Scale Nucleus
Aquarium
PerceptiLabs
ML Image Classifier
Google Cloud TPUs
Roboflow Universe
Touchpoint Dashboard
Pretrained AI
Prodigy
Enovia
Omnify PLM
Arena PLM
Fusion Lifecycle PLM
Propel
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SLIM Suite
Based on our record, Prodigy seems to be a lot more popular than Scale Nucleus. While we know about 25 links to Prodigy, we've tracked only 2 mentions of Scale Nucleus. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 2 years ago
To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 3 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 / 7 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
Aquarium - Improve ML models by improving datasets they’re trained on
Enovia - ENOVIA offers product lifecycle management (PLM) solutions fostering innovation and operational excellence across industries.
PerceptiLabs - A tool to build your machine learning model at warp speed.
Omnify PLM - Omnify PLM is a business-ready product lifecycle management solution.
ML Image Classifier - Quickly train custom machine learning models in your browser
Arena PLM - Arena offers PLM solutions for manufacturing teams to speed prototyping, reduce scrap, and streamline supply chain management.
