HomeAustraliaAppen to Acquire Figure Eight, for Up To $300M

Appen to Acquire Figure Eight, for Up To $300M

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appenAppen Limited (ASX:APX), a Sydney, Australia-based global leader in the provision of high-quality, human-annotated datasets for machine learning and AI, is to acquire Figure Eight (previously known as CrowdFlower), a San Francisco, CA-based machine learning software platform which uses highly automated tools to transform unlabeled text, image, audio, and video data into high-quality AI training data.

Appen will pay USD $175M up-front and an additional payment of up to $125M in 2020 based on 2019 performance.

This acquisition combines Appenā€™s global crowd with Figure Eightā€™s innovative data annotation platform to create an end-to-end training data offering. Through the end of 2019, Figure Eight will operate largely independently as a division of Appen. Beyond 2019, the company’s team and technology will be integral to Appenā€™s future success.

Founded in in 2007 by Lukas Biewald, Figure Eight combines human and machine intelligence to provide high-quality annotated training data that powers innovative machine learning and business solutions. The company has released a variety of innovative capabilities to enhance its platform ā€“ including machine learning-assisted data labeling and video object tracking ā€“ that can create high-quality training datasets faster than human labeling alone.

Listed on the Australian Securities Exchange (ASX:APX) with offices worldwide and led by Mark Brayan, Chief Executive Officer, Appen is a global leader in the development of human-annotated datasets for machine learning and artificial intelligence. It brings over 20 years of experience capturing and enriching a wide variety of data types including speech, text, image and video, , working in over 180 languages and more than 130 countries.
The company partners with technology, automotive and eCommerce companies – as well as governments worldwide – to develop, enhance and use products that rely on natural languages and machine learning.

FinSMEs

11/03/2019

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