Next-gen fast plotting library running on WGPU using the pygfx rendering engine
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Updated
Oct 16, 2026 - Python
Next-gen fast plotting library running on WGPU using the pygfx rendering engine
Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform
Calibrated 151M Non-Autoregressive Decision Engine beating TypeSafe Jev & Laya on LocalLLaMA/typed-decisions (77.10% acc, 0.0636 Brier, 0.0144 ECE)
A small neural model for parsing date & time
Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground
Compile and explore arbitrarily large n-dimensional scientific data in the browser — points, lines, Gaussian splats and meshes, streamed from Zarr and rendered on the GPU.
WebGPU-based visuals for colour science applications
WebGPU/WebGL accelerated numpy-compatible array library for web browser
Cross-platform .NET performance engineering skill for coding agents, covering CPU, memory, GC, benchmarking, concurrency, startup, native profiling, GPU rendering, and production diagnostics on macOS, Windows, and Linux.
AI-native, source-available (PolyForm Perimeter) game-dev toolkit: bforge — deterministic headless-Blender asset forge for AI agents (138 ops, quality-gated) — proof-carrying asset/entity/world compilers, deterministic Python/Rust/Wasm simulation, glTF into Babylon.js/three.js/Godot, Rust services. Godot 4.7.1 Forward+ on WebGPU, reproducibly.
genome-spy-python is a declarative genomics visualization library for Python, built on top of the genome-spy JSON specification.
Blender plugin baking animated meshes to Vertex Animation Textures (VAT) or GPU Storage Buffers for Three.js (VAB) — export complex simulations, cloth, particles,...
INCENDIUM is a 4kb intro, featuring 3D fluid simulation and music done with WebGPU compute shaders
An open-source AI agent skill that helps coding agents port offline games to run in modern web browsers
NetSim — browser-based network simulator with a Cisco IOS-style CLI, packet capture (.pcap), and an on-device AI tutor. A zero-install, open-source CCNA lab. Live demo + FastAPI.
Deterministic-first PII/PHI de-identification you can prove: benchmarked recall, jurisdiction policy packs, reversible tokenization, audit trail. CLI + library + GitHub Action; optional GLiNER / Gemma contextual tier.
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