Chogo retweeted
Introducing Claude Fable 5.2 and Claude Mythos 5.2, designed to tackle the most daunting technical challenges.
They’re capable collaborators on ambitious projects in many fields, and show improvements in areas like coding, reasoning, and vision.
Chogo retweeted
🚨this is SERIOUSLY dangerous.
i just tested a free Claude skill called "teardown" and 3d artists and motion designers should start worrying.
stuff like this should cost money and until someone notices, here is my run.
what the skill does:
> one picture and one word from you, the name of the animal
> claude writes the bird as code, puts its own still next to your picture and reworks it 3 times before the film starts
> under the plates it packs 300 small parts in loops and hangs 7 glass feathers on every wing
> one clock drives everything: the wingbeat on the gauge, the cursor on the panel, the sound, all read from the same timeline file
> claude never sees the video, it reads a sheet of frames at every beat, fixes what is wrong and renders again until nothing is left
> your GPU captures it at 60 fps and a python script scores it on the same beats
this is the 3rd model i've run through it and this one landed on the 2nd generation.
the skill is free and sits in the article below 👇
Chogo retweeted
Gemini 4 Argon combined three open-source datasets to build an interactive 3D visualization of human anatomy.
Toggle different layers in motion, isolate muscles, or zoom inside a beating heart.
Chogo retweeted
We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:
Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:
Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:
Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:
Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!
In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.
Chogo retweeted
ok what the fuck. this was a dry google doc a moment ago
gave Opus 5.5 my Open Alignment brainstorm gdoc and asked for a video. now I want one for every doc I’ve ever written hahaha
Chogo retweeted
Opus 5.5 on Max effort - "make a dynamic 15-second motion graphics video that shows what an incredible motion designer you are, like it's your showreel for a résumé. go all out."
Chogo retweeted
Opus 5.5 designing LEGO 👀
I asked it to design a Microduck I can build with real LEGO pieces. It:
> designed it life-size using 1113 real LEGO parts
> verified: 3,204 connections, 0 collisions, every step buildable, centre of mass inside the feet 🤯
> made a 141-page LEGO-style booklet (237 steps)
> priced every piece in the browser and prepared the orders on BrickLink
Chogo retweeted
Deploying DiffusionGemma-Jev (djev) just got a lot easier. You can now spin up a Jev API-compatible endpoint on Google Cloud Run using a single command.
Performance is solid: ~35-60 ms for single step latency and batch@32 is ~100-123 requests/sec.
It's a straightforward way to experiment without needing your own GPU. Runs at roughly $3/hr and drops to $0 when idle.
Get the code and instructions here: github.com/taeold/djev-run
Chogo retweeted
Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe.
GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more affordable models to support work at scale.
We’ve also made caching and inference more efficient, and we’re passing the savings directly to you: 50% lower API prices for Sol and Luna compared with GPT‑5.6 promotional pricing.
Chogo retweeted
Another impressive Gemini 4 Pro output.
I asked it to build a 3D model of a commercial airliner.
Took around 15 minutes to make.
Pretty good output, honestly.
Chogo retweeted
I'm so excited that our @theworldlabs team has achieved a major milestone today! Introducing Atlas - a first of its kind multimodal world model trained from scratch! 🚀
Atlas is capable of generating frames with pixel-perfect camera control, reconstructing large scenes from as few as one single input image, simulating space-time by reframing videos, natively outputting 3D spaces from one or more input images, composing multiple posed images into a consistent 3d world, and more! This is the best camera conditioned world model ever, opening doors to many possible use cases from VFX to robotics. I'm so so so proud of our team!♥️
Chogo retweeted
Timelapse of the Astra agent building the simulation inside the simulation:
Chogo retweeted
We just shipped our official Qwen 3.8 27B Uncensored MLX build. Local. Uncensored. For🍎
2-bit, 4-bit, 6-bit & 8-bit — pick your poison based on RAM and speed.
No CUDA. No cloud. Just your Mac and the weights. Have fun!
huggingface.co/orcarouter/Qw…
Chogo retweeted
SpaceX rocket crashes into Moon, carving 100‑foot crater
A Falcon 9 stage slammed into the lunar surface at seven times the speed of sound, releasing energy equivalent to three tons of TNT
Still, the crater is too small to see from Earth with the naked eye
Readers added context they thought people might want to know
The attached video is not real footage of the impact. The Falcon 9 upper stage is believed to have crashed into the Moon as described, but no close-up video exists. The crater is too small to see from Earth.
earthsky.org/space/falcon-r…
projectpluto.com/25010d.htm
newscientist.com/article/258331…
Chogo retweeted
Opus 5 crushed Fable 5 at 3D destruction physics for 2x cheaper!
We gave four models the same task: build three self-contained HTML scenes with real physics
Prompts:
- A tornado that sucks in a whole field
- A wrecking ball taking down an apartment block
- An overloaded truck collapsing a truss bridge
Outputs:
- Opus 5: 55.9K tokens, $1.40
- Fable 5: 55.1K tokens, $2.82
- Kimi K3: 35.7K tokens, $0.55
- GPT 5.6: 20.1K tokens, $0.31
Opus got all three right unlike the other models. Houses fly up the funnel and out the top, the wall breaks where the ball hits and the rubble piles up, the bridge drops the truck into the river. Fable had almost nothing on the ground for the tornado to pick up, its building collapsed on its own before the ball even touched it and its bridge blew into sticks all at once. GPT is the cheapest here but its ball never reached the building at all and its bridge fell apart in a way nothing falls apart in real life. Kimi K3, the new Chinese frontier model, ended up in the same place as GPT
