Lawrence

Somewhere wishing it was Halloween. Production Design - Art Department

[Jordan Crowder @digijordan]

Electrical, plasma, jellyfish in the sky!

The most incredible image of a Sprite I’ve ever seen.

Sprites are essentially lighting that is ABOVE a thunderstorm.

Not so much rare, just VERY hard to capture or see.

They live for only a couple milliseconds.

IG @florian.riou

[lusso @luusssso]

The opening ceremonies of the 1984 Summer Olympics in L.A. might be the perfect color palette

[Charlie Knot @chuck_says_yes]

the normalization of casual misogyny like this directly contributes to rape culture. if you’re against what happened at cornell, you need to be against this too.

[he/him charlotte york @F0RTUNEFAV0URS]

when the lights turn on at the gay club

[nazanin @onapittance]

Saw this AI-generated sign outside of a spa that is a sign of a sign

[𝓡𝓸𝓫𝓮𝓻𝓽 / 𝓜𝓻.𝓕𝓻𝓲𝓴𝓲 🎃 @MrFreaki]

He visto muchas películas de terror que me han dado menos miedo que este anuncio

[Matt Van Swol @mattvanswol]

🚨WOW!!!

Students at a Georgia High School pranked their principal by staging a "fake fight" at school and calling the Principal to break it up...

...as he rushes in to pull the students apart, they all started singing him Happy Birthday

He's so revealed and happy.

[Spencer Althouse @SpencerAlthouse]

helllll yes I loved this response from Matthew Lillard at today's "Scream" NYCC panel about how his and Skeet Ulrich's characters are gay icons

Matthew: People approach us all the time like, "You are my queer awakening." And I just want to say that, for us, I think that it's super powerful that our relationship to these characters has nothing to do with being gay, but if it means something to a kid out there somewhere who's like, "Oh, I feel seen in this relationship," that it's important for us to hold that space for these queer icons. We were not doing queer on the day, but we're here for it 30 years later

Skeet: [puts his arm around Matthew] We're doing it now!

[Lawrence @LawrenceBritish]

@whereiskywon @BadwanBeef @itsjcmerlo @MichaelDell @TrumpAccounts Sounds like you may be a fan of socialist programs! Next let’s make sure our future generations have access to free/gov paid healthcare! 👍🏼

[STAR IS A BRYAN HODUKAVICH LOVER !! @cantrustmen]

I need to have a genuine sit down conversation with him

[𝐌𝐚𝐠𝐝𝐚𝐥𝐞𝐧𝐚 👑 @MrsMagdaBeard]

Commas go a long way, dude....

[Disney Filmatic @DisneyFilmatic]

How Disney used live acting to develop their animated characters and scenes in the early days 🎬✨

Walt Disney’s Alice in Wonderland (1951)

[Dave Schilling @dave_schilling]

Say less. I’ll be there.

[Lawrence @LawrenceBritish]

This made me cry :(

[Solo @kindadidittho]

oh I have a film for you to watch…

[m @msnetik]

beauty and the beast furniture becoming human again

[Declan @ME_MURPHY13]

Surely you clock it on the way in

[spongieupdatestv @spongieupdates]

It’s really messed up how he gets to leave with a half a billion dollars and live the rest of his life comfortably while thousands of his employees will likely be unemployed within the coming months.

[𝐊 ✰ @itssthyherinme]

I got too much on my plate right now 😩

[Daniel D'Addario @DPD_]

Bugs Bunny threatening Elmer Fudd:

[Aakash Gupta @aakashgupta]

Shazam could name any song back in 2002, on flip phones, with zero AI. You dialed the number 2580, held your phone up to the speaker, and hung up. 15 seconds later, a text came back with the song name. That same core trick still runs the app today.

The inventor was Avery Wang, a Stanford PhD in audio signal processing. His problem was brutal. Match a short clip recorded on a 2002 cell phone mic, in a noisy bar, against a database of a million songs, in seconds, over a phone call.

His solution treated music as geometry instead of sound.

The algorithm converts audio into a spectrogram, a picture of the song, then throws almost all of it away. It keeps only the peaks, the loudest frequency points at each moment in time. Bar chatter and blown-out speakers can wreck most of a recording. The peaks survive. Shazam only ever needed the peaks.

Those surviving points form what Wang called a constellation map, because it looks like a star field. Pairs of peaks get converted into hash numbers, and identifying a song becomes a dictionary lookup rather than an audio comparison. That made it fast enough to search a million tracks on 2002 hardware.

Wang published the full method openly in 2003 in a paper called "An Industrial-Strength Audio Search Algorithm." Anyone could read exactly how the magic worked. The moat was the database and the deals with carriers, never the secret.

Apple bought the company in 2018 for a reported $400 million. People have tagged over 100 billion songs since the very first one, Jeepster by T. Rex, during the beta in April 2002.

One deterministic signal-processing trick, written before most people had heard the phrase machine learning, and it's still so good that in 2026 everyone assumes it must be AI.