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.
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.
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.
PyTorch library for operator learning: neural networks that map between whole function spaces, not fixed grids, so a model trained at one resolution runs at any other. Bundles FNO, Tensorized FNO and related architectures, mainly for solving PDEs.
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.
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.
Provides a self-hosted machine translation HTTP API that runs offline using the open-source Argos Translate engine; offers Docker-based deployment and a simple HTTP interface for integration. Suited for privacy-conscious or offline translation deployments.
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.
Build internal web apps, dashboards, workflows and AI agents with a visual low-code builder that connects to databases, APIs, SaaS and object storage. Includes AI app generation, AI query builder and AI debugging plus self-hosting and enterprise features like RBAC and audit logs.
Extensible infinite-canvas React SDK for building whiteboards, diagramming tools and canvas apps — includes real-time multiplayer sync, a runtime Editor API, custom shapes/tools, and canvas primitives for LLM/AI integrations. Development free; production requires a license key.
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.