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How Hasty uses automation and rapid feedback to train AI models and improve annotation

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Computer vision is playing an increasingly pivotal role across industry sectors, from tracking progress on construction sites to deploying smart barcode scanning in warehouses. But training the underlying AI model to accurately identify images can be a slow, resource-intensive endeavor that isn’t guaranteed to produce results. Fledgling German startup Hasty wants to help with the promise of “next-gen” tools that expedite the entire model training process for annotating images.

Hasty, which was founded out of Berlin in 2019, today announced it has raised $3.7 million in a seed round led by Shasta Ventures. The Silicon Valley VC firm has a number of notable exits to its name, including Nest (acquired by Google), Eero (acquired by Amazon), and Zuora (IPO). Other participants in the round include iRobot Ventures and Coparion.

https://venturebeat.com/2020/11/24/how-hasty-uses-automation-and-rapid-feedback-to-train-ai-models-and-improve-annotation/