ViT: An Image Is Worth 16x16 Words
TL;DR: Cut an image into 16x16 patches, flatten them, project to embeddings, prepend a [CLS] token, add position embeddings, and feed the sequence to a standard transformer encoder. That’s ViT — a ...
Ceyblogs
NeRF: Representing Scenes as Neural Radiance Fields
TL;DR: NeRF encodes a 3D scene as a continuous function: feed in a 3D coordinate and a viewing direction, get back a color and a density. Render any viewpoint by marching rays through this function...
Articulate-Anything: Building Articulated 3D Assets with VLM Agents
TL;DR: Articulated 3D assets (doors that open, drawers that slide, laptops that fold) are essential for robot simulation but painful to build by hand — ~40 minutes per object with dedicated annotat...
ROBOMETER: Scaling General-Purpose Robotic Reward Models
TL;DR: Zero-shot reward tricks (like TOPReward) are elegant but limited. ROBOMETER asks: what happens if you actually train a reward model at scale? Built on Qwen3-VL-4B with three lightweight MLP ...
TOPReward: Zero-Shot Robot Rewards from Token Probabilities
TL;DR: Need a reward signal for robot learning but don’t want to train a reward model? Prompt a VLM with “this trajectory completes the task: True or False?” and use the log-probability of the “Tru...
Cosmos WFM (3/3): Applications — From Simulation to Reality
TL;DR: A pre-trained world model is only useful if it transfers to real-world tasks. Cosmos-Transfer translates simulator outputs into photorealistic video via ControlNet-style conditioning on edge...
Cosmos WFM (2/3): Training — Diffusion, Autoregressive, and Post-Training Recipes
TL;DR: Cosmos builds world models in two paradigms. Diffusion models generate video by iteratively denoising continuous latent tokens — flow matching (velocity prediction) replaces the earlier EDM ...
Cosmos WFM (1/3): Foundations — World Models, Data, and Tokenization
TL;DR: Physical AI — robots, self-driving cars, humanoids — can’t scale by training in the real world alone. A World Foundation Model (WFM) is a learned video simulator: given past frames and a per...
Connecting Claude to Your Django REST API with MCP
TL;DR: MCP lets Claude (and any compliant AI host) call your Django REST API as tools. This is a walkthrough of building a production MCP server on top of DRF — OAuth 2.1, discovery endpoints, ngin...
Hot Wheels and a Lesson in Cold Starts
TL;DR: I built a classifieds app for Hot Wheels collectors. Validated the problem, ran pilots, launched — and it died quietly from lack of critical mass. This is about doing everything “right” and ...