Discover the Best AI Resources
Curated essentials, no noise — just what matters
AI API2020
Manages OAuth, credential storage, API proxying, and deployable TypeScript integration functions so products and AI agents can access 800+ external APIs. Includes AI-assisted function generation, a production runtime with scaling and observability, and cloud or self-hosted deployment options.
AI Infra2020
Optimizes distributed PyTorch training and inference for very large models with ZeRO memory partitioning, parallelism, MoE, offload, and compression. Best when GPU memory, training cost, or cluster throughput is the bottleneck.
At 175 billion parameters, this autoregressive model becomes a strong few-shot learner: it handles translation, QA, and reasoning from a few prompt examples with no gradient updates, establishing in-context learning as an alternative to fine-tuning.
AI Image2020
PyTorch object detector built for shipping: train on your own data, then export to ONNX, CoreML, TFLite, or TensorRT with one command. Comes in five sizes (n/s/m/l/x) and adds instance-segmentation and classification heads beyond bounding-box detection.
Teaches classic machine learning through a 12-week, 26-lesson curriculum with quizzes, written lessons, assignments, projects, and multilingual translations.
AI Audio2020
Extracts vocals and instrumentals from audio using an ensemble of models — MDX-Net/MDX23C, Demucs v3/v4, and the VR architecture. Runs locally via a Tkinter GUI with GPU acceleration across Nvidia, AMD, Intel, and Apple chips.
AI Infra2020
An AI-native, weight-centric infrastructure for quantitative trading that produces target portfolio weight vectors to unify data ingestion, strategy composition, backtesting, and live/broker execution. Modular pipeline supports ML/DRL allocators, LLM-ready preprocessing, multi-source data, and Alpaca integration for paper/live trading.
AI Infra2020
Covers the full AI quant pipeline — point-in-time data, model training, backtesting, portfolio optimization, and order execution. Supports supervised learning, market dynamics, and RL on 20+ models, plus an LLM-based RD-Agent for factor mining.
Collects 60+ PyTorch implementations of neural network papers — transformers, diffusion, GANs, RL, optimizers — each annotated line-by-line and rendered beside the code at nn.labml.ai, so you study the math and a runnable implementation together.
AI Infra2020
Unified framework for few-shot evaluation of generative language models across 60+ academic benchmarks. Supports multiple model backends (Hugging Face, vLLM, APIs, local servers), configurable prompts/YAML configs, and reproducible exports for leaderboards and research comparisons.
AI Client2020
Privacy-first, self-hosted personal knowledge manager with block-level references, Markdown WYSIWYG editing and large-document performance; offers local-first storage, OpenAI-based AI writing/Q&A integration, OCR, mobile apps and Docker deployment.