Congrats on the launch! I haven’t had a chance to try out Active yet, but having had a project with Erik and the team a while back, they’re a great team to work with :)
Thank you! It was great working with you and your team as well :)
Launch HN: Encord (YC W21) – Unit testing for computer vision models
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Re: Launch HN: Encord (YC W21) – Unit testing for computer vision models
#12This 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.]
Re: Launch HN: Encord (YC W21) – Unit testing for computer vision models
#13This 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…
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
Re: Launch HN: Encord (YC W21) – Unit testing for computer vision models
#14This is amazing!!!
Re: Launch HN: Encord (YC W21) – Unit testing for computer vision models
#15This looks promising - but how is this different from tools like Aquarium Learning or Voxel51?
Re: Launch HN: Encord (YC W21) – Unit testing for computer vision models
#16This looks promising - but how is this different from tools like Aquarium Learning or Voxel51?
Those are both great tools. However, there are a number of differences, but the two most prominent are that: 1) Encord Active automatically analyses internal metrics to find the most relevant data and labels to focus on to improve model performance; and 2) it is optimised for the full 'continuous' training data workflow including the human-in-the-loop model validation and annotation.
Re: Launch HN: Encord (YC W21) – Unit testing for computer vision models
#17Congratulations Eric and Ulrik!