• Go from Data Warehouse to Data and AI platform with BigQuery Icon
    Go from Data Warehouse to Data and AI platform with BigQuery

    Build, train, and run ML models with simple SQL. Automate data prep, analysis, and predictions with built-in AI assistance from Gemini.

    BigQuery is more than a data warehouse—it's an autonomous data-to-AI platform. Use familiar SQL to train ML models, run time-series forecasts, and generate AI-powered insights with native Gemini integration. Built-in agents handle data engineering and data science workflows automatically. Get $300 in free credit, query 1 TB, and store 10 GB free monthly.
    Try BigQuery Free
  • 99.99% Uptime for MySQL and PostgreSQL on Google Cloud Icon
    99.99% Uptime for MySQL and PostgreSQL on Google Cloud

    Enterprise Plus edition delivers sub-second maintenance downtime and 2x read/write performance. Built for critical apps.

    Cloud SQL Enterprise Plus gives you a 99.99% availability SLA with near-zero downtime maintenance—typically under 10 seconds. Get 2x better read/write performance, intelligent data caching, and 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server with built-in vector search for gen AI apps. New customers get $300 in free credit.
    Try Cloud SQL Free
  • 1
    Agent S

    Agent S

    Agent S: an open agentic framework that uses computers like a human

    Agent S is an open-source agentic framework designed to enable autonomous computer use through an Agent-Computer Interface (ACI). Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    SMAC

    SMAC

    SMAC: The StarCraft Multi-Agent Challenge

    SMAC (StarCraft II Multi-Agent Challenge) is a benchmark environment for cooperative multi-agent reinforcement learning (MARL), based on real-time strategy (RTS) game scenarios in StarCraft II. It allows researchers to test algorithms where multiple units (agents) must collaborate to win battles against built-in game AI opponents. SMAC provides a controlled testbed for studying decentralized execution and centralized training paradigms in MARL.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB