Production-tested AI infrastructure tools for efficient AGI development and community-driven innovation

AutoMQ is a stateless Kafka on S3. 10x Cost-Effective. No Cross-AZ Traffic Cost. Autoscale in seconds. Single-digit ms latency. Multi-AZ Availability.

Enabling PyTorch on XLA Devices (e.g. Google TPU)

PyTorch distributed training acceleration framework

Fast and easy distributed model training examples.

0-Shot Tokenizer Transplant

Staging repo for development of native port of TypeScript

Minimalistic 4D-parallelism distributed training framework for education purpose

FlashMLA: Efficient MLA decoding kernels

Collection of autoregressive model implementation

Naptha is a framework and infrastructure for developing and running multi-agent systems at scale with heterogeneous models, architectures and data

Software for running personal agents locally that can interact with personal agents on other devices

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

TensorZero creates a feedback loop for optimizing LLM applications — turning production data into smarter, faster, and cheaper models.

A system that performs algorithmic trading

Ingest, parse, and optimize any data format ➡️ from documents to multimedia ➡️ for enhanced compatibility with GenAI frameworks

Easily deployable 🚀 API to convert PDF to markdown quickly with high accuracy.

A distributed job server built specifically for queuing and executing heavy SQL read jobs asynchronously. Separate out reporting layer from apps. MySQL, Postgres, ClickHouse.

Replicate and sync Kafka topics between clusters in realtime. Supports topic re-mapping, healthchecks, and hot failovers for high availability.

a tiny multidimensional array implementation in C similar to numpy, but only one file.

Job queuing service and async task runner.

Dedicated Resources for the Low-Level System Design. Learn how to design and implement large-scale systems. Prep for the system design interview.

Curated Collection of all Low level design Questions and implementation asked in major Tech companies , Get yourself prepared for the LLD round and ace the interview.

Simple and focused time-series tables for PostgreSQL, from Tembo

Postgres page inspector

A distributed datastore that never goes down.

Transactional outbox harvester for Postgres → Kafka, written in Go

🍕 A practical and imaginary food delivery microservices, built with golang, domain-driven design, cqrs, event sourcing, vertical slice architecture, event-driven architecture, and the latest techno…

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