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V7 Labs expands from data labeling into workplace automation

V7 spends $33M to automate computer vision AI model training data

Ironically, creating such AI faces a significant scalability issue. Artificial intelligence (AI) promises to assist, and perhaps even replace, humans in carrying out routine jobs and solving challenges that humans have been unable to address. It has to source and absorb ever-larger data troves because it is only as good as the models and data …

V7 Raises $33M in Series A Financing

V7 snaps up $33M to automate training data for computer vision AI models

V7's focus today is on computer vision and helping identify objects. It says it can learn what to do from just 100 human-annotated examples.

V7 Labs raises $3M to help AI teams automate training data workflows – TechCrunch

V7 Labs raises $3M to help AI teams ‘automate’ training data workflows V7 Labs, the makers of a computer vision platform that helps AI teams “automate” and future-proof their training data workflows as advances in AI continue, has picked up $3 million in funding. Leading the seed round is Amadeus Capital Partners, with participation from Partech, Nathan Benaich’s Air Street Capital and Miele Venture. Founded in 2018 by Singularity University alumnus Alberto Rizzoli and former R&D lead at RSI, Simon Edwardsson (the same team behind “seeing” app Aipoly), the V7 Labs platform promises to accelerate the creation of high-quality training data by 10-100x. It does this by giving users the ability to build automated image and video data pipelines, organize and version complex data sets, and train and deploy “state-of-the-art” vision AI models.

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