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Hive Media: Revolutionizing the Way We Understand On-Screen Content and Viewership
Hive is a full-stack deep learning platform focused on solving visual intelligence problems. While we are working with companies in sectors ranging from autonomous driving to facial recognition, our flagship enterprise product is Hive Media. As the name suggests, Hive Media is our complete enterprise solution utilizing deep learning to revolutionize traditional media analytics. However, […]
Back to Our Roots: Hive Data in Academia
Hive was started by two PhD students at Stanford who were frustrated with the difficulty of generating quality datasets for machine learning research. We found that solutions on the market were either too inaccurate or too expensive to conduct the typical research study. From those early days, we’ve now built one of the world’s largest […]
Multi-Indexing for Fuzzy Lookup
Have you wondered how Google and Pinterest can find visually similar images so quickly? How apps like Shazam can identify the song stuck in your head from just a few hums? This post is intended to provide a quick overview of the multi-indexing approach to fuzzy lookup, as well as some practical tips on how […]
Step-by-Step Guide to Deploying Deep Learning Models
This post goes over a quick and dirty way to deploy a trained machine learning model to production ML in Production When we first entered the machine learning space here at Hive, we already had millions of ground truth labeled images, allowing us to train a state-of-the-art deep convolutional image classification model from scratch (i.e. […]
Inside a Neural Network’s Mind
Why do neural networks make the decisions they do? Often, the truth is that we don’t know; it’s a black box. Fortunately, there are now some techniques that help us peek under the hood to help us understand how they make decisions. What has the neural network learned is attractive? Where does it look to […]
Hive – A Full-Stack Approach to Deep Learning
Here at Hive, we build deep learning models dedicated to solving visual intelligence problems – we take in unstructured visual data like raw image and video, and produce a structured output that helps understand the meaning of this content. The problems we’ve solved span numerous verticals, ranging from identifying winter Olympic sports to the model […]
