Prodigy
Enovia
Omnify PLM
Arena PLM
Fusion Lifecycle PLM
Propel
beCPG PLM
SLIM Suite
Labeling AI
Labelbox
Universal Data Tool
CrowdFlower
Amazon Mechanical Turk
Supervisely
Playment
ByteBridge.io
Labeling AI is a deep learning-based technology that automatically labels large amounts of data based on a small amount of pre-labeled data available. Labeling AI is an innovative tool that can save your time.
Auto labeling performs the labeling process of large datasets with minimal human intervention, required only to review the auto labeled data. Here is how it works in 3 simple steps: 1. Labeling Manually - Manually generate 100 labeled data. 2. Training Model - Train an auto labeling AI with the 100 pre-labeled data. Review and correct the results to enhance auto labeling performance. 3. Deploy the best AI - Repeat the previous step to generate 1,000, 10,000, or 100,000 auto-labeled data. Transform your auto labeling AI into an object detection AI model to perform object detection as needed.
Labeling AI offers a variety of options to easily label your data, including bounding and polygon tools.
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Based on our record, Prodigy seems to be more popular. It has been mentiond 25 times since March 2021. 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.
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: about 1 year 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
Enovia - ENOVIA offers product lifecycle management (PLM) solutions fostering innovation and operational excellence across industries.
Labelbox - Build computer vision products for the real world
Omnify PLM - Omnify PLM is a business-ready product lifecycle management solution.
Universal Data Tool - Machine learning, data labeling tool, computer vision, annotate-images, classification, dataset
Arena PLM - Arena offers PLM solutions for manufacturing teams to speed prototyping, reduce scrap, and streamline supply chain management.
CrowdFlower - Enterprise crowdsourcing for micro-tasks