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Launch HN: Encord (YC W21) – Unit testing for computer vision models

Encord Active Prodigy
  1. Open source active learning framework to improve model performance
    Pricing:
    • Open Source

    #Computer Vision #Machine Learning #Open Source

  2. Radically efficient machine teaching
    This is really cool. The annotation-to-testing-to-annotation-etc. Feedback loop makes a ton of sense, and I'd encourage others who may be confused on this post to look at the Automotus case study https://encord.com/customers/automotus-customer-story/ for the annotation side, but my understanding is the relationship between model outputs and annotation steering is out of scope for that project - do you know of tooling (open source or paid) that integrates an "Active" component similarly to what you do? Or is text a direction you want to go as well? [I'm a fan of Vellum (YC W23) for evaluation and testing of multiple prompts <a href="https://www.vellum.ai/blog/introducing-vellum-test-suites">https://www.vellum.ai/blog/introducing-vellum-test-suites</a> - but I don't believe they feed annotation workflows in an automated and full-circle way.].

    #Product Lifecycle Management (PLM) #Office & Productivity #Project Management 25 social mentions

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