Noah Lyons

I build GPU and ML systems for Apple Silicon and the browser: MLX kernels and model ports, browser-native WebGPU inference, and spatial tools for inspecting generated worlds.

Accepted upstream

• MLX Core: antialiased linear and cubic nn.Upsample and compiled-kernel correctness for negative-strided inputs.
• WebGPU Samples: an external Vision Transformer sample with interactive attention visualization.
• vLLM-MLX: lifecycle-managed model residency, including lazy loading, idle unload, cancellation-safe transitions, and public lifecycle state.
• MLX-LM: rotating KV cache support for sliding-attention layers.
• MLX serving: 15 merged contributions to MLX OpenAI Server and five merged contributions to oMLX, centered on streaming, tool calls, reasoning parsers, cancellation, cache integrity, and API compatibility.

See the full contribution index, selected reviews, and independent deployment evidence.

Browser-native GPU inference

• @kaminos/webgpu-inference-kit is a composable WebGPU runtime for tensors, kernels, staged programs, route adapters, and cooperative scheduling.
• moge-webgpu runs MoGe-2 depth and surface-normal estimation in browser-native compute shaders.
• sharp-webgpu turns a single image into 3D Gaussian splats in the browser.
• sf3d-webgpu generates textured 3D meshes in browser-native WebGPU.
• kimodo-webgpu runs NVIDIA's 282M-parameter text-to-motion diffusion transformer in browser WebGPU, with DDIM sampling, denoising, and forward kinematics on the client.

Apple Silicon ML

• mlx-nf4 is a standalone native Metal NF4 extension for stock MLX, verified from a clean source install on M2 Pro and exercised end to end by double-quantized GPT-2 and the 9.3B mlx-ideogram4 image pipeline.
• cosmos3-mlx is a full-source MLX port of NVIDIA's 16B Cosmos 3 Nano world model for text/image-to-video and joint video/audio generation.
• wilor-mlx rebuilds WiLoR hand-pose estimation end to end in MLX.
• trellis2mlx and pixal3d-mlx bring image-to-3D generation to Apple Silicon without PyTorch.

Current work

Kaminos is very much a work in progress: it is the research bench where I explore the ideas that interest me most right now, especially browser-native ML, spatial interfaces, and tools for inspecting and shaping generated worlds. The WebGPU inference kit above is the most mature reusable component to emerge from that work.

Contact: n.lyons53@gmail.com