UI/UX Designer ✍︎ Frontend Developer ✌︎
Maryland, USA
Joined June 2011
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Billy Mitchell retweeted
Someone needs to stop Claude Opus 5.5. It turned one picture into a robot octopus I can take apart piece by piece.
i just said "make the model" and what came back floored me.
the build:
> the picture set the look, every petal, lens and link is three.js code
> opus rendered one still next to the picture and fixed the gaps for 3 rounds before it touched the film
> the first pass looked like a toy, so it went back and packed 202 links and 480 wheels into 8 arms
> every arm is one draw call, posed every frame by walking its chain of bends
> something opens every 2-3 seconds: the lens unscrews, the mantle hinges, the pump rises out spinning
> at 0:16 the whole thing blows apart on a 330° turntable and reassembles before the turn ends
25 seconds, 2,616 lines of code and one octopus that leaves the frame on its own.
the skill, the prompt and the live sim 👇
Billy Mitchell retweeted
“The Republicans will fix it this time”
“The Democrats will fix it this time”
Billy Mitchell retweeted
AI is really getting out of hand—they’ve got Tupac Shakur linking up with Kobe Bryant, Michael Jackson, Biggie, Bruce Lee, Elvis & Fidel Castro. 😳😭🎤
Who’s got that sweet @OpenAI #sora2invitecode ? #Designer over here looking to make some crazy stuff. 🤙🏻
Billy Mitchell retweeted
Nano is a depth-aware atmospheric haze plugin that uses ML depth estimation to add physically accurate fog and light scattering to your footage.
Works *best* on log footage with visible light sources - it analyzes scene highlights then creates airlight (atmospheric scatter) and halation (light bloom) that responds to actual depth in the scene.
Pretty clever approach to getting that cinematic haze look without having to pump a fog machine on set.
Makes the OG Trapcode Shine look extremely dated (basically 2D light streaks masked by luminance values), and is yet way more controllable than the current crop of generative AI video-to-video tools.
Billy Mitchell retweeted
Here are some facts NOT covered by graphs:
— AI inference costs fell 99.7% in 2 years.
— Training costs for frontier models approaching $1B+
— Energy per token dropped 105,000x in 10yrs
— 45% of global data center electricity consumption was in the US.
20/20
