Castle Global
https://castleglobal.comAbout
In 2013, we set out to rethink consumer products through the lens of machine learning. Today, we have 100m+ consumers using our products that all sit on top of our machine learning platform. We continue to apply machine learning to rethink consumer product development, while we solve mission-critical problems for companies, non-profits and governments.
ABOUT HIVE.AI
Hive was founded by two Stanford graduate students determined to build practical applications using novel deep learning technologies. From the beginning, we knew that high-quality datasets were critical to creating deep learning models. However, we also knew that the quantity of labeled data also has a huge impact on model performance. With this in mind, we first started by building a data labeling platform specifically designed to solve machine learning problems. This platform, Hive Data, is now the world’s largest distributed human workforce for data labeling and produces millions of high-quality annotations every day. Hive Data allows us to label uncommonly large datasets at a fraction of the cost that other data labeling solutions would charge. Once Hive Data was built, we were able to quickly label enormous datasets and rapidly build a suite of machine learning models that now form our core offerings in Hive Predict. Our Hive Predict team has since built a wide range of custom machine learning models spanning a range of verticals including media, retail, security, and autonomous driving. Drawing on this experience and expertise, we then set out to build a stand-alone analytics platform for TV advertising called Hive Media. Hive Media synthesizes our company's fundamental technologies and leverages industry partnerships to deliver a truly revolutionary product. Hive offers the only true, full-stack deep learning platform in the world, assisting clients with data labeling, model building, and the development of full enterprise solutions.
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Meet GuppShupp - Bharat’s first AI Friend that truly understands you.
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