Fan-Service Rocks!, fin
Best. Lecture. Ever. This episode is clearly the source of the “PG” promise of nudity, despite steam and chibification keeping things squeaky clean. And I’m confident the steam was not a buy-the-Bluray tease; it’s not that kind of show.
Anyway, along with limestone deposits, we get a discussion of future plans, and to the surprise of absolutely nobody, Nagi wants to teach, Shoko wants to become Yoko, and Ruri stumbles on her answer with a little help from her friends. The series closes with a montage of the near future, and a glimpse at Ruri’s suspiciously-familiar adult form.
Corn, popped
Literally for once. I hadn’t planned on making caramel corn Sunday night, but out of nowhere, my mother asked me how much unpopped corn you need to make 8 quarts of popcorn. She’d found a recipe for caramel corn somewhere, and it assumed you knew the conversion ratio. I ended up at popcorn.org, which says 2 TBSP of kernels for a quart of popped corn.
They also had a smaller, allegedly easier recipe that only required 5 quarts of the white stuff.
It somehow ended up being my job to run the air popper and follow the recipe, and the only difficulty was that the premium popcorn they’d bought produced significantly more volume than expected. 8 TBSP of kernels would have been more than enough.
I suspect I’ll also be drafted into making the next batch, this time with nuts.
Reminder: I am not actually this fat or this bald, I have much better trigger discipline, and I’m left-handed. Qwen is, shall we say, “not good” at guns, and definitely has a problem with the concept of holsters:
(I didn’t even ask to be holding the gun, just “holstered at his left hip”)
Diablo 4, season 10
I generally start new seasons with a Necromancer minion build, because being escorted by a pack of skellies does a good job of keeping you from getting overwhelmed at low levels as you acquire not-entirely-crappy gear and start to build up cash, materials, and abilities. Once you get some rare drops, it becomes an easy way to reach Torment 4 (Hand of Naz unique gloves, Nagu and Ceh runes, and Aspect of Occult Dominion cast on a helmet give you 14 skeletal mages and six spirit wolves to do your killing).
I’m currently farming in T3 because it’s faster, trying to get an Ophidian Iris for my incinerate/hydra sorcerer. I also thought I’d need some uniques to build up a whirlwind barbarian, but they’re letting you powerlevel alts through the seasonal content again, so I unlocked Deafening Chorus at level 30, and I already had an item enchanted with Aspect of Fierce Winds (DC = shouts are always active at +50%, AoFW = activating a shout creates 3 dust devils). The Neo and Ceh runes are another way of creating a pack of spirit wolves, so damage just kinda happens while you run around. And you’re also berserk and unstoppable at all times, with increased damage reduction and speed, making farming less of a chore.
(this is approximately 10% as chaotic as actually playing this build)
Reminder: X hallucinates your “interests”
If your feed seems skewed, it’s time to go in and uncheck the auto-generated horseshit “interests”. This week, mine was:
#2i2, ABC News, Abema TV, Action, Action & adventure books, Adam Schefter, Ado, Adventure, Age of Empires, Air travel, Alien, Andy Dalton, Animated works, Anthem, At home, Australia national news, B’z, Bad Bunny, Big 10 football, Biology, Blade Runner, Blu-ray, Board games, Borderlands, Breaking Bad, Breaking Bad, Breaking Bad, Breitbart News, Brit Hume, Buckingham Palace, Byron York, CBS, California, Careers, Climate change in the United States, Coaches, College Football, College Football, College Football 2023-2024, Colombia political figures, Colombia politics, Comic works, Construction, Cooperative games, Cracker Barrel, Cygames, Damon Jones, Data centers, Dating Apps, David Fincher, Dolly Parton, Dune, Elizabeth MacDonald, Eric Trump, Europe, Family films, Famous comedians, Folk music, Free-to-play games, George Clooney, George Soros, Glenn Beck, Greta Thunberg, Grindr, Gulf News, Hard rock, Home improvement, Homeschooling, Human resources, IPOs, J-pop, JB Pritzker, Jake Tapper, Jen Psaki, Jimmy Kimmel, Jimmy Kimmel Live, Jimmy Kimmel Live, Joy Reid, Kaori Maeda, Katie Pavlich, Keira Knightley, King Charles, Larry Elder, Late night talk, Latin music, Latin pop, LeBron James, Legal drama, Letitia James, Live: College Football, Manga series, Megan McArdle, Merrick Garland, Meta, Monster Hunter, NASA, NFL Football, NPR, Nate