Showing 2 open source projects for "blocks"

View related business solutions
  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
    Start Free
  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
    Start Free
  • 1
    Burn

    Burn

    Burn is a new comprehensive dynamic Deep Learning Framework

    Burn is a new comprehensive dynamic Deep Learning Framework from Tracel AI built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. Burn emphasizes performance, flexibility, and portability for both training and inference. Developed in Rust, it is designed to empower machine learning engineers and researchers across industry and academia.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 2
    Luminal

    Luminal

    Deep learning at the speed of light

    Luminal is a framework designed to accelerate and simplify the development of systems-level data applications by using a typed, functional, and streaming-first approach. Instead of treating data processing as a series of ad-hoc scripts, Luminal models transformations as strongly typed building blocks that can be composed into reliable, scalable pipelines. The project emphasizes correctness and performance by requiring explicit types for the data flowing through transformations, reducing runtime surprises and allowing for highly optimized execution. It is particularly well-suited for data engineering workflows where large datasets must be processed incrementally, efficiently, and deterministically. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next