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.
AI Others2021
Curated self-study roadmap and reading-list for learning computer science end-to-end — organizes open courses, textbooks, and project recommendations across programming languages, systems, algorithms, AI/ML and more; aimed at motivated learners planning a 2–3 year self-directed path.
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.
AI Audio2022
edge-tts is a Python module that enables the use of Microsoft Edge's online text-to-speech service directly from Python code or via command-line tools like edge-tts and edge-playback, without requiring Microsoft Edge, Windows, or an API key.
AI Infra2022
Provides runtime support for reversible effects and reactive coeffects so components can be declared, composed, and hot-replaced safely; includes effect tracking, coeffect resolution, a declarative component loader and HMR — aimed at plugin-driven agent harnesses and dynamic systems.
AI Infra2022
Fused CUDA kernels that compute exact attention without ever writing the full N×N score matrix to GPU memory, cutting memory from quadratic to linear and speeding up training and inference on A100/H100. Ships FlashAttention-2/3 plus KV-cache decode paths.