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

Re:Launch HN: Encord (YC W21) – Unit testing for computer vi... by btown on Wednesday January 31, 2024 @05:32PM (#39210361)

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/ which has a great diagram.

For those of us with similar needs for annotation and "unit testing," but on text corpuses, I'm aware of https://prodi.gy/ 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 https://www.vellum.ai/blog/introducing-vellum-test-suites - but I don't believe they feed annotation workflows in an automated and full-circle way.]

[ Parent | on HN ]

Re:Launch HN: Encord (YC W21) – Unit testing for computer vi... by elandau25 on Wednesday January 31, 2024 @06:01PM (#39210657)

Good question! We are focused on vision at the moment, but we are indeed looking at text in the future. Happy to connect and have a chat around that if you are open as we would be curious to hear more about new text use cases

[ Parent | on HN ]