AI Infra2020
Sits between PyTorch and micrograd: eager tensors with autograd plus a small, fully hackable compiler that fuses operations into kernels. Adding a new accelerator backend takes about 25 low-level ops, so it runs on CUDA, Metal, AMD, and WebGPU.
MCP Server2020
Exposes a self-hosted WhatsApp HTTP/REST API that runs a real WhatsApp Web instance so apps and AI agents can read/send messages, manage contacts, and automate flows. Offers three engine modes (WEBJS, NOWEB, GOWS), Docker images, and MCP support; relies on WhatsApp Web so blocking risk exists.
A 12-week, 24-lesson beginner-friendly AI curriculum with executable Jupyter notebooks, quizzes and labs that teach neural networks, computer vision, NLP, generative models and ethics using PyTorch and TensorFlow examples.
MLOps2021
Unified metadata platform for data discovery, observability, and governance — central metadata repository, column-level lineage, and a pluggable ingestion framework with 84+ connectors. Suited for teams that need searchable data catalogs, automated lineage, and collaborative data governance.
AI Infra2021
Runs, manages, and scales AI workloads across 20+ clouds, Kubernetes, Slurm, and on-prem from one YAML or Python spec. Auto-provisions GPUs/TPUs, fails over across regions and providers when capacity is short, and routes jobs to the cheapest option.
AI Client2021
Self-hostable personal “AI second brain” that turns web pages and documents into a searchable knowledge base, builds custom agents and automations, and connects to local or cloud LLMs with multi-platform access.
AI Deploy2021
Serves predictive and generative ML models on Kubernetes via a single InferenceService CRD, with scale-to-zero, canary rollouts, and an OpenAI-compatible LLM path on vLLM. One autoscaling abstraction over PyTorch, XGBoost, ONNX, and HuggingFace.
MLOps2021
Orchestrates ML training pipelines and production agent workflows from one Python codebase that runs unchanged from a laptop to Kubernetes or any cloud. Auto-versions artifacts, models, and agent checkpoints, with no orchestrator or framework lock-in.
AI Infra2022
A continuously-updated, categorized self-hosting guide that catalogs tools, deployment notes and resources for containers, networking, home automation and running LLMs/chatbots locally; provided as a long, structured README with links and quick setup tips.
AI Deploy2022
Deploys PyTorch models directly on phones, microcontrollers, and embedded hardware via ahead-of-time compilation to a ~50KB C++ runtime. Delegates subgraphs to 12+ backends (XNNPACK, CoreML, Qualcomm, ARM Ethos-U) with torchao quantization.
AI Dataset2022
Provides 115M public GitHub source files (≈873GB of code, ~1TB uncompressed) with per-file metadata (repo, path, language, license). Supports streaming, language/license filtering and full download for training and evaluating code LLMs and code generation models.
AI Infra2022
Compiles plain Python functions into GPU or CPU kernels at runtime via a JIT decorator, with differentiable output that plugs into PyTorch, JAX, and Paddle. Ships physics, robotics, geometry, and FEM primitives — particles, meshes, ray-casting, FFT.