
https://networks.skewed.de/net/douban…
back in my day video games and movies had piss filters on for artistic intent, these clankers should learn to respect the groundwork old timers like RE5 and GTA IV laid [huck tugh, that's the sound of me spitting into a bucket]
RE: https://mefi.social/@MissConstrue/116540178337660516
This perspective is debatable in the books, but the movies definitely foreground it.
Good post.
Crepes, with the lemon curd and meringue from Tuesday. Bacon and egg (mine the one I stole white from to wash a tourtiere last night), tea and coffee. Probably more movies at home today. Concert Friday, weekend up in the air. #TogetherBreakfast https://photos.app.goo.gl/C4uRNEf17YYYAVqi6
#LetterboxdFriday #LastFourWatched for this week- I mean, The Royal Hotel was from a previous week (not watching a ton of movies lately), but I did see three flicks since the last time. Finally took in World War Z (weird) ahead of its sequel. The Well was awesome- great twist- and Mike and Dave was hilar…
I haven't been seeing a lot of movies in the theater, lately. It's mainly because hollywood hasn't been releasing a lot of movies lately. I still pay Marcus a monthly fee for their membership program, though and I am up to 7 credits. I need to make more room in my schedule to see something.
Cyril Cyril & Le Syndicat du Futur - "Le gros Hit" (2026)
If you know me, you know I love silly and absurd tv, movies, music, etc. So I was psyched to hear this groovy, energetic song from The Geneva-based experimental folk/jazz duo Cyril Cyril.
They literally handed the microphone over to their own kids and the result is a delightfully surreal, playful, and minimalist French indie-pop track.
The lyrics are 😂 and the deadpan delivery against the danceable m…
🕰️ Those were the days!
Real animation done by a real human.
Today marks 20 YEARS since "Animator vs. Animation" by Alan Becker was posted to https://www.newgrounds.com/movies
MINI MOVIE REVIEW
"Remarkably Bright Creatures"
This movie was like if a Hallmark or Lifetime movie became watchable and had a budget.
It's simple and fun, and Sally Field still has it.
My wife, as usual, told me I should read the book because it's much better.
#Movies #Netflix
Last night, I filled a gap in my basic knowledge by watching 'Titanic' 🙂↕️
Good movie 👍🏻
#Titanic #Movies #ShareYourMovies
One of the few YT channels I'll just stop, tap, and watch. Just dropped.
#film #movies #FilmMaking #cinema
These: Das 80er Revival hat mit dem des Kalten Kriegs zu tun.
#kino #movies #fashion
If you didn't know about this collection of shows, check it out. Aadam Jacobs collection at the Internet Archive. Seeing he was Chicago based I took the chance to search and sure enough, he has a few Troubled Hubble shows. Amazing. https://archive.org/details/@aadam_jac
Good morning, Fediverse. ☕
Please keep in mind that today will be another day on which we are going to succeed in not going entirely mad, probably.
#DailyAppreciation #Movies #AnimatedGIFs
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 38 nodes and 96 edges.
Tags: Social, Fictional, Weighted
Tubi becomes the first streamer to launch a native app within ChatGPT, allowing viewers to find movies or shows to watch by using conversational phrases (Lauren Forristal/TechCrunch)
https://techcrunch.com/2026/04/08/tubi-is-the-first-strea…
wonderful piece on watching horror movies for comfort #movies
I'm very sad I will not be able to see Speed Racer in theaters. All the times are terrible for me.
#movies
Claude Code is good at doing research!
In this case helping find the disposition of 126,000 digitized US Supreme Court dockets (cert denied or full opinion), and then reporting why in a archive.org review (using like a wikipedia discussion).
This took real hand-holding and QA to be sure, but it is super helpful. Looked at court listener, the supreme court site (and the old one via the wayback machine!), the Caselaw Access Project at harvard. So good.
Watching that best of all Bond movies. Moonraker
A catalog of free & public domain movies from Archive.org and YouTube
https://select.github.io/movies/
Born To Watch - A Movie Podcast
With many thousands of hours of movie-watching under their belts, these friends bring a unique, seasoned perspective where they don't take themselves or the movies too seriously...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/born-t
Introducing #KinoPolis 🎞️ — a personal screening room for early cinema.
Films from 1896 to the 1930s, free to watch, organized into collections like German Expressionism, Soviet Montage, and Early Hitchcock.
Come get lost in the movies that invented movies!
http://w…
There are a few evergreen movie quotes that every German knows but which might not be well-known or popular in their countries of origin (note: German movies have always been dubbed for general audiences).
