Aquarium VS Prodigy

Aquarium (https://aquariumlearning.com/) | Remote Only (North American Timezones) | Full Time Aquarium is an ML data management system that helps ML teams improve their models by improving their datasets. Aquarium uncovers problems in your dataset, then helps you edit or add data to fix these problems and optimize your model performance. We are looking for our first Product Manager and are also hiring for... - Source: Hacker News / over 2 years ago

#ML is maturing and teams are less concerned about having enough #data, but rather having the right data. ML data management tooling helps improve ML models by improving datasets. Check out our piece below that discusses trends in the space and startups like aquariumlearning.com, Tryunbox.ai, Lightly.ai, Scale, and Labelbox. https://medium.com/memory-leak/ml-data-management-a-primer-a635a5eac858. Source: over 2 years ago

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... - Source: Hacker News / 3 months ago

Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post. The steps... - Source: Hacker News / 8 months ago

Prodigy AI - Offers software engineers career coaching, skill assessment, and job matching. Visit Prodigy AI. - Source: dev.to / 9 months ago

I essentially want to use a Combo of OCR + NER to attempt to identify this, but I'm not sure NER is well suited for this, as it is not natural language, so there is little context to go off of. I was thinking of perhaps using Prodigy, a data annotation tool, to annotate Candidate Names, Races, etc, and perhaps it will be able to learn off of image data alone wheat these fields tend to look like. Source: 12 months ago

I come from a similar application area, where I try to tag (annotation/label) a taxonomy of products iteratively. You are trying something slightly different, AFAIU, labeling a flat set of songs, each song with a set of tags from ontology (directed graph)From an application point of view, this is what taxonomists often do, when migrating products from one catalog to another: mapping one taxonomy to another. There... Source: over 1 year ago