Implementation of Mimic-Video, Video-Action Models for Generalizable Robot Control Beyond VLAs

An extra set of tools for managing Supabase projects going beyond the possibilities of regular Supabase CLI

PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)

An MCP Server to patch existing files using block format

Anthropic's Interactive Prompt Engineering Tutorial

The best ChatGPT that $100 can buy.

PCB tooling by Diode Computers, Inc.

Official implementation of "MetaSDF: Meta-learning Signed Distance Functions"

Official PyTorch codebase for Regularized Interpolation in 4D Neural Fields Enables Optimization of 3D Printed Geometries.

Pipeline training and inference Anomalib models UI in Anomaly Detection

Easily and securely send things from one computer to another 🐊 📦

GPT-5 coding examples

A lightweight, powerful framework for multi-agent workflows

[CVPR 2024 Oral] Rethinking Inductive Biases for Surface Normal Estimation

[CVPR 2025] official implementation of “Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection”

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

Control and Interpretation of Production via Hybrid Expertise and Reasoning

The Official PyTorch Implementation of "Brain-like Variational Inference" (NeurIPS 2025 Paper)

DIY 3D Printable Robotic Arm

Benchmark for robotic tabletop manipulation memory-intensive tasks

Lightweight coding agent that runs in your terminal

Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

[ICLR 2025] Implementation of "FACTS: A Factored State-Space Framework For World Modelling"

An AI Hedge Fund Team

EdgeVLA: An open-source edge vision-language-action model for robotics.

[ICML 2025] Official PyTorch implementation of LongVU

FiLM: Visual Reasoning with a General Conditioning Layer

Official PyTorch implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States

A work-in-progress board-level hardware description language (HDL) providing design automation through generators and block polymorphism.

A PyTorch implementation of Model Agnostic Meta-Learning (MAML) that faithfully reproduces the results from the original paper.