Cohn, Navy Midshipmen, Neuroscience, Nintendo, Nintendo Switch, Nursing & nurses, Nyheim Hines, Olympic Canoeing, Outerwear, PGA Tour, Partner Track, Patricia Heaton, Paul Bettany, Paul Sperry, Persona, Pfizer, Phil Mickelson, Plastic models, PlayerUnknown’s Battlegrounds, Popcorn, Professions, R&B and soul, Razer, Reggaeton, Reuters, Rie Takahashi, Ryan Saavedra, SKE48, SPY×FAMILY, School festivals, Sculpting, Smartmatic, Snack Food, Soul music, Sports, Spy × Family, Starbucks, Stefan Kuntz, Stephen King, Steve Jobs, Stevie Wonder, Sydney Sweeney, Target, Ted Nugent, Texas, The 60s, The Independent, Threads (Meta), Trap, Twilight Saga, USA Today, Upper body fitness, Venezuela political figures, Venezuela politics, Verizon, Voice actors, Voting Machines - Government/Education, Warren Kenneth Paxton, Water sports, Wells Fargo, Whataburger, Wine, Writing, Yahoo News, Young Magazine, Zenless Zone Zero, Zerohedge, Zombie Land Saga, Zoology, college_football_2023, ゾンビランドサガ, 異世界かるてっと
Not only have I never engaged with any tweet on most of these subjects, most aren’t even things that someone I follow would make fun of. And for the few that were memed by someone, that context should be taken into account. Pointing and laughing at something doesn’t mean you want to see more of it.
The only nice thing I can say about this list is that it’s just garbage, not explicitly hard-Left garbage.
Random randoms of randomness
Someone on the SwarmUI Discord posted a complex prompt that uses the app’s native randomizing syntax to create a wide variety of people portraits with diverse (both meanings) faces. It’s like a Perl one-liner had sex with a MadLibs book:
(analog photography.:2) in <random:an indoor|an outdoor|a studio> setting.
<random:<setvar[gender,false]:man><setvar[pronoun_n,false]:he><setvar[pronoun_p,false]:his>|<setvar[gender,false]:woman><setvar[pronoun_n,false]:she><setvar[pronoun_p,false]:her>|<setvar[gender,false]:person><setvar[pronoun_n,false]:they><setvar[pronoun_p,false]:their>>the <var[gender]> is in <var[pronoun_p]> <random:early|late|> (<random:teen years|twenties|thirties|forties|fifties|sixties|seventies|eighties>:2)..
<var[pronoun_n]> has a distinctive <random:oval|round|square|heart-shaped|long|oblong|diamond|triangular> face, looking <random:pleasant with a gentle smile|energetic with a broad smile and a cheerful grin|radiant, beaming with joy and sparkled eyes|amused, with a slight smirk and a twinkle in the eye|contended, in a peaceful and serene expression|playful, with a mischievous glint, hinting at fun|warm and welcoming|hopeful and optimistic|blissful, lost in happy thoughts|thoughful, deeply pensive|curious, eyes wide with interest and head tilted on a side|observant and scrutiny|introspective, lost in reflection|calm and peaceful|serene, untroubled|focused, intently concentrating|weary and exhausted|melancholic and wistful|pensive with a hint of sadness|resigned in acceptance|wistful, longing for the past|anxious with worry in the eyes|reserved, keeping it formal|overjoyed in exhuberant happiness|very sad in a genuine sorrow with tears|angry, bursting in rage|surprised, startled with wide-eyed wonder|fearful, apprehensive and scared|determined with strong will and resolve|intense, experiencing a deep feeling|smiling sadly|thoughtfully amused|weary but determined|curiously spektikal and doubtful|serenely hopeful>.
<var[pronoun_n]> has <random:porcelain|ivory|rosy-fair|pale golden|peach|golden|olive|light tan|tan|bronze|caramel|warm brown|cool brown|chocolat|deep bronze|ebony|rich dark brown|honeyed|copper|russet> <random:flawless|velvety|polished|dimpled|porous|weathered|sun-kissed|bumpy|freckled|densely freckled> <random:skin with <random:small,large, prominent> moles|skin with <random:faint, noticeable, prominent> (scars:<random:1,2,3,4,5>).|skin>, <random:pixie cut|buzzcut|chin-length|jawline-length|shoulder-length|collarbone-length|mid-back length|waist-length|long|classic bob|layered bob> <random:jet black|raven black|soft black|chocalate brown|dark mahogany|chestnut brown|medium brown|light brown|ash brown|auburn|platinum blonde|golden blonde|honey blonde|strawberry blonde|ash blonde|dirty blonde|fiery red|ginger red|burgundy|silver gray|charcoal grey|snow white|salt-and-pepper|bronze|mahogany|russet|ombre|blue> hair with a <random:high hairline|low hairline| widow's peak|straight hairline>; <random:high|medium|low> and <random:wide|narrow|average> <random:sloping|straight|with prominent brow bone> forehead.
