Google Research

Experiencing Visual Blocks for ML: Visual Prototyping of AI Pipelines

  • Ruofei Du
  • Na Li
  • Jing Jin
  • Michelle Carney
  • Jun Jiang
  • Xiuxiu Yuan
  • Kristen Wright
  • Mark Sherwood
  • Jason Mayes
  • Lin Chen
  • Jingtao Zhou
  • Zhongyi Zhou
  • Ping Yu
  • Adarsh Kowdle
  • Ram Iyengar
  • Alex Olwal
ACM (2023) (to appear)

Abstract

We demonstrate Visual Blocks for ML, a visual programming platform that facilitates rapid prototyping of ML-based multimedia applications. As the public version of Rapsai , we further integrated large language models and custom APIs into the platform. In this demonstration, we will showcase how to build interactive AI pipelines in a few drag-and-drops, how to perform interactive data augmentation, and how to integrate pipelines into Colabs. In addition, we demonstrate a wide range of community-contributed pipelines in Visual Blocks for ML, covering various aspects including interactive graphics, chains of large language models, computer vision, and multi-modal applications. Finally, we encourage students, designers, and ML practitioners to contribute ML pipelines through https://github.com/google/visualblocks/tree/main/pipelines to inspire creative use cases. Visual Blocks for ML is available at http://visualblocks.withgoogle.com.

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