Experiencing Visual Blocks for ML: Visual Prototyping of AI Pipelines

Ruofei Du,Na Li,Jing Jin,Michelle Carney,Xiuxiu Yuan, Kristen Wright, Mark Sherwood, Jason Mayes, Lin Chen, Jun Jiang, Jingtao Zhou, Zhongyi Zhou,Ping Yu,Ram Iyengar,Adarsh Kowdle,Alex Olwal

ADJUNCT PROCEEDINGS OF THE 36TH ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE & TECHNOLOGY, UIST 2023 ADJUNCT(2023)

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摘要
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 [3], 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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关键词
visual programming,large language models,visual prototyping,multi-modal models,node-graph editor,deep neural networks,data augmentation,deep learning,visual analytics
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