<var[pronoun_p]> <random:sparse|dense|regular|asymmetrical> eyebrows are <random:thin|medium|thick|bushy> and <random:arched|straight|angled upward|angled downward|rounded|curved>, <random:matching hair color|darker than hair|lighter than hair>, <random:almond-shaped|round|upturned|downturned|hooded|monolid|> <random:large|medium|small> eyes show a beautiful <random:sky blue|deep sapphire blue|grey-blue|turquoise|emerald green|olive green|hazel green|dark chocolate brown|light hazel brown|golden brown|mahogany brown|mixture of brown, green, and gold|silver grey|slate grey> hue<random:|, deep-set into <var[pronoun_p]> face|, protruding forward>, <random:short|medium|long> <random:sparse||thick> <random:straight|naturally curled|heavily curled with mascara> eyelashes.
<var[pronoun_n]> sports a <random:large|medium|small|pointed> <random:straight nose, with a classic and balanced profile|roman nose with a prominent bridge and a hump|greek nose, with a straight bridge and refined tip|snub nose, upturned and delicate|aquiline nose, hooked and curved downwards|button nose, nicely rounded|hawk-like nose, strong and prominent|wide nose, broad at the nostrils|narrow nose with a thin bridge|long nose, extended length from brow to tip>, <var[pronoun_p]> cheeks are <random:rosy, naturally flushed|dimpled with cute indentations|freckled|sun-kissed|sculpted sharp|softly curved>. <var[pronoun_n]> has <random:large|medium|small> <random:full, voluminous|thin, delicate|wide, spreading across <var[pronoun_p]> face|distinctive bow-shaped|softly curved round|down-turned drooping|> <random:lips.|lips with a defined cupid's bow.|lips with a prominent lower lips.|lips with a prominent upper lips.> <var[pronoun_p]> chin is <random:large|medium|small|strong|weak> and <random:rounded|square|pointed|cleft|receding|prominent|doubled, with fullness under the chin>, <var[pronoun_n]> has a <random:strong|soft|square|rounded|well defined|soft> and <random:wide|narrow> jawline, completing <var[pronoun_p]> face.
<var[pronoun_p]> build is <random:slender|lean|muscular|stocky|robust|petite|large-framed>, <var[pronoun_n]> stands in an <random:upright|slouching|stooped|relaxed|casual|tense|stiff> posture, showcasing <var[pronoun_p]> <random:broad|wide|narrow|sloping|rounded|square> shoulders and <random:full|flat|narrow> chest. <var[pronoun_p]> arms are <random:long|short|muscular|toned|slender|lean|strong|robust>, completed with <random:delicate|rough|small|large> hands.
<var[pronoun_n]> wears a <random:formal|casual|loose|fitted|tight> <random:cotton|silk|wool|denim|leather> <random:shirt|blouse|t-shirt|sweater|jacket> contrasting with <var[pronoun_p]> hair.
…and that’s why I converted it to the dynamicprompts YAML format, which revealed all sorts of typos and awkward phrasing. I added weighting to improve realism (completely random choices produce a lot of unusable crap), cleaned up the option lists, and added a new one to push Qwen Image away from its default faces.
My version is here, in my new Github repo for random genai-related stuff. The Python script I use as a wrapper for the dynamicprompts library is in there, too.
You know it’s time for a new theme when…
…you weed 500 images down to 162 and say, “forget the toes, maybe I’ll just use them all as wallpaper”. I’m not going to blog that many, though, so I deathmatched it down to 18 based on the newly revised-and-randomized sfnal locations.
I started with ~900 retro-sf locations generated by several different online and offline LLMs, fed them all to Claude to categorize and create sentence patterns, and then threw 500 imaginary pretty girls on top. Many of the results were visually incoherent, and quite a few had nothing about them that even hinted at SF, retro or otherwise, but most met the goal of being lively and colorful without drawing attention away from the girl.
No refine&upscale for this batch; it’ll run overnight for the full set of 162, so I probably won’t kick it off today.
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