One such example is from French comedian Louis de Funès and I've never heard the original words. Looked it up in Youtube today. 1971 movie! Relieved to see it's a literal translation and the voice actors captured the French exchange perfectly!
dbtropes_feature: Artistic works and their tropes
A bipartite network of artistic works (movies, novels, etc.) and their tropes (stylistic conventions or devices), as extracted from tvtropes.org. The date of this snapshot is uncertain.
This network has 152093 nodes and 3232134 edges.
Tags: Informational, Relatedness, Unweighted
https…
Lets hunt for some DVDs!
just got 4 DVDs in the mail:
The fly
Paterson
Minecraft the movie
Pikachu detective
😎😄
#physicalmediacollection #movies #dvds
Movie Magick
We have one mission with this podcast - To bring the joy of movies to as many people as possible, and create a space for all people and opinions to be shared and heard...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/talking-flicks/
🤚 Getting a 2160p screen to watch 2160p movies.
👉️ Getting a 2160p screen to watch 1080p movies in split-screen with working.
Just did Mike and Dave Need Wedding Dates and it was easily one of the best, funniest comedies I've seen in a while. Just unreal 😂
#movies
I neeeeed to see the Mile End Kicks movie. Apparently they have lots of artists covering every song from Jagged Little Pill.
and a lot of the smaller artists I already know.
#music #movies
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 18 nodes and 50 edges.
Tags: Social, Fictional, Weighted
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 42 nodes and 109 edges.
Tags: Social, Fictional, Weighted
So far, "Mando" did $246M on a budget of $145M before marketing. "The Marvels" was #Disney's biggest failure w/$203M lifetime revenue.
▶️ The #Mandalorian & Grogu's Box Office Has Officially Just Soared Past the MCU's Biggest Ever Bomb - ComicBook.com
Off to the local Limelight Cinema with a friend tomorrow morning (Tuesday) to see the new Star Wars movie. Tradition dictates coffee and cinnamon donuts for our film viewing snack.
#HalPriceTuesday #Movies #StarWars
dbpedia_starring: DBpedia film-actor network
A bipartite network of movies and the actors that played in them, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 157184 nodes and 281396 edges.
Tags: Economic, Employment, Unweighted
https://network…
I saw something, 'What's your favorite Spielberg film?' and it got me thinking. It's very tough. I think mine has to be Raiders. Closely followed by Minority Report. What's yours?
#film #films #movies
douban: Douban friendship network (2009)
A friendship network among users on Douban.com, a Chinese website providing recommendations for books, music, and movies.
This network has 154908 nodes and 327162 edges.
Tags: Social, Online, Unweighted
https://networks.skewed.de/net/douban…
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 32 nodes and 80 edges.
Tags: Social, Fictional, Weighted
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 50 nodes and 169 edges.
Tags: Social, Fictional, Weighted
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 37 nodes and 71 edges.
Tags: Social, Fictional, Weighted
dbtropes_feature: Artistic works and their tropes
A bipartite network of artistic works (movies, novels, etc.) and their tropes (stylistic conventions or devices), as extracted from tvtropes.org. The date of this snapshot is uncertain.
This network has 152093 nodes and 3232134 edges.
Tags: Informational, Relatedness, Unweighted
https…
dbtropes_feature: Artistic works and their tropes
A bipartite network of artistic works (movies, novels, etc.) and their tropes (stylistic conventions or devices), as extracted from tvtropes.org. The date of this snapshot is uncertain.
This network has 152093 nodes and 3232134 edges.
Tags: Informational, Relatedness, Unweighted
https…
movielens_100k: MovieLens 100K (1998)
Three bipartite networks that make up the MovieLens 100K Dataset, a stable benchmark dataset of 100,000 ratings from 1000 users on 1700 movies. These data capture the tag-movie, user-movie, and user-tag networks. (Also available from MovieLens are 1M, 10M and 20M folksonomy datasets.).
This network has 24129 nodes and 95580 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 25 nodes and 91 edges.
Tags: Social, Fictional, Weighted
movielens_100k: MovieLens 100K (1998)
Three bipartite networks that make up the MovieLens 100K Dataset, a stable benchmark dataset of 100,000 ratings from 1000 users on 1700 movies. These data capture the tag-movie, user-movie, and user-tag networks. (Also available from MovieLens are 1M, 10M and 20M folksonomy datasets.).
This network has 24129 nodes and 95580 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 35 nodes and 96 edges.
Tags: Social, Fictional, Weighted
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 38 nodes and 96 edges.
Tags: Social, Fictional, Weighted
dbpedia_starring: DBpedia film-actor network
A bipartite network of movies and the actors that played in them, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 157184 nodes and 281396 edges.
Tags: Economic, Employment, Unweighted
https://network…
dbpedia_starring: DBpedia film-actor network
A bipartite network of movies and the actors that played in them, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 157184 nodes and 281396 edges.
Tags: Economic, Employment, Unweighted
https://network…